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• MP2PRT: Evaluation of an Inflammation Polygenic Risk Score (iPRS) to Predict Cancer Related Cognitive Impairment and Fatigue in Patients Receiving Chemotherapy for Non-Metastatic Breast Cancer in URCC0701 and URCC10055

  This study is a secondary analysis of cancer related cognitive impairment (CRCI) and cancer related fatigue (CRF) among participants in URCC0701 and URCC10055 from the University of Rochester NCI Community Oncology Research Program (NCORP) Research Base. CRCI and CRF are common, troublesome, and dose-limiting toxicities reported by patients undergoing breast cancer chemotherapy that have an etiologic basis linked to low-grade systemic inflammation. Chronic, low-grade systemic inflammation is, in part, genetically determined with common single nucleotide polymorphisms (SNPs) capturing variation across individuals. This study aimed to 1) determine whether an inflammation polygenic risk score (iPRS) is associated with CRCI or CRF, 2) determine whether the relationship between the iPRS and CRCI or CRF is modified by exercise at the time of cancer treatment, 3) identify SNPs associated with serum cytokines measured at the time of cancer treatment, and 4) identify novel CRCI- and CRF-associated risk SNPs via genome-wide association analyses. We found that there was a significant inverse correlation between the iPRS and change in fatigue score from pre-chemotherapy to post-chemotherapy while there was no statistically significant association between the iPRS and cognitive impairment score. The inverse relationship between the iPRS and fatigue may be explained in part by the finding that the iPRS was also significantly associated with greater pre-chemotherapy fatigue, suggesting that women with a genetic predisposition to low-grade systemic inflammation (i.e., high iPRS) have more fatigue at the time of breast cancer diagnosis and, therefore, are less likely to worsen over the course of treatment. In contrast, women with a low iPRS had significantly less fatigue pre-chemotherapy and a significant worsening of fatigue from pre- to post-chemotherapy. The relationship between the iPRS and fatigue remained after adjustment for patient and cancer treatment covariates and was most pronounced in women who reported regularly exercising for at least 6 months prior to starting their cancer treatment. Exploratory genome-wide analysis identified a novel risk locus on chromosome chr6q27, tagged by rs9365961, associated with CRCI. This locus is upstream of TBXT, which encodes an embryonic nuclear transcription factor previously associated with susceptibility to neural tube defects. The genome-wide SNP data, patient-reported CRCI and CRF outcome measures, and covariate data used in this analysis are available through dbGaP.

  Study phs003688

• The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program 'CASCADE'

  Background: Understanding the cancer genome is seen as a key step in improving outcomes for cancer patients. Genomic assays are emerging as a possible avenue to personalised medicine in breast cancer. The majority of work in this area has targeted primary tumours however, and very few studies have performed comprehensive profiling of advanced disease. Evolution of the cancer genome during the natural history of breast cancer is largely unknown, as is the profile of disease at death. We sought to study in detail these aspects of advanced breast cancers that have resulted in lethal disease. Methods and Findings: Three patients with ER-positive, HER2-negative breast cancer and one patient with triple negative breast cancer underwent rapid autopsy as part of an institutional prospective community-based rapid autopsy program. Cases represented a range of management problems in breast cancer, including late relapse after early stage disease; de novo metastatic disease; discordant disease response and disease refractory to treatment. Between 5 and 12 metastatic sites were collected at autopsy together with available primary tumours and longitudinal metastatic biopsies taken during life. Samples underwent paired tumour-normal whole exome sequencing and single nucleotide polymorphism arrays. Subclonal architectures were inferred by jointly analysing all samples from each patient. Mutations were validated using high depth amplicon sequencing.Between cases, there were significant differences in mutational burden, driver mutations, mutational processes and copy number variation. Within each case, we found dramatic heterogeneity in subclonal structure from primary to metastatic disease and between metastatic sites, such that no single lesion captured the breadth of disease. Metastatic cross seeding was found in each case and treatment drove subclonal diversification. Subclones displayed parallel evolution of treatment resistance in some cases, and apparent augmentation of key oncogenic drivers as an alternative resistance mechanism. We also observed the key role of mutational processes in subclonal evolution.Limitations of this study include the potential for bias introduced by joint analysis of formalin fixed archival specimens with fresh specimens, and the difficulties in resolving subclones with whole exome sequencing. Other alterations that could define subclones such as structural variants or epigenetic modifications were not assessed. Conclusions: This study highlights the variety of mechanisms that shape the genome of metastatic breast cancer, and the value of studying advanced disease in detail. Treatment drives significant genomic heterogeneity in breast cancers which has implications for disease monitoring and treatment selection in the personalised medicine paradigm.

  Study EGAS00001002153

• DNA methylomes of monozygotic twins clinically discordant for multiple sclerosis

  Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. Although genetic susceptibility is important, a modest concordance rate for MS in monozygotic (MZ) twins suggests that interaction with other risk factors is required to develop clinical symptoms. In this study, we examined whether DNA methylation differences contribute to the discordant clinical manifestation of MS in MZ twins, and studied the impact of MS treatments on the DNA methylome. Genome-wide DNA methylation profiles of peripheral blood mononuclear cells (PBMCs) of 45 MZ twins clinically discordant for MS were generated using the Illumina HumanMethylationEPIC array. Repetitive element methylation and selected differentially methylated positions (DMPs) were validated using targeted deep bisulfite sequencing (TDBS). In addition, we performed whole genome bisulfite sequencing (WGBS) to profile CD4+ memory T-cells of a subset of four MS discordant MZ twins. Our results show that interferon treatment causes robust DNA methylation changes and several epigenetic biomarkers for interferon treatment response were identified. However, overall the PBMC-based methylomes of the MS discordant MZ twins were highly similar, since large systematic methylation differences (>5%) were absent in the data. This suggests that previously reported large methylation changes are probably caused by genetic rather than epigenetic differences. In addition, our data does not support the hypothesis that the observed maternal parent-of-origin effect in MS is due to genomic imprinting errors, and no evidence was found that copy number variations explain the discordant phenotype in these MZ twins. Although not genome-wide significant, a couple of DMPs associated with the MS phenotype were identified and successfully technically replicated using TDBS, including a differentially methylated region (DMR) in the promoter of the transmembrane protein encoding gene TMEM232. Another MS-associated DMP, located in an enhancer in the gene body of the transcription factor ZBTB16, was also associated with medium-term glucocorticoid treatment history. WGBS analysis confirmed this DMP as a promising epigenetic biomarker for glucocorticoid treatment. In conclusion, this epigenome-wide association study (EWAS) in genetically identical twins identified a DMR in the TMEM232 promoter as a candidate loci associated with the clinical manifestation of MS. In addition, epigenetic biomarkers for MS treatments were identified, revealing that not only short-term, but also medium-term treatment effects are detectable in immune cells, which should be taken into account in future EWAS designs.

  Study EGAS00001003147

• Genes and Blood Clotting Study (GABC)

  Objectives: Use genome-wide approaches to identify genetic variants that influence common thrombosis and hemostasis factors, as well as selected common human traits. Design/Methods: The GABC study was a prospective sibling cohort design. Siblings were recruited by targeted email to the undergraduate and graduate student email lists at the University of Michigan. Healthy persons between 14 and 35 years old who had healthy siblings within the same age restriction were able to participate. Study participants agreed to an online informed consent and subsequently completed a 52-question online survey describing their specific bleeding traits as well as many common human traits. Fifty milliliters of blood was collected into a citrate-dextrose solution (ACD) from each participant. An aliquot of whole blood was used for an automated complete blood count analysis and the remainder was processed into platelet poor plasma and buffy coat portions. Plasma and buffy coat aliquots were snap frozen and stored in liquid nitrogen for future studies. 1189 individuals representing 507 sibships were collected between 06/26/2006 and 01/30/2009. Phenotyping Survey Details: To characterize individual bruising and bleeding history, the online survey recorded answers to questions based on a modified von Willebrand Disease (VWD) screening questionnaire. To characterize a collection of participant's common human traits, the survey recorded answers to questions about height, weight, presence of skin tags, history of acne, eye color, hair color, hair line characteristics, skin sunburn sensitivity, skin tanning ability, natural skin color, freckling, cheek dimpling, earlobe shape, shoe size, foot arch characteristics, hand fifth digit morphology, history of dyslexia, history of migraine headaches, history of seasonal allergies, history of apthous ulcers, tendency to sneeze while walking into a bright sunny place, history of dental caries, need for corrective eye lenses, handedness and like or dislike of strongly flavored foods. Biochemical phenotyping: Assays for plasma Von Willebrand Factor (VWF) antigen were performed using ELISA and "Alphalisa" techniques. Automated complete blood count analysis was performed on a Bayer Advia 120 on all participants (including WBC differential, RBC indices, and platelet count.) For the dbGaP v2 update, new biochemical phenotypes have been submitted and include von Willebrand Factor, von Willebrand Factor propeptide, plasminogen, gamma prime fibrinogen, ADAMTS 13, antithrombin III, protein C, and protein S. All new phenotypes were obtained using "Alphalisa" techniques. Genotyping Details: SNP genotyping was performed using genomic DNA extracted from peripheral blood at the Broad Institute, (MIT/Harvard). Genotyping was performed on the Illumina Omni-1 quad chip at the Broad Institute. For the dbGaP v2 update, genotyping data from the Illumina Human Exome was deposited. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to blood clotting through large-scale genome-wide association studies of siblings. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization was performed by the primary investigators at the University of Michigan, Ann Arbor, and at the GEI-funded GENEVA Coordinating Center at the University of Washington. This study serves as a resource for investigators who are interested in the genetic determinants of specific plasma proteins in a healthy population. The sibling cohort design allows for linkage analysis in addition to association studies. Analysis of thrombosis and hemostasis related traits should help elucidate specific biochemical and genetic networks that maintain hemostasis. We hope to identify specific genetic determinants of VWF levels in order to better understand the factors that influence the development of VWD.

  Study phs000304

• PyEGA3 download client

  PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

  Documentation access/download/files/pyega3

• A Prospective Natural History Study of Diagnosis, Treatment and Outcomes of Children with SCID Disorders

  Individuals with a recent or new diagnosis of severe combined immune deficiency (including infants who were identified by newborn screening) may be eligible to be enrolled on the PIDTC research study 6901. Speak to your doctor to determine if you or your child may be eligible. Protocol 6901 follows patients with SCID prospectively, meaning the 6901 study enrolls participants where there is a plan to receive a blood and marrow transplant, enzyme therapy, or gene therapy in the future. Patients are then followed according to a schedule set out by the study protocol after the procedure. The times the study requests follow up will be the same as when your doctor would want to be seeing you or your child as part of their regular ongoing medical care. Patients with "leaky SCID", reticular dysgenesis, and Omenn syndrome may also be eligible to participate in 6901. The 6901 research study does NOT dictate how your or your child's doctors should treat you or your child, as the PIDTC recognizes that there are many complex factors that go into this decision. The decision about how you or your child with SCID will be treated is made by your doctor. The 6901 study simply follows how you or your child do over time. There are no experimental therapies on this study. The 6901 study has been open since August 2010, and continues to be open and enrolling patients to the present day. The study plans to enroll approximately 250 patients with SCID. By studying new patients undergoing treatment for SCID, the goal is to learn more about: (1) outcomes from the treatment of SCID in the modern era of medicine, (2) what factors lead to the best long-term outcomes, such as best donor, conditioning regimen, timing of transplant, etc. and (3) what impact newborn screening and the early diagnosis of SCID has had on the long-term outcomes following BMT or gene therapy. A significant amount of information is also being gathered on how and when the immune system recovers after BMT, quality of life for long-term survivors, and about whether children develop normally after treatment. The 6901 study is the largest coordinated prospective study of patients with SCID ever performed. Information that we will learn, both now and in the future, will help doctors and other health professionals to better treat children with SCID. All hospitals within the PIDTC are enrolling patients with SCID on 6901, ensuring that the outcomes are reflective of what happens in the "real world" as opposed to at just one or two large centers.

  Study phs001392

• Prader-Willi Syndrome and Early-onset Morbid Obesity Natural History Protocol

  This observational study will involve the comprehensive assessment of the medical, behavioral and nutritional history and the clinical features of individuals with Prader-Willi syndrome and individuals with features of PWS-like/EMO. A blood sample will be obtained from the participants in order to create a DNA and RNA repository. In those PWS participants with a known deletion a blood sample will be collected for DNA in order to perform array comparative genome hybridization (aCGH) microarray or Methylation-Specific Multiplex Ligation-dependent Probe Amplification (MS-MLPA) studies to characterize the extent of the deletion. DNA samples will be sent to the Consortium Center at Baylor College of Medicine for the performance of the aCGH studies and to either Dr. Driscoll or Dr. Butler lab for MS-MLPA analysis. No drugs or treatments will be administered through this protocol. Our goal is to enroll as many participants as possible over a 8 year period. Currently we have enrolled 297 total subjects of which 265 have PWS and 32 EMO. Our original goal was to have enrolled over the first 5 years a clinical database of 200 individuals with PWS and 100 with EMO. We have exceeded expectations in PWS enrollment, but have fallen short in the enrollment of individuals with EMO. Therefore, we would like to reset our goals. We now propose to have an enrollment goal of 400 total subjects of which 350 will have PWS and 50 will have EMO. Eligible participants will be initially enrolled in the natural history study from the 4 clinic sites currently involved with PWS (University of Florida, Kansas University Medical Center, Vanderbilt University and University of California at Irvine). Participants assessed will serve to provide a background of information and a willing cohort for future interventional studies. All participants will have had standard genetic testing at a commercial laboratory prior to entry into the study. The PWS participants will be classified into one of the 3 main molecular classes (deletion, UPD and ID). The EMO participants will have had laboratory testing ruling out PWS and chromosomal aneuploidy (e.g., trisomy 21, Klinefelter syndrome, etc.). Going forward we feel it is important that all newly recruited EMO subjects have an aCGH as part of their evaluation so we can identify those with discrete deletions, duplications or copy number variants (CNV) and compare them to those without aCGH abnormalities. The participants will be assessed annually (0-3 years of age) or biennially (> 3 years) in the Clinical Research Center (or equivalent facility) using standardized protocol including photographs for documentation purposes to compare the evolution of the clinical phenotype.

  Study phs000575

• TOPDECC-Trans-omics for Precision Dentistry and Early Childhood Caries: Genome-Wide Genotyping (CIDR) and Microbiome in the ZOE 2.0 Study

  The ZOE 2.0 study is a cross-sectional genetic epidemiologic investigation of early childhood oral health, conducted in a state-wide, community-based, multi-ethnic sample of 3-5-year-old preschool-age children in North Carolina, United States. Between 2016-2019, 8,059 children were enrolled and 6,404 of them underwent comprehensive oral-clinical examinations that provided usable data on dental caries (i.e., early childhood caries; ECC) phenotypes. Saliva samples and supragingival biofilm samples were collected by 10 trained and calibrated examiners during the clinical encounters that took place in enrolled children's preschool (Head Start) centers. Specifically, the study enrolled participants and conducted clinical examinations in 260 Head Start centers that belonged to 34 Head Start programs in NC. 6,262 participants provided clinical data and had extracted DNA that met quantity and quality criteria for high-density genotyping and 6,144 of them were retained in the genome-wide association study (GWAS). Additional information on oral health-related behaviors, risk factors and self-reported outcomes was collected prior to the conduct of the clinical exam using self-administered questionnaires completed by children's guardians. Height and weight measurements were used to derive measures of adiposity. A domestic water sample for fluoride concentration measurement was obtained after the clinical examination for approximately 25% of study participants, to provide a measure of environmental exposure to this known caries-preventive agent and this information was subsequently imputed to the entire cohort using a novel GIS-informed method. Supragingival biofilm samples for microbiome analyses were collected from all participating children. Biofilm samples from a pilot 5% (n=300) of the cohort were carried forward to WGS (metagenomics; MTG) and RNAseq (metatranscriptomics; MTX) analyses, and these sequence data are being released via the Sequence Read Archive (SRA) in this dbGaP accession: 300 participants with MTG, 297 of those with MTX. Of note, the 17 participants with MTG data did not have genotypes produced, therefore the study's released participant total count is 6161, including 6144 (with genotypes released) plus 17 (with no genotypes released but with MTG data in the SRA).The study's primary objective is to identify risk loci and gene sets/pathways for ECC and related traits (e.g., caries prevalence and severity) by conducting a trans-ethnic GWAS. Genotyping is based on the Infinium™ Global Diversity Array and the TOPMed panel is used for imputation via the University of Michigan Imputation server. Secondarily, the ZOE 2.0 seeks to determine prevalence and severity of dental caries, other oral disease outcomes, and putative risk factors for dental caries in this low-income population-based sample of European-, African-, and Hispanic/Latino-American preschool-age children.

  Study phs002232

• Neoantigen-Targeted CD8+ T-Cell Responses 1 With PD-1 Blockade Therapy

  Background: The primary target of T-cell responses induced against cancer cells are peptides derived from non-synonymous mutations presented by HLA (neoantigens). However, the large diversity of HLA alleles and restricted availability of clinical samples have limited the study of the specificity and the evolution over time of the neoantigen-specific T cell responses induced after treatment with immune checkpoint blockade (ICB) immunotherapy. Methods: We applied a newly developed neoepitope-specific T cell isolation technology to perform a longitudinal landscape analysis of the neoepitope-specific T cells in peripheral blood and tumor from 11 patients with metastatic melanoma; 7 with response and 4 with no response to ICB. Briefly, first using computational prediction, the putative neoantigens in each patient were ranked based on affinity for the patient's HLA and expression levels. Then hundreds of barcoded capture reagents consisting of the patient HLA class I subtypes loaded with the corresponding predicted neoantigen were made and used to isolate neoepitope-specific T cells. Once isolated, the TCRs and the barcodes were sequenced. Finally, the tumor reactivity of the isolated neoepitope-specific TCRs (neoTCRs) was assessed upon co-culture of autologous melanoma cell lines from each patient with primary human T cells expressing the neoTCRs generated using a CRISPR-based non-viral gene editing to replace the endogenous TCRs. Results: The tumor mutation burden ranged between 3507 and 177 for patients with response to therapy and 977 to 31 for patients without response to therapy. We screened a median of 172 predicted neoantigen-HLA per patient across their 6 HLA molecules and isolated neoTCRs in all 11 patients. The number of mutations targeted ranged between 13 and 1. We assessed the neoTCR-tumor reactivity in samples from 3 patients with response and 3 patients without response. 39 of the 62 neoTCRs demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Multiple T cell clonotypes recognized a limited number of mutations in 7 patients with response (median of 41 different neoTCR clonotypes per patient), and the T cell specificities were recurrently detected in the blood and the tumor over time. Samples from 4 patients without response to therapy also demonstrated neoepitope-specific T cell responses in blood and tumor to a similarly restricted number of mutations, but lacked TCR polyclonality (median 6.5 neoTCR clonotypes per patient) and were not recurrently detected in sequential samples. Conclusion: Effective ICB therapy is associated with polyclonal neoepitope-specific T-cell responses in the tumor and blood that recognize a limited number of immunodominant mutations and are recurrently detected over time.

  Study phs003153

• Heart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis Therapy - (HFN ATHENA-BioLINCC)

  ObjectiveTo assess whether high-dose spironolactone treatment for patients with acute heart failure lowers natriuretic peptide levels and improves outcomes better than usual care.BackgroundAcute heart failure (AHF) accounts for more than a million hospitalizations in the United States annually. The role of low-dose mineralocorticoid receptors antagonists (MRAs) therapy as a neurohormonal antagonist is well established for the treatment of chronic heart failure and reduced ejection fraction. However, the role of high-dose MRA therapy in AHF remained uncertain. A previous clinical trial suggested that the benefits of high-dose MRA therapy in AHF included lower natriuretic peptide levels, less congestion, better renal function, and less need for an intravenous diuretic. The use of intravenous loop diuretics can intensify secondary hyperaldosteronism among AHF patients, and hyperaldosteronism directly contributes to diuretic resistance in AHF. Elevated aldosterone levels in AHF are associated with an increased risk of cardiovascular mortality and HF readmission. Hospitalizations for heart failure are associated with increased risk of mortality and/or readmission.The HFN-ATHENA trial was conducted to determine if mineralocorticoid receptor antagonists administered at high doses relieved congestion, decreased diuretic resistance, and mitigated the effects of adverse neurohormonal activation in AHF.SubjectsThe ATHENA trial enrolled 360 participants. Of these, 178 participants were randomized to usual care treatment (placebo or low-dose spironolactone) and 182 participants were randomized to high-dose spironolactone.DesignThe study intervention was initiated within 24 hours of patients receiving the first dose of intravenous diuretics. Participants not taking spironolactone at enrollment were randomized to 100 mg spironolactone or a placebo. Participants taking low-dose spironolactone before their hospital admission were randomized to 100 mg or 25 mg per day in the usual care treatment arm. Prescription of all other medications, including diuretics, was left at the discretion of the treating physician. The study drug was discontinued after 96 hours and further MRA use was left to the treating physician's discretion. The primary end point was the proportional change in the log NT-proBNP levels from randomization to 96 hours (or at the hospital discharge if the discharge occurred earlier than 96 hours). Secondary endpoints included: (1) a clinical congestion score; (2) dyspnea relief; (3) daily cumulative net urine output for up to 96 hours; (4) net weight change from baseline to 96 hours or discharge (whichever came first); (5) furosemide equivalents of the loop diuretic dosage at discharge; and (6) the development of in-hospital worsening HF, with signs and symptoms requiring additional therapy.ConclusionsThere was no significant difference in the primary or secondary endpoints between the high-dose treatment arm and the usual care treatment arm.

  Study phs003506

• Studies of Left Ventricular Dysfunction (SOLVD-BioLINCC)

  Data Access NOTE:Please refer to the "Authorized Access" section below for information about how access to the data from this accession. Access differs from many other dbGaP accessions. ObjectivesThis study was initiated in 1986, primarily to evaluate the effects of enalapril, an ACE inhibitor, on long-term mortality and major morbidity in a group of participants with left ventricular dysfunction. Two large separate trials were run concurrently as part of SOLVD: 1) a prevention trial of participants with low ejection fraction but no overt symptoms of CHF and, 2) a treatment trial of participants with low ejection fraction and symptoms of CHF. In addition, participants at selected sites were entered into substudies to evaluate the effect of enalapril on a number of intermediate outcomes such as right and left ventricular function and hemodynamics, LV mass and wall stress, hormones, arrhythmias, exercise capacity, and quality of life in subsets of participants. Lastly, a registry of 6,336 participants with congestive heart failure of LV dysfunction was designed to describe the clinical course of an unselected group of participants. Background Congestive Heart Failure (CHF) is a major and increasingly recognized public health problem. The recognition that participants with CHF often have elevated peripheral vascular resistance has led to the introduction of vasodilator therapy, which has emerged as an important component of its treatment. Of the vasodilators, the angiotensin-converting enzyme (ACE) inhibitors appeared to be the most promising. In 1985, little was known about the impact of any long-term drug treatment on survival. SOLVD Registry: The SOLVD Registry is a hospital-based observational study, conducted at selected SOLVD hospitals, of participants with at least moderate left-ventricular dysfunction (EF ≤ 45%) and/or radiologically confirmed heart failure. It consists of a main study (n=6,273) and a substudy (n=898). Although there is overlap between the Registry and the SOLVD trials, the Registry sample is not a subset of SOLVD nor is it the pool of participants eligible for both trials. Participants A total of 2,569 participants were enrolled into the treatment study and 4,228 participants were enrolled in the prevention study. The dataset available through the NHLBI contains the prevention and treatment study data as well as the registry data. Conclusions In the prevention trial, a significant reduction in the incidence of heart failure and the rate of related hospitalizations was observed for participants in the enalapril arm. A statistically significant reduction in mortality was not observed in the enalapril treatment arm; however, there was a trend toward fewer total deaths and deaths due to cardiovascular causes among the enalapril participants (SOLVD Investigators, et al., 1992, PMID: 1463530).

  Study phs003668

• Analyzing Somatic Mutagenesis in Systemic Sclerosis

  The study was undertaken with the aim of estimating differences in the mutational burden in lung tissues from healthy vs systemic sclerosis (SSc) patients. SSc is an auto-immune disease, with patients often developing cancer. However, the etiology of this phenomenon is poorly understood. As such we sought to uncover potential molecular mechanisms prevalent within SSc tissues that might be potentiating cancer. Samples were randomly collected from individuals from two broad ethnic groups, European (EA) and African American (AA). In total, samples were obtained from 7 individuals belonging to the EA group and 4 individuals from the AA group. For this study, ethnicity was not included as a confounding variable, given that the data set has roughly comparable number of individuals from both ethnicities for the healthy and SSc cohorts. Study participants ranged in age from 37-63 years old. Median age (52 years old) of healthy individuals was comparable to the SSc cohort (~48 years old). Participants were self-described as current/former smokers or non-smokers. Lung tissues were obtained under a protocol approved by the University of Pittsburgh Institutional Review Board. Written informed consent statements were provided to the University of Pittsburgh IRB by the study participants/patients. Sample sizes were determined by the ability of bulk lung fibroblast tissues to stably propagate in culture until single cell clones could be obtained. Samples for which sufficient cell density could not be achieved for downstream high-depth sequencing analysis were excluded from the study and are not reported. Five or greater than 5 samples are collected from each cohort including healthy and SSc patients. Subjects were allocated to two basic cohorts based on diagnosis at the time of explant. Participants with no reported lung anomalies were allocated to the "healthy" cohort, whereas individuals with reported lung abnormalities, primarily SSc with pulmonary fibrosis and/or hypertension were allocated to the "SSc" cohort. All tissue samples were cultured, propagated and processed in identical fashion without requiring individual-specific protocols. Additionally, equivalent amounts of DNA were used for preparing sequencing libraries from both cohorts, and all samples were sequenced using Illumina whole genome sequencing (WGS) and analyzed using identical computational pipelines. Our study primarily discovered that there is a significantly higher burden of somatic mutations in SSc samples, compared to healthy samples. We observed an overall increase in a range of mutations in genomes of SSc patients, including single base substitutions, indels, structural variants and copy number alterations. Additionally, we uncovered a novel mutation signature associated with SSc samples, hinting at the activity of POLH in these samples, and highlighting the potential nexus between inflammation, DNA damage, and cancer.

  Study phs003700

• Prevention and Early Treatment of Acute Lung Injury (PETAL) Acetaminophen in Sepsis: Targeted Therapy to Enhance Recovery (ASTER) (PETAL ASTER-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL ASTER include plasma, urine and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: To determine whether acetaminophen increases days alive and free of organ dysfunction in sepsis participants compared with placebo.Background: Acetaminophen (paracetamol) has many effects that can be beneficial in sepsis treatment, including analgesia, antipyresis, cyclooxygenase-2 inhibition, as well as a potent and specific hemoprotein reduction that can block hemoglobin-induced oxidation of lipids and other substrates. The majority of sepsis participants experience elevated circulating cell-free hemoglobin levels, which is associated with development of organ dysfunction including acute respiratory distress syndrome (ARDS) and death.Acetaminophen has been found in observational studies to be associated with improved survival in critically ill sepsis participants with elevated plasma cell-free hemoglobin, and small clinical trials have had positive sepsis participant outcomes such as reduced plasma biomarkers of lipid peroxidation and improved kidney function. However, a large, randomized trial of acetaminophen administration for treatment of fever in participants with suspected infection did not show a mortality benefit. The NHLBI PETAL Network initiated ASTER as a larger phase trial to examine the utility of plasma cell-free hemoglobin level as a biomarker for future sepsis trials and whether acetaminophen would increase the number of days alive and free of organ support for participants with sepsis and respiratory or circulatory organ dysfunction. Participants: A total of 447 participants were enrolled and randomized, 227 to the acetaminophen arm and 220 to the placebo arm. Data from 40 participants who were randomized to the Vitamin C arm, which was stopped early (see Design section below), is also included.Design: ASTER was a phase 2b multicenter, randomized, double-blind trial. The study originally had a 3-arm platform trial in which participants were randomized 1:1:1 to treatment with intravenous acetaminophen, vitamin C, or a common placebo. The vitamin C arm of the trial was stopped after enrolling 79 participants due to external clinical trial data for vitamin C.Participants randomized to the acetaminophen arm received acetaminophen at the dose of 1 g in 100 mL diluent (or 15 mg/kg if actual body weight was Conclusions: Intravenous acetaminophen was considered to be safe but did not significantly improve days alive and free of organ support in critically ill sepsis participants. There was no significant interaction between cell-free hemoglobin levels and acetaminophen.

  Study phs003900

• A Phase I Study of the Treatment of Recurrent Malignant Glioma with CAN-3110 (AKA rQNestin34.5v.2), a Genetically Engineered HSV-1 Virus

  This study is a "first-in-human" phase 1 trial of recurrent, IDH wild-type glioblastoma (rGBM) patients treated with CAN-3110 (aka rQNestin34.5v.2), a genetically modified oncolytic herpes simplex virus 1 (HSV-1). The study was a 3+3 dose-escalation study starting at a single intra-tumoral injection of 106 PFU CAN-3110 going up to 1010 PFU in half-log increments (cohorts 1-9). An expansion cohort (cohort 10) was treated with 109 PFU injected into up to 5 sites within a single tumor. Principal findings of the study conclude that:CAN-3110 was safe at all tested doses (no dose-limiting toxicities reached)HSV-1 seropositive patients survived significantly longer than HSV-1 seronegative patients in this study - longer than expected based on historical rGBM controlsHSV-1 seropositive patients were significantly more likely to clear CAN-3110 (HSV-1) antigen from their tumors based on immunohistochemical stainingCAN-3110 treatment-induced CD8+/CD4+ T-cell recruitment to injected tumor sites altered TCR beta diversity in both tumor infiltrating leukocytes (TILs) and PBMCs, and initiated changes in specific TCR beta clonotypes and immune gene signatures which were associated with post-treatment survival.Data provided in dbGaP for this study include:Bulk RNA-Seq data for 13 pre/post-treatment pairs of rGBM tumors corresponding to 12 unique patients (patient 28 was treated with CAN-3110 at two different timepoints). This data is provided as raw sequencing reads (.fastq), kallisto pseudoalignment transcript-level read counts (abundance.tsv files), gene-level abundance matrix (Gene_Level_Expression_Matrix.tsv), and immune gene signature scores matrix (Immune_Gene_Signatures_Matrix.tsv). Sequencing was performed as paired 150bp sequencing on NovaSeq6000 S4 Illumina flow cells. Library preparation varied by batch as described in the included RNAseq_Metadata.xlsx table.TCR beta DNA sequencing performed by Adaptive Biotechnologies for 21 pre/post-treatment pairs of rGBM tumors and PBMCs representing 20 unique patients (patient 28 was treated with CAN-3110 at two different timepoints). Note that all tumor pairs with TCR beta sequencing data also have available bulk RNA-Seq data. The TCR beta sequencing data is provided as an excel spreadsheet (TCRbeta_Sample_Overview.xslx), which provides a broad level summary of the sequencing on a per-sample basis (# of TCRbeta templates, T cell fraction, TCR beta diversity metrics, etc.) and as a large tab separated value file (Full_TCRbeta_Rearrangement_Details.tsv), which provides information per sample at the level of each unique TCR beta sequence (amino/nucleic acid sequence, VDJ gene usage, etc.).An excel table of de-identified metadata for the patients involved in this study.

  Study phs003378

• Cryptococcosis in Previously Healthy Adults

  Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

  Study phs003871

• Atezolizumab Plus Personalized Neoantigen Vaccination in Patients with Urothelial Cancer: a Phase 1 Trial

  This is a phase 1 single center clinical trial evaluating a multi-peptide personalized neoantigen vaccine, PGV001, in combination with atezolizumab for patients with urothelial cancer. Patients were enrolled in either the adjuvant or metastatic setting. Those in the adjuvant setting included patients considered high risk of recurrence (pathological stage ypT2-T4 or ypN+ for those treated with prior neoadjuvant chemotherapy or pT3-T4 or pN+ for those not treated with prior neoadjuvant chemotherapy). Those in the metastatic setting included patients progressing after prior chemotherapy or those with at least stable disease after chemotherapy treated as “switch maintenance” therapy. The primary endpoint was feasibility (including the number of neoantigens identified per patient, vaccine production time, the proportion of patients consenting to the vaccine development phase for whom a vaccine product was prepared, and the proportion of patients eligible for the treatment phase who completed the priming cycle 1 of PGV001 plus atezolizumab) and safety. Secondary endpoints included the objective response rate, progression-free survival or disease-free survival, overall survival, and immunomodulatory effects of treatment. Urothelial tumor tissue and normal tissue or peripheral blood specimens were utilized for DNA sequencing. HLA typing was performed utilizing genomic DNA isolated from whole blood, and RNA sequencing was performed utilizing tumor tissue specimens. Neoantigen prediction and final selection for incorporation into the vaccine was determined by the OpenVax computational pipeline. 12 patients were initially enrolled into the vaccine development phase and 10 patients initiated the treatment phase. PGV001 was administered with poly-ICLC and tetanus peptide on subsequent days for up to 10 doses, including an initial priming cycle 1. Atezolizumab was administered every 3 weeks for up to 1 year in the adjuvant setting or 2 years in the metastatic setting. The vaccine was feasible and safe, the median vaccine production time was 20.3 weeks, and 100% of patients that initiated the treatment phase completed the priming cycle. The most common treatment-related adverse events were local grade 1 injection site reactions, fever, and fatigue. Three of the 4 patients in the adjuvant setting remained disease-free at median follow-up of 39.5 months. There was a 40% objective response rate among patients with measurable disease in the metastatic setting. The single patient treated as “switch maintenance” therapy remained with no evidence of disease at 39.4 month follow-up. All patients demonstrated on-treatment neoantigen-specific T cell reactivity, as measured by ELISPOT and flow cytometry assays. Overall, PGV001 plus atezolizumab was feasible, safe, and warrants further investigation. Whole exome sequencing from tumor tissue and normal tissue or whole blood specimens and RNA sequencing from tumor tissue specimens will be available through dbGaP.

  Study phs003922

• Capturing the Genetic Diversity of the Himba Population

  The Himba people are a semi-nomadic, Bantu-speaking pastoralist group from the northwestern Kunene region of Namibia. Because of their limited population size, restricted geographic distribution, and endogamy, founder populations represent an ideal system for genetic analyses due to reduction of the confounding environmental and cultural variables. The original study used genotype data and demographic interview data to understand family dynamics and ancestry in a population of Himba pastoralists. HLA allele calls and genome-wide methylation array data were later generated for a subset of the initial dataset for 2 additional studies. These 3 molecular datasets, available through dbGaP, are relevant to broader studies of ancestry, allele frequencies and the relationship of Himba to other ethnic groups in sub-Saharan Africa. The Himba population provides a unique opportunity to study questions regarding extra-pair paternity and mate selection because Himba culture allows both men and women, married and not, to take multiple partners. Previous estimates of extra-pair paternity rates in human populations have been very low, but these estimates lack global and cultural diversity in population representation. Thus, investigating the rate of extra-pair paternity in the Himba greatly aids in understanding the global variation in non-paternity rates among human populations. Saliva samples were collected from parents and children, and were genotyped on Illumina SNP array platforms (MEGAex and H3Africa). In total, 678 individuals' genotype array data are deposited. Paternity results were de-identified and protected by a double blind protocol (no researcher has full knowledge of individual paternity results). Due to the sensitive nature of this study, paternity assertions are not available for access. For a subset of 360 individuals, HLA class 1 (A, B, C) and class 2 (DPA1, DPB1, DQA1, DQB1, DRB1) genes were targeted for DNA sequencing using a probe-based capture method. HLA alleles at the four field resolution were determined from the sequence capture using the consensus calls obtained from two algorithms: NGSengine® 2.10.0 (GenDX, Utrecht, the Netherlands) and HLA Explore™ (Omixon Biocomputing Ltd. Budapest, Hungary). These data were used to investigate evidence for mate selection based on HLA dissimilarity in the Himba. Himba cultural norms permit concurrent arranged marriages and chosen sexual partnerships allowing us to directly test for evidence of disassortative mate selection based on HLA genotype. Due to the sensitive nature of this study, partnership data are not available for access.For a subset of 51 Himba individuals methylation array data was generated from the saliva-derived DNA. These data were generated in order to investigate the accuracy of epigenetic age predictors in this population and to construct population-specific epigenetic age predictors in a subsequent publication. Chronological ages are available for these 51 individuals.

  Study phs001995

• Exploratory novel biomarker and resistance mechanism of milademetan, an MDM2 inhibitor, in MDM2 amplified intimal sarcoma from an open-label phase 1b/2 trial ���NCCH1806/MK004���

  Amplified Murine double minute 2 (MDM2) is found in > 70% of intimal sarcoma, known as one of the ultra-rare sarcomas. Milademetan (DS3032, RAIN-32) is a novel, specific, small-molecule MDM2 inhibitor that disrupts MDM2 and the tumor suppressor protein p53 interactions in tumor cells. We conducted a phase 1b/2 trial (Trial registration No: JMA-IIA00402) in patients with amplified MDM2 wild-type TP53 intimal sarcoma as a sub-study under the nationwide large registry for rare cancers in Japan (MASTERKEY Project). Eleven patients were enrolled, and ten were included in the efficacy analysis. Two (20%) patients had durable responses for > 15 months. Milademetan provided clinical benefits in patients with amplified MDM2 intimal sarcoma. Predictive biomarkers other than amplified MDM2 and acquired resistance mechanisms for milademetan are unknown. Whole-exome and RNA sequencing analyses of pre-treatment tissue samples were conducted to identify determinants of response. Genomic alterations were analyzed for 10 patients, and gene expression was analyzed for 9 patients using their pre-treatment tissue samples. Targeted sequencing of cell-free DNA (cfDNA) samples (liquid biopsy) was also conducted sequentially at three points [before treatment with milademetan (baseline), at Cycle 2 Day1, and at the time of disease progression] to identify determinants of response and resistance. From whole-exome and RNA sequencing analyses of pre-treatment tissue samples, we could not find any molecular pathways associated with the anti-tumor activity of milademetan. Focusing on 8 genes (CDK4, CDKN2A, CDKN2B, EGFR, ERBB3, MDM2, PDGFRA, TP53) known to be frequently affected in intimal sarcoma and 10 genes (AKT1, ATM, BBC3, CDKN1A, CDKN1C, CHEK2, MDM4, PMAIP1, PPM1D, TWIST1) reported to be associated with MDM2 inhibitor responses; we found that anti-tumor activity correlated with amplified TWIST1 (p-value = 0.028) and negatively with CDKN2A loss (p-value = 0.071). Eight of the 10 patients had their cfDNA collected sequentially at baseline, at Cycle 2 Day1 and disease progression; however, one did not consent to the exploratory analysis study using cfDNA, and one had cfDNA collected at baseline but not at disease progression due to ongoing treatment. Of the eight patients, TP53 mutations in cfDNA were detected in one and five patients at baseline and disease progression, respectively. The cfDNA allele frequency of TP53 mutations increased with disease progression. CDKN2A loss and amplified TWIST1 could be associated with the anti-tumor activity of milademetan in patients with MDM2 amplified intimal sarcoma. Acquired TP53 mutations were detected in sequential liquid biopsies as loss-of-function mutations, and these TP53 mutations might compromise the anti-tumor activity.

  Study JGAS000619

• Privacy Notice for Helpdesk service

  Privacy Notice for EGA Helpdesk service This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from users of the service: Name Email address Job title Date and time when the support request was sent We will use your personal data for the following purposes: To provide uninterrupted user access to the service To better understand the needs of the users and guide future improvements of the service To create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organizations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-helpdesk

• GEnomics and Transcriptomics of Human INsulinoma (GETHIN)

  The Genomics and Transcriptomics of Human Insulinoma (GETHIN) The common forms of diabetes - Types 1 and 2 - ultimately result from a deficiency of insulin-producing pancreatic beta cells. The Genomics and Transcriptomics of Human Insulinoma (GETHIN) study was performed in order to identify novel approaches to inducing human pancreatic beta cells to replicate and regenerate. As a corollary, developing drugs that are able to expand human beta cell mass in people with diabetes should reverse diabetes. Unfortunately, identifying druggable pathways that can enhance human beta cell replication has been a major challenge. In 2017, there is only one class of drugs - the harmine analogues - that can induce human beta cells to replicate, and in this case, higher replication rates are desirable. Thus, identifying additional drugs and druggable pathways is a priority in diabetes research. Insulinomas are rare, benign adenomas of the pancreatic beta cell that cause excess insulin production and hypoglycemia: exactly the opposite of Types 1 and 2 diabetes. Beta cell proliferation rates in insulinomas are abnormally high. Thus, the premise for The Genomics and Transcriptomics of Human Insulinoma study is that benign human insulinomas hold the genomic and transcriptomic "recipe", and the repertoire of druggable pathways, that can be exploited to induce regeneration or replication of human beta cells in diabetes. Because, insulinomas are so rare, are almost always benign (non-malignant), and are easily resected by laparoscopic surgery, little attention has been paid to understanding the genomics or transcriptomics of insulinoma. There are at present only three published studies employing next-gen sequencing in insulinoma (PMID:24326773; PMID:25787250; and PMID:25763608). These studies contained 10, 7 and 8 insulinomas, respectively, and highlighted likely mutations in YY1 and MEN1. Our goal was to markedly expand the database and to add RNAseq to these earlier studies. The GETHIN study reports next-gen sequencing on 38 insulinomas, by far the largest series of human insulinomas subjected to next-gen sequencing (see the Selected publications section for reference). This includes paired (genomic plus tumor) whole exome sequencing on 26 human insulinomas (22 sequenced at Mount Sinai, 4 downloaded from Cao et al, PMID:24326773), and 25 sets of RNAseq from insulinomas, some of which also had paired whole exome sequencing, and some of which did not. The insulinoma RNAseq was compared to RNAseq from 22 sets of FACS-sorted normal human beta cells. Since insulinomas are so rare, the 38 insulinomas were collected by several investigators at several institutions over several decades, but most (22 whole exome sets, and all RNAseq) were sequenced at the Icahn School of Medicine at Mount Sinai in New York. The current dataset contains whole exome sequencing and RNAseq on the 11 insulinomas harvested at Mount Sinai. The four from Cao et al can be retrieved from Cao et al PMID:24326773. Fastq files from the remaining 23 insulinomas will be added as the local IRBs and Institutional Certifications are acquired. Complete patient data are provided in our Nature Communications report. Going forward, our intention is to expand this series, with the goal of sequencing 100 human insulinomas. These will be added to dbGaP as they accrue. Paired-end whole exome sequencing (mean usable sequencing depth 79X and 105X for blood and insulinoma, respectively) was performed using an Illumina HiSeq 2500. Insulinoma and sorted normal beta cell RNAseq was performed on Ribozero and polyA paired end libraries using the Illumina HiSeq 2500. Complete sequencing and bioinformatic details are provided in our Nature Communications report. The principal findings from the study are that although each insulinoma has a different set of presumptive driver mutations, the majority converge on genes that are members of the Polycomb Complex, Trithorax Complex and other epigenetic modifying enzymes. In addition, 20% of insulinomas have copy number loss or loss of heterozygosity of all or most of chromosome 11, and the majority display abnormalities in CpG methylation and imprinting control on the imprinted Chr 11 p15.5-15.4 region that contains INS, IGF2, CDKN1C, KCNQ1, and other genes involved in beta cell specification and proliferation.

  Study phs001422

• Genetic Basis of Early Onset Bicuspid Aortic Valve Disease

  The study protocol was approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston (HSC-MS-11-0185). Study recruitment began on July 1, 2017, and concluded on March 30, 2022. After written informed consent, we enrolled probands with early onset BAV disease (EBAV), which we defined as individuals with BAV who were under the age of 30 at the time of first clinical event. Clinical events were defined as aortic replacement, aortic valve surgery, aortic dissection, moderate or severe aortic stenosis or aortic regurgitation, large aneurysm (Z > 4.5), or intervention for BAV-related conditions. Those with hypoplastic left heart, known genetic mutations, genetic syndromes, or complex congenital heart disease were excluded. Samples were collected and genotyped as previously reported. For comparison, we analyzed a cohort of older individuals of European ancestry with sporadic BAV disease selected from the International BAV Consortium (BAVGWAS). Phenotypes were derived from record review with confirmation of image data whenever possible [25-26]. The computational pipeline for CNV analysis of Illumina single nucleotide polymorphism (SNP) array data included three independent CNV detection algorithms.GenomeStudio was used to exclude samples with indeterminate sex or more than 5% missing genotypes, and single nucleotide polymorphisms (SNPs) with GenTrain = 0. Principal component analysis was used to remove outliers that did not cluster with European ancestry. Prior to CNV analysis, each dataset was trimmed by selecting a common set of 650,000 SNPs that were genotyped on each of the microarrays used in this study.Three independent algorithms (PennCNV, cnvPartition, and QuantiSNP) were used to generate CNV calls and sample-level quality statistics from SNP intensity data. PennCNV and QuantiSNP were run on Unix clusters and cnvPartition data were exported from GenomeStudio. The analysis was run using default configurations. PennCNV was used to generate QC data and remove CNV calls that intersect with polymorphic genomic regions. Samples that met any of the following criteria were excluded, standard deviation of the LogR ratio (obtained from PennCNV) > 0.35 or number of CNVs > 2 standard deviations above the mean for each data set. CNV calls less than 20 Kilobases in length and/or spanned by fewer than 6 probes were excluded. The overlap function for rare CNVs in PLINK was used to construct CNV regions (CNVRs) after adjacent regions were merged using PennCNV. LogR ratio (LRR) and B allele frequency (BAF) data at CNVRs and calls of interest were visualized in GenomeStudio for validation. For segregation analysis, GenomeStudio was used to determine the presence of CNVs in relatives.A total of 22,014 unselected control Illumina Genotypes obtained from the Database of Genotypes and Phenotypes were analyzed using identical methods (S1 Table). The Wisconsin Longitudinal Study (WLS) includes data on a cohort of 10,300 individuals who graduated from Wisconsin high schools in 1957. The Health and Retirement Study (HRS) includes data on 37,000 individuals aged 50 above from 23,000 households across the United States. Principal component analysis was used to select European ancestry genotypes from these datasets for analysis. Datasets were paired for case-control analysis based on the concordance of log-transformed sample-level quality control statistics (number of CNV calls and standard deviation of logR ratios). Chi-squared or Fisher exact tests were used to compare CNV frequencies in cases and controls.Rare CNV functions in PLINK (v1.7) were used to perform permutation-based burden tests or gene set-based enrichment tests. Case control burden tests were restricted to CNVs that were longer than 110 Kb and less than 0.1% in frequency. CNV overlap functions in PLINK were used to identify rare CNVs that intersect between datasets or involve specific BAV or CHD genes . The list of candidate genes included 190 CHD genes that have strong cumulative evidence to cause BAV or related congenital malformations from human or animal model data. Genome Reference Consortium Human Build 37 was used for CNV annotation [34].

  Study phs003705

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study: Whole Exome Resequencing in Glaucoma

  This is a study of primary open angle glaucoma (POAG) conducted through exome sequencing of cases and comparison of variant frequencies with general population frequencies available in dbGAP and controlled for sequencing platform artifact to minimize false positives. POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. This study builds upon the efforts of an on-going collaborative consortium that studied 2,170 POAG cases and 2,347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition for NEIGHBOR was harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). In NEIGHBOR, cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The Glaucoma Exome Sequencing study has one Principal Investigator: Theresa Gaasterland (UCSD) and two Co-Investigators: Robert Weinreb, MD, and Kang Zhang, MD, PhD, all of whom are part of the NEIGHBOR, subsequently NEIGHBORHOOD, consortium, which in turn has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). NEIGHBOR collaborators who contributed samples and/or expertise to the Glaucoma Exome Sequencing study included the following: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollenstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland), Marshfield Clinic (Cathy McCarty). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping through exome sequencing, which was performed at the University of California, San Diego, was provided by the National Eye Institute (RC2 EY020678-01).

  Study phs000558

• Biological Determinants of Peritoneal Dialysis Outcomes

  Peritoneal Dialysis (PD) is a technique for treating kidney failure where fluid is instilled into the body's peritoneal cavity. Fluid and solutes travel across the peritoneum, and this is critical to successful PD. Studies have shown that certain demographic and clinical variables explain a small part of the variability in baseline peritoneal solute transfer rate and water transfer function across the peritoneum. This study sought to identify the common genetic variants associated with the baseline peritoneal function in patients starting treatment with PD and change in function upon treatment with PD. This study has two specific aims: Aim 1: To identify and validate genetic loci that influence the peritoneal solute transfer rate (PSTR) at start of PD. Aim 2: To identify and validate genetic loci in pre-specified biologic pathways with change in peritoneal ultrafiltration capacity. This study incorporates data from participants' peritoneal solute transfer rate in their first ever peritoneal equilibrium test (PET) and changes in the transfer of water across the peritoneal membrane over time in a sub-group of participants, demographic information, and results from laboratory analysis of DNA, blood, and dialysate. This study comprises patient populations from pre-existing biorepositories in Europe, and prospectively enrolled participants in United States, Canada, United Kingdom, and Australia. Clinical data related to the participants' peritoneal solute transfer rate from their first ever Peritoneal Equilibrium Test (PET), demographic information, and change in ultrafiltration capacity over time, are correlated with various genetic markers of interest. For individuals enrolled prospectively, blood and dialysate were collected at the first study visit. Annually, subjects either underwent a PET as standard of care or perform an additional 4-hour dwell as part of the study. These subsequent measures were utilized to determine change in ultrafiltration capacity over time. Inclusion criteria included adults over the age of 20 who are able to provide consent and had a record of a PET within 6 months of starting PD. Subjects with missing outcome data and that did not pass genotyping QC were excluded. Genotyping was performed in two batches using the Illumina InfiniumOmni2-5-8v1-3_A1 array with 2,372,784 single nucleotide variants (SNVs) in the first batch (n=1957). The second genotyping batch (n=1053) was on the InfiniumOmni2-5-8v1-4_A1 array with 2,382,209 SNVs. Imputation was performed using the Michigan Imputation Server and the HRC1.1 genotype reference. The Institutional Review Board of the University of Washington has “dbGaP-certified” the consent forms used to enroll participants in Australia, Canada, and United States and the genotype-phenotype data from the participants (n=827) deposited in the public repository. Furthermore, it has been determined that under the EU-GDPR regulations, depositing data of participants enrolled in UK, Belgium, and Sweden (n=2,023) into dbGaP “serves no lawful purpose” as the consent form used for enrolling participants did not obtain explicit permission for depositing data in a public repository.

  Study phs002996

• Whole-Genome Sequencing in Multiplex Epilepsy Families

  Epilepsy is one of the most common neurologic disorders, affecting approximately 4% of individuals at some time in their lives. More than 30% of people with epilepsy continue to have seizures despite treatment, and improved approaches to treatment and prevention are sorely needed. In the search for new strategies to reduce the burden of disease, the discovery of specific genes that influence risk offers a novel opportunity to clarify pathogenic mechanisms, identify susceptible individuals prior to seizure onset, and treat and prevent seizures in people at risk. Despite clear evidence of the importance of genetics in susceptibility to epilepsy, only limited progress has been made in identifying the specific genes that influence risk. One of the greatest challenges for genetic research on this disorder is its extreme clinical and genetic heterogeneity. Although epilepsy is broadly defined by recurrent unprovoked seizures, it is so variable in its clinical manifestations, natural history, and treatment response that most epileptologists view it as a collection of different syndromes ("epilepsies") with distinct etiologies. The genetic effects on susceptibility are also likely to be extremely variable, ranging from rare variants with high penetrance (some of which produce Mendelian patterns of inheritance) to common variants with low penetrance. Recent findings strongly suggest that rare gene variants play a major role in the genetic architecture of the epilepsies. The purpose of this study was to discover new genetic risk factors for epilepsy. The primary approach was to use whole-genome sequencing to interrogate classes of genetic variants, including very rare variants, in multiplex families. Our main hypothesis was that, in at least some proportion of these families, a single variant would explain all instances of epilepsy. Variants identified within the families could then be tested for cosegregation within the family and also validated by seeing enrichment in sporadic epilepsy cases. Furthermore, understanding the impact of rare variation in epilepsy also has the potential to provide insight into the genetic architecture of other complex human diseases. Our analysis focused on families containing multiple individuals with non-acquired (idiopathic or unknown cause) epilepsy under the hypothesis that these would be enriched for genetic control. The families studied had been previously collected and phenotyped in detail, and contain an average of 3.8 individuals per family with a range of different types of epilepsy. We selected one or two affected individuals from each family for sequencing. This work has generated NGS data on 60 samples from 29 multiplex epilepsy families. We have established that, under a monogenic model of inheritance, sequencing pairs of distantly related relatives is an effective method for reducing the number of candidate variants. Critically, we have found that no single variant can explain a large proportion of these epilepsy families. This work emphasizes that identifying causal variants among the many genetic candidates found in this work will require very large sample sizes and gene-based analyses.

  Study phs000690

• CIDR: NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

  Recessive forms for many structural brain disorders (SBDs), including cerebellar hypoplasia (CBH), corpus callosum hypoplasia (CCH), cobblestone lissencephaly (COB), classical lissencephaly (LIS), microcephaly (MIC), and pontocerebellar hypoplasia (PCH), have been described. Patients usually present to the clinic with neurodevelopmental disorders (NDDs), including autism, epilepsy, intellectual disability, and cerebral palsy. Subsequent brain MRI usually leads to the diagnosis of an SBD. While a handful of genes that cause these diseases have been identified, most patients do not have mutations in these genes, suggesting that there is still much work to be done in identifying the genetic causes of these disorders. We have recruited a cohort of families with inherited SBDs, most from families with documented parental consanguinity with more than one affected member. Current approaches utilizing exome sequencing of SBD affected members still leave most cases unsolved, in part because there are too many possible variants to consider. Linkage analysis will allow us to extract all the useful genetic information from the family, taking advantage of each genetically informative meiosis in each family. We propose to analyze up to 100 SBD families for 500 samples per year for 4 years, through the CIDR SNP Genotyping Service, in parallel with already-funded exome sequencing of affects, leveraging off an already funded Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) effort to identify new causes of SBDs. Understanding the pathogenetic mechanisms underlying recessive pediatric SBDs will lead to better diagnostic and therapeutic opportunities for patients, and may shed light on complex NDDs. Ultimately, this work will identify new genetic disease loci to provide insight into pediatric SBD, with the hope to mitigate the impact of SBD worldwide.Public Health Significance: NDDs affect approximately 4-­6% of the general population, most notably children, and are evident in disorders, such as intellectual disability, epilepsy, and autism, with estimated yearly costs of $51.2B for intellectual disability, $11.5B for cerebral palsy, and $2.5B for visual impairment, making up >5% of total health care costs. Recessive NDDs impose enormous personal, social, and economic costs because of the early onset and the lifetime of medical dependence that often ensues. Genetic testing is critical to the diagnosis and treatment of these diseases. Many of the diseases under study have no treatment or cure. Structural brain diseases (SBDs) underlie a large percentage of these diseases, and are defined loosely as any condition in which defects in the structure or volume of a key brain component. SBDs are divided into major categories based upon the anatomical brain location. The major types involve the anatomical structures of the developing neural tube, forebrain, hindbrain, cerebral cortex, and those affecting overall brain size. For the purposes of this application, we have excluded SBDs resulting from environmental causes (i.e. prematurity-­induced), those below the brainstem, or those unlikely to be due to a germline or de novo mutation (i.e. focal SBDs or simplex disease).

  Study phs002621

• Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP): COVID-19 Testing and Vaccination Social Network Diffusion for Diverse Criminal Legal Involved Communities

  This RADx-UP Phase II proposal, "Social network diffusion of COVID-19 prevention for diverse Criminal Legal Involved Communities", will implement a situation appropriate COVID-19 testing and vaccination social network diffusion intervention - C3 - building upon RADx-UP Phase I lessons and successful social network prevention interventions developed previously by the research team. C3 Criminal Legal Involved (CLI) populations encompass those non-incarcerated who have experienced recent arrest, incarceration, probation, parole or diversion programs such as drug courts. While increases in COVID-19 testing have been observed among this group, there remain members with limited testing history as well as individuals who are vaccine hesitant. COVID-19 prevention messaging can no longer be simplified to "everyone test and/or everyone vaccinate" as testing and vaccination decisions among community members are sensitive to personal histories (i.e., prior infection), local infection rates (i.e., low rates) and testing/vaccination availability. As COVID-19 prevention efforts have become more complicated (i.e., test if exposed), people tend to focus on the messenger, and particularly those that are close to them. Personal connections and communications within existing personal network structures, such as families, friends and other trusted acquaintances represent the cornerstone to increase situation appropriate testing and overcoming COVID-19 vaccine hesitancy. C3 builds upon RADx-UP I, by using a network diffusion approach facilitated through motivational interviewing purposefully geared to mobilize one's own organic social network to increase context appropriate testing and vaccine uptake. Through this process we will maximize the primary benefit and impact of this type of intervention which also has the intended effect of increasing likelihood that the messenger themselves will undergo the same behavior change that they have been trained to promote. We will leverage infrastructure developed in RADx-UP Phase I, which includes 4 high-impact sites across the Central US from Phase I: Baton Rouge LA, Little Rock AR, Indianapolis IN, and Chicago IL. We will utilize established engagement efforts already in place and continue to fully integrate communities in the strategic application of the intervention. We will use the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework to guide implementation. C3 aims to: Aim 1a. Test the efficacy (3-month situation appropriate testing or vaccination) of a network diffusion intervention (C3) versus an existing COVID-19 testing and vaccine linkage to care intervention among: 1) primary study participants (primary outcome); and 2) secondary study participants connected to primary participants (secondary outcome) using a RCT design. Aim 1b. Explore the mechanisms for differential intervention effects at the individual and network-level that may increase situation appropriate testing and/or vaccination uptake. Aim 2. Examine key RE-AIM components in real time tied to the implementation of the network diffusion intervention (C3).

  Study phs003234

• Heart Failure Network: Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEF (HFN INDIE-BioLINCC)

  Data Access NOTEPlease refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.ObjectiveTo determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction. Background Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF. Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first. Design HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇O2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e' ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected. Conclusions Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity. Borlaug et al., 2018, PMID: 30398602.

  Study phs003667

• OncoArray: Prostate Cancer

  Original description of the study: From ELLIPSE (linked to the PRACTICAL consortium), we contributed ~78,000 SNPs to the OncoArray. A large fraction of the content was derived from the GWAS meta-analyses in European ancestry populations (overall and aggressive disease; ~27K SNPs). We also selected just over 10,000 SNPs from the meta-analyses in the non-European populations, with a majority of these SNPs coming from the analysis of overall prostate cancer in African ancestry populations as well as from the multiethnic meta-analysis. A substantial fraction of SNPs (~28,000) were also selected for fine-mapping of 53 loci not included in the common fine-mapping regions (tagging at r2>0.9 across ±500kb regions). We also selected a few thousand SNPs related with PSA levels and/or disease survival as well as SNPs from candidate lists provided by study collaborators, as well as from meta-analyses of exome SNP chip data from the Multiethnic Cohort and UK studies. The Contributing Studies: Aarhus: Hospital-based, Retrospective, Observational. Source of cases: Patients treated for prostate adenocarcinoma at Department of Urology, Aarhus University Hospital, Skejby (Aarhus, Denmark). Source of controls: Age-matched males treated for myocardial infarction or undergoing coronary angioplasty, but with no prostate cancer diagnosis based on information retrieved from the Danish Cancer Register and the Danish Cause of Death Register. AHS: Nested case-control study within prospective cohort. Source of cases: linkage to cancer registries in study states. Source of controls: matched controls from cohort ATBC: Prospective, nested case-control. Source of cases: Finnish male smokers aged 50-69 years at baseline. Source of controls: Finnish male smokers aged 50-69 years at baseline BioVu: Cases identified in a biobank linked to electronic health records. Source of cases: A total of 214 cases were identified in the VUMC de-identified electronic health records database (the Synthetic Derivative) and shipped to USC for genotyping in April 2014. The following criteria were used to identify cases: Age 18 or greater; male; African Americans (Black) only. Note that African ancestry is not self-identified, it is administratively or third-party assigned (which has been shown to be highly correlated with genetic ancestry for African Americans in BioVU; see references). Source of controls: Controls were identified in the de-identified electronic health record. Unfortunately, they were not age matched to the cases, and therefore cannot be used for this study. Canary PASS: Prospective, Multi-site, Observational Active Surveillance Study. Source of cases: clinic based from Beth Israel Deaconness Medical Center, Eastern Virginia Medical School, University of California at San Francisco, University of Texas Health Sciences Center San Antonio, University of Washington, VA Puget Sound. Source of controls: N/A CCI: Case series, Hospital-based. Source of cases: Cases identified through clinics at the Cross Cancer Institute. Source of controls: N/A CerePP French Prostate Cancer Case-Control Study (ProGene): Case-Control, Prospective, Observational, Hospital-based. Source of cases: Patients, treated in French departments of Urology, who had histologically confirmed prostate cancer. Source of controls: Controls were recruited as participating in a systematic health screening program and found unaffected (normal digital rectal examination and total PSA < 4 ng/ml, or negative biopsy if PSA > 4 ng/ml). COH: hospital-based cases and controls from outside. Source of cases: Consented prostate cancer cases at City of Hope. Source of controls: Consented unaffected males that were part of other studies where they consented to have their DNA used for other research studies. COSM: Population-based cohort. Source of cases: General population. Source of controls: General population CPCS1: Case-control - Denmark. Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPCS2: Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPDR: Retrospective cohort. Source of cases: Walter Reed National Military Medical Center. Source of controls: Walter Reed National Military Medical Center ACS_CPS-II: Nested case-control derived from a prospective cohort study. Source of cases: Identified through self-report on follow-up questionnaires and verified through medical records or cancer registries, identified through cancer registries or the National Death Index (with prostate cancer as the primary cause of death). Source of controls: Cohort participants who were cancer-free at the time of diagnosis of the matched case, also matched on age (±6 mo) and date of biospecimen donation (±6 mo). EPIC: Case-control - Germany, Greece, Italy, Netherlands, Spain, Sweden, UK. Source of cases: Identified through record linkage with population-based cancer registries in Italy, the Netherlands, Spain, Sweden and UK. In Germany and Greece, follow-up is active and achieved through checks of insurance records and cancer and pathology registries as well as via self-reported questionnaires; self-reported incident cancers are verified through medical records. Source of controls: Cohort participants without a diagnosis of cancer EPICAP: Case-control, Population-based, ages less than 75 years at diagnosis, Hérault, France. Source of cases: Prostate cancer cases in all public hospitals and private urology clinics of département of Hérault in France. Cases validation by the Hérault Cancer Registry. Source of controls: Population-based controls, frequency age matched (5-year groups). Quotas by socio-economic status (SES) in order to obtain a distribution by SES among controls identical to the SES distribution among general population men, conditionally to age. ERSPC: Population-based randomized trial. Source of cases: Men with PrCa from screening arm ERSPC Rotterdam. Source of controls: Men without PrCa from screening arm ERSPC Rotterdam ESTHER: Case-control, Prospective, Observational, Population-based. Source of cases: Prostate cancer cases in all hospitals in the state of Saarland, from 2001-2003. Source of controls: Random sample of participants from routine health check-up in Saarland, in 2000-2002 FHCRC: Population-based, case-control, ages 35-74 years at diagnosis, King County, WA, USA. Source of cases: Identified through the Seattle-Puget Sound SEER cancer registry. Source of controls: Randomly selected, age-frequency matched residents from the same county as cases Gene-PARE: Hospital-based. Source of cases: Patients that received radiotherapy for treatment of prostate cancer. Source of controls: n/a Hamburg-Zagreb: Hospital-based, Prospective. Source of cases: Prostate cancer cases seen at the Department of Oncology, University Hospital Center Zagreb, Croatia. Source of controls: Population-based (Croatia), healthy men, older than 50, with no medical record of cancer, and no family history of cancer (1st & 2nd degree relatives) HPFS: Nested case-control. Source of cases: Participants of the HPFS cohort. Source of controls: Participants of the HPFS cohort IMPACT: Observational. Source of cases: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has been diagnosed with prostate cancer during the study. Source of controls: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has not been diagnosed with prostate cancer during the study. IPO-Porto: Hospital-based. Source of cases: Early onset and/or familial prostate cancer. Source of controls: Blood donors Karuprostate: Case-control, Retrospective, Population-based. Source of cases: From FWI (Guadeloupe): 237 consecutive incident patients with histologically confirmed prostate cancer attending public and private urology clinics; From Democratic Republic of Congo: 148 consecutive incident patients with histologically confirmed prostate cancer attending the University Clinic of Kinshasa. Source of controls: From FWI (Guadeloupe): 277 controls recruited from men participating in a free systematic health screening program open to the general population; From Democratic Republic of Congo: 134 controls recruited from subjects attending the University Clinic of Kinshasa KULEUVEN: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases recruited at the University Hospital Leuven. Source of controls: Healthy males with no history of prostate cancer recruited at the University Hospitals, Leuven. LAAPC: Subjects were participants in a population-based case-control study of aggressive prostate cancer conducted in Los Angeles County. Cases were identified through the Los Angeles County Cancer Surveillance Program rapid case ascertainment system. Eligible cases included African American, Hispanic, and non-Hispanic White men diagnosed with a first primary prostate cancer between January 1, 1999 and December 31, 2003. Eligible cases also had (a) prostatectomy with documented tumor extension outside the prostate, (b) metastatic prostate cancer in sites other than prostate, (c) needle biopsy of the prostate with Gleason grade ≥8, or (d) needle biopsy with Gleason grade 7 and tumor in more than two thirds of the biopsy cores. Eligible controls were men never diagnosed with prostate cancer, living in the same neighborhood as a case, and were frequency matched to cases on age (± 5 y) and race/ethnicity. Controls were identified by a neighborhood walk algorithm, which proceeds through an obligatory sequence of adjacent houses or residential units beginning at a specific residence that has a specific geographic relationship to the residence where the case lived at diagnosis. Malaysia: Case-control. Source of cases: Patients attended the outpatient urology or uro-onco clinic at University Malaya Medical Center. Source of controls: Population-based, age matched (5-year groups), ascertained through electoral register, Subang Jaya, Selangor, Malaysia MCC-Spain: Case-control. Source of cases: Identified through the urology departments of the participating hospitals. Source of controls: Population-based, frequency age and region matched, ascertained through the rosters of the primary health care centers MCCS: Nested case-control, Melbourne, Victoria. Source of cases: Identified by linkage to the Victorian Cancer Registry. Source of controls: Cohort participants without a diagnosis of cancer MD Anderson: Participants in this study were identified from epidemiological prostate cancer studies conducted at the University of Texas MD Anderson Cancer Center in the Houston Metropolitan area. Cases were accrued in the Houston Medical Center and were not restricted with respect to Gleason score, stage or PSA. Controls were identified via random-digit-dialing or among hospital visitors and they were frequency matched to cases on age and race. Lifestyle, demographic, and family history data were collected using a standardized questionnaire. MDACC_AS: A prospective cohort study. Source of cases: Men with clinically organ-confined prostate cancer meeting eligibility criteria for a prospective cohort study of active surveillance at MD Anderson Cancer Center. Source of controls: N/A MEC: The Multiethnic Cohort (MEC) is comprised of over 215,000 men and women recruited from Hawaii and the Los Angeles area between 1993 and 1996. Between 1995 and 2006, over 65,000 blood samples were collected from participants for genetic analyses. To identify incident cancer cases, the MEC was cross-linked with the population-based Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii, and unaffected cohort participants with blood samples were selected as controls MIAMI (WFPCS): Prostate cancer cases and controls were recruited from the Departments of Urology and Internal Medicine of the Wake Forest University School of Medicine using sequential patient populations as described previously (PMID:15342424). All study subjects received a detailed description of the study protocol and signed their informed consent, as approved by the medical center's Institutional Review Board. The general eligibility criteria were (i) able to comprehend informed consent and (ii) without previously diagnosed cancer. The exclusion criteria were (i) clinical diagnosis of autoimmune diseases; (ii) chronic inflammatory conditions; and (iii) infections within the past 6 weeks. Blood samples were collected from all subjects. MOFFITT: Hospital-based. Source of cases: clinic based from Moffitt Cancer Center. Source of controls: Moffitt Cancer Center affiliated Lifetime cancer screening center NMHS: Case-control, clinic based, Nashville TN. Source of cases: All urology clinics in Nashville, TN. Source of controls: Men without prostate cancer at prostate biopsy. PCaP: The North Carolina-Louisiana Prostate Cancer Project (PCaP) is a multidisciplinary population-based case-only study designed to address racial differences in prostate cancer through a comprehensive evaluation of social, individual and tumor level influences on prostate cancer aggressiveness. PCaP enrolled approximately equal numbers of African Americans and Caucasian Americans with newly-diagnosed prostate cancer from North Carolina (42 counties) and Louisiana (30 parishes) identified through state tumor registries. African American PCaP subjects with DNA, who agreed to future use of specimens for research, participated in OncoArray analysis. PCMUS: Case-control - Sofia, Bulgaria. Source of cases: Patients of Clinic of Urology, Alexandrovska University Hospital, Sofia, Bulgaria, PrCa histopathologically confirmed. Source of controls: 72 patients with verified BPH and PSA<3,5; 78 healthy controls from the MMC Biobank, no history of PrCa PHS: Nested case-control. Source of cases: Participants of the PHS1 trial/cohort. Source of controls: Participants of the PHS1 trial/cohort PLCO: Nested case-control. Source of cases: Men with a confirmed diagnosis of prostate cancer from the PLCO Cancer Screening Trial. Source of controls: Controls were men enrolled in the PLCO Cancer Screening Trial without a diagnosis of cancer at the time of case ascertainment. Poland: Case-control. Source of cases: men with unselected prostate cancer, diagnosed in north-western Poland at the University Hospital in Szczecin. Source of controls: cancer-free men from the same population, taken from the healthy adult patients of family doctors in the Szczecin region PROCAP: Population-based, Retrospective, Observational. Source of cases: Cases were ascertained from the National Prostate Cancer Register of Sweden Follow-Up Study, a retrospective nationwide cohort study of patients with localized prostate cancer. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PROGReSS: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases from the Hospital Clínico Universitario de Santiago de Compostela, Galicia, Spain. Source of controls: Cancer-free men from the same population ProMPT: A study to collect samples and data from subjects with and without prostate cancer. Retrospective, Experimental. Source of cases: Subjects attending outpatient clinics in hospitals. Source of controls: Subjects attending outpatient clinics in hospitals ProtecT: Trial of treatment. Samples taken from subjects invited for PSA testing from the community at nine centers across United Kingdom. Source of cases: Subjects who have a proven diagnosis of prostate cancer following testing. Source of controls: Identified through invitation of subjects in the community. PROtEuS: Case-control, population-based. Source of cases: All new histologically-confirmed cases, aged less or equal to 75 years, diagnosed between 2005 and 2009, actively ascertained across Montreal French hospitals. Source of controls: Randomly selected from the Provincial electoral list of French-speaking men between 2005 and 2009, from the same area of residence as cases and frequency-matched on age. QLD: Case-control. Source of cases: A longitudinal cohort study (Prostate Cancer Supportive Care and Patient Outcomes Project: ProsCan) conducted in Queensland, through which men newly diagnosed with prostate cancer from 26 private practices and 10 public hospitals were directly referred to ProsCan at the time of diagnosis by their treating clinician (age range 43-88 years). All cases had histopathologically confirmed prostate cancer, following presentation with an abnormal serum PSA and/or lower urinary tract symptoms. Source of controls: Controls comprised healthy male blood donors with no personal history of prostate cancer, recruited through (i) the Australian Red Cross Blood Services in Brisbane (age range 19-76 years) and (ii) the Australian Electoral Commission (AEC) (age and post-code/ area matched to ProsCan, age range 54-90 years). RAPPER: Multi-centre, hospital based blood sample collection study in patients enrolled in clinical trials with prospective collection of radiotherapy toxicity data. Source of cases: Prostate cancer patients enrolled in radiotherapy trials: CHHiP, RT01, Dose Escalation, RADICALS, Pelvic IMRT, PIVOTAL. Source of controls: N/A SABOR: Prostate Cancer Screening Cohort. Source of cases: Men >45 yrs of age participating in annual PSA screening. Source of controls: Males participating in annual PSA prostate cancer risk evaluations (funded by NCI biomarkers discovery and validation grant), recruited through University of Texas Health Science Center at San Antonio and affiliated sites or through study advertisements, enrolment open to the community SCCS: Case-control in cohort, Southeastern USA. Prospective, Observational, Population-based. Source of cases: SCCS entry population. Source of controls: SCCS entry population SCPCS: Population-based, Retrospective, Observational. Source of cases: South Carolina Central Cancer Registry. Source of controls: Health Care Financing Administration beneficiary file SEARCH: Case-control - East Anglia, UK. Source of cases: Men < 70 years of age registered with prostate cancer at the population-based cancer registry, Eastern Cancer Registration and Information Centre, East Anglia, UK. Source of controls: Men attending general practice in East Anglia with no known prostate cancer diagnosis, frequency matched to cases by age and geographic region SNP_Prostate_Ghent: Hospital-based, Retrospective, Observational. Source of cases: Men treated with IMRT as primary or postoperative treatment for prostate cancer at the Ghent University Hospital between 2000 and 2010. Source of controls: Employees of the University hospital and members of social activity clubs, without a history of any cancer. SPAG: Hospital-based, Retrospective, Observational. Source of cases: Guernsey. Source of controls: Guernsey STHM2: Population-based, Retrospective, Observational. Source of cases: Cases were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PCPT: Case-control from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial SELECT: Case-cohort from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial TAMPERE: Case-control - Finland, Retrospective, Observational, Population-based. Source of cases: Identified through linkage to the Finnish Cancer Registry and patient records; and the Finnish arm of the ERSPC study. Source of controls: Cohort participants without a diagnosis of cancer UGANDA: Uganda Prostate Cancer Study: Uganda is a case-control study of prostate cancer in Kampala Uganda that was initiated in 2011. Men with prostate cancer were enrolled from the Urology unit at Mulago Hospital and men without prostate cancer (i.e. controls) were enrolled from other clinics (i.e. surgery) at the hospital. UKGPCS: ICR, UK. Source of cases: Cases identified through clinics at the Royal Marsden hospital and nationwide NCRN hospitals. Source of controls: Ken Muir's control- 2000 ULM: Case-control - Germany. Source of cases: familial cases (n=162): identified through questionnaires for family history by collaborating urologists all over Germany; sporadic cases (n=308): prostatectomy series performed in the Clinic of Urology Ulm between 2012 and 2014. Source of controls: age-matched controls (n=188): age-matched men without prostate cancer and negative family history collected in hospitals of Ulm WUGS/WUPCS: Cases Series, USA. Source of cases: Identified through clinics at Washington University in St. Louis. Source of controls: Men diagnosed and managed with prostate cancer in University based clinic. Acknowledgement Statements: Aarhus: This study was supported by the Danish Strategic Research Council (now Innovation Fund Denmark) and the Danish Cancer Society. The Danish Cancer Biobank (DCB) is acknowledged for biological material. AHS: This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119). ATBC: This research was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C, and HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services. BioVu: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding and by the National Center for Research Resources, Grant UL1 RR024975-01 (which is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). Canary PASS: PASS was supported by Canary Foundation and the National Cancer Institute's Early Detection Research Network (U01 CA086402) CCI: This work was awarded by Prostate Cancer Canada and is proudly funded by the Movember Foundation - Grant # D2013-36.The CCI group would like to thank David Murray, Razmik Mirzayans, and April Scott for their contribution to this work. CerePP French Prostate Cancer Case-Control Study (ProGene): None reported COH: SLN is partially supported by the Morris and Horowitz Families Endowed Professorship COSM: The Swedish Research Council, the Swedish Cancer Foundation CPCS1 & CPCS2: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, DenmarkCPCS1 would like to thank the participants and staff of the Copenhagen General Population Study for their important contributions. CPDR: Uniformed Services University for the Health Sciences HU0001-10-2-0002 (PI: David G. McLeod, MD) CPS-II: The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. CPS-II thanks the participants and Study Management Group for their invaluable contributions to this research. We would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. EPIC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); the Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation, Greek Ministry of Health; Greek Ministry of Education (Greece); the Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); the Statistics Netherlands (The Netherlands); the Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, Spanish Ministry of Health ISCIII RETIC (RD06/0020), Red de Centros RCESP, C03/09 (Spain); the Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and Västerbotten, Fundacion Federico SA (Sweden); the Cancer Research UK, Medical Research Council (United Kingdom). EPICAP: The EPICAP study was supported by grants from Ligue Nationale Contre le Cancer, Ligue départementale du Val de Marne; Fondation de France; Agence Nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES). The EPICAP study group would like to thank all urologists, Antoinette Anger and Hasina Randrianasolo (study monitors), Anne-Laure Astolfi, Coline Bernard, Oriane Noyer, Marie-Hélène De Campo, Sandrine Margaroline, Louise N'Diaye, and Sabine Perrier-Bonnet (Clinical Research nurses). ERSPC: This study was supported by the DutchCancerSociety (KWF94-869,98-1657,2002-277,2006-3518, 2010-4800), The Netherlands Organisation for Health Research and Development (ZonMW-002822820, 22000106, 50-50110-98-311, 62300035), The Dutch Cancer Research Foundation (SWOP), and an unconditional grant from Beckman-Coulter-HybritechInc. ESTHER: The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. The ESTHER group would like to thank Hartwig Ziegler, Sonja Wolf, Volker Hermann, Heiko Müller, Karina Dieffenbach, Katja Butterbach for valuable contributions to the study. FHCRC: The FHCRC studies were supported by grants R01-CA056678, R01-CA082664, and R01-CA092579 from the US National Cancer Institute, National Institutes of Health, with additional support from the Fred Hutchinson Cancer Research Center. FHCRC would like to thank all the men who participated in these studies. Gene-PARE: The Gene-PARE study was supported by grants 1R01CA134444 from the U.S. National Institutes of Health, PC074201 and W81XWH-15-1-0680 from the Prostate Cancer Research Program of the Department of Defense and RSGT-05-200-01-CCE from the American Cancer Society. Hamburg-Zagreb: None reported HPFS: The Health Professionals Follow-up Study was supported by grants UM1CA167552, CA133891, CA141298, and P01CA055075. HPFS are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. IMPACT: The IMPACT study was funded by The Ronald and Rita McAulay Foundation, CR-UK Project grant (C5047/A1232), Cancer Australia, AICR Netherlands A10-0227, Cancer Australia and Cancer Council Tasmania, NIHR, EU Framework 6, Cancer Councils of Victoria and South Australia, and Philanthropic donation to Northshore University Health System. We acknowledge support from the National Institute for Health Research (NIHR) to the Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden Foundation NHS Trust. IMPACT acknowledges the IMPACT study steering committee, collaborating centres, and participants. IPO-Porto: The IPO-Porto study was funded by Fundaçäo para a Ciência e a Tecnologia (FCT; UID/DTP/00776/2013 and PTDC/DTP-PIC/1308/2014) and by IPO-Porto Research Center (CI-IPOP-16-2012 and CI-IPOP-24-2015). MC and MPS are research fellows from Liga Portuguesa Contra o Cancro, Núcleo Regional do Norte. SM is a research fellow from FCT (SFRH/BD/71397/2010). IPO-Porto would like to express our gratitude to all patients and families who have participated in this study. Karuprostate: The Karuprostate study was supported by the the Frech National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la ProstateKarusprostate thanks Séverine Ferdinand. KULEUVEN: F.C. and S.J. are holders of grants from FWO Vlaanderen (G.0684.12N and G.0830.13N), the Belgian federal government (National Cancer Plan KPC_29_023), and a Concerted Research Action of the KU Leuven (GOA/15/017). TVDB is holder of a doctoral fellowship of the FWO. LAAPC: This study was funded by grant R01CA84979 (to S.A. Ingles) from the National Cancer Institute, National Institutes of Health. Malaysia: The study was funded by the University Malaya High Impact Research Grant (HIR/MOHE/MED/35). Malaysia thanks all associates in the Urology Unit, University of Malaya, Cancer Research Initiatives Foundation (CARIF) and the Malaysian Men's Health Initiative (MMHI). MCCS: MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MCC-Spain: The study was partially funded by the Accion Transversal del Cancer, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI09/00773-Cantabria, PI11/01889-FEDER, PI12/00265, PI12/01270, and PI12/00715), by the Fundación Marqués de Valdecilla (API 10/09), by the Spanish Association Against Cancer (AECC) Scientific Foundation and by the Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Also sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d'Oncologia de Catalunya (XBTC). MCC-Spain acknowledges the contribution from Esther Gracia-Lavedan in preparing the data. We thank all the subjects who participated in the study and all MCC-Spain collaborators. MD Anderson: Prostate Cancer Case-Control Studies at MD Anderson (MDA) supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388. MDACC_AS: None reported MEC: Funding provided by NIH grant U19CA148537 and grant U01CA164973. MIAMI (WFPCS): ACS MOFFITT: The Moffitt group was supported by the US National Cancer Institute (R01CA128813, PI: J.Y. Park). NMHS: Funding for the Nashville Men's Health Study (NMHS) was provided by the National Institutes of Health Grant numbers: RO1CA121060. PCaP only data: The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. For HCaP-NC follow-up data: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. For studies using both PCaP and HCaP-NC follow-up data please use: The North Carolina - Louisiana Prostate Cancer Project (PCaP) and the Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study are carried out as collaborative studies supported by the Department of Defense contract DAMD 17-03-2-0052 and the American Cancer Society award RSGT-08-008-01-CPHPS, respectively. For any PCaP data, please include: The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. For studies using PCaP DNA/genotyping data, please include: We would like to acknowledge the UNC BioSpecimen Facility and LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). For studies using PCaP tissue, please include: We would like to acknowledge the RPCI Department of Urology Tissue Microarray and Immunoanalysis Core for our tissue processing, storage and sample disbursement. For studies using HCaP-NC follow-up data, please use: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. The authors thank the staff, advisory committees and research subjects participating in the HCaP-NC study for their important contributions. For studies that use both PCaP and HCaP-NC, please use: The authors thank the staff, advisory committees and research subjects participating in the PCaP and HCaP-NC studies for their important contributions. PCMUS: The PCMUS study was supported by the Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2-2009; DFNI-B01/28/2012) with additional support from the Science Fund of Medical University - Sofia (contract 51/2009; 8I/2009; 28/2010). PHS: The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490, and HL34595. PHS members are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. PLCO: This PLCO study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHPLCO thanks Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention at the National Cancer Institute, the screening center investigators and staff of the PLCO Cancer Screening Trial for their contributions to the PLCO Cancer Screening Trial. We thank Mr. Thomas Riley, Mr. Craig Williams, Mr. Matthew Moore, and Ms. Shannon Merkle at Information Management Services, Inc., for their management of the data and Ms. Barbara O'Brien and staff at Westat, Inc. for their contributions to the PLCO Cancer Screening Trial. We also thank the PLCO study participants for their contributions to making this study possible. Poland: None reported PROCAP: PROCAP was supported by the Swedish Cancer Foundation (08-708, 09-0677). PROCAP thanks and acknowledges all of the participants in the PROCAP study. We thank Carin Cavalli-Björkman and Ami Rönnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skilful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. We acknowledge The NPCR steering group: Pär Stattin (chair), Anders Widmark, Stefan Karlsson, Magnus Törnblom, Jan Adolfsson, Anna Bill-Axelson, Ove Andrén, David Robinson, Bill Pettersson, Jonas Hugosson, Jan-Erik Damber, Ola Bratt, Göran Ahlgren, Lars Egevad, and Roy Ehrnström. PROGReSS: The PROGReSS study is founded by grants from the Spanish Ministry of Health (INT15/00070; INT16/00154; FIS PI10/00164, FIS PI13/02030; FIS PI16/00046); the Spanish Ministry of Economy and Competitiveness (PTA2014-10228-I), and Fondo Europeo de Desarrollo Regional (FEDER 2007-2013). ProMPT: Founded by CRUK, NIHR, MRC, Cambride Biomedical Research Centre ProtecT: Founded by NIHR. ProtecT and ProMPT would like to acknowledge the support of The University of Cambridge, Cancer Research UK. Cancer Research UK grants (C8197/A10123) and (C8197/A10865) supported the genotyping team. We would also like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge, UK. We would also like to acknowledge the support of the National Cancer Research Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT) collaborative (grant code G0500966/75466) which has funded tissue and urine collections in Cambridge. We are grateful to staff at the Welcome Trust Clinical Research Facility, Addenbrooke's Clinical Research Centre, Cambridge, UK for their help in conducting the ProtecT study. We also acknowledge the support of the NIHR Cambridge Biomedical Research Centre, the DOH HTA (ProtecT grant), and the NCRI/MRC (ProMPT grant) for help with the bio-repository. The UK Department of Health funded the ProtecT study through the NIHR Health Technology Assessment Programme (projects 96/20/06, 96/20/99). The ProtecT trial and its linked ProMPT and CAP (Comparison Arm for ProtecT) studies are supported by Department of Health, England; Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466, and The NCRI, UK. The epidemiological data for ProtecT were generated though funding from the Southwest National Health Service Research and Development. DNA extraction in ProtecT was supported by USA Dept of Defense award W81XWH-04-1-0280, Yorkshire Cancer Research and Cancer Research UK. The authors would like to acknowledge the contribution of all members of the ProtecT study research group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health of England. The bio-repository from ProtecT is supported by the NCRI (ProMPT) Prostate Cancer Collaborative and the Cambridge BMRC grant from NIHR. We thank the National Institute for Health Research, Hutchison Whampoa Limited, the Human Research Tissue Bank (Addenbrooke's Hospital), and Cancer Research UK. PROtEuS: PROtEuS was supported financially through grants from the Canadian Cancer Society (13149, 19500, 19864, 19865) and the Cancer Research Society, in partnership with the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec, and the Fonds de la recherche du Québec - Santé.PROtEuS would like to thank its collaborators and research personnel, and the urologists involved in subjects recruitment. We also wish to acknowledge the special contribution made by Ann Hsing and Anand Chokkalingam to the conception of the genetic component of PROtEuS. QLD: The QLD research is supported by The National Health and Medical Research Council (NHMRC) Australia Project Grants (390130, 1009458) and NHMRC Career Development Fellowship and Cancer Australia PdCCRS funding to J Batra. The QLD team would like to acknowledge and sincerely thank the urologists, pathologists, data managers and patient participants who have generously and altruistically supported the QLD cohort. RAPPER: RAPPER is funded by Cancer Research UK (C1094/A11728; C1094/A18504) and Experimental Cancer Medicine Centre funding (C1467/A7286). The RAPPER group thank Rebecca Elliott for project management. SABOR: The SABOR research is supported by NIH/NCI Early Detection Research Network, grant U01 CA0866402-12. Also supported by the Cancer Center Support Grant to the Cancer Therapy and Research Center from the National Cancer Institute (US) P30 CA054174. SCCS: SCCS is funded by NIH grant R01 CA092447, and SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SCPCS: SCPCS is funded by CDC grant S1135-19/19, and SCPCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). SEARCH: SEARCH is funded by a program grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SNP_Prostate_Ghent: The study was supported by the National Cancer Plan, financed by the Federal Office of Health and Social Affairs, Belgium. SPAG: Wessex Medical ResearchHope for Guernsey, MUG, HSSD, MSG, Roger Allsopp STHM2: STHM2 was supported by grants from The Strategic Research Programme on Cancer (StratCan), Karolinska Institutet; the Linné Centre for Breast and Prostate Cancer (CRISP, number 70867901), Karolinska Institutet; The Swedish Research Council (number K2010-70X-20430-04-3) and The Swedish Cancer Society (numbers 11-0287 and 11-0624); Stiftelsen Johanna Hagstrand och Sigfrid Linnérs minne; Swedish Council for Working Life and Social Research (FAS), number 2012-0073STHM2 acknowledges the Karolinska University Laboratory, Aleris Medilab, Unilabs and the Regional Prostate Cancer Registry for performing analyses and help to retrieve data. Carin Cavalli-Björkman and Britt-Marie Hune for their enthusiastic work as research nurses. Astrid Björklund for skilful data management. We wish to thank the BBMRI.se biobank facility at Karolinska Institutet for biobank services. PCPT & SELECT are funded by Public Health Service grants U10CA37429 and 5UM1CA182883 from the National Cancer Institute. SWOG and SELECT thank the site investigators and staff and, most importantly, the participants who donated their time to this trial. TAMPERE: The Tampere (Finland) study was supported by the Academy of Finland (251074), The Finnish Cancer Organisations, Sigrid Juselius Foundation, and the Competitive Research Funding of the Tampere University Hospital (X51003). The PSA screening samples were collected by the Finnish part of ERSPC (European Study of Screening for Prostate Cancer). TAMPERE would like to thank Riina Liikanen, Liisa Maeaettaenen and Kirsi Talala for their work on samples and databases. UGANDA: None reported UKGPCS: UKGPCS would also like to thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. UKGPCS should also like to acknowledge the NCRN nurses, data managers, and consultants for their work in the UKGPCS study. UKGPCS would like to thank all urologists and other persons involved in the planning, coordination, and data collection of the study. ULM: The Ulm group received funds from the German Cancer Aid (Deutsche Krebshilfe). WUGS/WUPCS: WUGS would like to thank the following for funding support: The Anthony DeNovi Fund, the Donald C. McGraw Foundation, and the St. Louis Men's Group Against Cancer.

  Study phs001391

• Genome-Wide Predictors of Treatment-Related Toxicities in SWOG S0221 Trial

  When undergoing treatment for breast cancer, many women experience severe side effects, some of which result in treatment-related death and some that can persist for years. Little is understood regarding factors that may predict drug toxicities. Pharmacogenetics, the investigation of variants in candidate genes in drug metabolism pathways, has been used to determine susceptibility to treatment-related toxicities, as well as to cancer recurrence. Although there have been some strong and important findings using this approach, such as identification of single nucleotide polymorphisms (SNPs) that predispose to side effects associated with thiopurines and irinotecan, there has been less progress in assessment of genetic variants that predispose to toxicities resulting from the multi-drug regimen commonly used to treat breast cancer, anthracyclines (A), cyclophosphamide (C), and taxanes (T). These difficulties in identification of key gene variants may be due to the complex metabolic pathways of these drugs, the lack of rate limiting enzymes in the processes, or the limitations of single SNP analysis, rather than capturing all of the variability across the genes. In addition to drug metabolism pathways, however, there may be a number of constitutional factors or other processes that affect damage to normal tissues in the course of chemotherapy, some known or hypothesized, such as DNA repair and oxidative stress pathways, and others not yet discovered. However, there have been no clear candidate genes that account for a large part of the variation in drug or treatment response, and there are likely important genes that influence sensitivity of cells to chemotherapy through unknown pathways which have not yet been identified or hypothesized. The present technological capabilities to screen the entire genome for variants that discriminate populations allows the opportunity to identify these as yet unknown pathways, and open the doors to exciting new avenues of research into mechanisms that had not been previously considered. We conducted a genome-wide scan (GWAS) in a clinical trial (S0221), in which women with high risk breast cancer were treated with different dosing schedules of C, A and T. Blood specimens were collected and banked, and DNA extracted for genotyping on the Illumina OMNI 1M platform. The GWAS data were used to examine genetic variants significantly associated with grades 3 and 4 toxicities, including peripheral neuropathy recorded during the T segment. In S0221, toxicities were graded according to the NCI Common Toxicity Criteria for Adverse Events (CTCAE). The neurotoxicity is predominantly a distal sensory neuropathy, which is characterized by pain, numbness, tingling, and reduced functional capacity in the extremities. Other symptoms include parasthesias, ataxia, impaired vibration and joint position sense, and loss of tendon reflexes. By using a GWAS approach, it is likely that important pathways not previously considered can be revealed as important in susceptibility to treatment-related toxicities, identifying those at greatest risk for alternate drugs or dose reduction, and opening new areas of research for prevention of taxanes-related neuropathy among patients receiving chemotherapy for breast cancer.

  Study phs001428

• Long-Term Outcome in Offspring and Mothers of Dexamethasone-Treated Pregnancies at Risk for Classical Congenital Adrenal Hyperplasia Owing to 21-Hydroxylase Deficiency

  Summary The purpose of this study is to perform the first long-term follow up study both of adolescents and young adults with a history of prenatal treatment with dexamethasone and of their mothers and to test for adverse medical or behavioral side effects. The emphasis will be on the outcome of this prenatal treatment in those fetuses who are not affected with steroid 21-hydroxylase deficiency (21OHD) form of congenital adrenal hyperplasia (CAH) and are either heterozygotes or homozygote-unaffected. Prenatal treatment of 46,XX fetuses with 21OHD (via administration of dexamethasone to the pregnant mother) has been shown to reduce the masculinization of the genitalia and, thereby, the later need for 'corrective' feminizing genital surgery and potential impairment of sexual functioning. Along with the suppression of excess prenatal androgen production and reduction of prenatal masculinization of the genitalia in 46,XX fetuses with 21OHD, prenatal dexamethasone treatment may reduce the behavioral masculinization that is well documented in untreated 46, XX patients with 21OHD. Those fetuses who are partially treated until diagnosis of an unaffected status (heterozygous or homozygous-unaffected) will be studied as well. This latter group is of importance because these fetuses are being unnecessarily treated, but we have no way of diagnosing the unaffected status before the 8th week of gestation when treatment must begin for the female fetus who is affected. As treatment is necessary only until term in the female fetus affected with classical CAH, male fetuses and unaffected or heterozygous female fetuses do not require treatment. Thus, only one out of eight fetuses will require prenatal treatment until term. Findings of adverse effects of glucocorticoid treatment in non-human mammals [1, 2] have raised concerns among other clinicians and investigators about potential adverse side effects of such treatment on the developing human. Thus, this study will address this concern and investigate the potential adverse side effects of prenatal treatment. Detailed Description Females with classical CAH owing to 21-hydroxylase deficiency are born with ambiguous genitalia due to the production of excess androgens in utero. Prenatal treatment with dexamethasone was inaugurated in 1978 by Maguelone Forest and has been the standard of practice in the United States since 1986. Dexamethasone, which crosses the placental barrier, suppresses the fetal adrenal gland production of androgens, thus preventing ambiguous genitalia in the affected female. Children of both sexes are prenatally treated as soon as pregnancies at risk are confirmed. Treatment in females with 21OHD continues to term, but is discontinued in males and unaffected females. To date, 685 pregnancies have been diagnosed, of which 366 fetuses were treated. These investigators will study prenatally treated adolescents and adults 12 years and older with respect to medical and behavioral outcomes (see Table 5). In addition, mothers of children prenatally treated for varying periods of time for suspected 21OHD will be studied for long-term side effects of dexamethasone treatment administered during pregnancy. The long-term outcome in these children and their mothers has never before been studied.

  Study phs001317

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Gene Discovery in Autosomal Dominant Focal Segmental Glomerulosclerosis (FSGS)

  Focal segmental glomerulosclerosis (FSGS) is a frequent cause of end-stage renal disease. The pathogenesis of FSGS has not been precisely defined and there are no consistently effective treatments. Recent studies identifying causal genes in rare, inherited FSGS, including our own study, have associated mutations in at least six genes with familial FSGS, and each discovery has clarified molecular mechanisms of glomerular injury. To build on this productive line of inquiry, we have ascertained and carefully characterized 118 families with familial FSGS. We have screened the remainder of our families for mutations in genes known to cause FSGS and identified the causal mutations in an additional 6 kindreds; the genetic basis of disease in the remaining 111 families is unknown. The objective of this proposal is to use this valuable and unique family resource to systematically identify causal genes for familial FSGS. Limitations of current conventional linkage and positional cloning approaches include their requirement for large, multiplex families. In addition, narrowing candidate areas in traditional linkage analysis can be difficult due to large regions that lack recombination events and hence these regions have required cumbersome and lengthy screening for causative mutations. Powerful new genetic tools can facilitate this screening process and improve variant discovery in smaller families. In particular, efficient whole-exome sequencing, the targeted capture of protein-coding gene sequences, should be particularly useful in our studies since most Mendelian disorders are caused by mutations affecting exomes of the target gene. Thus, by combining genome-wide linkage analysis (GWLS) and whole-exome sequencing, we can maximize impact of our family data and accelerate identification of novel mutations in FSGS. In preliminary studies, we have used this combination to identify a novel variant in the WT1 (Wilms' Tumor-1) gene in one FSGS family, and we have evidence suggesting it is the causal mutation. This success provides proof-of-concept and provides a roadmap of how genes will be identified and evaluated in the proposed studies. Our hypothesis is that causes of inherited FSGS in our cohort of families will be sequence variants in the coding region of genes not previously associated with familial FSGS. We aim to: 1) Use GWLS and whole-exome sequencing to identify genetic variants associated with familial FSGS. 2) Characterize functional consequences of candidate causative mutations and 3) Determine the prevalence in the Duke FSGS dataset of these new causative mutations identified in Aim 2. Any genes found to have causative mutations will be sequenced in the remaining families and take full advantage of our family resource. By combining genome-wide linkage analysis (GWLS), whole-exome sequencing, and characterization of variants' functional consequences, we will significantly improve understanding of normal glomerular biology and of the pathogenesis of FSGS and related glomerular diseases. Moreover, our discoveries are likely to reveal new opportunities to improve therapy for a disease that currently has few effective treatments.

  Study phs000777

• Heart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure Patients (HFN EXACT-BioLINCC)

  ObjectivesTo determine the effect of allopurinol after 24 weeks on a composite clinical endpoint that classifies subject's clinical status (improved, worsened, unchanged) in patients with heart failure and high uric acid levels.BackgroundMorbidity and mortality rates for patients with heart failure are high, despite guideline-recommended therapy. Heart failure is characterized by an imbalance between left ventricular (LV) performance and myocardial energy consumption. There is a growing body of evidence that suggests oxidative stress contributes to ventricular and vascular remodeling, and disease progression in heart failure. Targeting potential source(s) of oxidative stress, e.g. Xanthine oxidase (XO), was the focus of recent clinical trials and epidemiological studies. Increased XO activity has been shown to lead to production of superoxide and uric acid (UA). Serum uric acid levels are included in heart failure risk scores, and hyperuricemia is present in about 25% of patients with heart failure. Hyperuricemia is associated with exercise intolerance, reduced survival, and worsening symptoms. The EXACT-HF trial tested allopurinol, an inhibitor of XO, as a potential target therapy for hyperuricemic heart failure patients.Subjects253 subjects were enrolled in the EXACT-HF study. 128 participants were randomized to the allopurinol arm, and of those participants, 119 completed the trial and 9 did not. 125 participants were randomized to the placebo arm, and of those participants, 116 completed the trial and 9 did not.DesignEXACT-HF was a multi-center, double-blind, placebo controlled, 24-week trial of allopurinol. Eligible participants had to be receiving a stable regimen for at least two weeks (3 months for beta-blockers) prior to randomization. Participants were randomized by an automated system to either the allopurinol or placebo arm, and started treatment within 12 hours of completing the baseline visit. During the first week, participants in both treatment arms received 300mg daily of the respective medications. For the following 23 weeks, participants in both treatment arms received 600mg daily of the respective medications. Patients unable to tolerate 600 mg were maintained on 300 mg.The primary endpoint was a composite clinical endpoint (CCE) that classified a subject's clinical status as improved, worsened, or unchanged at 24 weeks. The CCE was determined based on the following: death; hospitalization, emergency room visit or emergent clinic visit for worsening HF; medication change for worsening HF; and Patient Global Assessment using a 7-point scale. Secondary endpoints at 12 and 24 weeks included changes in quality of life as assessed by the Kansas City Cardiomyopathy Questionnaire, and submaximal exercise capacity as assessed by a 6-minute walk test.ConclusionsParticipants who received allopurinol had significantly less serum uric acid laboratory levels after 24 weeks; however, no significant difference was observed in the primary and secondary endpoints between the allopurinol and placebo-treated patients. Therefore, in high-risk HF patients with reduced ejection fraction and elevated uric acid levels, xanthine oxidase inhibition with allopurinol failed to improve clinical status, exercise capacity, quality of life, or LVEF at 24 weeks (Circulation. 2015 May 19; 131(20):1763-71).

  Study phs003533

• Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) was designed to evaluate the hypothesis that amiodarone or a conservatively programmed shock-only, single-lead implantable cardioverter defibrillator (ICD) would decrease the risk of death from any cause in a broad population of patients with mild-to-moderate heart failure. Background Patients with congestive heart failure (CHF) can die suddenly and unpredictably from arrhythmia despite the use of proven medical therapies, such as beta-blockade. Two approaches have been developed to prevent sudden death among patients with CHF: therapy with amiodarone and therapy with an ICD. However, most of the mortality data on amiodarone and ICD therapy at the time of the study had been obtained in clinical trials performed after myocardial infarction in patients without CHF or those with ventricular arrhythmias. Thus, more data was needed to guide these therapies in patients who did not meet these criteria. Participants There were a total of 2521 participants. 847 were randomly assigned to placebo, 845 to amiodarone, and 829 to ICD therapy. Design Before randomization, participants underwent electrocardiography, a 6-minute walk test, 24-hour ambulatory electrocardiography, liver and thyroid function studies, and chest radiography. Participants were required, if clinically reasonable, to receive treatment with a beta-blocker and an angiotensin-converting-enzyme inhibitor, as well as an aldosterone antagonist, aspirin, and statins, when appropriate. Participants were randomly assigned in equal proportions to receive placebo, amiodarone, or a single-chamber ICD programmed to shock-only mode. Participants assigned to amiodarone or matching placebo began therapy as outpatients immediately after randomization. Placebo and amiodarone were administered as a loading dose of 800 mg/day for one week, 400 mg/day for three weeks, and then as a daily maintenance dosage according to weight and bradycardia status. Participants assigned to ICD therapy received their device a median of three days after randomization. The goal of ICD therapy was to treat only rapid, sustained ventricular tachycardia or ventricular fibrillation. Dual-chamber or biventricular devices, or antitachycardia or rate-response pacing therapies were not permitted. The ICD was uniformly programmed to have a detection rate of 187 beats per minute or more. Antibradycardia pacing was initiated only if the intrinsic rate decreased to less than 34 beats per minute. Median follow-up was 45.5 months. The primary end point was death from any cause. Secondary outcome measures included cardiac mortality, arrhythmic mortality, morbidity, quality of life, and incremental cost-effectiveness of the interventions. Each active treatment arm was compared to the placebo drug arm. Conclusions In participants with NYHA class II or III CHF and LVEF of 35% or less, amiodarone had no favorable effect on survival, whereas single-lead, shock-only ICD therapy reduced overall mortality by 23%.

  Study phs003654

• Inorganic Nitrite Delivery to Improve Exercise Capacity in Heart Failure with Preserved Ejection Fraction (INDIE-HFpEF): Heart Failure Network (HFN INDIE-Imaging)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objective: To determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction.Background: Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF.Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants: A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first.Design: HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇o2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e′ ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected.Data Availability: Data available from this study includes transthoracic echocardiogram images from multiple timepoints. There are 199 echocardiographic exams available, totaling over 13,100 individual echocardiogram images. Conclusions: Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity.Reference: Borlaug et al., 2018, PMID: 30398602.

  Study phs003804

• Idiopathic Pulmonary Fibrosis Network (IPFNet) Sildenafil Trial of Exercise Performance in Idiopathic Pulmonary Fibrosis (IPFNet-STEP-IPF-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The STEP-IPF study sought to evaluate whether treatment with sildenafil would improve walk distance, dyspnea, and quality of life in participants with advanced idiopathic pulmonary fibrosis (IPF).Background: IPF is a chronic, progressive lung disease of unknown cause that is characterized by the histopathologic pattern of usual interstitial pneumonia. Progression to end-stage respiratory insufficiency and death within 5 years after the onset of symptoms is characteristic. To date, no pharmacologic therapies have definitively been shown to improve survival or quality of life in participants with this disease.Participants with severe IPF have abnormalities of the pulmonary vasculature leading to decreased levels of resting and exercise-induced production of nitric oxide. Since nitric oxide is a potent pulmonary vasodilator, reduced levels are associated with pulmonary vasoconstriction and impaired gas exchange. Sildenafil (Revatio, Pfizer) is a phosphodiesterase-5 inhibitor that stabilizes the second messenger of nitric oxide, cyclic guanosine monophosphate, which leads to pulmonary vasodilatation. Such vasodilatation could improve ventilation–perfusion matching and thus gas exchange in with IPF.Design: STEP-IPF was a double-blind, randomized, placebo-controlled trial of oral sildenafil (20 mg three times daily). Participants meeting eligibility criteria were randomly assigned in a 1:1 ratio to receive sildenafil or matched placebo with the use of a permuted-block design, with stratification according to clinical center. The primary outcome was the presence or absence of an improvement of at least 20% in the 6-minute walk distance at 12 weeks, as compared with baseline. Key secondary outcomes included changes in the 6-minute walk distance, degree of dyspnea, and quality of life.Screening procedures included the taking of a detailed history, a physical examination, spirometry, echocardiography, CT imaging, and measurements of lung volume on plethysmography, carbon monoxide diffusion capacity, and arterial blood gases. Eligible participants returned for an enrollment visit within 6 weeks after screening. All participants received an initial dose of a study drug at this visit and were monitored for 60 minutes for adverse effects. Follow-up visits were scheduled at 1, 6, and 12 weeks. After completion of the 12-week visit, all participants were started on treatment with open-label sildenafil. Visits were scheduled at 13, 18, and 24 weeks; at 28 weeks, serious adverse events and vital status were documented. Testing of the 6-minute walk distance was performed with the use of a standardized protocol at the time of screening and enrollment and at study visits at 6, 12, 18, and 24 weeks. Participants with pulse oxygen saturation below 88% received supplemental oxygen. Conclusions: This study did not show a benefit for sildenafil for the primary outcome. The presence of some positive secondary outcomes creates clinical equipoise for further research. There were small but significant differences in arterial oxygenation, carbon monoxide diffusion capacity, degree of dyspnea, and quality of life favoring the sildenafil group.

  Study phs004085

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at: mfreeberg@ebi.ac.uk , or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addressesDate and time of a visit to the service website Operating systemAmount of data transmittedBrowserEmail address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the serviceTo better understand the needs of the users and guide future improvements of the serviceTo monitor website activities according to and in compliance with the Terms of UseTo better understand the needs of the website visitors and guide future improvements of the serviceTo conduct and monitor website security activitiesTo create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you.Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data.Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. 9. CookiesWe use cookies and similar technologies that are strictly necessary for the correct functioning and security of the EGA website (for example, to enable core site features and to help protect the service). These cookies do not store information that directly identifies you.You can set your browser to block or delete cookies. Please note that if you disable strictly necessary cookies, parts of the website may not function properly.Published on February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• Women's Health Initiative Clinical Trial and Observational Study - Imaging

  Objectives: The clinical trial assessed the safety and efficacy of three interventions. Specifically, it evaluated (1) the major health benefits and risks of estrogen plus progestin and estrogen alone, (2) the effects of a low-fat eating pattern on risk of colorectal cancer, and (3) the efficacy of calcium with vitamin D supplementation for preventing hip and other fractures. The objective of the memory study was to determine whether estrogen plus progestin therapy protects global cognitive function, and evaluate the therapy's effect on the incidence of dementia and mild cognitive impairment.The observational study is examining the relationship between lifestyle, socioeconomic, health, and other risk factors with cardiovascular, breast cancer, colorectal cancer and osteoporotic fracture outcomes. Secondary objectives include providing more reliable estimates of the extent to which known risk factors predict disease, more precise estimates of new occurrences of disease, and to provide a future resource for the identification of new or novel risk factors especially factors found in blood. Background: The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing the major causes of death, disability, and frailty in postmenopausal women, specifically heart disease, cancer, and osteoporotic fractures. The WHI is primarily composed of an observational study (OS), as well a clinical trial (CT) with three components: Hormone Replacement Therapy (HT), Dietary Modification, (DM) and Calcium/Vitamin D supplementation (CaD).Prior to the WHI, observational studies suggested that postmenopausal hormone therapy was associated with a decreased risk of coronary heart disease (CHD). Potential cardioprotection was based on generally supportive data on lipid levels in intermediate outcome clinical trials, trials in nonhuman primates, and a large body of observational studies suggesting a 40% to 50% reduction in risk among users of either estrogen alone or, less frequently, combined estrogen and progestin. Observational studies primarily examining unopposed estrogen preparations have suggested a 30% to 50% reduction in coronary events, and an 8% to 30% increase in breast cancer with extended use. Other research findings indicated that hormone therapy was also associated with a decreased risk of osteoporosis and increased bone density. The WHI HT trials were designed to test the effects of postmenopausal hormone therapy on risk for coronary heart disease and assess overall risks and benefits in predominantly healthy women. The Women's Health Initiative Memory Program (WHIMS) consists of a suite of studies which include cohorts of women who participated in the WHI HT trials. Postmenopausal women have a greater risk than men of developing Alzheimer's disease, but studies of the effects of estrogen therapy on Alzheimer's disease have been inconsistent. Additionally, observational studies have suggested that postmenopausal hormone treatment may improve cognitive function, but data from randomized clinical trials have been sparse and inconclusive. International comparisons and migration studies have suggested that countries with 50% lower fat intake than the US population had approximately one third the risk of colorectal cancer. Additionally, fairly consistent evidence existed for an effect of dietary fat, vegetables and fruits, and grains on colorectal cancer risk from within-country observational studies, although the protective effect of lower fat intake was no longer clear after adjusting for energy intake. The WHI DM trial was the first randomized trial to directly address the health effects of a low-fat eating pattern in predominantly healthy postmenopausal women from diverse racial/ethnic, geographic, and socioeconomic backgrounds. Osteoporosis is a major cause of injury, loss of independence, and death, and contributes to hip fractures. Observational evidence and data from previous randomized clinical trials suggest that calcium and/or vitamin D supplements may slow bone loss and reduce the risk of falls in postmenopausal and elderly women. However, evidence from trials, observational studies, and meta-analyses of calcium and vitamin D supplementation with respect to hip and other fractures was limited at the time the WHI was initiated. In two prior randomized trials, calcium plus vitamin D supplements did not reduce the risk of nonvertebral fractures among older women. When the WHI CaD trial was designed, guidelines recommended daily intakes of 800 to 1200 mg of calcium with 400 IU of vitamin D for the prevention of osteoporosis, which was not met by many American women. Therefore, the WHI CaD trial was designed to test the primary hypothesis that postmenopausal women randomly assigned to calcium plus vitamin D supplementation would have a lower risk of hip fracture and, secondarily, of all fractures than women assigned to placebo. Subjects: Postmenopausal women ages 50 to 79 were eligible to participate. A woman was considered postmenopausal if she had experienced no vaginal bleeding for 6 months (12 months for women under 55 years of age), had had a hysterectomy, or had ever used postmenopausal hormones. Recruitment was carried out in 40 US clinical centers in 1993-1998. The clinical trial components had additional specific inclusion or exclusion criteria.A total of 68,132 women were randomized into at least one component of the clinical trial. 27,347 women were enrolled in the hormone therapy component with 16,608 in the estrogen plus progestin trial and 10,739 in the unopposed estrogen trial, 48,835 women were enrolled in the diet modification component, and 36,282 women were enrolled in the calcium/vitamin D component. 7,479 women 65 years of age and older at baseline and that participated in the HT trial component were enrolled in the ancillary memory study. Women who were either ineligible or unwilling to participate in the clinical trial component were enrolled in the observational study. For example, many potential participants to the clinical trial component of the study were already undertaking a low fat diet or were using hormone replacement therapy. The effect of the selection process was that women enrolled in the observational study tended to have healthier lifestyles compared to those enrolled in the clinical trial. In total, 93,676 subjects were enrolled in WHI OS, with over 16% being members of a racial/ethnic minority group. The first WHI Extension Study enrolled 115,407 consenting participants from all components of the original WHI study for an additional five years of follow-up, from 2005 to 2010. In 2010, 93,567 women consented to continued follow-up. Design: The clinical trial component of the WHI included three randomized comparisons: hormone therapy, dietary modification, and calcium/vitamin D supplementation. Women could have been randomized into one, two or all three trials.The hormone therapy trial enrolled women to one of two double-blinded trials: estrogen (0.625 mg of conjugated equine estrogens daily) plus progestin (2.5 mg of medroxyprogesterone acetate daily) or estrogen alone. Women with a prior hysterectomy were eligible for the trial of unopposed estrogen. Women with an intact uterus at screening were initially also eligible for unopposed estrogen, but were reassigned to the trial of combined postmenopausal hormones beginning in 1995. Both trials randomized participants 1:1 to either hormone therapy or placebo. A 3-month washout period was required before baseline evaluation of women using postmenopausal hormones at initial screening. Study participants were contacted by telephone 6 weeks after randomization to assess symptoms and reinforce adherence. Follow-up contacts by telephone or clinic visit occurred every 6 months, with clinic visits required annually. The estrogen plus progestin trial was halted in July 2002 after a mean 5.2 years of follow-up because health risks, including increased risk of breast cancer and cardiovascular disease, exceeded benefits. The estrogen alone trial was stopped early in March 2004, because an increased risk of stroke was found with no benefit for coronary heart disease. The primary outcome was coronary heart disease (CHD) (nonfatal myocardial infarction and CHD death), with invasive breast cancer as the primary adverse outcome. The dietary modification trial evaluated the effect of a low-fat, high fruit, vegetable, and grain diet on preventing cardiovascular disease and cancer. Participants were randomly assigned to an intervention or a comparison group in the ratio of 2:3 for cost-efficiency. The intervention was an intensive behavioral modification program, using 18 group sessions in the first year and quarterly sessions thereafter, led by specially trained and certified nutritionists. The program was designed to promote dietary change with the goals of reducing total fat to 20% of energy intake, increasing vegetables and fruits to at least 5 servings daily and grains to at least 6 servings daily. The intervention did not include total energy reduction or weight loss goals. Comparison group participants received a copy of the US Department of Health and Human Services' Dietary Guidelines for Americans and other health-related materials but were not asked to make dietary changes. Dietary intake was monitored using the WHI food frequency questionnaire at 1 year and in a rotating one-third subsample every year thereafter. Women completed a medical update questionnaire every 6 months, and medical records were sought for all women reporting colorectal cancer. The primary outcome was invasive colorectal cancer incidence. Participants in the calcium/vitamin D trial were randomized 1:1 to either supplements or placebo. Active tablets contained 500 mg of elemental calcium (as calcium carbonate) and 200 IU of vitamin D3, to be taken twice daily with meals. The presence and severity of symptoms, safety concerns, and outcomes were ascertained at annual clinic visits and telephone or clinic visits at intervening six-month intervals. Risk factors for fracture were assessed by questionnaire, interview, and clinical examination. The primary outcome was incidence of hip fracture. Participants in the observational study attended a baseline examination and were re-examined three years later. Participants completed annual updates of exposures and clinical outcomes by mail. Final data were collected by mail during the close-out period in April 2004 to March 2005. The major clinical outcomes of interest were coronary heart disease, stroke, breast cancer, colorectal cancer, endometrial cancer, ovarian cancer, osteoporotic fractures, diabetes, and total mortality. Most outcomes were initially ascertained by self-report on an annual questionnaire and documented by hospital and related records. Charts with potential cardiovascular, cancer, and fracture outcomes were sent to the local physician adjudicator for evaluation and classification. Staff at the Clinical Coordinating Center coded and adjudicated all cancers of major interest in the study using standardized SEER guidelines. In 2005, WHI participants were invited to join the Extension Study for an additional five years of follow-up in order to collect long-term outcomes. Participants completed annual data collection forms primarily by mail, similar to the OS follow-up. Women reporting study outcomes were contacted by WHI field center staff to obtain additional details and medical records, which were evaluated by physician adjudicators. In 2010, the woman remaining were invited to join the next Extension Study. In the second extension, women were divided into two groups, one of which would have outcomes documented with medical records (the Medical Records Cohort, MRC), and the other would just be followed by self-report (the Self-Report Cohort, SRC). The MRC consists of women who were in the hormone therapy trials, and all African-American and Hispanic women. In 2012-2013, a subset of the MRC was identified for a potential in-home visit to collect blood and several objective measures of physical functioning. Conclusions: Overall health risks exceeded benefits from use of combined estrogen plus progestin after an average 5.2 year follow-up among healthy postmenopausal US women (Rossouw et al., 2002, PMID:12117397). Among postmenopausal women aged 65 years or older, estrogen plus progestin did not improve cognitive function when compared with placebo (Rapp et al., 2003, PMID: 12771113), increased the risk for probable dementia, and did not prevent mild cognitive impairment (Shumaker, et al., 2003, PMID: 12771112). The use of conjugated equine estrogen increased the risk of stroke, decreased the risk of hip fracture, and did not affect CHD incidence in postmenopausal women with prior hysterectomy after an average of 6.8 years of follow-up (Anderson et al., 2004, PMID: 15082697). Over approximately 8 years of follow-up, a low-fat dietary pattern did not reduce the risk of colorectal cancer (Beresford, et al., PMID: 16467233). Calcium with vitamin D supplementation resulted in a small but significant improvement in hip bone density; however, no significant difference was observed in hip fractures (Jackson, et al., 2006, PMID: 16481635). A recent review summarizes the conclusions from the WHI clinical trials with a focus on clinical practice (Manson, et al., 2024, PMID: 38691368).Description of ECG Imaging Data: Electric cardiograms (ECGs) were given to all clinical trial participants at baseline and in years 3, 6, and 9 of the original WHI study.EKG data consist of 12 lead 10 seconds ECGS sampled at 500Hz via GE ECG machines and process via GE MUSE system. The ECG waveform were directly exported from GE MUSE using MUSE export function in XML format, which include EKG waveform data as well as other ECG characteristics. Waveform data is in base64 encoded format, when it is decoded, it is a binary data that can be used to draw waveform graph. Many programming languages and data tools have built in functions to decode base64 strings. All the other necessary information is included in the LeadData section, total byte size, total sample size etc. (usually 1 sample is 2 bytes). See example below: encoded-data (base64 encoded string) JwAoAC0AKAAiACIAJAAkACQAIwAiACIAHgAcABwAGwAZABgAGAAYABcAEwAQABAAEAAL^/AAsADAAM... decoded-binary-data (1 sample is 2 bytes) 270028002D002800220022002400240024002300220022001E001C001C001B00 1900180018001800170013001000100010000B000B000C000C000D000D000D00 0A000A000A0009000600040004000700070005000500020... These binary values are integers (Y axis data of the graph), hence it is a straightforward process to draw the waveform graph. Acquisition dates have been redacted from this ECG data to comply with WHI policy. All acquisition dates within files and in file names have been set to January 1, 1900 (19000101) to comply with this policy.

  Study phs003824

• A Genome-Wide Association Study in Breast Cancer Patients from the Prospectively Randomized SUCCESS Trial

  The SUCCESS-A Study (http://www.success-studie.de) is a randomized Phase III study of response to treatment of early primary breast cancer with adjuvant therapy after surgical resection. The primary outcome is disease-free survival and secondary outcomes are overall survival and toxicity. The study design includes comparison of two pairs of treatment regimes performed in sequence. The first randomization contrasts treatment with and without Gemcitabine (3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC)-chemotherapy, followed by 3 cycles of Docetaxel(D)-chemotherapy versus 3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC), followed by 3 cycles of Gemcitabine-Docetaxel(DG)-chemotherapy). The second randomization contrasts treatment with Zoledronate for two versus five years. Patients were recruited from 2005 to 2007 and a total of 3754 patients were included from 250 study sites across Germany. Genome-wide SNP microarray data and phenotype outcomes for the first phase of the study (treatment with and without Gemcitabine) are included in the GARNET (Genomics and Randomized Trials Network) pharmacogenomic study in this dbGaP submission. (The Zoledronate treatments are still underway). SUCCESS-A is a an open-label, multicenter, 2x2 factorial design, randomized controlled, Phase III study comparing the disease free survival after randomization in patients treated with 3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC)-chemotherapy, followed by 3 cycles of Docetaxel(D)-chemotherapy versus 3 cycles of Epirubicin-Fluorouracil-Cyclophosphamide(FEC), followed by 3 cycles of Gemcitabine-Docetaxel(DG)-chemotherapy, and to compare the disease free survival after randomization in patients treated with 2 years of Zoledronate versus 5 years of Zoledronate in patients with early primary breast cancer. Patients were required to have histopathological proof of axillary lymph node metastases (pN1-3) or high risk node negative, defined as: pT>2 or histopathological grade 3, or age , ≤ 35 or negative hormone receptor, but were not allowed to have evidence of distant disease. Patients were entered into the study no later than 6 weeks after complete resection of the primary tumor. No antineoplastic treatment other than surgical treatment, the defined cytotoxic and endocrine treatment, and radiotherapy was allowed prior to study entry and during the course of the study. After surgery, leading to complete resection of the invasive and intraductal components of the primary tumor, patients were randomized to one of the following two treatments for the first phase of the project (which is included in this GARNET pharmacogenomics study): AA: 3 cycles of 5-Fluorouracil 500 mg/m² i.v. body surface area and Epirubicin 100 mg/m² i.v. and Cyclophosphamide 500 mg/m² i.v., (FEC100), each administered on day 1, repeated on day 22, subsequently followed by 3 cycles of Docetaxel 75 mg/m² body surface area i.v. (D), and Gemcitabine 1000 mg/m² i.v. (30 min infusion) (G), administered on day 1, followed by Gemcitabine 1000 mg/m² i.v. (30 min infusion) on day 8, repeated on day22 AB: 3 cycles of 5-Fluorouracil 500 mg/m² i.v. body surface area and Epirubicin 100 mg/m² i.v. and Cyclophosphamide 500 mg/m² i.v., (FEC100), each administered on day 1, repeated on day 22, subsequently followed by 3 cycles of Docetaxel 100 mg/m² body surface area i.v. (D), administered on day 1, repeated on day 22 A second randomization was made for assigning patients to one of the following two subsequent treatments for the second phase of the project (NOT included in the pharmacogenetic study in this dbGaP submission): BA: Zoledronic acid 4 mg i.v., every 3 months for the duration of two years, subsequently followed by zoledronic acid 4 mg i.v., every 6 months for the duration of additional three years BB: Zoledronic acid 4 mg i.v., every 3 months for the duration of two years Patients with positive hormone receptor status (≥10% positively stained cells for estrogen and/or progesterone) of the primary tumor were recommended to receive Tamoxifen treatment 20 mg p.o. per day for 2 years, after the end of chemotherapy . Subsequent to chemotherapy, postmenopausal patients with positive hormone receptor status were recommended to be treated with Anastrozole (Arimidex®) 1 mg p.o. for additional 3 years, premenopausal patients will continue Tamoxifen treatment for those additional 3 years. In addition to tamoxifen, all patients with positive hormone receptor status of the primary tumor and under the age of 40 or restart of menstrual bleeding within 6 months after the completion of cytostatic treatment or with premenopausal hormone levels as defined below were recommended to receive Goserelin (Zoladex®) 3.6 mg subcutaneously every 4 weeks over a period of 2 years following chemotherapy. Premenopausal endocrine status will be assumed, if the following serum levels are met: LH < 20 mIE/ml, FSH < 20 mIE/ml and E2 > 20 pg/ml. Endocrine therapy will start after the end of chemotherapy. All patients with breast conserving therapy or more than 3 axillary lymph node metastases or in the following cases after mastectomy will receive adjuvant radiotherapy: T3/T4-carcinoma, T2-carcinoma > 3 cm, multicentric tumor growth, lymphangiosis carcinomatosa or vessel involvement, involvement of the pectoralis fascia or a safety margin < 5 mm. Radiotherapy was usually performed after the chemotherapy and parallel to the beginning of the zoledronic acid therapy. Initially, DNA was extracted for performing SNP microarray assays using blood collected at baseline prior to the first randomization. However, the first set of SNP microarray results indicated a quality problem with approximately 50% of the DNA samples. A majority of the problematic samples were replaced with DNA extracted from redrawn blood. The remaining problematic samples were 'restored' using an Illumina FFPE Restoration procedure. A total of 3322 subjects (1638 from arm AA and 1684 from arm AB) were successfully genotyped. Among those, 1771 were from original blood samples, 1092 from redrawn blood samples and 459 from restored blood samples. The SUCCESS-A study is part of the Genomics and Randomized Trials Network (GARNET, http://www.garnetstudy.org) funded by the National Human Genome Research Institute (NHGRI). The overarching goal is to identify novel genetic factors that contribute to disease-free survival for breast cancer patients using different forms of chemotherapy through large-scale genome-wide association studies of treatment response in randomized clinical trials. The study was conducted at the University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Germany. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were performed at the GARNET Coordinating Center at the University of Washington.

  Study phs000547

• Genome-Wide Association Study of Anorexia Nervosa (Price Foundation, Klarman Family Foundation, Center for Applied Genomics at the Children's Hospital of Philadelphia, Scripps Translational Sciences Institute Clinical Translational Science Award)

  Twin studies are consistent with substantial heritability in anorexia nervosa (AN), although detecting and confirming individual risk alleles has been difficult, due to small effects of single alleles and limited samples in prior studies. Methods: 1105 AN DNA samples obtained in a multisite study and 3733 pediatric patients of normal body weight were genotyped using the Illumina 610Q chip at The Center for Applied Genomics at The Children's Hospital of Philadelphia. Cases and controls were of European ancestry. Single nucleotide polymorphism (SNP) genotypes were subjected to quality control procedures, including elimination of SNPs with: call rates < 95%, minor allele frequency < 5%, and if Hardy-Weinberg equilibrium testing yielded p < 0.0001. Samples were removed if not of European ancestry or if showing cryptic relatedness. Eight AN DNA samples were deleted for low call rate, and 51 AN samples were deleted for cryptic relatedness. The statistical program, PLINK, was used to calculate a P value for each SNP passing quality control using the Cochran-Armitage trend test. The PennCNV program was used to define copy number variation (CNV). Results: We performed a genome-wide association study (GWAS) using with 1033 AN cases and 3733 controls (genomic inflation factor = 1.08). There were 11 SNPs with P<1X10-5 [(rsID, chromosome location, nearest gene, distance to nearest gene (base-pair), P value) rs6959888, 7q21.13, ZNF804B, 0, 1.63E-06; rs17725255, 20p11.23, CSRP2BP, 39396, 1.72E-06; rs10494067, 1p13.3, NTNG1, 0, 5.83E-06; rs2383378, 14q12, AKAP6, 0, 6.41E-06; rs410644, 5q14.1, SSBP2, 40462, 6.74E-06; rs4479806, 5p14.1, CDH9, 156926, 7.79E-06; rs957788, 13q33.3, FAM155A, 0, 8.11E-06; rs830998, 2q31.1, LRP2, 0, 8.68E-06; rs6782029, 3p25.3, VGLL4, 0, 9.04E-06; rs512089, 9p21.3, ELAVL2, 47984, 9.85E-06; rs3808986, 11q24.3, APLP2, 29217, 9.92E-6]. CNV analyses were performed on 1015 AN cases and 3532 controls. Overall frequencies of common or rare CNVs were similar between cases and controls. Specific rare and large (>500 kb, <1%) CNVs of interest included deletion of a large (~1.4Mbp) region of chr13q12 found in 2 AN samples and at a 10 fold lower frequency in a large sample (72,918) of subjects containing the genes SGCG, SACS, TNFRSF19, MIPEP, PCOTH, C1QTNF9B, SPATA13, MIR2276, and C1QTNF9, and an overlapping deletion and a duplication observed in 3 AN samples overlapping the CNTN6 and CNTN4 genes. Partially overlapping ~ 30 kb duplications were seen in 12 AN cases and in 1 control at the CDC5L gene on chromosome 6. Partially overlapping deletion of the 3' half of the PSTPIP1 gene was seen in 5 AN cases and no controls. Finally, a ~ 60 kb deletion of the PLEC1 gene was observed in 5 AN cases and in none of 3532 controls. Discussion: This is the first GWAS of AN. These preliminary results are consistent with absence of a major gene effect in AN. These results are consistent with genetic risk conveyed by multiple common alleles of small effect, as well as some uncommon CNVs of potentially larger effect. None of the implicated genes has a clear role in eating behavior. It must be emphasized that these results are preliminary and an additional ~ 400 AN cases will be analyzed as time and resources permit. These results require confirmation through study of independent populations of AN women.

  Study phs000679

• Treatment of Pulmonary Hypertension and Sickle Cell Disease with Sildenafil Therapy (Walk-PHaSST)

  Pulmonary arterial hypertension (PAH) is a progressive condition characterized by narrowing or stiffening pulmonary arterioles resulting in increased pulmonary blood pressure and reduced delivery of oxygenated blood to the body. It is a common complication of sickle cell disease and initially presents with the symptom of shortness of breath (dyspnea) on exertion. As the condition worsens, other symptoms such as dizziness, lower extremity edema, and chest pain can develop. The drug, sildenafil, works by relaxing blood vessels in the lungs which reduces pulmonary blood pressure and allows more oxygenated blood to circulate. Increased levels of oxygenated blood allows individuals with PAH to tolerate more activity, but guidelines for using sildenafil in patients with PAH and sickle cell disease were unavailable at the time of the Walk-PHaSST trial.Participants were screened for the existence of pulmonary hypertension with a six minute walk test and a Doppler echocardiogram that assessed TRV, diastolic function, and valvular and systolic function. Subjects with TRV ≥ 2.7 m/s received further clinical evaluation for possible causes of pulmonary hypertension. Other screening data included medical history, a physical exam, and standard laboratory testing. For individuals with moderate to severe pulmonary hypertension (TRV ≥ 3.0), a cardiac catheterization was done at the baseline and week 16 data collection periods.Subjects eligible for the main intervention trial based on screening results were randomized in a 1:1 double blind fashion to receive sildenafil or placebo for 16 weeks. Subjects received 20 mg of oral sildenafil or matching placebo 3 times daily for 6 weeks, followed by 40 mg 3 times daily for 4 weeks, followed by 80 mg 3 times daily for 6 weeks, as tolerated. Participants could also receive other therapies as needed to manage sickle cell and related complications. The primary outcome measure of the trial was change in the six minute walk test, a standard indicator of a person's heart and lung function and exercise capacity, from baseline to week 16. After completing the study treatment (or placebo), participants could choose to be part of the open-label follow-up phase of the study and continue to be assessed for up to one year.The study was intended to screen about 1000 subjects and randomize 132 subjects, however it was terminated early due to the unforeseen increase in adverse events in participants treated with sildenafil as compared to placebo. When the study was stopped, 33 participants had completed the trial. Subjects continued to be monitored, but were instructed to taper sildenafil treatment over three to seven days.There was no evidence that treatment with sildenafil impacted the six minute walk distance from baseline to week 16. In addition, treatment with sildenafil appeared to increase rates of hospitalization due to sickle cell disease pain.Due to in part to the early termination of the trial, the majority of subject data was collected from the screening phase of the study (n=720), as opposed to the main intervention trial (n=74).Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002383

• ALCHEMIST Study

  The ALCHEMIST study will accrue patients that are potentially eligible for the Intergroup adjuvant studies and perform central EGFR and ALK genotyping using a central reference laboratory certified by the Clinical Laboratory Improvement Amendments of 1988 (CLIA). Patients may either present prior to surgery with resectable NSCLC, may present following complete resection (before or after adjuvant chemotherapy). Eligibility is limited to those with NSCLC of a non-squamous histological subtype and those with adequate performance status and organ function for future trial eligibility. All subjects must submit tissue for central EGFR and ALK genotyping, as well as additional tissue for advanced genomics at the CCG. Subjects may have had local genotyping done prior to registration, however if these results shows no targetable EGFR or ALK alterations (or if it shows a KRAS mutation) then the patient will not be eligible for this screening protocol given the primary aim is to facilitate accrual to the adjuvant studies. All subjects will provide peripheral blood for matched normal DNA. All subjects (including those known to have EGFR or ALK alterations with local genotyping) will have formalin-fixed tissue collected for central genotyping. The testing will be performed at Response Genetics (Los Angeles, CA), a commercial CLIA-certified laboratory. ALK FISH will be performed using the Vysis break-apart probe and EGFR sequencing will be performed of exons 18-21. It is preferred that a full tumor block be submitted, but if unavailable, 15 unstained slides can be submitted. Genotyping results are expected to be provided to the treating clinician within 14 business days of submission so they can be used to determine eligibility for the randomized adjuvant studies, or to confirm the local results. Results will also be reported at intervals to the study team for update into the Alliance database. In addition to the commercial genotyping at Response Genetics, tissue will be collected for research genomics by CCG. For those patients with a block available, this will be forwarded to the CCG after clinical testing at Response Genetics. For patients without a block available, 15 unstained slides should be submitted to the CCG BCR for exploratory analysis. A peripheral blood specimen will also be collected and sent to the CCG BCR to use as matched normal. Specimens will be coded. Over the course of the study, the CCG will perform advanced genomic analysis of the resected lung cancer specimens in a research, non-CLIA environment. Following completion of the genomic analysis, the results can be matched with the clinical follow-up results using a link between the samples codes and the patient identifiers for correlative analyses. Subjects participating in the follow-up portion of the ALCHEMIST study, as well as those participating in the adjuvant therapeutic studies, are expected to undergo a standard-of-care diagnostic biopsy to confirm recurrence. At least two core biopsies, minimum, should be obtained as part of this recurrence biopsy. Paraffin embedded tissue from this biopsy will be used for confirmation of recurrence, for CLIA genomics to plan subsequent clinical trials, and for additional research genomics by the CCG. Plasma will additionally be collected at recurrence and sent to CCG for study of circulating free DNA (cfDNA). Data for the ALCHEMIST study is not yet available to be accessed by the public at this time; when ready it will be made available at the GDC Data Portal.

  Study phs001140

• NHLBI Family Heart Study (FamHS-Visit1 and FamHS-Visit2)

  The Family Heart Study (FamHS) was funded by the National Heart, Lung, and Blood Institute (NHLBI). It was begun in 1992 with the ascertainment of 1,200 families, half randomly sampled, and half selected because of an excess of coronary heart disease (CHD) or risk factor abnormalities as compared with age- and sex-specific population rates (Higgins et al. 1996). The families, with approximately 6,000 individuals, were sampled on the basis of information on probands from four population-based parent studies: the Framingham Heart Study, the Utah Family Tree Study, and two Atherosclerosis Risk in Communities (ARIC) centers (Minneapolis, and Forsyth County, NC). A broad range of phenotypes were assessed at a clinic examination in broad domains of CHD, atherosclerosis, cardiac and vascular function, inflammation and hemostasis, lipids and lipoproteins, blood pressure, diabetes and insulin resistance, pulmonary function, and anthropometry (FamHS Visit 1). Approximately 8 years later, study participants belonging to the largest pedigrees were invited for a second clinical exam (FamHS Visit 2). A total of 2,756 Caucasian subjects in 508 extended families were examined. A two-phase design was adopted for the genome wide association (GWA) study. In phase-1, 1007 subjects were chosen, equally distributed between the upper and lower quartile of age- and sex-adjusted values for coronary artery calcification, assessed by CT scan in Visit 2. These subjects were chosen to be largely unrelated; 34% of the subjects were from unique families, while 200 other subjects had 1 or more siblings selected into the sample, yielding a sample of 465 unrelated subjects. The remaining family members (N=1749) were genotyped in the phase-2 for replication of the top hits from the phase-1. The results presented here represent those for the analysis of the phase-1 case-control sample for variables assessed in FamHS Visit 1 (from 1992 to 1995) and for the variables assessed in FamHS Visit 2 (from 2002 to 2003). All subjects were typed on the Illumina HumMap 550 chip (Phase 1 genotype). Of these, 33 (3.3%) were excluded due to technical errors, call rates below 98%, and discrepancies between reported sex and sex-diagnostic markers. The final sample of 974 subjects have Visit 2 phenotypes, approximately 100 of these do not have Visit 1 phenotypes. There was no significant plate-to-plate variation in allele frequencies. The covariate adjustments were performed separately by sex using cubic polynomial age and clinical centers, and retaining the terms in the stepwise regression analysis that were significant at the 5% level. Extreme outliers (>4 SD from the mean) were set aside, temporarily, for the adjustments. The final phenotypes were computed for all individuals using the best mean regression models and standardizing to 0 mean and unit variance. The FamHS has contributed GWA results in many phenotype domains (antropometric and adiposity, atherosclerosis and coronary heart disease, lipid profile, diabetes and glicemic traits, metabolic syndrome etc) to meta-analyses and various consortia, including Heard-Costa et al. 2009, Köttgen et al. 2010, Teslovich et al. 2010, Nettleton et al. 2010, Lango et al. 2010, Heid et al. 2010, Speliotes et al. 2010, Dupuis et al. 2010, Kraja et al. 2011.

  Study phs000221

• Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Version 3 (ROC-Cardiac Epistry 3-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data The ROC Cardiac Epistry version 3 include all cardiac arrest cases entered into the ROC database from April 1, 2011 to June 30, 2015. This is separate from versions 1 and 2 because of the major changes in how and which data were collected. Version 3 represents the following major changes to the structure and data collection: separate ED Arrival and Hospital Admits forms, mandatory ED and Hospital elements and a revamped CPR Process form. For ROC traumatic injury Epistry data please see: ROC-Trauma Epistry Objectives To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest; to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes. Background Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes. Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants There were 120,306 participants. Design ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly.

  Study phs003726

• Acute Respiratory Distress Network (ARDSNet) Studies 01 and 03 Lower Versus Higher Tidal Volume, Ketoconazole Treatment and Lisofylline Treatment (ARMA/KARMA/LARMA) (ARDSNet-ARMA/KARMA/LARMA-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ARMA/KARMA/LARMA include plasma, serum and urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The primary objective of the KARMA trial was to investigate the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS. The Ketoconazole arm of the study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. Background Participants suffering from ARDS are extremely ill, require mechanical ventilation and, despite improvements in medical care and technology, had a mortality rate as high as 50 percent. An excessive inflammatory response is characteristic of ALI of which ARDS represents the most severe end of the pathophysiologic spectrum. The inflammatory response includes increased numbers of neutrophils activated to produce cytokines, proteases, and reactive oxygen intermediates. Pulmonary injury may also be enhanced by alveolar and tissue macrophages as a producer of vasoactive substances, neutrophil chemoattractants, and procoagulant substances. Ketoconazole, a synthetic antifungal imidazole, also has anti-inflammatory activities and may inhibit neutrophil recruitment via several different pathways known to be involved in the development of ALI and ARDS. Lisofylline causes a marked decrease in the circulating levels of the major oxidizable species of free fatty acids and also inhibits proinflammatory intracellular signaling. Mechanical ventilation in participants with ALI and ARDS have traditionally used tidal volumes of 10 to 15 ml per kilogram of body weight. These large tidal volumes are often necessary to achieve normal partial pressure of arterial carbon dioxide and pH, but may induce inflammatory responses through disruption of pulmonary epithelium and endothelium. Mechanical ventilation at lower tidal volumes may reduce injurious lung stretch and decrease the inflammatory response. Participants The Ketoconazole and Lisofylline trials were designed as 2 x 2 factorials and included 220 participants in each trial. A total of 860 participants were randomized into the ventilator management trial. Participants enrolled in the Lisofylline or Ketoconozole studies had to be concurrently enrolled in the ventilator management study and were first randomized into a ventilator strategy and then to drug or placebo. Conclusions Ketoconazole was found to be safe but did not reduce mortality, duration of mechanical ventilation, or improve lung function. Lisofylline was also found to be safe and to have no beneficial effect for participants with ALI or ARDS. Ventilation at lower tidal volumes resulted in reduced mortality and an increase in the number of days without ventilator support. (PMIDs: 10789668, 11902249, 10793162).

  Study phs003734

• Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Versions 1 and 2 (ROC-Cardiac Epistry 1 and 2-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data: The ROC Cardiac Epistry versions 1 and 2 include all cardiac arrest cases entered into the ROC database from December 1, 2005 to April 1, 2011. ROC Cardiac Epistry 3 includes cardiac arrest cases captured between 2011 and 2015, and introduced significant changes in how and which data were collected.For ROC traumatic injury Epistry data, please see: ROC-Trauma Epistry Objectives: To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest;to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes.Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 109,326 cardiac arrest events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly.

  Study phs003803

• Coronary Artery Risk Development in Young Adults (CARDIA-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related Studies: Other CARDIA data available include:phs000236.v2.p2 PAGE: CALiCo: Coronary Artery Risk Development in Young Adults(CARDIA) phs000309.v3.p2 The CARDIA-GENEVA Study phs000399.v1.p2 NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (CARDIA) phs000613.v1.p2 NHLBI CARDIA Candidate Gene Association Resource (CARe) phs003675.v1.p1 CARDIA Multi-omics Obesity & CVD Substudy – Year 20 Untargeted Metabolomics Data phs001612.v3.p2 NHLBI TOPMed: CARDIA (Coronary Artery Risk Development in Young Adults) phs003045.v1.p1 Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA) phs000285.v4.p3 CARDIA_Cohort Available Data: Available data for request include exam data through Year 30 and outcomes and death data through 2022. Additionally, data from 28 ancillary studies are available for request.Objectives: The original objectives of CARDIA were to document levels of risk factors for coronary artery disease and potential determinants of these risk factors in young adults; to study the interrelationships of risk factors and lifestyles and to document behavioral and environmental changes during the transition from young adulthood to middle age; to compare cross-sectional and longitudinal data on age-related trends in cardiovascular disease risk factors; and to compare levels and evolution of risk factors between men and women, blacks and whites, and in groups of differing socioeconomic status. Goals of the study have evolved to emphasize understanding determinants of left ventricular mass, emerging obesity and hypertension, and sequelae of hypertension in pregnancy.Background: CARDIA is designed to increase understanding of contributors to changes in cardiovascular disease (CVD) risk factors during the critical years of transition from young adulthood to middle age. CARDIA was funded initially in 1983 for a five-year cycle that included two rounds of examinations. Contract renewals have allowed for subsequent re-examinations.Participants: Black and white men and women; ages 18-30 years at entry with a range of attained education; original sample size: 5,115.Design: CARDIA is a population-based observational study of 5,115 participants aged 18-30 years recruited in 1985-1986. The sample was designed to achieve approximately balanced subgroups of race, gender, education (high school or less and more than high school) and age (18-24 and 25-30). Forty percent of the cohort had no more than a high school education. A total of nine examinations have been completed in the cohort with examination cycles at year 2 of the project and years 5, 7, 10 , 15, 20, 25, and 30.In addition to standard measurements of blood pressure, anthropometry, blood lipids, smoking behavior, physical activity, diet, pulmonary function, and many psychological factors, CARDIA has other included measurements (in subsets or in the full cohort) to obtain unique information on other aspects of risk factor development and early morbidity. These have included: graded exercise treadmill testing; echocardiography, particularly for measurement of left ventricular mass; cardiovascular reactivity; serum cotinine; Lp(a), apoE phenotype, apolipoprotein A1 and B; homocysteine; skin reflectance; body composition by dual X-ray absorptiometry; glucose tolerance testing; vascular resistance and compliance; and plasma renin activity and sympathetic nervous system activity.

  Study phs003739

• Small molecule inhibitors of LOXL synergize with 5-AZA to restore erythropoiesis in myeloid neoplasms

  Objectives: Bone marrow (BM) stroma and microenvironmental factors in the BM milieu of myeloid neoplasms are increasingly being recognized as novel perspective therapeutic targets. Lysyl oxidases (LOX/LOXL) are crucial enzymes that cross-link collagen and contribute to the deposition of aberrant stiff extracellular matrix (ECM) in the BM of patients with myelodysplastic syndromes (MDS) and myeloproliferative neoplasms (MPN). Here, we studied whether inhibition of LOX/LOXL enzymes produced by BM-derived MSCs favors the differentiation of MDS/MPN hematopoietic stem cell and progenitor cells (HPSCs) and enhances the effects of 5-azacytidine (5-AZA). Methods: Primary co-cultures of MSCs and HPSCs were established from n=31 MDS/MPN patients and treated with the pan-LOX/LOXL inhibitor PXS-5505, 5-AZA or the combination of both for 4 days. At the end of co-culture, HSPC differentiation was assessed by CFU assays and flow cytometry. In some of the experiments, MSCs monolayers were pre-treated or not with PXS-5505 for 6 days and decellularized using 20 mM ammonia. Subsequently, autologous HSPCs were cultured on ECM matrices in the presence of 5-AZA or PXS-5505 + 5-AZA combination with or without inhibitors of integrin signaling such as blebbistatin, Y-27632 and αvβ3-integrin blocking antibodies. Patient-derived xenografts (PDX) were established in NSG mice based on intrafemoral co-injection of HSPCs and autologous MSCs. PDX were treated with 3 cycles of 5-AZA (75 mg/m2), PXS-5505 (30 mg/kg on alternate days for the duration of 5-AZA treatment) or combination of both. Results: MSCs of MDS and MPN patients displayed significant overexpression of LOX/LOXL transcripts as compared to healthy age-matched controls. Remarkably, LOX/LOXL inhibition in MSCs/HSPCs co-cultures increased erythroid differentiation of patient HSPCs that had suboptimal or no response to 5-AZA alone. From a total of n=31 advanced stage MDS/MPN patients, n=11 (35.5%) responded to the combination treatment, which was evidenced by a significant increase of CD235a+CD45- erythroid cell production compared to 5-AZA/PXS/untreated arms (p<0.05). Of note, combination treatment with 5-AZA + PXS-5505 facilitated differentiation of CD235+ erythroid progenitors from HSPCs sub-clones with low mutational VAFs. The presence of MSCs was necessary for the effects of the combination treatment and required direct cell contacts between MSCs and HSPCs. Moreover, PXS-5505-mediated alterations of the ECM composition alone were sufficient to induce erythroid differentiation. Inhibition of integrin-mediated signaling using blebbistatin, Y-27632 and αvβ3-integrin antibodies completely abrogated the effects of PXS-5505 induced erythroid differentiation. In vivo, the combination of PXS-5505 + 5-AZA favored erythroid differentiation of HSPCs and confirmed the in-vitro results. The combination treatment of 5-AZA + PXS-5505 induced the greatest reduction of disease burden as assessed by decrease of spleen indexes, total engraftment rates, BM fibrosis and mutational VAF profiles. Conclusions: The combination of 5-AZA + LOX/LOXL inhibitor PXS-5505 in MDS and MPN synergistically restores erythropoietic differentiation of primary HSPCs. The effect is dependent of contact interaction between HSPCs and niche components, such as MSCs and MSCs-derived ECM. Our data propose a strong rationale for a BM niche targeted combination treatment with 5-AZA + PXS-5505 in transfusion dependent MDS and MPN, which will be assessed in forthcoming clinical trials.

  Study EGAS00001006174

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• EGA account management

  How to manage your EGA account Welcome to the documentation page for creating an EGA user. The European Genome-Phenome Archive (EGA) is a platform for archiving, managing, and sharing human genomic and phenotypic data. To submit, access, and manage requests for the data hosted on the EGA platform, users are required to register for an account. This documentation page provides step-by-step instructions for creating an EGA user account, as well as information on the different types of EGA user accounts and their associated privileges. You can check the EGA data flow for a better understanding. Manage EGA account step-by-step guide Contact Information Public Keys Password Authenticator Federated Identity Sessions Request an EGA account step-by-step guide Fill in this form.You cannot use a generic email account (e.g., Gmail). Make sure you use your institutional email account.Your email is by default your username.The criteria for a strong password is: It should contain between 8 and 32 charactersIt should contain at least one uppercase letterIt should contain at least one numberIt should contain at least one special characterYou will need to wait for the Helpdesk team to check your identity. Please allow two business days for this step.After the Helpdesk validation step, you will receive an email with a link to validate your institutional email.Click the link to verify your email. It will redirect you to the EGA website.As soon as your account has been validated, you will be able to start adding more information to your EGA profile. For that, you first need to log in using your credentials from step 1. Manage EGA account step-by-step guide As a logged-in user, go to your profile by clicking on Welcome > My Profile. To modify it, click the Edit button.You will see the following options: Contact Information In this section, you can modify the personal information of your EGA account. Public Keys Adding a public key is necessary for downloading data via Live Outbox distribution. If you don’t know how to generate your key, you can follow the instructions available on How do I create a key? Password In the Password tab, you can change your password anytime to ensure the security of your account. However, if you receive an email notifying you that your password was modified and you did not initiate the change, it could be a sign that your account has been compromised. In this case, you should immediately contact our Helpdesk team to report the issue and receive assistance in restoring your account security. Authenticator You can set your two-factor authentication (2FA) system for your EGA account as an identity and access management security method that requires two forms of identification to access resources and data. To obtain your code, please follow the instructions below, also available in the Authenticator tab in your profile. Sessions The Sessions tab displays a list of all devices where you are currently logged in as an EGA user. This includes any open sessions you have on your computer, phone, or other devices. By reviewing the list of active sessions, you can monitor the devices that have access to your account and ensure that there are no unauthorised logins. If you notice any suspicious activity, you can close the sessions from this page to immediately terminate access to your account from the unauthorised device.

  Documentation how-to-manage-your-account

• Genome-Wide Association Study of HCC in Non-Asian USA Population

  This GWAS of HCC relied on existing biological and data resources from 7 USA sites and one Canadian site which allows for the integration of genetic and environmental data. Total of 2199 case patients and 1103 non cancer controls were genotyped. Case patients are defined as patients with pathological or radiological diagnosis of HCC with and without chronic hepatitis C virus infection. Study was restricted to Caucasian population without prior infection with chronic HBV infection. All DNA samples were extracted from peripheral blood. Study population of the participated sites are: Site-1: University of Texas MD Anderson Cancer Center A hospital based-case-control study was initiated at UT MD Anderson Cancer Center in 2000 and approved by the Institutional Review Board of The University of Texas M. D. Anderson Cancer Center. Study design was previously described in detailed (1-3). Written informed consent for an interview and for a biological sample was obtained from each participant. At time of diagnosis prior to treatment exposure. Case patients were recruited from the population of patients with newly diagnosed HCC who were evaluated and treated at the institution's gastrointestinal medical and surgical oncology outpatient clinics. Inclusion criteria were as follows: a pathologically confirmed diagnosis of HCC, U.S. residency, and the ability to communicate in English. Patients with concurrent or past history of other types of cancers were excluded. Control subjects were healthy spouses of patients with cancers other than liver, gastrointestinal, lung, or head and neck (smoking-related cancers) undergoing treatment at our institution. Eligibility criteria for control subjects were the same as those for patients, except that control subjects could not have ever had cancer. A short, structured questionnaire was used to screen potential control subjects on the basis of eligibility criteria. Control subjects and patients were recruited simultaneously. Case patients and control subjects were interviewed by well-trained interviewers who followed a written protocol to guide ascertainment and reduce surveillance, interviewer, and recall bias. No proxy interviews were conducted. The interviewers used a structured and validated questionnaire to collect information about demographic characteristics and potential risk factors for HCC such as personal smoking history, alcohol use, medical history, occupational history, and family history of cancer. Blood samples from cases and controls were tested for HBV and HCV. HCV antibodies, hepatitis B surface antigen, and antibodies to hepatitis B core antigen were detected by use of a third-generation enzyme-linked immunosorbent assay (ELISA) (Abbott Laboratories, North Chicago, IL). Important clinical information were retrieved from patients' medical records. Total of 1188 case patients and 278 controls from MD Anderson study were genotyped. Site-2: Mayo Clinic Case patients and controls included in the study from Mayo clinic were recruited as part of Mayo International Hepatobiliary Neoplasia Register and Biorepository. Only USA patients and controls were participated. All cases and controls signed informed consent indicating their willingness to participate in genetic studies. Epidemiological and clinical data were collected from participants and retrieved from medical records. Total of 522 HCC case patients and 182 controls were genotyped in this study. Site-3: Toronto University Molecular Epidemiology of Hepatobiliary Tumors (HBT study, CAPCR 09-0289) is a hospital-based study that includes 1710 patients diagnosed with liver, bile duct or gallbladder adenocarcinoma (Hepatocellular carcinoma - HCC; cholangiocarcinoma - CCA; and gall bladder adenocarcinoma -GBCa) recruited at University Health Network (UHN) between 2009 and 2018. HBT study is a prospective study of cancer patients that collects self-reported demographic and epidemiological data, medical records/clinical information and blood samples for research purposes. Eligible patients recruited between 2009 and March 15 2016 were selected to participate in the Genome-Wide Association Study in Patients with Hepatocellular Carcinoma (GWAS in HCC, CAPCR 15-9943-CE), a sub-study of the HBT study. Eligible prospective patients recruited after March 15 2016 signed the Addendum to the HBT consent form and became eligible to participate in the GWAS in HCC study. Total of 271 cases and 21 controls were genotyped from Toronto University Site-4: University of Pittsburgh The design of the study has been described previously (4-6). Briefly, this population-based study enrolled 120 HCC patients and 230 matched controls from black, Hispanic, and non-Hispanic white residents of Los Angeles County who were between 18 and 74 years of age at diagnosis from January 1995 through December 2001. HCC Cases were identified through the Los Angeles County Cancer Surveillance Program. We sought to recruit up to two control subjects per case from the neighborhoods where HCC patients resided at the time of diagnosis, who were matched to the index case by sex, age (within 5 years), and race (Hispanic white, non-Hispanic white, black). Blood samples (plasma and buffy coat), medical and lifestyle factors were collected from all consenting participants. Total of 65 cases and 60 controls were genotyped in this study Site-5: South Western Dallas Under IRB approval, HCC Cases and controls were prospectively collected since 2015 from the outpatient Liver clinics from Parkland Health and Hospital System and UT Southwestern Medical Center, two large health systems in Dallas TX. A Total of 31 cases and 29 controls were genotyped from site 5. Site-6: Columbia University HCC patients from Columbia are those recruited as part of the Herbert Irving Comprehensive Cancer Center Database Shared Resource which seeks to recruit all cancer patients for potential future studies. The PI is Dr. Katherine Crew AAAL5871. This resource collects sociodemographic, lifestyle and clinical data on patients as well as a blood sample. Those who indicated on their consent form that they would participate in genetic studies were included. Total of 79 case patients with HCC were genotyped from Columbia University. Site-7: University of Michigan The study population included from University of Michigan were included from a prospective study of with chronic HCV infection recruited in Ann Arbor Patients who had under- gone liver transplantation, known coinfection with HIV, life expectancy <12 months due to extra-hepatic illnesses, or were receiving HCV treatment at enrolment, were excluded. Protocol, surveys, and data forms were developed where each enrolled patient completed the same questionnaire All patients provided written informed consent before enrolment in the study. The study was approved by the institutional review board or ethics committee at the University of Michigan. Detailed study description was previously published (7). Total of 44 cases and 347 controls were genotyped Site-8: Veteran Administration Medical Center in Houston This research including written informed consent form was jointly approved by Institutional Review Boards for the Baylor College of Medicine and the Michael E. DeBakey VA Medical Center in Houston, Texas. Study details have been previously published (8). Briefly, we prospectively recruited consecutive HCV-infected veterans prior to their previously scheduled HCV clinic visit at a large tertiary care VA medical center between May 1, 2009 and December 31, 2012. Patients completed a research assistant (RA) administered survey interrogating medical and risk factor history including lifetime alcohol use, had anthropometric measurements taken, and completed a fasting venipuncture for performance of the FibroSure-ActiTest as a measure of hepatic pathology. We restricted our current analysis to individuals who were: (1) White male veterans between 18 and 70 years; (2) had no history of HCC, liver transplant, decompensated liver disease including ascites, dementia, or psychosis; (3) were serologically-confirmed to have chronic HCV and to be negative for both HIV and active HBV infection; (4) were not currently receiving anti-HCV pharmacotherapy; and (5) had FibroSURE testing shown F3/F4 fibrosis consistent with cirrhosis.

  Study phs001744

• Neural Systems, Inhibitory Control, and Methamphetamine Dependence

  The Neural Systems, Inhibitory Control, and Methamphetamine Dependence study started in 2011 and is currently finishing data collection for its last participants. The study included methamphetamine abusing individuals and healthy control participants aged 18-55 years. Participants who qualified over the telephone were scheduled to visit the London Laboratory at the UCLA Semel Institute for Neuroscience and Human Behavior for the In-Person Screening Phase. The screening procedures, usually scheduled over two visits, determined if participants were eligible to complete the subsequent study visits. Both groups completed identical screening procedures, with the exception of more in-depth drug use questions for the methamphetamine users. After providing written consent, participants completed questionnaires about their mood, medical, psychiatric and drug use history, personality and life experiences. They also provided a urine sample to determine what drugs they recently used and a breath sample to determine the carbon monoxide levels in their system. The drug screen tested for recent methamphetamine, cocaine, opiates/opioids, benzodiazepines, THC and other amphetamines. Methamphetamine participants needed to test positive for methamphetamine at admission. If methamphetamine participants tested positive for any drugs other than methamphetamine or marijuana, and if healthy control participants tested positive for any drugs other than marijuana, they were excluded from the study. Additionally, the urine samples of female participants were tested for pregnancy; pregnant females were also excluded. If no exclusionary criteria were met during the first screening visit, participants completed a second screening visit to ensure they were mentally and physically healthy enough to participate. The second screening visit included a psychiatric diagnostic interview (DSM-IV (SCID-I) for first 500 participants and the MINI International Neuropsychiatric Interview M.I.N.I for the last 50 participants). Additionally, laboratory tests and procedures were completed by the UCLA General Clinical Research Center and interpreted by a study physician. Laboratory tests included vital signs (heart rate--BPM, blood pressure, and respirations), an electrocardiogram (ECG) to record the electrical activity of the heart, and an 18-cc blood sample to perform laboratory tests which included a complete chemistry and metabolic panel, hepatic panel, Hepatitis-C tests, and HIV test. The laboratory tests from this blood sample ensured that participants' liver and kidneys were functioning normally, and that their standard blood counts (red cell, white cell, and salts) were also normal. If a Hepatitis-C (HCV) or HIV test was positive, participants were not allowed to continue in the study and their results were reported to the California State Health Department. Participants deemed eligible to continue in the methamphetamine group participated on an outpatient basis or were admitted to the UCLA Medical Center to participate on an inpatient basis for up to 10 days. Typically, detectable levels of methamphetamine in urinalysis remain for 2-3 days, therefore inpatient days 0-3 served as a "washout period" and the methamphetamine abusing inpatient participants provided daily urine samples to test for recent drug use and pregnancy (female participants only). Outpatient participants were also required to remain abstinent from all drugs except nicotine and marijuana for at least 4 days prior to study sessions. Self-reported abstinence for outpatients was verified by urine toxicology and saliva screening at every visit to UCLA before completion of study procedures. Neurocognitive assessments, about three hours each, typically took place on two separate days. The purpose of the neurocognitive sessions were to assess participants' intellectual and neurocognitive functioning. On either the same day as the neurocognitive testing or on separate days, both methamphetamine abusers and healthy controls were administered a structural MRI to collect information on brain structure.

  Study phs001197

• PAK4 inhibition improves PD-1 blockade immunotherapy

  Introduction with rationale and aims for study Immune checkpoint blockade therapies have significantly altered the current landscape of cancer treatment. However, this immunotherapy still fails more often than it succeeds. There are now evidences that the lack of tumour infiltration by immune cells is the main mechanism of primary resistance to PD‐1 blockade therapies for cancer. It has been postulated that cancer cell‐intrinsic mechanisms may actively exclude T cells from tumours, suggesting that the finding of actionable molecules that could be inhibited to increase T cell infiltration may synergize with checkpoint inhibitor immunotherapy. With the idea of finding potential drivers of immune exclusion, we performed RNA sequencing analysis of biopsies from melanoma patients and compared the transcriptomic differences of samples that where infiltrated with those that did not have immune infiltration. Methods RNAseq analysis of gene expressions on biopsies from melanoma patients treated with checkpoint blockade were analysed. We focused on the variable of "infiltration: yes or no,", e.g. tumors that were well infiltrated by immune cells with those that kept immune cells out. Sequencing revealed a list of genes whose expression differed between the infiltrated and noninfiltrated tumors. The kinase PAK4 stood out as a good candidate for inhibition treatment in the future as it was consistently enriched in the samples without immune infiltration. To test whether immunotherapy would work better if we deleted PAK4, we first knocked out PAK4, using CRISPR‐Cas9, in the ‐resistant melanoma cell line, B16. Then they injected the melanoma cells into mice and observed that PAK4 KO tumours now responded to PD‐1 blockade. In order to elucidate whether pharmacological inhibition of PAK4 could recapitulate the results observed in the B16 PAK4 KO tumours, we obtained the PAK4 inhibitor, KPT-9274, from Karyopharm Therapeutics. Indeed, inhibiting PAK4 in combination with anti‐PD‐1 immunotherapy significantly slowed the growth of the B16 melanomas more than either drug alone. Results and Conclusions Transcriptomic analysis of melanoma tumors that were well infiltrated by immune cells with those that kept immune cells out revealed a list of genes whose expression differed between the infiltrated and non-infiltrated tumours. The result suggests that p21 activated kinase 4 (PAK4) is enriched in non-responding tumour biopsies with low T cell and dendritic cell infiltration. In addition, PAK4 decreased WNT activity, a signalling pathway that has previously been involved in immune exclusion. In mouse models, genetic deletion of PAK4 increased T cell infiltration and reversed resistance to PD‐1 blockade in a CD8 T cell-dependent manner. Furthermore, combination of with the PAK4 inhibitor, KPT-9274, improved anti‐tumour responses compared to anti‐PD‐1 alone. Therefore, high PAK4 expression is correlated with low T cell and dendritic cell infiltration and lack of response to PD‐1 blockade, which could be reversed with PAK4 inhibition. The data establish a rationale for targeting this kinase with inhibitors in combination with immune checkpoint inhibitors for patients. Future work and data that we can anticipate for this study Oncogenic signalling pathways and specially the WNT signalling pathway, have been associated with lack of immune infiltration and resistance to PD‐1 blockade therapies. Here, we show that PAK4 overcome resistance to PD‐1 blockade while significantly decreases WNT signalling activity. Therefore, it constitutes the first potential druggable target that is able to reverse oncogenic driven immune cell exclusion. However, the fully mechanism whereby PAK4 sensitizes tumours to immunotherapy remains to be fully elucidated. It is necessary to address whether PAK4 inhibition overcomes resistance through WNT signalling inhibition or if other signalling pathways are involved in the observed phenotype.

  Study phs001919

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• Genomic Diagnosis and Individualized Therapy of Highly Penetrant Genetic Diabetes

  The most common and well-known causes of diabetes are type 1 and type 2 diabetes; however, there are many other etiologies of diabetes. At least 1-2% of diabetes cases result from high penetrance single gene defects, most commonly in a gene encoding either a transcription factor involved in beta cell development and function or the enzyme glucokinase (GCK). Others have mutations in transcription factors necessary for beta cell development and function. This subset of monogenic diabetes cases is autosomal dominant and is known as "Maturity-Onset Diabetes of the Young" (MODY). Patients with type 1 diabetes are insulin dependent, meaning they lack insulin production and therefore require multiple daily injections of insulin, as well as multiple times a day blood glucose monitoring. This can be quite burdensome. Type 2 diabetes is predominantly an insulin resistance problem and can often be managed with pills initially, but there are many who also require insulin either at diagnosis or later on in their disease course. Usually, monogenic diabetes is misdiagnosed as type 1 or type 2 diabetes and thus treated suboptimally. Those with monogenic diabetes, due to a defect in a gene encoding a transcription factor, respond extremely well to a class of oral diabetes medications called sulfonylureas. Those with GCK-MODY often have a mild, stable, fasting, nonprogressive hyperglycemia for which pharmacological treatment is often not necessary. It is important to accurately diagnose our patients with the correct etiology to their diabetes for a multitude of reasons. Accurately diagnosing a patient with MODY, for example, can predict their clinical course and we can tailor treatment accordingly. If diagnosed with a transcription factor MODY, we can try switching the patient from insulin to an oral sulfonylurea, and if diagnosed with a GCK-MODY, we can consider discontinuing pharmacological treatment altogether. With specific tailoring of treatment, we would hope to improve quality of life by discontinuing perhaps multiple daily injections of insulin and glucose checking as these may not be necessary. In addition, we would hope to improve glycemic control with an eventual decreased cost to society by decreasing the complication rate of diabetes, resulting in less specialty referrals, lab tests, supplies and procedures. Further, given MODY is an autosomal dominant condition with a 50% chance of inheritance to first-degree family members, we could offer testing to asymptomatic family members which could lead to prevention and/or early diagnosis and treatment. Overall, testing for monogenic diabetes is underutilized clinically. Testing is being done in the U.K., but in the U.S. we are lagging behind. This is most predominantly due to lack of knowledge and concern over cost. In addition, it is difficult to differentiate the relatively small number of monogenic diabetes cases from the larger number with type 1 and type 2 diabetes as each of these etiologies have overlapping characteristics. In fact, many patients with monogenic diabetes are being misdiagnosed with type 1 and type 2 diabetes. There are recommendations set forth by different societies on who to consider screening for monogenic diabetes. However, these recommendations are difficult to employ clinically as they are general recommendations, there is no specific algorithm, and they are based on varying levels of evidence. The purpose of this study is to implement a personalized diabetes medicine program to enhance the identification of individuals and families affected by highly penetrant diabetes gene mutations through a combination of systematic screening and genetic testing at the University of Maryland Center for Diabetes and Endocrinology, the Baltimore VA Medical Center and additional partner centers at Geisinger Health System and Bay West Endocrinology Associates, and other UM outpatient clinics. Our hope is to develop an approach that can be eventually implemented across the United States so that we can more often uncover the correct etiology to diabetes, tailor treatment accordingly, and test asymptomatic family members.

  Study phs001771

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Detroit Research on Cancer Survivors (ROCS) and Disparities and Cancer Epidemiology - Colorectal Cancer (DANCE)

  The goals for this study were as follows:1. Enroll a total of 5,060 African Americans newly diagnosed with cancer into the Detroit Research on Cancer Survivors (Detroit ROCS) Cohort. These population-based cases will be ascertained through the Detroit Metropolitan Detroit Cancer Surveillance System (MDCSS), a founding member of the NCI SEER Program. Participation at baseline will include a written, web-based, or telephone interview, saliva and/or blood collection, and tumor block retrieval, with detailed cancer-related information coming from the MDCSS registry and medical records.2. Enroll a subgroup of colorectal cancer patients identified through the Louisiana Tumor Registry (LTR). An additional 500 colorectal cancer patients, approximately half non-Hispanic white and half African American, will be identified through the LTR and enrolled into the ROCS protocol. The survey is the same survey administered to the ROCS cohort. The Louisiana (“DANCE-CRC”) cohort will not be followed beyond baseline, and blood will not be collected (tumor tissue, however, will be collected, deidentified, and sent for processing through Dr. Rozek's laboratory at Georgetown University).The proposed cohorts will provide for a broad research agenda evaluating cancer outcomes in African Americans across a variety of factors from individual, provider, health care system and community perspectives. These factors include tumor characteristics driving individualized treatment planning, quality of life after a diagnosis and recurrence. Utilizing the MDCSS registry, we will enroll a large population-based sample of African-American cases with lung, breast, colorectal, and prostate cancers and their caregivers resulting in a cohort that will provide substantial benefit to the cancer research community. KCI has a strong history of research in the African-American community and the faculty represents a breadth of experience that includes clinical oncology, genetic epidemiology, environmental exposures, quality of life, treatment decision making, racism/discrimination, and health behaviors. Drs. Schwartz and Beebe-Dimmer have been and will continue to be generous collaborators with other institutions to ensure that this resource will be extensively utilized. The proposed overall cohort will be the only one of its kind, to our knowledge, filling a substantial gap in our understanding of the determinants driving cancer outcomes in African Americans. In addition to registry data detailing cancer specifics, yearly surveys have collected information about individualized treatment experiences, heath histories, family histories, quality of life after a diagnosis, recurrence and caregiving. Population: Adult cancer survivors (see inclusion criteria in next section) Molecular Technologies: Genotyping: Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) DNA Sequencing: Illumina NovaSeq X Plus using XLEAP-SBS (sequencing by synthesis) Whole genome sequencingPrincipal Findings: The preliminary data collected reinforces differences by race in factors affecting cancer outcomes. Variants in DNA damage repair genes and HOXB13 may be important cancer risk factors for Black men diagnosed with prostate cancer, and are more frequently observed in men with a family history of cancer. ROCS participants reported high rates of a family history of cancer. The high rate of eligibility for Cancer genetic counseling among ROCS participants supports the need for interventions to increase referrals and uptake of genetic counseling among African Americans 60% of ROCS participants reported participating in regular physical activity (PA), with 24% reporting ≥150 min/wk. There were no differences by sex, but prostate cancer survivors were the most likely to report participating in regular PA, whereas lung cancer survivors were the least likely. Survivors who reported participating in regular PA reported higher health-related quality of life and lower depression. More African American than White survivors reported financial hardship and limiting care. More White than African American survivors reported utilizing assets, while more African American survivors reported cancer-related debt. Data available in dbGaP: Individual phenotype data Individual genotype data Individual sequencing dataSample types: Germline DNA

  Study phs003116

• Trial of Late Surfactant for Prevention of Bronchopulmonary Dysplasia: A Study in Ventilated Preterm Infants Receiving Inhaled Nitric Oxide (TOLSURF-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To assess whether late surfactant treatment in extremely low gestational age newborn (ELGAN, ≤28 week gestation) infants requiring ventilation at 7-14 days safely improves survival without bronchopulmonary dysplasia.Background: Bronchopulmonary dysplasia (BPD) is the most common form of chronic lung disease in children with an estimated 15,000 new cases annually in the United States. BPD affects infants born prematurely, is a major contributor to the cost of prematurity each year, and is associated with long-term pulmonary disability, neurodevelopmental abnormalities and death.Increases in the survival of ELGAN infants have resulted in another form of BPD, which is characterized by impaired alveolar and microvascular development with excess tone and reactivity of airway smooth muscle. Despite treatments to enhance lung maturation, premature infants often need prolonged intubation and mechanical ventilation and/or oxygen support. When mechanical ventilation is required longer than 7 days, BPD results in 70% of surviving ELGAN infants. Most of these infants experience clinical episodes of increased requirement for ventilatory support that are associated with dysfunctional surfactant, which is primarily due to low surfactant protein B (SP-B). In pilot studies of late surfactant treatment in premature infants, there was short-term improvement in SP-B content. These prior studies provided the rationale for a larger clinical trial for later doses of surfactant treatment to prevent episodes of respiratory decompensation and BPD. Participants: 511 infants were eligible for randomization of the 2693 infants screened. Of the 511 infants eligible for randomization, there were 252 infants allocated to the treatment arm and 259 infants allocated to the placebo arm.Design: The study was designed to assess the effect of late doses of surfactant on survival without BPD at 36 weeks post menstrual age (PMA) in ELGAN infants who required intubation and mechanical ventilation between 7 and 14 days of age and were receiving Inhaled nitric oxide (iNO). Infants were stratified within clinical centers and gestational age groups and randomized to treatment with calfactant, a natural surfactant extracted from bovine lung lavage fluid, or a sham procedure.All infants received iNO according to the protocol used in the Nitric Oxide Chronic Lung Disease (NOCLD) trial. A masked syringe containing either a standard dose of calfactant for the treatment group, or air for the placebo group, was administered to the infant behind a screen by staff not involved in providing the infant's clinical care. Monitor and ventilator alarms were turned off during dosing to avoid unblinding of clinical staff. To accommodate research staff availability and infant instability, the dosing interval was not strictly set but could be repeated every 24 – 72 hours up to 5 doses if the infant still required intubation. Dosing could be discontinued by physician request or parental withdrawal from the study. Due to parental preference, the first infant in a multiple birth was randomized according to the randomization schedule and subsequent infants were assigned to the same treatment group. Follow-up to assess pulmonary and neurologic development continued until 2 years of age, with treatment group blinding maintained. The primary outcome was survival without BPD at 36 weeks PMA. Secondary outcomes included BPD at 40 weeks PMA, pulmonary outcome at 12–24 months of age, and neurodevelopmental outcome at 2 years of age. Conclusions: There were no significant differences observed between the treatment group and the control group for survival without BPD at 36 weeks or 40 weeks.

  Study phs003899

• Pomalidomide for the Treatment of Bleeding in HHT (PATH-HHT)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine efficacy (reduction in severity of epistaxis), tolerability, and improvement in quality of life of pomalidomide compared to placebo after 24 weeks of treatment.Background: This study addresses the efficacy of pomalidomide in the treatment of epistaxis in patients with Hereditary Hemorrhagic Telangiectasia (HHT) who have anemia and/or require blood transfusion or iron infusion for treatment of bleeding-induced anemia and iron deficiency. HHT (also known as Osler-Weber-Rendu disease) is an inherited bleeding disorder. Over 95% of patients develop recurrent epistaxis, which may be severe and result in chronic anemia, need for iron infusions and blood transfusions, substantial psychiatric comorbidity (including depression and post-traumatic stress disorder) and reduction in health-related quality of life (HRQoL). HHT is clinically diagnosed using the Curacao criteria, which consists of 1) spontaneous and recurrent epistaxis, 2) telangiectasias at characteristic sites, 3) visceral arteriovenous malformations (AVMs) or telangiectasias, and 4) a first degree relative with HHT (inheritance is usually autosomal dominant). Patients with three criteria are considered to have definite HHT, and those with 2 criteria probable HHT. HHT affects approximately 1 in 3,800 individuals. Significant manifestations of HHT often do not appear until the third or fourth decades, sometimes later.Participants: 144 patients from 11 clinical centers were enrolled.Design: This is a multi-center, double blind, randomized placebo-controlled trial that investigated the efficacy and safety of pomalidomide in patients with HHT and chronic epistaxis leading to iron-deficiency anemia or requiring intravenous iron infusions or blood transfusion.Screening evaluation included the Epistaxis Severity Score (ESS) with three-month recall, which reflected the patient's history of epistaxis and bleeding over the prior three months, as well as detailed review of iron infusion and red cell transfusion over the preceding six months. Eligible patients were provided a diary to record the duration of each epistaxis event that occurred during the 4 weeks prior to the baseline visit, and then returned for the baseline randomization visit, at which time patients underwent genetic testing, if this had not been previously performed, and completed an ESS with 4-week recall and quality of life assessments. Patients were randomized 2:1, stratified by study site, to either pomalidomide 4 mg/day or matching placebo during each of six 28 day cycles (24 weeks). Patients were seen every four weeks during treatment, and at a 4-week post-treatment follow-up visit to measure the ESS (with 4-week recall), laboratory assessments including iron stores and need for iron infusion, CBC, and metabolic profile. Patients were assessed for adverse events (AE) throughout the study. Treatment dosage could be reduced, or temporarily or permanently discontinued following AE-specific guidelines related to fatigue, cytopenias or other toxicities.Quality of life assessments were completed at baseline, and the 12- and 24-week visits, and the 4-week post-treatment follow-up visit using validated NIH instruments of 1) Neuro-QOL satisfaction with social roles and activities, 2) PROMIS emotional distress – depression, and 3) PROMIS fatigue, and the HHT-specific quality of life instrument developed specifically for this study. The effect of pomalidomide on duration of epistaxis was assessed via diary between weeks 8-12, 20-24 and the 4-week post-treatment period.Conclusions: Among patients with HHT, pomalidomide treatment resulted in a significant, clinically relevant reduction in epistaxis severity. No unexpected safety signals were identified (Al-Samkari et al., 2024; PMID: 39292928)

  Study phs003948

• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• Substantial somatic genomic variation and selection for BCOR mutations in human induced pluripotent stem cells

  Human Induced Pluripotent Stem Cells (hiPSC) are an established patient-specific model system where opportunities are emerging for cell-based therapies. We compared and contrasted hiPSCs derived from different tissues, skin and blood, in the same individual. We show extensive single-nucleotide mutagenesis in all hiPSC lines, although fibroblast-derived hiPSCs (F-hiPSCs) are particularly heavily mutagenized by ultraviolet (UV)-related damage. We utilized genome sequencing data on 454 F-hiPSCs and 44 blood-derived hiPSCs (B-hiPSCs) to gain further insights. Across 324 whole genome sequenced (WGS) F-hiPSCs derived by the Human Induced Pluripotent Stem Cell Initiative (HipSci), UV-related damage is present in ~72% of cell lines, sometimes causing substantial mutagenesis (range 0.25-15 per Mb). Furthermore, we find remarkable genomic heterogeneity between independent F-hiPSC clones derived from the same reprogramming process in the same donor, due to oligoclonal populations within fibroblasts. Combining WGS and exome-sequencing data of 452 HipSci F-hiPSCs, we identify 272 predicted pathogenic mutations in cancer-related genes, of which 21 genes were hit recurrently three or more times, involving 77 (17%) lines. Notably, 151 of 272 mutations were present in starting fibroblast populations suggesting that more than half of putative driver events in F-hiPSCs were acquired in vivo. In contrast, B-hiPSCs reprogrammed from erythroblasts show lower levels of genome-wide mutations (range 0.28-1.4 per Mb), no UV damage, but a strikingly high prevalence of acquired BCOR mutations in ~57% of lines, indicative of strong selection pressure. All hiPSCs had otherwise stable, diploid genomes on karyotypic pre-screening, highlighting how copy-number-based approaches do not have the required resolution to detect widespread nucleotide mutagenesis. This work strongly suggests that models for cell-based therapies require detailed nucleotide-resolution characterization prior to clinical application.

  Dataset EGAD00001007029

• Best Practices for DACs

  Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

  Documentation access/data-access-committee/best-practices

• Detection of Colorectal Cancer Susceptibility Loci Using Genome-Wide Sequencing

  The Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) is a collaborative effort comprised of a coordinating center and scientific researchers from well-characterized cohort and case-control studies. This international consortium aims to accelerate the discovery of common and rare genetic risk variants for colorectal cancer by conducting large-scale meta-analyses of existing and newly generated genome-wide association study (GWAS) data, whole genome sequencing, replicating and fine-mapping of genetic discoveries, and investigating how genetic risk variants are modified by environmental risk factors. To expand these efforts, we assembled case-control sets or nested case-control sets from 6 different North American or European studies. Summary descriptions and study participant inclusions/exclusion criteria for each of these studies are detailed below. Cancer Prevention Study II (CPS II): The CPS II Nutrition cohort is a prospective study of cancer incidence and mortality in the United States, established in 1992 and described in detail elsewhere (Calle et al., 2002 PMID:12015775; Campbell et al., 2014 PMID:25472679). At enrollment, participants completed a mailed self-administered questionnaire including information on demographic, medical, diet, and lifestyle factors. Follow-up questionnaires to update exposure information and to ascertain newly diagnosed cancers were sent biennially starting in 1997. Reported cancers were verified through medical records, state cancer registry linkage, or death certificates. The Emory University Institutional Review Board approves all aspects of the CPS II Nutrition Cohort. We restricted to samples that had blood DNA source. Controls were matched to cases in a case/control ratio of 2:1 on reference year and sex. Darmkrebs: Chancen der Verhütung durch Screening (DACHS): This German study was initiated as a large population-based case-control study in 2003 in the Rhine-Neckar-Odenwald region (southwest region of Germany) to assess the potential of endoscopic screening for reduction of colorectal cancer risk and to investigate etiologic determinants of disease, particularly lifestyle/environmental factors and genetic factors. Cases with a first diagnosis of invasive colorectal cancer (International Classification of Diseases 10 codes C18-C20) who were at least 30 years of age (no upper age limit), German speaking, a resident in the study region, and mentally and physically able to participate in a one-hour interview, were recruited by their treating physicians either in the hospital a few days after surgery, or by mail after discharge from the hospital. Cases were confirmed based on histologic reports and hospital discharge letters following diagnosis of colorectal cancer. All hospitals treating colorectal cancer patients in the study region participated. Based on estimates from population-based cancer registries, more than 50% of all potentially eligible patients with incident colorectal cancer in the study region were included. Community-based controls were randomly selected from population registries, employing frequency matching with respect to age (5-year groups), sex, and county of residence. Controls with a history of colorectal cancer were excluded. Controls were contacted by mail and follow-up calls. The participation rate was 51%. During an in-person interview, data were collected on demographics, medical history, family history of CRC, and various life-style factors, as were blood and mouthwash samples. Routine formalin-fixed, paraffin-embedded (FFPE) tumor samples from the patients enrolled were requested from the pathology institutes and used for tumor tissue analyses. This analysis includes participants with blood source DNA that were recruited up to 2010 in this ongoing study. Controls were matched to cases on reference age and sex in a case/control ratio of 2:1. Health Professionals Follow-up Study (HPFS): A parallel prospective study to the NHS (Nurses' Health Study). The HPFS cohort comprised 51,529 men aged 40-75 who, in 1986, responded to a mailed questionnaire (Rimm et al., 1990 PMID:2090285). Participants provided information on health related exposures, including current and past smoking history, age, weight, height, diet, physical activity, aspirin use, and family history of colorectal cancer. Colorectal cancer and other outcomes were reported by participants or next-of-kin and were followed up through review of the medical and pathology record by physicians. Overall, more than 97% of self-reported colorectal cancers were confirmed by medical record review. Information was abstracted on histology and primary location. Incident cases were defined as those occurring after the subject provided the blood sample. Prevalent cases were defined as those occurring after enrollment in the study but before the subject provided the blood sample. Follow-up evaluation has been excellent, with 94% of the men responding to date. Colorectal cancer cases were ascertained through January 1, 2008. In 1993-1995, 18,825 men in the HPFS mailed blood samples by overnight courier, which were aliquoted into buffy coat and stored in liquid nitrogen. In 2001-2004, 13,956 men in the HPFS who had not provided a blood sample previously mailed in a swish-and-spit sample of buccal cells. Incident cases were defined as those occurring after the subject provided a blood or buccal sample. Prevalent cases were defined as those occurring after enrollment in the study in 1986, but before the subject provided either a blood or buccal sample. Participants with histories of cancer (except nonmelanoma skin cancer), ulcerative colitis, or familial polyposis, case-control sets were excluded. Control participants were required to be free of invasive colorectal cancer and non-invasive (stage 0 in situ) colorectal cancer. For this study, only European ancestry participants with blood source DNA and incident colorectal cancer cases were eligible for selection. Since enrollment year and sex matched exactly, controls were randomly selected in a case/control ratio of 2:1. Nurses Health Study (NHS): The NHS cohort began in 1976 when 121,700 married female registered nurses age 30-55 years returned the initial questionnaire that ascertained a variety of important health-related exposures (Belanger et al., 1978 PMID:248266). Since 1976, follow-up questionnaires have been mailed every 2 years. Colorectal cancer and other outcomes were reported by participants or next-of-kin and followed up through review of the medical and pathology record by physicians. Overall, more than 97% of self-reported colorectal cancers were confirmed by medical-record review. Information was abstracted on histology and primary location. The rate of follow-up evaluation has been high: as a proportion of the total possible follow-up time, follow-up evaluation has been more than 92%. Colorectal cancer cases were ascertained through June 1, 2008. In 1989-1990, 32,826 women in NHS I mailed blood samples by overnight courier, which were aliquoted into buffy coat and stored in liquid nitrogen. In 2001-2004, 29,684 women in NHS I who did not previously provide a blood sample mailed a swish-and-spit sample of buccal cells. Incident cases were defined as those occurring after the subject provided a blood or buccal sample. Prevalent cases were defined as those occurring after enrollment in the study in 1976 but before the subject provided either a blood or buccal sample. Participants with histories of cancer (except nonmelanoma skin cancer), ulcerative colitis, or familial polyposis, case-control sets were excluded. For this study, only European ancestry participants with blood source DNA and incident colorectal cancer cases were eligible for selection. Since enrollment year and sex matched exactly, controls were randomly selected in a case/control ratio of 2:1. Prostate, Lung, Colorectal and Ovarian Cancer Screening Trail (PLCO): PLCO enrolled 154,934 participants (men and women, aged between 55 and 74 years) at ten centers into a large, randomized, two-arm trial to determine the effectiveness of screening to reduce cancer mortality. Sequential blood samples were collected from participants assigned to the screening arm. Participation was 93% at the baseline blood draw. White colorectal cancer cases with a family history of colorectal cancer (no history of ulcerative colitis, Crohn's Disease, diverticulitis, Gardner's syndrome, Familial Polyposis) and successful genotyping from previous Peters GWAS were selected for this project. Controls were matched to cases on reference age and sex in a case/control ratio of 2:1. Women's Health Initiative (WHI): WHI is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are: Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d) or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo. The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. All centrally confirmed White cases of invasive colorectal cancer, or death from colorectal cancer were selected as potential cases from the March, 2011 database. Case priory lists are: 1) have positive family history of colorectal cancer; 2) randomly select cases until we get a total of n=800 cases. Control participants were required to be White, free of invasive colorectal cancer and non-invasive (stage 0 in situ) colorectal cancer. Centrally denied cases of colorectal cancer were not allowed into the control pool. Case and control participants were subject to the following exclusion criteria: (1) had prior history of colorectal cancer at baseline; (2) had no available DNA (DNA searching as Nov 15, 2012); (3) cannot be deposited to dbGaP; (4) lost to follow-up after enrollment; (5) selected for WHI study M26 Phase II. Controls were matched to cases in a case/control ratio of 2:1. In order to get 2 cases with 1 control, cases were grouped by enrollment year (a total of 5 groups). For each year group, around 50% cases were selected to match controls. In total, 401 cases were selected to match controls. Matching was done on enrollment year, which was matched exactly. For additional information, see dbGaP: phs000200 and ClinicalTrials: NCT00000611.

  Study phs001554

• Dental Caries: Whole Genome Association and Gene x Environment Studies

  Dental caries (also known as tooth decay) remains the most common chronic disease of childhood, five times more common than asthma and seven times more common than environmental allergies, with more than 40% of children exhibiting caries when they enter kindergarten. In 2005, it was estimated that dental health care costs were approximately $84 billion, of which 60% or about $50 billion were related to treatment of dental caries. Although overall caries prevalence has declined over the last 40 years, dental caries in the primary dentition and mean caries rates in children ages 2-11 has increased markedly over the past 12 years. Childhood caries is a serious public health issue because of associated health problems and because disparities in oral health have led to substantially higher average disease prevalence among children in poverty and in under-served racial and ethnic groups. These issues are of such concern that in 2005, the American Academy of Pediatrics made children's oral health one of their top areas of focus, as it is for the majority of the NIDCR "Disparities Centers". The etiology of dental caries has been studied for many years. Multiple factors contribute to a person's risk for caries, including: 1) environmental factors such as diet, oral hygiene, fluoride exposure and the level of colonization of cariogenic bacteria and 2) host factors such as salivary flow, salivary buffering capacity, position of teeth relative to each other, surface characteristics of tooth enamel and depth of occlusal fissures on posterior teeth. In spite of all that is known about this disease, there are still individuals who appear to be more susceptible to caries and those who are extremely resistant, regardless of the environmental risk factors to which they are exposed, implying that genetic factors also play an important role in caries etiology. This conclusion is supported by studies in both humans and animals, with the most compelling evidence coming from studies of twins reared apart in which investigators found significant resemblance within monozygotic (MZ) but not dizygotic (DZ) twin pairs for percentage of teeth and surfaces restored or carious and estimated the genetic contribution to caries as 40%. Other recent studies of twins reared together estimated the heritability for caries, adjusted for age and gender, as ranging from 45-64%. Despite the strong evidence of a genetic component to risk for dental caries, there have been only a few studies of candidate genes in caries, and no published genome-wide scans. A comprehensive genome wide search is the only approach that will allow us to identify those genetic regions likely to harbor genes increasing the risk for dental caries, and eventually to identify the etiologic genes and to explore the interaction of those genes with microbiological, dietary, fluoride, and behavioral factors that are known to be associated with caries risk and progression. Therefore, the goal of this study is to perform genome-wide association (GWA) studies of dental caries with a large panel of SNP's (610,000) in families and individuals ascertained through multiple US sites (University of Pittsburgh and University of Iowa). The v2 release of this study includes 96 additional individuals who were genotyped with the CCDG: Dental Caries and CL/P in Guatemala project (dbGaP accession number phs000440) to augment the data initially presented here. These subjects were genotyped on the Illumina 610 platform to make their data comparable. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to dental caries through large-scale genome-wide association studies of well-characterized families and individuals at multiple sites in the U.S. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR, U01-DE018903). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. Samples of some participants in this study were selected for further genomic analysis. These results will be available in the dbGaP CIDR study: Center for Oral Health Research in Appalachia (COHRA) Genomic Studies of Oral Health and Disease (phs001591).

  Study phs000095

• Epidemiological study comparing rates and risk factors for dementia in African Americans in Indianapolis and Yoruba living in Ibadan, Nigeria

  In 1991 collaboration between researchers at Indiana University School of Medicine and the University of Ibadan, Ibadan, Nigeria established the Indianapolis-Ibadan Dementia Project. It is a longitudinal, prospective population-based comparative epidemiological study of the prevalence and incidence rates and risk factors of Alzheimer's disease and other age associated dementias. The project compares samples of community-dwelling elderly (age > 70 years) African Americans living in Indianapolis to Yoruba living in Ibadan, Nigeria, employing the same research design, methods, and investigators. It initially reported significantly lower prevalence rates of disorders in the Yoruba compared to the African Americans. In subsequent waves of the study (1994-1995, 1997-1998) incidence rates, rates of newly diagnosed cases, were also found to be significantly lower in the Yoruba. In genetic studies, the frequency of the APOE 4 allele was about the same in the two groups. APOE 4 was a significant risk factor for Alzheimer's disease and dementia in the Americans, while no association was found for the Yoruba. The APOE 2 allele appears to be protective in the Americans, but not the Yoruba. A constellation of factors often associated with vascular risk including a history of hypertension, diabetes, and high cholesterol levels is less common in the Yoruba than in the American group. An interaction was observed between cholesterol, APOE genotype and Alzheimer's disease in both study groups. In 2001-2002 survivors of the original cohort were once again evaluated (N~800 in each site) and 2,000 additional individuals age 70 years and older were enrolled in each site. Blood samples were collected from approximately 1,500 study participants in each site for genetic studies and analysis of biochemical risk factors for vascular disease. Subsequent waves of field work were conducted in 2004, 2007, 2009, and 2011. This fieldwork followed the classic two-stage study design. The study design involves an in-home screening interview with the study participant, which includes a cognitive assessment, medical history and current medications, brief neurological examination, height and weight, blood pressure measurement and assessment of social involvement. There is also a screening interview with a close relative of the study participant to assess activities of daily living, personality change, and medical history of the study participant. On the basis of the screening interview a sample of study participants (N~500 in each site) is selected for a full clinical diagnostic dementia work up which includes a neurological test battery, extensive interview with a family member and examination by a clinician. Diagnoses are made in a consensus diagnosis conference using the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition (DSM-III R) and International Classification of Diseases 10th Revision (ICD-10) for dementia. The criteria of the National Institute for Neurological and Communicative Disease and Stroke-Alzheimer's Disease and Related Disorders Association were used to diagnose possible and probable Alzheimer's disease. The focus of the study is risk factors for dementia and Alzheimer's disease, but also of particular importance is the question of mild cognitive impairment. This refers to the condition of having some decline in cognition but the decline is not sufficient to meet the criteria for dementia. We have studied this over the course of this project. In follow up studies of individuals who have this diagnosis about one third of them are better at follow up, about a third are about the same, and about a third decline more to meet the criteria for dementia. This is a very important issue for researchers because the ultimate goal of the research is to figure out how to identify the individuals who will definitely progress to dementia. If there are clear identifiers, it would be possible to make interventions, while individuals still function well, and possibly prevent the development of dementia altogether or delay the onset significantly. This is crucial because at the moment individuals usually do not enter into the medical care system until the dementia symptoms are quite severe, and the pathological damage to the brain cannot be undone.

  Study phs000378

• High-Risk Breast Cancer GWAS

  The GWAS includes High Risk Women from the following epidemiological studies of breast cancer, comprising a total of 3,719 cases and 3,642 controls (cases/controls: MEC, 0/200; ABCFR, 326/418; FCCC, 56/3; BCFR-UT, 66/32; CNIO-BC, 87/92; GESBC, 65/0; LIFE, 164/0; MARIE, 41/105; MAYO, 208/210; MNYR, 293/409; MSKCC, 310/0; NC-BCFR, 234/233; OFBCR, 553/560; POSH, 377/0; HBOC, 47/47; BBCS, 612/1333; UPENN, 280/0 This study was funded by a grant CA165038 to Christopher Haiman (University of Southern California) and John Hopper (University of Melbourne) from the National Cancer Institute, National Institute of Health. The contributing studies: Multiethnic Cohort (MEC). This study was supported by grant UM1 CA164973 from the National Cancer Institute, National Institute of Health. Ontario Familial Breast Cancer Registry, the Ontario site of the Breast Cancer Family Registry Cohort (OFBCR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Utah Breast Cancer Family Registry (BCFR-UT). This study was supported by grant UM1 CA164920 from the National Cancer Institute. New York site of the Breast Cancer Family Registry (MNYR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Northern California site of the Breast Cancer Family Registry (NC-BCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Australian Breast Cancer Family Registry (ABCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Breast Cancer Study (CNIO-BC). This study has been partially funded by The Spanish Network on Rare Diseases (CIBERER) and the Spanish National Genotyping Center (CEGEN). Genetic Epidemiologic Study of Breast Cancer (GESBC). The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and German Cancer Research Center (DKFZ). Mammary Carcinoma Risk Factor Study (MARIE). This study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Hereditary Breast and ovarian Cancer: Genetic and Molecular Studies (HBOC). This study was supported by National Cancer Institute grant CA58860 and The Lon V Smith Foundation: LVSF-44528. Mayo Clinic inherited breast and ovarian cancer study (MAYO). This study was supported by the Breast Cancer Research Foundation, NIH grants CA192393, CA176785, and an NIH CA116201 Specialized Program of Research Excellence (SPORE) in Breast Cancer. British Breast Cancer Study (BBCS); Mammographic oestrogens and growth factor study (MOG). The BBCS and the MOG study are funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledge NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). Genotyping of non-BRCA1/2 mutation carriers (UPENN). The study is supported by the Basser Research Center at the University of Pennsylvania, Rooney Family Foundation, NIH grants CA176785 and CA192393, the Breast Cancer Research Foundation, the Susan G. Komen Foundation for the Cure and Macdonald Family Foundation. Clinical Significance of Germline BRCA Mutations (MSKCC). The study is supported by the Robert and Kate Niehaus Clinical Cancer Genetics Research Initiative, The Breast Cancer Research Foundation, and the Cancer Center Support Grant from the National Institute of Health, National Cancer Institute 5P30 CA08748-40. Women's Learning the Influence of Family and Environment (LIFE). This study was supported by grants CA17054 and CA74847 from the National Cancer Institute, National Institutes of Health, No. 4PB-0092 from the California Breast Cancer Research Program of the University of California. Philadelphia site of the Breast Cancer Family Registry at Fox Chase Cancer Center (FCCC). This study is supported by NIH grant CA164920.

  Study phs000929

• Cardiovascular Cell Therapy Research Network (CCTRN): A Phase II, RCT of Mesenchymal Stem Cells & Cardiac Stem Cells in Subjects With Ischemic HF (CONCERT HF-BioLINCC)

  Data Access Note: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectivesTo assess the feasibility, safety, and efficacy of autologous mesenchymal stromal cells (MSCs) and c-kit positive cardiac cells (CPCs), alone or in combination, in participants with ischemic heart failure.Background The prognosis of heart failure (HF) caused by chronic ischemic cardiomyopathy (coronary artery disease and prior myocardial infarction), hereby referred to as “ischemic HF”, remains poor. Many studies have explored the use of various types of stem or progenitor cells in participants with chronic ischemic HF, with encouraging results. Several clinical trials have suggested that MSCs and CPCs are both safe and beneficial in participants with ischemic HF. At the time of this study, no information was available on the efficacy of MSCs and CPCs in humans, however, both cell types have been shown to attenuate left ventricle (LV) dysfunction in animal models. Preclinical models indicate that combining MSCs and CPCs increases the therapeutic effects, but this had not yet been tested in humans. The CONCERT-HF study was initiated to assess whether autologous MSCs and CPCs, alone or in combination, can be manufactured and delivered to participants with ischemic HF; are well-tolerated; and improve LV function, quality of life, and functional capacity, and/or reduce scar size. Participants A total of 125 participants were randomized with 33 participants randomized to the MSCs and CPCs group, 29 participants to the MSCs alone group, 31 participants to the CPCs alone group, and 32 participants to the placebo group. Design The CONCERT-HF study was a multi-center Phase II, double-blind, randomized, placebo-controlled trial designed to evaluate the feasibility, safety, and efficacy of MSCs alone, CPCs alone, and their combination compared with placebo as well as each other in patients with ischemic HF. In Stage 1 (open label, lead-in study) participants were randomized 1:1 to either a standard-of-care control group (i.e., they did not undergo harvest, mapping, or injection procedures) or combination therapy (MSCs + CPCs, as described for Stage 2) to complete safety assessments. Once approval was granted for Stage 2, participants were randomized (1:1:1:1) to one of four treatments: placebo, autologous MSCs (target dose, 150 × 106 cells), autologous CPCs (target dose, 5 × 106 cells), or a combination of autologous MSCs and CPCs. At the harvest visit, right ventricular endocardial biopsy (EMB) was performed in participants randomized to receive CPCs alone or a combination of MSCs and CPCs. Participants randomized to receive MSCs alone or placebo had a sham procedure (right heart catheterization without EMB). All participants underwent a bone marrow aspiration and approximately 14 weeks later had transendocardial, electromechanically-guided injections of study product. Visits occurred at 1 day, 1 week, and 1, 3, 6, and 12 months after study product injection. A telephone contact took place at 24 months to assess the participant's current medications, as well as morbidity and mortality. Study endpoints included measures of safety, feasibility, and efficacy. Safety outcomes included all adverse events grade 2 and higher, including major adverse cardiac events (MACE) related to HF (death, hospitalization for worsening HF, and HF exacerbation not requiring hospitalization). Efficacy endpoints included quality of life, MRI measures of LV function and structure, functional capacity, and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. Conclusions In patients with ischemic HF, autologous MSCs and CPCs, alone or in combination, are safe and feasible; CPCs were associated with a reduction in the incidence of MACE related to HF compared to placebo; MSCs, either alone or in combination with CPCs, were associated with improved quality of life; these seemingly beneficial effects of CPCs and MSCs on clinical outcome were not associated with changes in LV function or structure; and combination therapy with MSCs and CPCs was associated with the best clinical outcomes with respect to both MACE related to HF and quality of life.

  Study phs004055

• Idiopathic Pulmonary Fibrosis Network AntiCoagulant Effectiveness in Idiopathic Pulmonary Fibrosis (IPFNet-ACE-IPF-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The ACE-IPF trial tested the hypothesis that treatment with warfarin at recognized therapeutic doses would reduce rates of mortality, hospitalization, and declines in Forced Vital Capacity (FVC) in subjects with Idiopathic pulmonary fibrosis (IPF).Background: IPF is a chronic, progressive lung disease of unknown cause characterized by the histopathologic pattern of usual interstitial pneumonia. The median survival of patients with IPF after the onset of symptoms is 2 to 5 years. Prior animal and human studies in pulmonary fibrosis provide a compelling rationale to examine anticoagulation as a therapeutic approach in IPF. Large epidemiologic studies link IPF with thrombosis-related clinical events, such as an increased risk of acute coronary syndrome and deep vein thrombosis. The suspected causal relationship may extend beyond simple coagulation cascade-induced thrombus formation, as procoagulant enzymes may directly stimulate fibrosis via cell surface receptor - mediated responses.Participants: Patients aged 35 to 80 years with progressive IPF were potentially eligible. Progressive IPF was defined as a history of (1) worsening of dyspnea, or (2) physiologic deterioration defined as an absolute decline of either FVC greater than or equal to 10% or DlCO greater than or equal to 15%, a reduction in arterial oxygen saturation of greater than or equal to 5%, or progression of radiographic findings. Between December 14, 2009 and April 1, 2011, 145 subjects were enrolled: 72 in the warfarin group and 73 in the placebo group. The mean age for the population was 67 years. 27% of the subjects were women and 92% were white.Participants were excluded if they met any of the following criteria: current indication for, or treatment with, warfarin, prasugrel, or clopidogrel combined with aspirin; the presence of an increased risk of bleeding; a recent cerebral vascular accident or gastrointestinal bleeding; any current signs or symptoms of severe, progressive, or uncontrolled comorbid illness; and their presence on the active list for lung transplantation. Design: ACE-IPF was a double-blind, randomized, placebo-controlled trial of warfarin targeting an international normalized ratio (INR) of 2.0 to 3.0 in patients with IPF. Subjects were randomized in a 1:1 ratio to warfarin or matching placebo for a planned treatment period of 48 weeks. Study subjects were provided two strengths of warfarin tablets (1 mg and 2.5 mg) or matching placebos. Subjects measured their INR with encrypted meters at least weekly. Participants were seen at screening, baseline, and at 16, 32, and 48 weeks after enrollment. Home monitoring was validated by plasma INR measurement at the week 1 and 16 visits.The primary outcome was a composite endpoint based on the time to all-cause mortality; nonelective, nonbleeding hospitalization; or a decrease in the absolute FVC greater than or equal to 10% from baseline value. Secondary outcome measures included rates of mortality, hospitalization, respiratory-related hospitalization, acute exacerbation, bleeding, cardiovascular events, and changes over time in FVC, 6-minute walk test distance, DlCO, plasma fibrin D-dimer levels, and quality of life (QOL).Conclusions: The study did not show a benefit for warfarin in the treatment of patients with progressive IPF and was terminated due to excess mortality in the warfarin treatment group. Treatment with warfarin was associated with an increased risk of mortality in an IPF population who lacked other indications for anticoagulation.Reported causes of death indicated 11 of the 14 were respiratory-related in the warfarin group versus three of the three in the placebo group. There were also three cardiovascular deaths in the warfarin group versus none in the placebo group. No deaths were attributed to bleeding. The warfarin group also demonstrated an increased rate of combined all-cause hospitalization and all-cause mortality. (Am J Respir Crit Care Med. 2012 Jul 1;186(1):88-95.)

  Study phs004070

• Prematurity and Respiratory Outcomes Program (PROP) Core Database Protocol (PROP-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The Prematurity and Respiratory Outcomes Program (PROP) was performed to identify suitable predictors of respiratory outcomes that may serve as surrogate endpoints in future trials of prevention and therapy of respiratory diseases in preterm infants.Background: Acute and chronic respiratory morbidities are common in premature births, and can pose significant risk to the infant's health, particularly during the first two years of life. One such condition is bronchopulmonary dysplasia (BPD) where infants require oxygen therapy due to abnormal repair and impaired lung development after acute lung injury. BPD poses a high mortality risk, even in infants that survive the initial hospitalization. Regardless of BPD diagnosis, preterm infants frequently return for medical care due to symptoms of post-prematurity respiratory disease (PRD), which includes intermittent or chronic wheezing, cough without cold, poor growth, apnea and cyanosis, and lower respiratory tract infections. Impaired lung function can persist into adulthood, contributing to chronic respiratory diseases including asthma and emphysema.However, at the time of the PROP study, there were no objective measures to predict which preterm infants would have persistent respiratory problems after discharge from the hospital. Furthermore, improved survival rates of premature infants and the high prevalence of lasting respiratory morbidities highlight the need for more comprehensive strategies to address both short-term and long-term respiratory complications. Thus, the Prematurity and Respiratory Outcomes Program (PROP) was formed to investigate multiple research hypotheses on the molecular mechanisms that contribute to respiratory disease risk of premature neonates over the first year of life. Specifically, PROP investigators hypothesized that in survivors of extreme prematurity to 36 weeks postmenstrual age (PMA), specific biologic, physiologic and clinical data obtained during the initial hospitalization will predict respiratory morbidity between discharge and 1 year corrected age. Participants: A total of 835 infants were enrolled.Design: PROP was a collaboratively developed multicenter prospective cohort study of very preterm infants from birth through the time of discharge from the NICU and up to one year corrected age.Clinical data included maternal and infant demographics, co-morbidities, and daily infant respiratory, nutritional, and medication data until discharge. These were prospectively collected from birth using medical record review and family interviews. After discharge, phone interviews were conducted with the infant's main caregiver at 3, 6, 9 and 12 months corrected age to assess domains of respiratory morbidity. At 6 and 12 months corrected age, a survey of environmental respiratory irritant exposures and an assessment for gastroesophageal reflux disease were also completed. A standardized physical exam was performed at 36-40 weeks PMA and again at one year corrected age. The exam focused on anthropometrics, vital signs, and respiratory system signs. At 34-41 weeks PMA and within one week of anticipated discharge based on physiologic stability, a set of non-invasive respiratory assessments were performed to assess physiologic biomarkers in infants that were not mechanically ventilated or receiving non-invasive positive pressure ventilation. Respiratory inductance plethysmography (RIP) was performed before and after inhaled albuterol to assess potential airway reactivity. During the RIP study, continuous pulse oximetry was performed during quiet sleep in order to analyze oxygen desaturations and apneas. Standardized oxygen requirement challenge tests were performed at about 36 weeks PMA, and at about 40 weeks PMA if the infant was still hospitalized and was not eligible for, or failed, the previous challenge. Failure was defined as SpO2 20 seconds at any point in the testing. Infants breathing ambient air or that passed the 36 week challenge test underwent a hypoxia challenge consisting of a 15-minute trial of FiO2 of 0.15. Failure was defined as SpO2 The primary outcome was respiratory morbidity, as measured by the presence or absence of substantial post-prematurity respiratory disease (PRD) up to one year corrected age. PRD was classified as a positive response in at least one of four morbidity domains during at least two separate parental interviews. The domains were respiratory medications, hospitalizations for cardiopulmonary cause, respiratory symptoms, and home technology dependence (oxygen, ventilator, or CPAP/BiPAP). Mortality from a respiratory cause was also incorporated.

  Study phs004117

• HBCC Postmortem Psychiatric Molecular Studies

  This postmortem study examines molecular, genetic and epigenetic signatures in the brains of hundreds of subjects with or without mental disorders conducted by the DIRP NIMH Human Brain Collection Core (HBCC). The brain tissues are obtained under protocols approved by the CNS IRB (NCT00001260), with the permission of the next-of-kin (NOK) through the Offices of the Chief Medical Examiners (MEOs) in the District of Columbia, Northern Virginia and Central Virginia. Additional samples were obtained from the University of Maryland Brain and Tissue Bank (contracts NO1-HD-4-3368 and NO1-HD-4-3383) (http://www.medschool.umaryland.edu/btbank/ and the Stanley Medical Research Institute: http://www.stanleyresearch.org/brain-research/). Clinical characterization, neuropathological screening, toxicological analyses, and dissections of various brain regions were performed as previously described (Lipska et al. 2006; PMID: 16997002). All patients met DSM-IV criteria for a lifetime Axis I diagnosis of psychiatric disorders including schizophrenia or schizoaffective disorder, bipolar disorder and major depression. Controls had no history of psychiatric diagnoses or addictions. SNP array: Array-based genotyping was performed on most samples published in this collection. The number of SNPs assayed via Illumina chips varied between 650,000 and 5 Million. Cerebellar tissue was generally used for genotyping studies. # Diagnosis SNP Array 1 Anxiety Disorder 1 2 Autism Spectrum Disorder 13 3 Bipolar Disorder 114 4 Control 387 5 Eating Disorder (ED) 2 6 Major Depressive Disorder (MDD) 186 7 Obsessive Compulsive Disorder (OCD) 5 8 Post-Traumatic Stress Disorder (PTSD) 0 9 Schizophrenia 220 10 Other 7 11 Tic Disorder 3 12 Undetermined 1 13 Williams Syndrome 2 Table: Numbers of samples in each diagnostic category. DNA extraction: 45-80 mg of cerebellar tissue was pulverized for DNA extractions. The QIAamp DNA mini Kit (Qiagen) method was employed for tissue DNA extraction. The tissue was initially lysed using Tissue Lyser (Qiagen) and extractions were accomplished according to manufacturer's protocol. The DNA was captured in 500uL elution buffer. The concentrations were measured using Thermo Scientific's NanoDrop 1000/NanoDrop ONE. The mean yield was 128.85 uG (+/- 79.48), the mean ratio of 260/280 was 1.87 (+/- 0.105), and the mean ratio of 260/230 was 2.48 (+/-1.75). Genotyping methods: Three types of Illumina Beadarray chips were used: HumanHap650Y, Human1M-Duo, and HumanOmni5M-Quad (San Diego, California). The genotyping was done according to the manufacturer's protocol (Illumina Proprietary, Catalog # WG-901-5003, Part # 15025910 Rev.A, June 2011). Approximately, 400ng DNA was used and each DNA sample was QC tested for 260/280 ratio by nanodrop and DNA band intactness on 2% agarose gel. Briefly, the samples were whole-genome amplified, fragmented, precipitated and resuspended in appropriate hybridization buffer. Denatured samples were hybridized on prepared Bead Array Chips. After hybridization, the Bead Chip oligonucleotides were extended by a single fluorescent labeled base, which was detected by fluorescence imaging with an Illumina Bead Array Reader, iScan. Normalized bead intensity data obtained for each sample were loaded into the Illumina Genome Studio (Illumina, v.2.0.3) with cluster position files provided by Illumina, and fluorescence intensities were converted into SNP genotypes. Microarray: We generated RNA expression data using array technology for psychiatric subjects compared to non-psychiatric subjects as controls. We used tissues from three different brain regions i.e. hippocampus, dorsolateral prefrontal cortex (DLPFC), and dura mater for a large cohort of individuals (total number 552 subjects for hippocampus, 800 for DLPFC and 146 for dura). Total RNA was extracted from ~100 mg of tissue using the RNeasy kit (Qiagen) according to the manufacturer's protocol. RNA quality and quantity were examined using the Bioanalyzer (Agilent, Inc) and NanoDrop (Thermo Scientific, Inc), respectively. Samples with RNA integrity number (RIN) # Diagnosis DLPFC Hippo Dura 1 Anxiety Disorder 1 0 0 2 Autism Spectrum Disorder 14 6 0 3 Bipolar Disorder 90 49 0 4 Control 336 270 75 5 Eating Disorder (ED) 2 1 0 6 Major Depressive Disorder (MDD) 144 87 0 7 Obsessive Compulsive Disorder (OCD) 5 3 0 8 Post-Traumatic Stress Disorder (PTSD) 6 0 0 9 Schizophrenia 192 125 71 10 Other 5 6 0 11 Tic Disorder 3 3 0 12 Undetermined 1 1 0 13 Williams Syndrome 2 1 0 Table: Numbers of samples in each diagnostic category. RNA-Seq of Dorso-lateral prefrontal cortex: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. RNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. RNA isolation: Total RNA from 468 HBCC samples was isolated from approximately 100 mg homogenized tissue from each sample by TRIzol/chloroform extraction and purification with the Qiagen RNeasy kit (Cat#74106) according to manufacturer's protocol. Samples were processed in randomized batches of 12. The order of extraction for schizophrenia, bipolar, and MDD disorders and control samples was assigned randomly with respect to diagnosis and all other sample characteristics. The mean total RNA yield was 24.2 ug (+/- 9.0). The RNA Integrity Number (RIN) was determined by 4200 Agilent TapeStation System. Samples with RIN DLPFC RNA-Seq quantified expression data are provided for 364 samples. Data were generated, QC'd, processed and quantified as follows: RNA library preparation and sequencing: All samples submitted to the New York Genome Center for RNAseq were prepared for sequencing in randomized batches of 94. The sequencing libraries were prepared using the KAPA Stranded RNAseq Kit with RiboErase (KAPA Biosystems). rRNA was depleted from 1ug of RNA using the KAPA RiboErase protocol that is integrated into the KAPA Stranded RNAseq Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. Schizophrenia Bipolar Control 89 65 210 Table: Numbers of samples in each diagnostic category. RNA-Seq of subgenual anterior cingulate cortex (sgACC): All the 200 post-mortem brain samples (61 controls; 39 bipolar disorder; 46 schizophrenia; 54 major depressive disorder) were collected by the HBCC, DIRP, NIMH. RNA Extraction and Quality Assessment: Tissue from sgACC was pulverized and stored at -80°C. Total RNA was extracted from 50-80 mg of the tissue using QIAGEN RNeasy Lipid Tissue Mini Kit (QIAGEN, Cat. # 74804) with DNase treatment (QIAGEN, Cat. # 79254). The RNA Integrity Number (RIN) for each sample was assessed with high-resolution capillary electrophoresis on the Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, California). The concentration of RNA and their 260/280 ratio (2.1+/- 0.032 SD) were determined with NanoDrop (Thermo Scientific). RNA sequencing: Stranded RNA-Seq libraries were constructed after rRNA depletion using Ribo-Zero GOLD (Illumina). RNA sequencing was performed at National Institute of Health Intramural Sequencing Center (NISC). Schizophrenia Bipolar Control MDD 46 39 61 54 Table: Numbers of samples in each diagnostic category. Whole Genome Sequencing: All brains were collected and dissected at the HBCC, DIRP, NIMH. This study generates whole genome sequencing data using sequencing of DNA in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) or cerebellum of 443 individuals with schizophrenia, bipolar disorder and major depressive disorder and non-psychiatric controls. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. DNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. All specimens were dissected from right or left hemisphere of frozen coronal slabs. DNA Library Preparation and Sequencing: All samples submitted to the New York Genome Center for WGS were prepared for sequencing in randomized batches of 95. The sequencing libraries were prepared using the Illumina PCR-free DNA sample preparation Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. A quantitative PCR assay (KAPA), with primers specific to the adapter sequence, was used to determine the yield and efficiency of the adaptor ligation process. Performed on the Illumina HiSeqX with 30X coverage. Schizophrenia Bipolar Control 115 78 230 Table: Numbers of samples in each diagnostic category. ChIP-Seq: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. This study generates epigenetic data using sequencing of DNA after chromatin immunoprecipitation (ChIP-Seq) for marks H3K4me3 and H3K27ac in the dorsolateral prefrontal cortex (DLPFC). Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029,6574. Chromatin precipitation, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. Chromatin immunoprecipitation (ChIP) assays for histone marks H3K4me3 and H3K27ac were carried out using Native ChIP. Micrococcal Nuclease (MNase) (Sigma, N3755) treatment was used to digest chromatin into mononucleosomes. The following antibodies were used for chromatin pull-down: anti-H3K4me3 (Cell Signaling, Cat# 9751BC, lot 7) and anti-H3K27ac (Active Motif, Cat# 39133, Lot # 31814008). Histone modification-enriched genomic DNA fragments were recovered using Protein A/G magnetic beads (Thermo Scientific, 88803-88938 or Millipore 16-663), and then washed, eluted, and treated with RNAse A and proteinase K. Final ChIP DNA products were isolated using phenol-chloroform extraction followed by ethanol precipitation. The efficiency of each ChIP assay was validated using Qubit concentration measurement and qPCR for positive (GRIN2B, DARPP32) and negative (HBB) control genomic regions. Only ChIP assays that passed quality control were further processed for library preparation and sequencing; this included ChIP DNA that was not detectable on Qubit but showed a good signal and expected enrichment patterns in qPCR. HISTONE_MARK H3K27ac H3K4me3 Input Bipolar 56 4 7 Control 158 11 24 Schizophrenia 79 11 12 Table: Numbers of individuals in each assay grouped by histone mark or input.Long-Read Whole-Genome Sequencing (WGS) Cohort Description: Brain specimens were obtained from the Human Brain Collection Core (HBCC), part of the NIH NeuroBioBank. Samples were collected under protocols approved by the NIH CNS Institutional Review Board (IRB) (NCT03092687), with informed consent from next-of-kin (NOK). Collection was coordinated through the Offices of the Chief Medical Examiners (MEOs) in Washington, D.C., Northern Virginia, and Central Virginia. Clinical metadata and documentation are publicly available via the NIMH Data Archive (NDA) (Collection #3151) https://nda.nih.gov/edit_collection.html?id=3151 Eligibility Criteria No clinical diagnosis of major neuropsychiatric or neurodegenerative diseaseNo diagnosis of cognitive impairment during life All individuals were confirmed to be neurologically normal at time of deathDemographics Initial cohort size: 155 individuals Ancestry: All individuals self-identified as African or African-admixed Mean age at death: 44.2 years (range: 18–85 years) Sex distribution: 36.4% femaleSample Processing: Frozen frontal cortex tissue was dissected and processed according to the public protocol: https://www.protocols.io/view/processing-human-frontal-cortex-brain-tissue-for-p-kxygxzmmov8j/v2. High-molecular-weight DNA was extracted and libraries were prepared using the Oxford Nanopore Technologies (ONT) LSK-114 kit. Sequencing was performed using ONT PromethION flow cells (R10.4.1 chemistry) Data Processing and Quality Control: Basecalling: Conducted using Guppy v6.38 Read Alignment: Reads were aligned to the GRCh38 reference genome using minimap2 Sample Identity Verification: Sample identity was validated by comparing ONT-derived SNP calls with matched short-read WGS genotypes to ensure concordance and prevent sample swaps Variant Calling and Phasing: Reads were base-called with Guppy v6.38. Reads were aligned to GRCh38 using minimap2. We verified sample identity by cross-checking ONT SNV calls with the existing short-read WGS genotypes, confirming no sample switches. The napu pipeline (https://github.com/nanoporegenomics/napu_wf) produced; haplotype-resolved assemblies, joint small-variant (SNV/indel) calls, and multi-caller structural-variant sets, all reported on GRCh38 and phased where possible. Raw signal data were basecalled to obtain 5-methyl-cytosine (5mC) status; methylation tags were added to the phased BAM files. Genome-wide methylation summaries are provided in BED format.Dataset Filtering and Exclusions: All 155 samples underwent sequencing and SNP-based ancestry inference 8 samples were excluded due to ancestry inconsistent with African or African-admixed background 1 sample was excluded due to insufficient sequencing quality Final Sample Set: 146 high-quality samples from individuals of African or African-admixed ancestry were retained for downstream analyses See PMID: 39764002 for further analysis detailsDiagnosis#SamplesControl155Table: Diagnostic Summary.Note: The data derived from HBCC resources were removed from dbGAP and are now available in the NIMH Data Archive (NDA). They include genotypes, short read whole genome sequencing (WGS), epigenetics (DNA methylation, ChIP-seq for histones), RNA expression (qPCR, microarray, RNA-seq, single nucleus RNA-seq) of various brain regions in cases with schizophrenia, bipolar disorder, major depression, substance use disorders and normative controls. Please access our NDA collection (https://nda.nih.gov/edit_collection.html?id=3151) for further detail.

  Study phs000979

• FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

  The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

  Blog fega-faqs-elixir-ahm-2024

• GAW16 Framingham and Simulated Data

  Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

  Study phs000128

• National Eye Institute (NEI) Age-Related Eye Disease Study (AREDS)

  The Age-Related Eye Disease Study (AREDS) was initially designed as a long-term multi-center, prospective study of the clinical course of age-related macular degeneration (AMD) and age-related cataract. In addition to collecting natural history data, AREDS included a clinical trial of high-dose vitamin and mineral supplements for AMD and a clinical trial of high-dose vitamin supplements for cataract. AREDS participants were 55 to 80 years of age at enrollment and had to be free of any illness or condition that would make long-term follow-up or compliance with study medications unlikely or difficult. On the basis of fundus photographs graded by a central reading center, best-corrected visual acuity and ophthalmologic evaluations, 4,757 participants were enrolled in one of several AMD categories, including persons with no AMD. The clinical trials for AMD and cataract were conducted concurrently. AREDS participants were followed on the clinical trials for a median time of 6.5 years. Subsequent to the conclusion of the clinical trials, participants were followed for an additional 5 years and natural history data were collected. The AREDS research design is detailed in AREDS Report 1. AREDS Report 8 contains the mainline results from the AMD trial; AREDS Report 9 contains the results of the cataract trial. Blood samples were also collected from 3,700+ AREDS participants for genetic research. Genetic samples from 600 AREDS participants (200 controls, 200 Neovascular AMD cases, and 200 Geographic Atrophy cases) were selected using data available in March 2005 and then were evaluated with a genome-wide scan. These data, as well as selected phenotypic data, were made available in the dbGaP. DNA from AREDS participants, which is currently being stored in the AREDS Genetic Repository, is available for research purposes. However, not all of the 3,700+ AREDS participants who submitted a blood sample currently have DNA available. In addition to including the data from the genome-wide scan on the 600 original samples, this second version of the AREDS dbGaP database provides a comprehensive set of data tables with extensive clinical information collected for the 4,757 participants who participated in AREDS. The tables include information collected at enrollment/baseline, during study follow-up, fundus and lens pathology, nutritional estimates, quality of life measures and measures of morbidity and mortality. In November 2010, over 72,000 high quality fundus and lens photographs of 595 AREDS participants (of the original 600 selected for the genome-wide scan) were made available in the AREDS dbGaP. In addition to the genome-wide scan data, the fundus and lens grading data for these participants are also available through the AREDS dbGaP. Details about the ocular photographs that are available may be found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs". In January 2012, a measure of daily sunlight exposure was added in a separate "sunlight" table. Furthermore, the "followup" table has been revised. The visual acuity for the right eye was inadvertently missing at odd-numbered visits (01, 03, 05, etc.). This data is now part of the table. In February 2014 over 134,500 high-quality fundus photographs (macular field F2) of 4613 AREDS participants were added to the existing AREDS dbGaP resource. The AREDS dbGaP image archive already contains over 72,000 high quality fundus and lens photographs of 595 AREDS participants for whom dbGaP-accessible genotype data exist. Information about the available ocular photographs found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs" has been updated with an addendum. It is hoped that this resource will better help researchers understand two important diseases that affect an aging population. These data may be applied to examination and inference on genetic and genetic-environmental bases for age-related diseases of public health significance and may also help elucidate the clinical course of both conditions, generate hypotheses, and aid in the design of clinical trials of preventive interventions. Definitions of Final AMD Phenotype Categories Please see phd001138.1 for a detailed description of how AREDS participants' final AMD phenotype was categorized. User's Guide for AREDS Phenotype Data A detailed User's Guide for the AREDS phenotype data is available. This User's Guide is meant to be a comprehensive document which explains the complexities of the AREDS data. It is recommended that all researchers using AREDS phenotype data make use of this User's Guide.

  Study phs000001

• A Randomized, Double-Blind, Crossover Study of Sodium Phenylbutyrate (Buphenyl) and Low-Dose Arginine (100 mg/kg/day) Compared to High-Dose Arginine (500 mg/kg/day) Alone on Liver Function, Ureagenesis and Subsequent Nitric Oxide Production in Patients with Argininosuccinic Aciduria (ASA)

  Individuals with Urea Cycle Disorders (UCD) cannot remove ammonia, a waste product, from the blood. At present there is little information on the use of sodium phenylbutyrate (Buphenyl™) in children with argininosuccinic aciduria (ASA). It is hoped that this drug may help lower ammonia and argininosuccinic acid levels in patients with ASA. Through this study we hope to learn whether the use of sodium phenylbutyrate (Buphenyl™) in patients with ASA, in addition to diet and arginine therapy, will decrease liver damage and the number of periods during which ammonia levels are high. The primary study objective is to determine if the treatment of ASA patients with sodium phenylbutyrate (Buphenyl™) in conjunction with lowered doses of arginine improves liver function as measured by short-term assessment of synthetic activity and the use of stable isotope tracers to assess ureagenesis and nitric oxide production. Twelve patients with ASA will be studied using a randomized, cross-over design. Medical records will be reviewed to confirm the diagnosis prior to enrollment. Patients will be on the each arm of the study for one week each preceded by a three day washout period. Patients will come to the Baylor College of Medicine General Clinical Research Center in Texas Children's Hospital for an inpatient hospitalization. This hospitalization is for diet control, clinical evaluation, and stable isotope infusions for measurement of in vivo rates of ureagenesis and nitric oxide production. During the washout periods Buphenyl™ or other alternative route medications, e.g., benzoate, will be discontinued and arginine will be administered at the standard therapeutic dose of 500 mg/kg/day or 10 grams/m2. Following randomization, subjects will be maintained on either high-dose arginine (500 mg/kg/day or 10 grams/m2) alone, or the alternative of low-dose arginine (100 mg/kg/d or 2 grams/m2) along with sodium phenylbutyrate (500 mg/kg/day or 10 grams/m2). For the second week they will be crossed over to the other arm of the study preceded by another three day washout. Previous medications and dietary protein intake (0.6 g/kg/day or current metabolic diet) will be continued during both arms of the study. The two arms may be performed as separate ten-day admissions. The decision to design the study with two arms, high-dose arginine and low-dose arginine/Buphenyl™, was reached after weighing several considerations. First, the current accepted practice for treatment of ASA is high-dose arginine. Based on metabolic flux studies, we have quantified the effects of this dose of arginine as compared to standard doses of Buphenyl™/phenylacetate on ureagenesis. Since the study is not designed or intended to address the independent effects of Buphenyl™ as compared to arginine alone, Buphenyl™ was added for safety reasons to accommodate loss of clearance of nitrogen by decreasing the arginine dose. Moreover, based on our experience with recruiting for previous versions of this study, most ASA patients with liver dysfunction are on an alternative route ammonia scavenger medication in addition to arginine. We found that this has in fact become an accepted practice. Hence, when considering study design from both a safety and recruitment perspective, it was most reasonable to design the study to investigate specifically the hypothesis that the production and presence of argininosuccinic acid leads to liver dysfunction. Since both low-dose arginine with Buphenyl™ and high-dose arginine alone lead to a decreased production of argininosuccinic acid, and both are currently accepted therapies in ASA and UCDs in general, the need to address their effects distinctly is not being investigated at this time. Sodium phenylbutyrate dosage will be 500 mg/kg/day in patients weighing less than 20kg and 10 g/m2/day in larger patients. Daily dosage will be given in equally divided doses 4 times per day. In order to ensure that the study remains double-blind to investigators, study staff and subjects, the Investigational Pharmacy Service at Texas Children's Hospital will dispense both the Buphenyl™ and arginine in powder form which is compounded into capsules or will be mixed with syrpalta (up to 5 grams will dissolve in 10cc liquid) and administered orally or through nasogastric or gastrostomy tube. No nasogastric tube should be placed or gastrostomy performed solely for the purpose of inclusion in this study. Because the reported adverse effects of sodium phenylbutyrate include gastritis, participants will be started on a standard dose of ranitidine (Zantac™), or comparable drug, during both arms of the study.

  Study phs001305

• Resuscitation Outcomes Consortium (ROC) Prehospital Resuscitation Using an Impedance Valve and Early Versus Delayed Analysis (PRIMED) (ROC-PRIMED-BioLINCC)

  Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Objective: The purpose of this study was to examine two different treatments during a cardiac arrest that occurs outside of the hospital and whether either or both treatments would increase the number of people who lived to hospital discharge with satisfactory functional status. The first treatment involved using a device called the Impedance Threshold Device (ITD). The other treatment involved the amount of CPR given before the emergency medical services (EMS) providers first looked at the heart rhythm to determine if a shock is needed.Background: Out-of-hospital cardiac arrest is a common and lethal problem with a low survival rate, leading to an estimated 330,000 deaths each year in the United States and Canada. The traditional approach to out-of-hospital cardiac arrest has been to emphasize early analysis of cardiac rhythm, with delivery of defibrillatory shocks, if indicated, as quickly as possible. It has been suggested, however, that many participants may benefit from a period of CPR before the first analysis of rhythm.The impedance threshold device (ITD) is designed to enhance venous return and cardiac output during CPR by increasing the degree of negative intrathoracic pressure. Previous studies have suggested that the use of an ITD during CPR may improve survival rates after cardiac arrest. This effect is achieved by preventing the passive inflow of air into the chest during chest recoil between chest compressions without impeding active ventilation. The ITD has been found to improve hemodynamics, the perfusion of vital organs, and neurologically intact survival in studies in animals. The results of small, short-term clinical trials have suggested that the ITD can increase systolic blood pressure during resuscitation and improve short-term survival rates. Participants: In the ITD study, 4,345 participants were assigned to sham ITD and 4,373 to active ITD, while in the early versus later rhythm analysis, 5,290 participants were assigned to early cardiac rhythm analysis, and 4,643 were assigned to later cardiac rhythm analysis. This study qualified for exception from informed consent required for emergency research.Design: Most participants were enrolled simultaneously in both the early analysis versus later analysis component and the active ITD versus sham ITD component of the trial.The use of an active ITD was compared with that of a sham ITD in participants at 10 ROC sites in the United States and Canada. Participants, investigators, study coordinators, and all care providers were unaware of the treatment assignments. EMS personnel were trained in ITD function, proper use of the ITD, and all aspects of protocol implementation, with an emphasis on the optimal performance of CPR according to local guidelines. The first EMS responders to arrive at the scene of the arrest who were equipped with a randomly assigned ITD (active or sham) attached the device between the ventilation bag and face mask or between the bag and an advanced airway. Responders were encouraged to implement use of the device within 5 minutes after their arrival or as soon as clinically possible. Each of the 10 participating ROC centers was also divided into approximately 20 clusters. All episodes of cardiac arrest in a cluster were randomly assigned to one CPR strategy; after a set period of time, ranging from 3 to 12 months, all episodes in that cluster were then assigned to the other strategy. Participants in the early-analysis group were assigned to receive 30 to 60 seconds of chest compressions and ventilations (sufficient time to place defibrillator electrodes) before electrocardiographic (ECG) analysis, and those in the late-analysis group were assigned to receive 3 minutes of chest compressions and ventilations before ECG analysis. The start and stop times for CPR were recorded by the responders, and the information was supplemented by the recording of defibrillator time. Conclusions: All 10 sites halted enrollment in November 2009 when the data and safety monitoring board recommended termination because interim analysis showed that the findings were not likely to change with continuation of the study. Neither use of the ITD nor the amount of CPR given before cardiac rhythm analysis significantly improved survival with satisfactory function (i.e., a score of ≤3 on the modified Rankin scale) among participants with out-of-hospital cardiac arrest receiving standard CPR. There were also no significant differences in the secondary outcomes, including rates of return of spontaneous circulation on arrival at the emergency department, survival to hospital admission, and survival to hospital discharge.

  Study phs003825

• Lung Tissue Research Consortium (LTRC-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from LTRC include DNA, Plasma, Serum, Tissue - FFPE Cassettes, Tissue – RNALater Frozen, and Tissue - Snap Frozen. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: The LTRC was a biobank resource established by the NHLBI to collect and distribute lung tissue, blood samples, clinical data, and radiographic studies from participants with chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), other related idiopathic interstitial pneumonias (IIP) and interstitial pneumonias associated with connective tissue diseases who undergo medically-indicated lung resection. All tissue and blood specimens and clinical data were banked centrally and stored for distribution to external investigators who have approved study proposals to investigate the pathogenesis or management of lung diseases. The ultimate goal of this program was to enable research that illuminates the pathobiology of lung diseases and leads to novel interventional treatments for these conditions. Background: Chronic lung diseases are a main cause of death and disability in the United States. COPD affects over 14 million individuals in the United States and represents the third leading cause of mortality. Cigarette smoking is a major risk factor. However, only one of six individuals who smoke develops COPD. This could imply either an individual susceptibility or an additional immunologic or infectious injury to lung cells. Current treatments offer symptomatic relief, but do not prevent disease progression. Better understanding of disease pathogenesis, including the potential roles of lung parenchymal cell apoptosis, immunologic injury, and inflammation may lead to therapies that improve survival and quality of life. Interstitial pneumonias, including IPF and those associated with connective tissue disease, are less common than COPD, but for many of these diseases there are poor outcomes. For example, IPF has a 50% survival rate 2-3 years following diagnosis, and currently no treatment exists which prolongs survival. The prevalence of IPF is approximately 28 cases per 100,000. The underlying histology of IPF is usual interstitial pneumonia (UIP), which can also occur in connective tissue diseases. The incidences of other interstitial pneumonias such as non-specific interstitial pneumonia (NSIP) or acute interstitial pneumonia (AIP) are less frequent but also occur as an expression of interstitial lung disease in the connective tissue diseases. Moreover, there is significant crossover of these three interstitial pneumonias so that cases of IPF/UIP may also reveal fibrotic NSIP and be complicated by episodes of AIP. This implies common injuries but dissimilar histological responses. All of these processes are characterized by epithelial injury, uncontrolled fibroproliferation and the deposition of collagen, irrespective of the histology. It is clear that a better understanding of the genesis of the interstitial pneumonias is required before effective interventions can be developed. Participants: A total of 4,486 participants were enrolled, and lung tissue was obtained from 3,333 of these participants.Design: Written informed consent of each participant was required before any LTRC procedure was performed. Phenotypic data were then obtained that included recording of relevant medical information, a limited exposure history, radiological evaluation, and pulmonary physiological and lung function testing. Questionnaires were administered to determine the extent of symptoms, associated medical illnesses, smoking, environmental and occupational exposures, and quality of life. Laboratory testing included pulmonary function testing, a six-minute walk test, and chest x-ray CT. Blood specimens were collected both for defining the clinical phenotype of donors and to obtain serum, plasma, and DNA for later investigative purposes. At the time of surgery, lung tissues were collected and processed for long-term storage. The LTRC collected only the 'non-tumorous' portions of lung tissue from surgical procedures performed for primary or metastatic lung tumors and received those specimens only after the local pathologist had procured all tissue required for clinical care. Samples of appropriate size were cut and placed in formalin, RNAlater, glutaraldehyde, or liquid nitrogen within 30 minutes of excision (approximately 5% of cases exceeded this target time). Blood and tissue specimens were subsequently shipped to a central Tissue Repository for further processing and long-term storage. A Radiology Center provided quality control and quality assessment of CT data. A Data Coordinating Center managed study operations and maintained a repository of study data. Conclusions: LTRC established a biospecimen collection that is unique in its size, diseases included, standardization of methods, and extent of phenotypic data, serving as a valuable resource to facilitate research on the pathobiology of lung diseases.

  Study phs003913

• NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

  The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

  Study phs003047

• The Primary Open-Angle Glaucoma Genes and Environment (GLAUGEN) Study

  Background Information: Primary open-angle glaucoma (POAG) is an age-related, intraocular pressure (IOP)-dependent progressive optic neuropathy that ultimately leads to irreversible blindness. Vision loss from POAG is a condition of public health significance. Current evidence suggests that POAG is a polygenetic disease modified by environmental influences. Despite the fact that a positive family history of disease is an important risk factor for POAG, conventional linkage and candidate gene approaches have revealed less than 5% of the genetic component of the disease. Furthermore, there is no consensus on environment risk factors for POAG. Elevated IOP is the only modifiable risk factor for POAG; yet, lowering IOP slows, but does not halt the disease process. Study Objectives: The overall goal of our research is to elucidate the pathogenesis of POAG so that cost-effective disease detection and primary prevention strategies can be implemented. The primary aim of the Glaucoma Gene Environment Initiative (GLAUGEN), funded by the Human Genome Research Institute (NHGRI), is to discover genetic loci associated with POAG. The secondary aim of GLAUGEN, funded by NHGRI and the National Eye Institute, is to discover gene environment interactions in POAG. Methods and study populations: For this study, we have assembled cases and controls from three studies: the Nurses' Health Study (NHS), the Health Professionals Follow-up Study (HPFS) and the Genetic Etiologies of POAG (GEP) project based at Massachusetts Eye and Ear Infirmary (MEEI). This case-control group includes 1057 unrelated cases and 1272 controls. Members of the NHS and HPFS also have repeated environmental exposure data collected prior to a diagnosis of POAG. NHS - The Nurses Health Study started in 1976 under the direction of Dr. Frank E. Speizer. With funding from the NIH, registered nurses from 11 US states were invited to complete a detailed questionnaire regarding lifestyle and health biennially. Initially, 121,000 women responded to the baseline questionnaire. Currently, Dr. Susan Hankinson serves as the program director for the NHS. HPFS - The Health Professionals Follow-up Study began in 1986 under the direction of Drs. Walter Willett and Meir Stampfer. Under the auspices of the NIH, they enlisted 51,529 male health professionals from throughout the US to complete similarly designed biennial questionnaires. Beginning in 1990, questions regarding ocular health were added to biennial questionaires completed by health professionals participating in the NHS and HPFS. This allowed us to formulate (PI: S. Hankinson; NEI) and maintain (PI: L. Pasquale; NEI) a cohort at risk for POAG derived from the respective general cohorts who were under ophthalmic care. We then developed a definition of POAG that allowed us to identify cases from a population that was geographically dispersed. The centerpiece of this definition is the presence of reproducible visual field loss consistent with nerve fiber layer (NFL) dropout (the NFL contains the axons that comprise the optic nerve) on reliable tests. Reproducible visual field loss occurred in the context of anterior segment findings that did not suggest a secondary cause of elevated IOP and posterior segment findings that did not suggest a secondary cause of visual field loss. We selected controls from the cohort at risk for POAG on the basis of age, gender and time period when cases were identified. GEP - The Genetic Etiologies of POAG was initiated in 1996 with funding from the National Eye Institute under the direction of Dr. Janey Wiggs. The purpose of this work was to discover novel genetic loci associated with POAG. In the GEP, cases were derived predominantly from the Glaucoma Service at MEEI. The majority of cases had an examination by a glaucoma specialist and met the definition for POAG used in NHS and HPFS. Cases with only one reliable visual field consistent with NFL dropout were included if there was a cup-disc ratio of 0.7 or more. The majority of controls were patients who presented to the MEEI comprehensive ophthalmology service for routine eye examination or from spouses of MEEI patients with secondary forms of glaucoma. Other controls were identified from regional glaucoma screenings held throughout Massachusetts. Members of GEP have detailed ocular phenotype data but limited information on environmental exposures. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to primary open-angle glaucoma through large-scale genome-wide association studies of three well-characterized cohorts of cases and controls, some in matched pairs. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000308

• Serrated Colorectal Cancer: An Emerging Disease Subtype

  This dataset represents two combined study populations. Serrated Colorectal Cancer: An Emerging Disease Subtype (called the Advanced Colorectal Cancer of Serrated Subtype Study or ACCESS Study) was a grant awarded to investigate a newly-recognized, biologically-distinct subtype of colorectal cancer (CRC) called “serrated CRC.” The objective of this project was to characterize factors related to the genetic predisposition, clinical presentation, and prognosis of serrated CRC. The study recruited incident invasive CRC cases diagnosed between April 2016 and December 2018, aged 20-74 years at diagnosis. Cases were identified through the Surveillance, Epidemiology and End Results (SEER) cancer registry serving 13 counties in western Washington State. Eligibility for all individuals was limited to those who were English-speaking and could consent. Participation included completing a baseline epidemiologic questionnaire shortly after diagnosis, optional donation of a saliva sample for genetic analysis, and optional consent to release of medical records and tissue specimens related to their diagnosis. Tumor specimens were tested for serrated CRC-defining molecular characteristics. Further, we have vital status on all participants and cause of death on those that have died since enrollment. Hormones and Colon Cancer: Epigenetic Subtypes, Risks, and Survival (called the Post-Menopausal Hormones Study or PMH Study) was a grant awarded to investigate the impact of post-menopausal hormone use on colon cancer risk, tumor molecular characteristics, and outcomes. Eligible cases were females, newly diagnosed with invasive colorectal adenocarcinoma between October 1998 and February 2002, aged 50 to 74 years. Cases were residents of 10 out of the 13 counties in western Washington State served by the Surveillance, Epidemiology and End Results (SEER) cancer registry. Eligibility for all individuals was limited to those who were English-speaking with available telephone numbers, in which they could be contacted. Unrelated population-based controls were randomly selected according to age distribution (in 5-year age intervals) of the eligible cases by using lists of licensed drivers from the Washington State Department of Licensing (for individuals aged 50 to 64 years) and rosters from the Health Care Financing Administration (now the Centers for Medicare and Medicaid, for individuals older than 64 years). Participation included completing a baseline epidemiologic questionnaire, optional donation of a saliva sample for genetic analysis, and (for cases only) optional consent to release of medical records and tissue specimens related to their diagnosis. Tumor specimens were tested for epigenetic and other molecular characteristics. The ACCESS study was supported by funding from the National Cancer Institute of the National Institutes of Health (NCI/NIH) (R01CA196337, PI: Newcomb, PA), as was the PMH Study (R01CA076366, PI: Newcomb, PA). Additional support for the PMH Study came from the Seattle site of the Colon Cancer Family Registry (SCCFR) (U01CA167551, PI: Jenkins, M, and U01/U24CA074794, PI: Newcomb, PA). Additional support for case ascertainment was provided by the Cancer Surveillance System of the Fred Hutchinson Cancer Center, which is funded by Contract Number HHSN261201300012I; NCI Control Number: N01 PC-2013-00012; Contract Number HHSN261201800004I; and NCI Control Number: N01 PC-2018-00004 from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute with additional support from the Fred Hutchinson Cancer Center and the State of Washington. This research was also supported by the Genomics and Bioinformatics, Comparative Medicine, Specialized Pathology, Collaborative Data Services, and Experimental Histopathology Shared Resources of the Fred Hutch/University of Washington Cancer Consortium (P30 CA015704).Tumor marker testing was performed using formalin-fixed paraffin-embedded diagnostic tumor tissue specimens, and DNA extracted from those specimens. Testing for microsatellite instability (MSI) was based on either a 10-gene panel (BAT25, BAT26, BAT40, MYCL, D5S346, D17S250, ACTC, D18S55, D10S197, BAT34C4) or a 4-marker immunohistochemistry panel of DNA mismatch repair proteins (MLH1, MSH2, MSH6, PMS2). CpG island methylator phenotype (CIMP) testing was based on a validated quantitative DNA methylation assay using a five-gene panel (CACNA1G, IGF2, NEUROG1, RUNX3, SOCS1) or eight-gene panel (CACNA1G, IGF2, NEUROG1, RUNX3, SOCS1, MLH1, CRABP1, CDKN2A). Somatic p.V600E BRAF mutation status was tested for using a fluorescent allele-specific PCR assay. KRAS mutations in codons 12 and 13 were also assessed through forward and reverse sequencing of amplified tumor DNA. DNA was extracted from blood/saliva samples using conventional methods. The genotyping panel completed was the Build37 OncoArray500K-C, including 1%-6% blinded duplicates to monitor the quality of the genotyping. Quality control procedures were performed to 1) make sure that there were no patterns of missing data by batch, study, or plate, 2) check for gender discrepancies and kinship, 3) complete Principal Component Analysis, and 4) test for Hardy-Weinberg equilibrium (HWE). Samples were excluded based on call rate, heterozygosity, unexpected duplicates, gender discrepancy, and unexpectedly high identity-by-descent or unexpected genotypic concordance (>65%) with another individual. In addition, variants were excluded based on call rate (98%), lack of HWE in controls (P

  Study phs002171

• Incentives and Case Management to Improve Cardiac Care: Healthy Lifestyle Program (HeLP)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this study.Objectives: The HeLP study assessed how early case management, financial incentives contingent on cardiac-rehabilitation attendance, or both impacted adherence to cardiac rehabilitation among patients with lower socioeconomic status (SES) who had a cardiac-rehabilitation-qualifying diagnosis. Background:Cardiovascular disease (CVD) is the leading cause of death in the United States. Regular attendance at cardiac rehabilitation (CR) is the number one recommendation for patients who have experienced a recent cardiac event. CR is a secondary prevention outpatient program involving an individually tailored structured exercise program along with counseling and encouragement regarding lifestyle changes to reduce the recurrence of major cardiac events.Despite the benefits of CR attendance, enrollment and adherence to the program are low. This is particularly true of individuals of lower socioeconomic status (SES), who also generally suffer a higher burden from CVD on account of higher-risk cardiac profiles. As these profiles are the result of modifiable behavior targeted by CR (i.e., smoking, obesity, lack of physical activity), methods of increasing CR attendance among this population are necessary.Case management and financial incentives contingent on CR attendance are two potential strategies for addressing this issue. Previous studies have shown how trained case managers can support and assist patients with attending CR and improving their cardiac health, and how financial incentives can promote various types of health-related behavior. The purpose of the present study was to evaluate how these two interventions, individually and in tandem, fared at improving CR adherence among individuals of lower SES specifically. Participants:A total of 314 participants were screened, and 209 were randomized. All consented to have their data shared for research purposes. Design:Eligible patients were approached either while still in the hospital or during initial visits to CR. After obtaining informed consent, clinical and demographic characteristics (i.e., age, sex, education, race and ethnicity, smoking status, and CR-qualifying diagnosis) and depressive symptoms were collected. Participants then were randomized 2:3:3:3 to usual care (UC), case management starting in hospital (CM), financial incentives for attending CR (FI), or financial incentives plus case management (FICM). For all participants regardless of condition, an appropriate referral for CR was confirmed after randomization. Over the course of the study participants completed three assessments – one at intake, one after four months, and one after one year. Clinical (i.e., cardiorespiratory fitness, body composition, and cardiac-related quality of life) and sociocognitive (i.e., Beck Depression Inventory, Achenbach System of Empirically Based Assessment, and Behavior Rating Inventory of Executive Function) measures were obtained at each assessment. Participants randomized to the UC condition were contacted weekly by study staff for adverse event checks, but received no additional intervention. Participants randomized to the CM condition were immediately assigned a case manager. Case managers met with their participants, usually within 24 hours of consent while they were still in the hospital, to introduce themselves during an initial check-in. Within the first week of consent they completed a longer, more thorough initial needs assessment with their participant and established behavioral goals. For the next 16 weeks, case managers met with their participants at least once a week, typically over the phone, to discuss progress on these goals and address any problems or barriers that had arisen. Case managers also were available via phone outside of these regular meetings during normal working hours and Saturday mornings. Participants randomized to the FI condition could earn money for completing an initial CR orientation and attending CR sessions. Twenty dollars could be earned for completing the CR orientation session. CR attendance was reinforced on an escalating schedule starting at $10. Payments increased by $2 for each successive session attended, and capped out at a maximum of $40 per session. Unexcused absences resulted in the incentives for that session not being earned, and the potential earnings for the next scheduled session being reset to $10. Successful participation of two consecutive sessions following the reset resulted in the incentives being returned to the amount prior to the reset. In total, participants could earn $1220 for attending the initial orientation and all 36 sessions of CR. The primary outcome of interest was the percentage of participants who completed at least 30 sessions of CR. Secondary outcomes included the number of sessions completed, cardiorespiratory fitness (peak VO2 and estimated metabolic equivalents (METs)), body composition (waist circumference and BMI), depression scores, and both general and cardiac-related qualify of life. Conclusions:The two interventions involving financial incentives (i.e., financial incentives alone and financial incentives plus case management) significantly improved CR adherence compared to usual care. Subsequent analyses revealed that the combination of financial incentives and case management led to greater improvements in CR attendance than financial incentives alone.

  Study phs003737

• Programmatic submission based on XML

  Programmatic submissions (XML based) For further information please check our Submission FAQs, submission quickguide as well as submission terms! Introduction Besides the Submitter Portal tool, EGA supports programmatic sequence and clinical data metadata submissions. If you are not sure what this means, you may want to explore our brief metadata introduction. Programmatic submissions are recommended for array-based submission. Moreove, it may be of help if your submission is recurrent or it is difficult to manage manually due to its sheer size. Otherwise, we highly recommend using the Submitter Portal to perform submissions. In this page we will guide you through the required steps to programmatically submit data to the EGA. Programmatic submissions require your metadata to be structured for an easy and straightforward validation and archival. It basically consists in formatting your metadata as Extensible markup language (XML) files and submitting them to the EGA using the WEBIN Before submitting metadata to the EGA, it is important to ensure that the information in your XML files is compliant with our standards. You can see further details on how these standards are maintained at EGA at our EGA Schemas documentation page. Using WEBIN, you can validate your XML files against EGA's schemas to ensure that your metadata is compliant before submission. WEBIN services WEBIN production service WEBIN test service We advise you to submit your metadata to the test service when submitting to the production service for the first time. The test service is identical to the production service except that all submissions will be discarded in the following 24 hours. This allows you to learn about the submission process without having to worry about data being submitted. Authentication Authentication is required each time a submission is made. The submission service uses HTTPS protocol for metadata encryption and identification to provide a secure submission environment. Data file upload Both Runs and Analyses reference files (e.g. FASTQ need to be uploaded to the EGA before these metadata objects are submitted. In other words, if you submit a Run that references a file that we cannot find associated with your account, the metadata submission will fail. See further details on how to upload your files in our File Upload documentation. Metadata model of the EGA Our metadata model is formed by multiple metadata objects. Check further details in our documentation at our EGA Schema documentation page. Working with EGA XMLs files Now that the basic concepts of the EGA metadata have been described, you can start preparing your programmatic submission through XML. Here you will find the guidance on how to prepare the XML files. Programmatic Submission Tutorial Video Take a look at the Programmatic Submission Tutorial Video, which explains the workflow of a programmatic submission and goes over an example metadata submission. Programmatic Submission Tutorial Video. When building your XML files, we recommend using text editors (e.g.Sublime Text or VisualStudio) that allow you to visualise the structure of the XML with ease. Furthermore, these editors constantly check the consistency of the XML structure. Alternatively, and if the submission consists of a big number of objects (specially analyses), you may find the tool star2xml handy. This tool allows for a direct conversion between metadata in a tabular format (e.g. a spreadsheet) into XMLs. Identifying objects: Aliases and center names Every EGA object must be uniquely identified within the submission account using their alias attribute. The aliases can be used in submissions to make references between EGA objects. Let us dig into EGA's use of aliases and center names: alias: every object should have a name that is unique within your submission account. Once submitted successfully, every alias will be assigned a unique and permanent accession (EGA ID). refname: when an object references another by its alias, the alias of the referenced object goes into the "refname" attribute of the referencing object. For example, if a sample has the alias "sample1", and an experiment uses this sample, then the experiment's "EXPERIMENT/SAMPLE/refname" attribute should be "sample1". center_name: The "center_name" attribute is required within the submission XML and, if not provided when the object is submitted, it will be automatically filled using your default EGA account center_name. This element is the "controlled vocabulary acronym or abbreviation that is provided to the account holder when the account is first generated". If the submitter is brokering a submission for another institute, the submitter should use their special broker account name in broker_name while the data centre acronym remains in center_name. Log-in details should have been provided when you requested a submission account. Please contact our Helpdesk team if you have any questions. run_center: Many submitting centers contract out the actual sample sequencing to another center. In these cases, the sequencing center should be acknowledged in the run_center attribute. Again, this is controlled vocabulary and the acronym should be sought from EGA helpdesk before submitting. Please contact our Helpdesk team if you have any questions. Prepare your XMLs The goal of this section is to provide sufficient information to be able to create the metadata XML documents required for programmatic submissions. Please note, the EGA utilises the XML schemas maintained at the European Nucleotide Archive (ENA). It is important due to the fact that by using a similar system, some pieces of documentation from the ENA's programmatic submission can also help you with your programmatic submission to the EGA. For example, you can submit programmatically without using a Submission XML by following the steps at Submission actions without submission XML. A submission does not have to contain all different types of XMLs. For example, it is possible to submit only a few samples; or a study that is later to be referenced. You can submit each object one by one, or submit all in a batch: you choose what method of submission works best for you. We do recommend, nevertheless, that you submit the objects to be referenced (e.g. samples or studies) first, and the objects that reference these (e.g. experiments or datasets) afterwards. You can see a graphical view of these objects and their relationships at our EGA Schemas page. Independently of the submission scenario, you will always require a Dataset XML. The entity of a dataset is what is used to control access to the given data, in the form of runs or analyses. In other words, when a requester is granted access, it is through the dataset and the objects (e.g. runs or analyses) that the dataset contains, granting access to them in one go. Given the nature of the EGA, a dataset XML will always be required for the data access. First, we will differentiate between submissions of "raw" and "processed" data: Runs and Analyses, respectively. Run data submissions Raw data derives from instruments "as is". For example, a plain sequence file (e.g. FASTQ or unaligned BAM files) would be considered raw data. A typical raw (unaligned) sequence read submission consists of 8 XMLs: Submission Study Sample Experiment Run DAC Policy Dataset When technical reads (e.g. barcodes, adaptors or linkers) are included in the submitted raw sequences, a spot descriptor must be submitted to describe the position of the technical reads so that they can be removed. The following data files can be submitted without providing spot descriptor information in the experiment/run XML: BAM files (single reads) SFF files (single reads without barcodes) FastQ files (single reads without any technical reads) Complete Genomics files Analysis data submissions Processed data is, in some way, refined raw data. This includes raw data that has been processed by some form of analysis method (e.g. alignment, noise reduction, etc.). For example, an aligned sequence (e.g. BAM file), that was created using raw FASTQ files, would be a processed file. This category includes most types of data: sequence alignment files (e.g. BAM or CRAM), clinical data (e.g. phenopackets), sequence variation files (e.g. VCF), sequence annotation, etc. A typical EGA analysis data submission consists of 7 EGA XML: Submission Study Sample Analysis DAC Policy Dataset We accept three different types of analysis data submissions: BAM files (for multiple read alignments) VCF files (for sequence variations) Phenotype files (in any format) In anycase, keep in mind that samples must be created in order to be referenced in the analyses. In other words, the provenance of the information within the BAM, VCF and phenotype files Example XMLs Below you can find a non-extensive list of example XMLs with descriptive fields (i.e. explaining what to provide in each field). Furthermore, you can also find real examples (i.e. the true value of the provided fields) in our GitHub repository. Submission XML The submission XML is used to validate, submit or update any number of other objects. The submission XML refers to other XMLs. New submissions use the ADD action to submit new objects. Object updates are done using the MODIFY action and objects can be validated using the VERIFY action. Descriptive submission XML example True values submission XML example Study XML The study XML is used to describe the study containing a title, a study type and abstract as it would appear in a publication. Descriptive study XML example True values study XML example Please use the following notation within the property "STUDY_LINKS" when including PubMed citations in the Study XML: <STUDY_LINKS> <STUDY_LINK> <XREF_LINK> <DB>PUBMED</DB> <ID>18987735</ID> </XREF_LINK> </STUDY_LINK> </STUDY_LINKS> Sample XML The sample XML is used to describe the samples used to obtain the data, whether they were sequenced, measured in any other way, or have an associated phenotype. The mandatory fields include information about the taxonomy of the sample, sex, subject ID and phenotype. For example, the mandatory attribute fields for each sample would look like these, within the array of "SAMPLE_ATTRIBUTES": <SAMPLE_ATTRIBUTES> <SAMPLE_ATTRIBUTE> <TAG>subject_id</TAG> <VALUE>free text!</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>sex</TAG> <VALUE>female/male/unknown</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>phenotype</TAG> <VALUE>Free text, EFO terms (e.g. EFO:0000574) are recommended</VALUE> </SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTES> Sample is one of the most important objects to be described biologically, it is highly recommended that “TAG-VALUE” pairs are generated as SAMPLE_ATTRIBUTES to describe the sample in as much detail as possible. For example, were we to give the population ancestry of the sample, we could add a new attribute to the array, in which, for example, we would indicate that the sample derives from an individual of "Mende in Sierra Leone" (MSL), with an african ancestry: <SAMPLE_ATTRIBUTE> <TAG>Population</TAG> <VALUE>MSL</VALUE> </SAMPLE_ATTRIBUTE> Given that VALUE and TAG are free text, the combinations are limitless in order to give you full flexibility on the information you want to provide. We recommend you use the Experimental Factor Ontology (EFO) to describe the phenotypes of your samples. You can provide more than one phenotype by adding more items to the array of SAMPLE_ATTRIBUTES. Phenotypes considered essential for understanding the data submission should be provided. Each phenotype described should be listed as a separate sample attribute <SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTE>. There is no limit to the number of phenotypes that can be submitted. If a suitable EFO accession cannot be found for your phenotype attribute, please consider using another controlled ontology database (e.g. HPO, MONDO, etc.) before using free text. Descriptive sample XML example True values sample XML example Experiment XML The experiment XML is used to describe the experimental setup, including instrument platform and model details, library preparation details, and any additional information required to correctly interpret the submitted data. Where any of these values differ between runs, a new experiment object must exist, since runs are grouped by experiments. Each experiment references a study and a sample by alias, or if previously-submitted, by accession. Pooled data must be demultiplexed by barcode for submission. Descriptive experiment ( Illumina paired read ) XML example True values experiment ( Illumina paired read ) XML example Run XML The run XML is used to associate data files with experiments and typically comprises a single data file (e.g. a FASTQ file). Please note that pooled samples should be de-multiplexed prior submission and submitted as different runs. Descriptive run XML example True values run XML example Analysis XML Given that an analysis can be used to submit any type of processed data to the EGA, we will list below an example of each of the three most common types of analysis XMLs submitted to the EGA: sequence alignments (e.g. BAM files); sequence variation (e.g. VCF files); and clinical metadata or phenotypes (e.g. phenopackets). Regardless of the type of processed data submitted in the analysis, the analysis must be associated with a Study and can reference multiple types of other objects, from samples to experiments, if they are available at the EGA. Just like with Runs, whenever a file is submitted to the EGA through an analysis object, the file MD5 checksums must be present, in order for the EGA to validate file integrity upon transfer. This also includes index files when applicable (e.g. .bai.md5 files). Ideally, any analysis that uses a reference sequence for some kind of alignment (e.g. BAM, CRAM or VCF files), would contain metadata about the alignment, such as INSDC reference assemblies and sequences, by either using accessions (e.g. CM000663.1) or common labels (e.g. GRCh37). Read alignment (BAM) Analysis XML The Analysis can be used to submit BAM alignments to EGA. Only one BAM file can be submitted in each analysis and the samples used within the BAM read groups must be associated with Samples. Descriptive bam alignments XML example True values bam alignments XML example Sequence variation (VCF) Analysis XML The Analysis can be used to submit VCF files to EGA. Only one VCF file can be submitted in each analysis and the samples used within the VCF files must be associated with Samples. Download analysis XML (VCF) Phenotype files The Analysis XML can be used to submit phenotype files to the EGA. Only one phenotype file can be submitted in each analysis and the samples used within the phenotype files must be associated with EGA Samples. Download analysis XML (Phenotype) DAC XML The DAC XML describes the Data Access Committee (DAC) affiliated to the data submission. The DAC may consist of a group or a single individual and is responsible for the data access decisions based on the application procedure described in the POLICY.XML. As with any other object, if it was already submitted to the EGA, there is no need to submit it again: you can reference an existing object within the EGA. Hence, A DAC XML does not need to be provided if your submission is affiliated to an existing EGA DAC.. Further information on DACs can be found here, and you can always contact our Helpdesk team if you have further inquiries. Descriptive dac XML example True values dac XML example Policy XML The Policy XML describes the Data Access Agreement (DAA) to be affiliated to the named Data Access Committee. Descriptive policy XML example True values study XML example Dataset XML The dataset XML describes the data files, defined by the Run.XML and Analysis.XML, that make up the dataset and links the collection of data files to a specified Policy. The dataset xml is commonly the last metadata object to be submitted, since it references multiple other entities. Please consider the number of datasets that your submission consists of. For example, a case-control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Descriptive dataset XML example True values dataset XML example Validating and submitting your EGA Validating EGA's XMLs through Webin After you have ensured that the XMLs are properly formatted and contain all the required information. You can proceed to validate and submit your data. Use the curl command to validate your XML file: Once you have prepared your XML file and asserted you have access to Webin, you can validate your XML file programmatically against EGA's schemas using the curl command. There are multiple ways in which you can validate your XMLs. This variety has to do with the fact that: (1) there are 2 instances of Webin (test and production); and (2) that validation is a default step during submission. In other words, any time that you submit your data through Webin, it will be validated automatically before being accepted. This allows for 4 possible routes of validation, all having the same validation result: validating or submitting to either the production service or the test service of Webin. For example, directly validating a "study" object XML in the testing service (wwwdev…) would look like the following: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" In this command, you would need to replace <USERNAME> and <PASSWORD> with your EGA account username and password, respectively. You would also replace <INPUT_FILE> with the path to your XML file. A mock example would look like the following: curl -u ega-test-data@ebi.ac.uk:egarocks -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" The validation attempt can have different results depending on the given arguments: If your XML file is valid according to EGA's schemas, you will see a message indicating that your XML file is compliant. For example, see below for our mock example, where the "success" was "true" (i.e. no validation errors found). Nevertheless, notice how the "<STUDY accession=" is empty: it is because we were simply validating, so the study did not get an accession or ID. <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:19:28.850+01:00" submissionFile="submission-EBI-TEST_1681222768850.xml" success="true"> <STUDY accession="" alias="Mock example" status="PRIVATE"/> <SUBMISSION accession="" alias="SUBMISSION-11-04-2023-15:19:28:840"/> <MESSAGES> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If there are any errors or warnings, the tool will display them, allowing you to correct them before submitting your data to EGA. For example, in the following response, it is said that the object we were trying to submit was already existing, and therefore the "success" was "false". <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:12:35.609+01:00" submissionFile="submission-EBI-TEST_1681222355609.xml" success="false"> <STUDY alias="Example!_Human Microbiome Project SP56J" status="PRIVATE" holdUntilDate="2023-03-11Z"/> <SUBMISSION alias="SUBMISSION-11-04-2023-15:12:35:576"/> <MESSAGES> <ERROR>In study, alias: "Example!_Human Microbiome Project SP56J". The object being added already exists in the submission account with accession: "ERP127584".</ERROR> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If the curl command retrieves no response at all, please double check if your username and password are correctly provided. Also notice the "ACTION=..." argument passed to the Curl command. This specifies the action to take during the call to Webin, so we do not need a "Submission" XML just for a validation attempt. See more at submission actions without submission XML. Furthermore, validation of multiple files or objects (e.g. sample, experiment, study…) can be done in a single command by adding more arguments (i.e. '-F'). For example: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" -F "SAMPLE=@sample.xml" -F "DATASET=@dataset.xml" As mentioned above, beside "validate" action in the test environment, you can also validate your metadata by three other methods: "Validate" in the production server. From our example above, you simply need to take the "dev" away from the URL. curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the development server. From our example above, you would simply need to replace the action: from "validate" to "add". Whatever is submitted to this service will be discarded in 24h, so whether something gets submitted or not would not matter in the long run. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the productionserver. A combination of the previous two methods, which would render this attempt into a submission. This path is just to be taken when you are sure your metadata is compliant and what you want to submit. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" What happens after the submission of a dataset XML? Once you have completed the registration of your dataset/s please contact our Helpdesk Team to provide a release date for your study. Please note that all datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitter or DAC contact contact the EGA Helpdesk for the study to be released. We strongly advise you not to delete your data until EGA Helpdesk confirms that your data has been successfully archived.

  Documentation submission/metadata/submission/programmatic-submission-xml

• Longitudinal Study of Fluoride and Other Factors Related to Dental Fluorosis, Dental Caries, and Bone Health

  This project is a combination of the Iowa Fluoride Study and the Iowa Bone Development Study from 1992 - 2019. The Iowa Fluoride Study (IFS) began in 1992 with recruitment of 1,882 mothers of newborns from eight Iowa hospital post-partum wards from March 1992 to February 1995. The focus of the IFS was to collect detailed fluoride, general dietary intake, and other data several times per year from age 6 weeks on and relate them to dental fluorosis and dental caries (cavities). Data collection occurred 3-5 times per year initially, and then twice per year after ~ age 4. Dental exams of the primary (baby) teeth were initiated at ~ age 5.The Iowa Bone Development Study (IBDS) grew out of the IFS in 1998 when we added a "normal bone development" focus, and soon after the age 5 dental exams, we began to collect genetic samples and accelerometry (motion sensor) data. All then-active parents of IFS-participating children were invited to have their child join the IBDS, and the majority agreed to do so. The majority of participating children received both ~ age 5 dental exams and bone densitometry assessments. The bone densitometry at age 5 was determined by dual-energy X-ray absorptiometry (DXA) of the hip, lumbar spine, and whole body.Dental exams for caries and fluorosis were performed again at age 8-9, along with DXA bone scans and accelerometry. DXA scans and accelerometry were performed again at ages 11 and 15 years, along with peripheral quantitative computed tomography (pQCT) scans of the distal tibia and radius, but no dental exams were performed.At ages 13 and 17, dental exams, DXA and pQCT scans, as well as accelerometry, were obtained.At age 19, no dental exams were conducted, but repeat DXA and pQCT scans and accelerometry were obtained, along with multi-slice detector CT (MDCT) of the distal tibia.At age 23, we conducted the final wave of exams, which included dental, DXA, pQCT, MDCT, and accelerometry assessments.In addition, parents were invited to participate once with DXA bone scans and to also provide limited questionnaire data about their own fluoride and dietary exposures and physical activity.Note: Please refer to the document Iowa Fluoride Study/Iowa Bone Development Study (IFS/IBDS) - dbGaP Data Tables: A User's Guide - Version 2.0 for a detailed reference manual on all of the clinical data submitted for this project.Note: No genetic data or specimens were submitted with this study. However, many of the child/parent participants in the study were genotyped. These genotyping data are linked to dbGaP Study Accession: phs000095 under Dr. Mary Marazita: "Dental Caries: Whole Genome Association and Gene X Environment Studies".<img style="width: 1155px;" 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

  Study phs002203

• Osteoporotic Fractures in Men (MrOS)

  The Osteoporotic Fractures in Men Study (MrOS) is a multi-center prospective, longitudinal, observational study of risk factors for vertebral and all non-vertebral fractures in older men, and of the sequelae of fractures in men. The original specific aims of the study include: (1) to define the skeletal determinants of fracture risk in older men, (2) to define lifestyle and medical factors related to fracture risk, (3) to establish the contribution of fall frequency to fracture risk in older men, (4) to determine to what extent androgen and estrogen concentrations influence fracture risk, (5) to examine the effects of fractures on quality of life, (6) to identify sex differences in the predictors and outcomes of fracture, (7) to collect and store serum, urine and DNA for future analyses as directed by emerging evidence in the fields of aging and skeletal health, and (8) define the extent to which bone mass/fracture risk and prostate diseases are linked. The MrOS study population consists of 5,994 community dwelling, ambulatory men aged 65 years or older from six communities in the United States (Birmingham, AL; Minneapolis, MN; Palo Alto, CA; Monongahela Valley near Pittsburgh, PA; Portland, OR; and San Diego, CA). Inclusion criteria were designed to provide a study cohort that is representative of the broad population of older men. The inclusion criteria were: (1) ability to walk without the assistance of another, (2) absence of bilateral hip replacements, (3) ability to provide self-reported data, (4) residence near a clinical site for the duration of the study, (5) absence of a medical condition that (in the judgment of the investigator) would result in imminent death, and (6) ability to understand and sign an informed consent. To qualify as an enrollee, the participant had to provide written informed consent, complete the self-administered questionnaire (SAQ), attend the clinic visit, and complete at least the anthropometric, DEXA, and vertebral X-ray procedures. There were no other exclusion criteria. The baseline examination was completed over a 25-month period from March 2000 to April 2002. Participants completed questionnaires regarding medical history, medications, physical activity, diet, alcohol intake, and cigarette smoking. Objective measures of anthropometric, neuromuscular, vision, strength, and cognitive variables were obtained at a clinic visit. Skeletal assessments included DEXA, calcaneal ultrasound, and vertebral radiographs. Vertebral and proximal femoral QCT was performed on a subset (65%) of participants. Serum, urine, and whole blood specimens were collected. During the study period, participants complete a tri-annual questionnaire every four months that obtains information concerning the occurrence of incident falls and fractures. Follow-up is over 99% complete. All reported fractures are confirmed using physician review of radiology reports or study radiologist review of x-rays. All deaths are also centrally adjudicated using death certificates and recent hospitalization records. In additional to the baseline study visit and tri-annual questionnaires, all surviving active participants were invited to follow-up visits and questionnaires. A second comprehensive clinic visit was completed between March 2005 and May 2006 or about 4.5 years after baseline. Most baseline measures, including vertebral radiographs, were repeated at the second visit. A third comprehensive clinic visit was completed between March 2007 and March 2009 or about 7.0 years after baseline. Many baseline measures were repeated at the third visit. A measure of energy expenditure was also obtained utilizing an accelerometer based armband device. Surviving participants have also completed two extensive mailed questionnaires designed to updated information obtained at clinic visits. The first questionnaire was mailed between baseline and visit 2 between July 2002 and March 2004. The second questionnaire was mailed after the third questionnaire between March 2009 and February 2011. The MrOS Sleep Study, an ancillary study of the parent MrOS cohort, was conducted between December 2003 and March 2005 and recruited 3,135 MrOS participants for a comprehensive sleep assessment. Men were screened for nightly use of mechanical devices during sleep including pressure mask for sleep apnea (CPAP or BiPAP), mouthpiece for snoring or sleep apnea, or oxygen therapy and were generally excluded. The sleep visit included objective measures of sleep using actigraphy and polysomnography. Other measures at the sleep visit include neuropsychiatric measures, performance measures, health related questionnaires, routine exam measures previously completed at MrOS clinic visits and a urine and serum specimen collection. During the sleep study period, participants complete a tri-annual questionnaire every four months that contains information about incident cardiovascular events. All reported events are centrally adjudicated utilizing hospital records, study ECGs and other supporting documentation. The Hip Osteoarthritis study, another ancillary study of the parent MrOS cohort, was completed at the second clinic visit between March 2005 and May 2006. Participants were asked for consent for a hip x-ray and osteoarthritis measurements were obtained from these x-rays. DNA was extracted from baseline whole blood samples for use in genetic research. Consent for use of DNA was obtained through written consent. Raw GWAS data is housed at the study&#39;s coordinating center and not released as part of the dbGAP release. The raw data can be requested from the study&#39;s coordinating center. Only QC cleaned Plink files are available on dbGAP.

  Study phs000373

• Surgical Treatment for Ischemic Heart Failure (STICH-BioLINCC)

  Data Access NOTE: Please refer to the &#8220;Authorized Access&#8221; section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectiveTo compare medical therapy with coronary bypass surgery and/or surgical ventricular reconstruction for patients with congestive heart failure and coronary artery disease.BackgroundCoronary artery disease (CAD) is the most common cause of heart failure, which in turn is a major cause of death and disability globally. Evidence from previous clinical trials supports the use of coronary-artery bypass grafting (CABG) to relieve disabling symptoms of angina, particularly among high-risk subgroups with extensive CAD. However, the studies did not include patients with severe left ventricular dysfunction, and developments in medical therapy have since led to updated guidelines. In addition, the benefits of CABG in patients with ischemic cardiomyopathy had still not been clearly established at the time of this study. STICH sought to evaluate the role of CABG in the treatment of patients with CAD and left ventricular systolic dysfunction.Reduced left ventricular function may occur after myocardial infarction, often in conjunction with left ventricular remodeling, including left ventricular enlargement and changes in chamber geometry. Left ventricular remodeling is correlated with progression of heart failure and a poor prognosis. Therefore, a surgical approach to remodeling through left ventricular volume reduction could improve outcomes for patients with CAD and heart failure. Surgical ventricular reconstruction (SVR) has been shown to reduce the left ventricular volume, increase the ejection fraction, and improve ventricular function. There is also evidence that SVR performed with CABG may reduce the rate of hospitalization and improve ventricular function, as compared to CABG alone. As part of a second hypothesis, STICH additionally investigated whether SVR when added to CABG would improve outcomes in patients with heart failure and CAD.ParticipantsA total of 2,136 participants were enrolled in STICH. 1,212 were enrolled in the hypothesis 1 component of the trial, with 602 participants assigned to receive medical therapy alone, and 610 participants assigned to receive medical therapy plus CABG. 1,000 were enrolled in the hypothesis 2 component, with 499 participants assigned to receive medical therapy plus CABG, and 501 participants assigned to receive medical therapy plus CABG and SVR. 76 participants that were assigned to the CABG with medical therapy treatment were enrolled in both hypothesis components.DesignAfter initial determination of overall eligibility, participants were evaluated to determine which component of the STICH program was appropriate for them on the basis of suitable therapeutic options. All participants underwent cardiac imaging for assessment of left ventricular function and wall motion. Participants in the hypothesis 1 component were randomly assigned to receive either medical therapy alone or medical therapy plus CABG. Participants in the hypothesis 2 component were randomly assigned to receive either medical therapy plus CABG or medical therapy plus CABG and SVR.At baseline, demographic factors and clinical characteristics were assessed, including current medications and prior diagnostic and other cardiovascular procedures, and a physical examination was performed. Guideline-based recommendations for drug and device use were emphasized for all participants. All participants underwent follow-up evaluations at the time of discharge or at 30 days for participants still hospitalized, every 4 months for the first year, and every 6 months thereafter. The median length of follow-up was 56 months for hypothesis 1 and 48 months for hypothesis 2.For participants receiving CABG, arterial grafting for stenosis of the left anterior descending coronary artery was required for all participants without specific contraindications. The use of additional arterial conduits supplemented by vein grafts was recommended for revascularization of all major vessels with clinically significant stenoses. Concurrent mitral-valve surgery for regurgitation was performed at the discretion of the surgeon. For participants receiving SVR, the operation was most commonly performed during a single period of cardioplegic arrest after construction of bypass grafts. However, the procedure could also be performed with the heart beating in order to facilitate identification of the noncontractile zone of scarring. After an anterior left ventriculotomy was centered in the zone of anterior asynergy, a suture was placed in the interior of the ventricle to encircle the scar at the boundary between the akinetic and viable tissue. Visual inspection and palpation facilitated the judgment of whether a patch was needed to optimize the chamber size without deforming the left ventricle during closure of the ventriculotomy.The primary outcome for hypothesis 1 was the rate of death from any cause. The primary outcome for hypothesis two was a composite of death from any cause and hospitalization for cardiac causes.ConclusionsThere was no significant difference between medical therapy alone and medical therapy plus CABG for death from any cause, though participants that underwent CABG had lower rates of death from cardiovascular causes, death from any cause, or hospitalization for cardiovascular causes. Adding SVR to CABG reduced the left ventricular volume, as compared with CABG alone. However, this anatomical change was not associated with a greater improvement in symptoms or exercise tolerance, or with a reduction in the rate of death or hospitalization for cardiac causes.

  Study phs003493

• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• Unrelated Donor Reduced Intensity Bone Marrow Transplant for Children with Severe Sickle Cell Disease (BMT CTN-0601-BioLINCC)

  ObjectivesThe primary objective is to determine event-free survival (EFS) at 1 year after unrelated donor (URD) hematopoietic stem cell transplantation (HCT) using bone marrow (BM) in patients with sickle cell disease (SCD).BackgroundSickle cell disease (SCD), also known as sickle cell anemia, is an inherited blood disease that can cause organ damage, stroke, and intense pain episodes. Children with sickle cell disease experience organ damage, impaired quality of life, and premature mortality. A blood stem cell transplant is a treatment option for someone with a severe form of the disease. Prior to undergoing a transplant, people typically receive a conditioning regimen of high doses of chemotherapy and other medications to prepare the body to accept the transplant. This type of conditioning regimen is known as a myeloablative conditioning regimen, but it can result in toxicities and sterility. A conditioning regimen that uses lower doses of chemotherapy and medications may be safer for transplant recipients. This type of regimen is known as reduced intensity conditioning (RIC) regimen. RIC has a more favorable toxicity profile but is associated with higher rates of graft rejection (GR), especially with graft sources such as umbilical cord blood This study evaluated the safety and effectiveness of blood stem cell transplants, using bone marrow from unrelated donors, in children with severe SCD who receive a RIC regimen prior to the transplant.SubjectsPatients 3.0-19.75 years old with symptomatic SCD AND one or more of the following complications: (1)-(i) a clinically significant neurologic event (stroke) or any neurologic defect lasting > 24 hours and accompanied by an infarct on cerebral magnetic resonance imaging (MRI); OR, (ii) patients who have a Transcranial Doppler (TCD) velocity that exceeds 200 cm/sec by the non-imaging technique (or TCD measurement of >185 cm/sec by the imaging technique) measured at a minimum of 2 separate occasions one month or more apart; OR, (2) Minimum of two episodes of acute chest syndrome within the preceding 2-year period defined as new pulmonary alveolar consolidation involving at least one complete lung segment (associated with acute symptoms including fever, chest pain, tachypnea, wheezing, rales, or cough that is not attributed to asthma or bronchiolitis) despite adequate supportive care measures; OR, (3) History of 3 or more severe pain events (defined as new onset of pain that lasts for at least 2 hours for which there is no other explanation) per year in the 2 years prior to enrollment despite adequate supportive care measures (if patients are receiving hydroxyurea and compliant with therapy, being symptomatic is an indication for transplantation; however, if patients decline hydroxyurea or non-compliant with this therapy, they would still remain eligible for study if pain criteria as described above are met). Lansky/Karnofsky performance score must be &#8805; 40. Hemoglobin S must be &#8804; 45%. Patients must have an unrelated adult bone marrow donor who is HLA-matched at 8 of 8 HLA-A, -B, -C and -DRB1 at high resolution using DNA-based typing. Patients with bridging fibrosis or cirrhosis of the liver, with uncontrolled bacterial, viral, or fungal infection in the past month, or seropositivity for HIV are excluded. Patients with HLA-matched family donors, or who have received prior HCT, and females who are pregnant or breast feeding are excluded. Thirty patients were enrolled on this study and of these, 29 patients met the criteria and proceeded to the study transplant.DesignParticipants attended a study visit prior to the transplant to undergo a blood collection, neurocognitive testing to measure learning and brain function, magnetic resonance angiogram (MRA) and magnetic resonance imaging (MRI) scans. Questionnaires to assess quality of life were also completed. All patients received erythrocyte transfusions before transplant. Twenty-two days (-22) before the transplant, participants began receiving a reduced intensity conditioning regimen of chemotherapy and medications. On days -21, -20, and -19 participants weighing 10 kg or more received 10 mg, 15 mg, and then 20 mg of Alemtuzumab intravenously (IV) followed by 30 mg/m2/day IV on days -8 through -4 of Fludarabine. Eight days (-8) before the transplant, participants were admitted to the hospital to continue the conditioning regimen which included 140 mg/m2 IV of Melphalan on day -3. Participants received the bone marrow transplant on day 0. Prophylaxis for GVHD consisted of a calcineurin inhibitor (tacrolimus or cyclosporine) administered from day -3 through day 100 after graft infusion, with subsequent taper through day 180; methotrexate 7.5 mg/m2 on days 1, 3, and 6; and methylprednisolone 1 mg/kg per day from days 7 through 28, with subsequent taper by 20% per week. One week after the transplant continuing until the WBC is normal, participants received granulocyte-colony-stimulating factor (G-CSF). After leaving the hospital, participants attended study visits weekly during weeks 1 to 8, at day 60, weekly during weeks 9 to 14, at Day 100, at month 6, and at years 1 and 2. At all study visits, a blood collection, medical history review, and physical exam occurred. In addition, at day 100, month 6, and years 1 and 2, questionnaires to assess quality of life were completed. At select visits the following procedures were conducted: lung function testing, heart function testing, MRA and MRI scans, and neurocognitive testing.The primary outcome was 1-year EFS. Death, disease recurrence or graft rejection by 1 year were considered events for this endpoint.ConclusionsThe trial met its prespecified 1-year EFS, and significantly improved HRQL was reported posttransplant. However, although the Reduced-intensity conditioning (RIC) provided successful engraftment in most patients, the regimen cannot be considered safe for widespread adoption without modification due to the regimen-related toxicity (RRT) and high rate of chronic GVHD, which was the predominant cause of mortality.

  Study phs003470

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)

  The Cleveland Family Study is the largest family-based study of sleep apnea world-wide, consisting of 2284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study was begun in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. NIH renewals provided expansion of the original cohort (including increased minority recruitment) and longitudinal follow-up, with the last exam occurring in February 2006. Index probands (n=275) were recruited from 3 area hospital sleep labs if they had a confirmed diagnosis of sleep apnea and at least 2 first-degree relatives available to be studied. In the first 5 years of the study, neighborhood control probands (n=87) with at least 2 living relatives available for study were selected at random from a list provided by the index family and also studied. All available first degree relatives and spouses of the case and control probands also were recruited. Second-degree relatives, including half-sibs, aunts, uncles and grandparents, were also included if they lived near the first degree relatives (cases or controls), or if the family had been found to have two or more relatives with sleep apnea. Blood was sampled and DNA isolated for participants seen in the last two exam cycles (n=1447). The sample, which is enriched with individuals with sleep apnea, also contains a high prevalence of individuals with sleep apnea-related traits, including: obesity, impaired glucose tolerance, and HTN. Phenotyping data have been collected over 4 exam cycles, each occurring ~every 4 years. The last three exams targeted all subjects who had been studied at earlier exams, as well as new minority families and family members of previously studied probands who had been unavailable at prior exams. Data from one, two, three and four visits are available for 412, 630, 329 and 67, participants, respectively. In the first 3 exams, participants underwent overnight in-home sleep studies, allowing determination of the number and duration of hypopneas and apneas, sleep period, heart rate, and oxygen saturation levels; anthropometry (weight, height, and waist, hip, and neck circumferences); resting blood pressure; spirometry; standardized questionnaire evaluation of symptoms, medications, sleep patterns, quality of life, daytime sleepiness measures and health history; venipuncture and measurement of total and HDL cholesterol. The 4th exam (2001-2006) was designed to collect more detailed measurements of sleep, metabolic and CVD phenotypes and included measurement of state-of-the-art polysomnography, with both collection of blood and measurement of blood pressure before and after sleep, and anthropometry, upper airway assessments, spirometry, exhaled nitric oxide, and ECG performed the morning after the sleep study. Data have been collected by trained research assistants or GCRC nurses following written Manuals of Procedures who were certified following standard approaches for each study procedure. Ongoing data quality, with assessment of within or between individual drift, has been monitored on an ongoing basis, using statistical techniques as well as regular re-certification procedures. Between and within scorer reliabilities for key sleep apnea indices have been excellent, with intra-class correlation coefficients (ICCs) exceeding 0.92 for the apnea-hypopnea index (AHI). Sleep staging, assessed with epoch specific comparisons, also demonstrate excellent reliability for stage identification (kappas&gt;0.82). There has been no evidence of significant time trends-between or within scorers- for the AHI variables. We also have evaluated the night-to-night variability of the AHI and other sleep variables in 91 subjects, with each measurement made 1-3 months apart. There is high night to night consistency for the AHI (ICC: 0.80), the arousal index (0.76), and the % sleep time in slow-wave sleep (0.73). We have demonstrated the comparability of the apnea estimates (AHI) determined from limited channel studies obtained at in-home settings with in full in-laboratory polysomnography. In addition to our published validation study, we more recently compared the AHI in 169 Cleveland Family Study participants undergoing both assessments (in-home and in-laboratory) within one week apart. These showed excellent levels of agreement (ICC=0.83), demonstrating the feasibility of examining data from either in-home or in-laboratory studies for apnea phenotyping. Data collected in the GCRC were obtained, when possible, with comparable, if not identical techniques, as were the same measures collected at prior exams performed in the participants&#39; homes. To address the comparability of data collected over different exams, we calculated the crude age-adjusted correlations ~3 year within individual correlations between measures made in the most recent GCRC exam with measures made in a prior exam and demonstrated excellent levels of agreement for BMI (r=.91); waist circumference (0.91); FVC (0.88); and FEV1 (0.86). As expected due to higher biological and measurement variability, 149 somewhat lower 3-year correlations were demonstrated for SBP (0.56); Diastolic BP (0.48); AHI (0.62); and nocturnal oxygen desaturation (0.60). NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Cooperative Study of Sickle Cell Disease (CSSCD), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data will be created that includes records for approximately 50,000 study participants with approximately 50,000 SNPs from more than 1,200 selected candidate genes. In addition, a genome wide association study using a 1,000K SNP Chip will be conducted on approximately 9,500 African American participants drawn from the 50,000 participants in the nine cohorts. Some relevant CARe publications CARe Study: PMID 20400780 CVD Chip Design: PMID 18974833

  Study phs000284

• Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS)

  This pharmacogenomic study focused on the response of patients with MDD to an 8-week course of treatment with citalopram or escitalopram. Briefly, clinical assessments and research assessments were performed at each study visit as summarized in Table 1. Many patients continued on antidepressant medication after the 8 week study. Table 1: Study timeline and patient contacts. Week Consent/Med Hx Write Rx SI Qx SCID HRS-D17 QIDSC16 CGI-I 0 SC RC RC SC SC SC 4 RC RC SC SC RC 8 RC RC SC SC RC HRS-D17=Hamilton Rating Scale for Depression, QIDS-C16=Quick Inventory of Depressive Symptomatology, CGI-I=Clinical Global Impression-Improvement, SCID=Structured Clinical Interview for DSM-IV, SC=Study Coordinator, RC=Research Clinician. Enrollment and baseline assessment. Upon initial intake, the Study Coordinator (SC) obtained informed consent as well as clinical and demographic information, including history of bone marrow or liver transplant or blood transfusion within the previous 6 weeks, and prior history of treatment during the current major depressive episode. The SC completed the Structured Clinical Interview for DSM-IV (SCID), the HRS-D17 (17-item Hamilton Rating Scale for Depression) and the QIDS-C16 (Quick Inventory of Depressive Symptomatology) and reviewed the inclusion/exclusion criteria. After review with the Research Clinician (RC) and when appropriate, after a negative pregnancy test, the SC invited the subject to participate in the study if entry criteria were met. If the subject agreed, he/she received treatment according to the study protocol. Treatment schedule. Participants selected for inclusion in the study were seen at weeks 0, 4, and 8. The appropriate treatment antidepressant (citalopram or escitalopram) was determined following discussion between the patient and RC concerning medical, financial, and insurance considerations. The study medication citalopram was given in tablet or liquid form, depending on the patient&#39;s need. A fixed-flexible dose schedule was employed with the possibility of a dose escalation. In particular, the initial dose of citalopram was 20 mg and escitalopram was 10 mg. This dose was increased to 40 mg and 20 mg, respectively, after 4 weeks if the subject had a score of &#62;/= 6 on the QIDS-C16 and the RC concluded that the subject could tolerate the increase. If necessary, dose was reduced at the discretion of the RC. The importance of medication compliance was discussed with the subject, and subjects were asked to bring in the medication at each visit for the purpose of counting remaining pills to assess compliance. Participants may have had an abbreviated course of therapy if they were clearly intolerant of the drug or failed to respond to a 40 mg dose of citalopram or a 20 mg dose of escitalopram. They then received standard treatment from a primary physician or psychiatrist with different medications and/or therapeutic modalities (e.g. psychotherapy). Special attention was given to subjects with suicidal ideation. Those subjects were offered additional appointments as needed to ensure their safety. Participants were also contacted by telephone at week 1 and week 2 by the Clinical Nurse Specialist (CNS) or other study personnel to ensure medication compliance and patient safety. The CNS was supervised by the study psychiatrist and principal investigator and deferred to the physician&#39;s judgment as needed. The SC was trained to notify the RC at the time of the clinical visits or the phone interviews if the subject endorsed any suicidal ideation or plans. For those subjects who were unable to attend the follow-up visits as scheduled, the patient was contacted by phone to complete the HRS-D17/QIDS-C16. The participant was also asked to return to the clinic to complete a final blood draw for the study. Adjunctive and concurrent medications. Adjunctive treatments were those used to manage transient associated symptoms (e.g., insomnia) or transient or longer-term medication side effects (e.g., sexual dysfunction). Adjunctive treatments that were not used to treat depression were allowed during the study. However, drugs in the exclusion criteria for this study were not used as adjunctive therapies. Subjects were allowed to participate in the study while receiving concurrent medications for general medical conditions as long as there was no contraindication to use while taking citalopram or escitalopram. Drug efficacy phenotype evaluation. The change in QIDS-C16 score and change in HRS-D17 score were used as the major research outcome measures to assess drug response. At each clinical research visit, the RC also completed the Clinician Global Impression of Improvement (CGI-I) scale. For the primary genome-wide association analyses, dichotomous outcome variables, remission and response, were defined based on the QIDS-C16 last visit score. Remission was defined as a QIDS-C16 score of 5 or less, while response was defined as at least a 50% reduction in the QIDS-C16 score from baseline. Specimen collection. Specimen collections were obtained by the General Clinical Research Center (GCRC) at St. Mary&#39;s Hospital (SMH). Subjects had blood drawn on an outpatient basis at GCRC-SMH on three separate occasions - baseline (0), week 4 and week 8 visits. Prior to sample collection, date and time of last dose of study medication was gathered at the 4 and 8 week visits. For those patients who were unable to complete the regularly scheduled visits, a dismissal blood draw was requested. GCRC then shipped samples to Mayo Clinic&#39;s Biospecimens Accessioning and Processing Lab. Genotyping and biomarker assays. DNA from 529 patients was genotyped by the RIKEN Center for Genomic Medicine (Yokohama, Japan) using Illumina Human610-Quad BeadChips (Illumina, San Diego, CA). The study also included the determination of plasma drug levels at weeks 4 and 8, and metabolite levels at baseline and weeks 4 and 8 for a subset of subjects. The primary genome-wide association study based on these data, which includes a summary of the protocol, subject description, selection of subjects for genetic analyses, and definitions of clinical outcomes, was published in the Pharmacogenomics Journal (Ji et al., 2012).

  Study phs000670

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• Characterization of individual foci of multicentric/multifocal breast cancer using targeted next generation sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the ?quadrants? of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients? survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Dataset EGAD00001000624

• Privacy Notice for Data Access Committee Account

  Privacy Notice for EGA Data Access Committee Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at mfreeberg@ebi.ac.uk , orpost at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: email at dpo@embl.org, orpost at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, orpost at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eupost at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: NameEmail addressTitle/PositionOrganisationOrganisational affiliationBusiness addressTelephone numberIP addressesDate and time of a visit to the service websiteOperating systemAmount of data transmittedBrowserUsernamePassword The data controller will use your personal data for the following purposes: To provide DAC user account and authenticated access to the service,To publicly publish some information to facilitate scientific research,To better understand the needs of the data subjects and guide future improvements of the service,To create anonymous usage statistics (from number of DACs, datasets per DAC). 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data),The general public via Internet will get access to your name, email address, business address, telephone number and organisation you belong to. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Data categories ‘name`, `email address`, `telephone number`, `business address`; `organisation’ of the DAC user are published on the Internet. They thus become accessible to recipients in countries outside the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI), is necessary for important reasons of public interest embedded in the aims of EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-dac

• eMERGE Network Phase III Clinical Sequencing: eMERGEseq Panel

  The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in September 2007 and began its third phase in September 2015. eMERGE III consists of nine study sites, two central sequencing and genotyping facilities, and a coordinating center. eMERGE Phase III aims to: 1) sequence and assess the phenotypic implication of rare variants in a custom designed eMERGEseq panel consisting of 109 genes (including 56 ACMG actionable finding list genes and the top 6 genes from each site relevant to their specific aims), as well as approximately 1400 SNPs; 2) assess the phenotypic implications of these variants by developing, validating and implementing new phenotype algorithms, 3) integrate genetic variants into EMRs to inform clinical care; and 4) create community resources. Included in this study are: ~24,000 eMERGE participants from 10 eMERGE III study sites. Corresponding demographics, body mass index measurements. Top PheWAS codes generated from a collated list of ICD codes from all study sites. Study sites and participants include: Cincinnati Children&#39;s Hospital Medical Center (CCHMC): Cincinnati Children&#39;s Hospital Medical Center (CCHMC) is a not-for-profit hospital and research center pioneering breakthrough treatments, providing outstanding family-centered patient care and training healthcare professionals for the future, and dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. We bring a comprehensive electronic health record (EPIC), a deidentified i2b2 data warehouse of 680K patient records, a biobank with &#62;261,000 consents that allow return of results to &#62;84,000 patients and guardians who have provided DNA samples, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. CCHMC will help the eMERGE III Steering Committee identify genes for the eMERGE III targeted sequencing panel, provide 3,000 DNA samples from CCHMC patients to be sequenced, review targeted gene panels from clinical care at CCHMC for somatic mosaicism and reinterpretation, and further develop and disseminate a software workflow suite for sequence analysis. We will also extend our work generating phenotype algorithms using heuristic and machine learning methods to many new childhood diseases. We will develop tools to evaluate adolescent return of results preferences, examine the ethical and legal obligations and potential to reanalyze results, and develop clinical decision support for phenotyping, test ordering, and returning sequencing results. Children&#39;s Hospital of Philadelphia (CHOP): The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children&#39;s Hospital of Philadelphia (CHOP), and one of the world&#39;s largest genetics research programs, with to state-of-the-art high-throughput sequencing and genotyping technology. Our primary goal is to translate basic research findings to medical innovations. We aim to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders, including asthma, autism, epilepsy, pediatric cancer, learning disabilities, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Participants were recruited from the CAG biorepository (n&#62;450,000), specifically from &#62;100,000 CHOP pediatric patients and family members, which is enriched for rare-diseases (n&#62;12,000). Center for Applied Genomics, The Children&#39;s Hospital of Philadelphia We gratefully thank all the children and their families who enrolled in this study, and all individuals who donated blood samples for research purposes. Genotyping for this project was performed at the Center for Applied Genomics and supported by an Institutional Development Award from The Children&#39;s Hospital of Philadelphia. Sequencing was supported by the National Institutes of Health through an award from the National Human Genome Research Institute&#39;s Electronic Medical Records and Genomics (eMERGE) program (U01HG008684). Columbia University: The goal of the Columbia eMERGE III project is to develop methods for integrating genomic data in EHRs and to study the impact of such genomic informatics interventions on the health of a diverse, underserved urban adult English- and Spanish-speaking patient population in Northern Manhattan served by Columbia University Medical Center/New York-Presbyterian Hospital system. The study group is 2500 patients recruited from diverse clinics and community outreach centers of self-reported White (~61%), Asian (~11%), African-American (~11%), American Indian/Alaska Native (&#60;1%) racial and Hispanic (~33%) ethnic backgrounds. There are two subgroups in the study cohort - a retrospective group (N=1052) that includes patients from oncology and nephrology clinics, and a prospective one (N=1448) that includes healthy individuals as well as participants with diverse medical conditions. Confirmed pathogenic variants in 70 selected genes will be returned to participants and their healthcare providers through the EHR integration. Participants are able to choose the results they receive and will have the freedom to meet with a genetic counselor and a geneticist to review results. The impact of genetic testing on clinical care is determined by periodic monitoring of EHRs. Geisinger: Samples and phenotype data in this study were provided by the Geisinger MyCode&#174; Community Health Initiative. Participants are recruited across the Geisinger System via online consents or in-person consents at a hospital or clinic visit. Enrollment is ongoing with over 100,000 individuals currently consented. Partners Healthcare (Harvard University): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people&#39;s health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women&#39;s Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women&#39;s Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 70,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 130 million dollars in NIH research. Kaiser Permanente Washington/ (KPWA) / University of Washington (UW): KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N=2,500.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA&#39;s integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes N=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (N=1,255), in order to allow us to enrich germline pathogenic variants. Mayo Clinic: The Return of Actionable Variants Empirical (RAVE) Study was approved by the Mayo Clinic IRB. We recruited 2537 participants from Mayo Clinic biobanks in Rochester, MN, who had hypercholesterolemia or colon polyps, thereby enriching for Familial hypercholesterolemia (FH) and monogenic causes of colorectal cancer (CRC). Additional eligibility criteria were: 1) residents of Southeast MN who were alive and aged 18-70 years; 2) LDL-C level &#62;155 or &#62;120 mg/dl while on lipid-lowering therapy; 3) no known cause of secondary hyperlipidemia; and 4) no cognitive impairment or dementia that would compromise their ability to give written informed consent. Based on these criteria, we identified 5270 eligible patients and obtained informed consent from 3030 participants. Recruitment was conducted in waves and utilized mailed recruitment packets consisting of a study brochure, a written informed consent form, a baseline psychosocial questionnaire, and a return postage-paid envelope. DNA of 2537 participants was sent for CLIA-certified targeted sequencing of 109 genes including genes associated with FH and CRC. Targeted sequencing and genotyping was performed in a Central Laboratory Improvement Amendment (CLIA)-certified laboratory. Northwestern University: Samples and data used in this study were obtained from patients from Northwestern Medicine, an integrated healthcare system, formed through a partnership of Northwestern Memorial HealthCare and Northwestern University Feinberg School of Medicine. Participants include a retrospective cohort from the Northwestern Pharmacogenomics Study, funded through the eMERGE II project, NHGRI (3U01HG006388-02S1) and a prospective cohort from the Genetic Testing and Your Health Study, funded through the eMERGE III project, NHGRI (U01HG008673). Patients were eligible to participate if they were18 years or older and see a physician at Northwestern Medicine. Patients consented to genetic testing and to allow their results to be placed in their electronic medical record. Vanderbilt University Medical Center: Vanderbilt University Medical Center (VUMC) participants were enrolled in the eMERGE Network through the Vanderbilt Genome-Electronic Records (VGER) project. Patients were provided the appropriate consent to receive clinically relevant genetic results (N=2,700). Participants were eligible if aged 21 or over, had a healthcare provider at VUMC, and visited the provider at least 3 times in the past 3 years. Meharry Medical College: Inclusion of ethnic groups in genomic research is critical to identify possible reasons for health disparities. African-Americans are being enrolled in various outpatient clinics of Nashville General Hospital at Meharry, an inner city hospital primary serving a poorer patient group. A total of 500 African Americans with four cancer types demonstrating health disparities in this population - prostate, colon, breast, lung are identified and approached by clinical research coordinators. The purpose of the study is to determine if any genetic information can be identified from these patients who have or are at high risk of one of these disparate cancers. All participants provide written informed consent and HIPAA authorization to provide blood samples for broad research use and permission to access data in their hospital electronic medical record for research now and in the future. An extensive demographic profile is obtained and entered into a REDCap database. Blood samples are obtained for a panel of alleles from extracted DNA at Baylor. In addition, de-identified coded samples are processed and stored in a central biorepository for further DNA, RNA and proteomic analyses. The survey and phlebotomy are performed at the time of the initial contact and agreement to participate. Nearly all patients approached willingly agree to participate for potential benefit to themselves, family members, or humankind. Little concern is voiced of providing samples for genetic analysis. Study investigators will share results with the participants and providers if testing does not indicate high risk. Results indicating increased risk or actionable alleles for the patient and/or family will be returned by a genetic counselor. Monitoring of the patients&#39; health in this cohort will continue to be followed in the EMR to identify any future associations that might explain health disparities in African Americans. Proposals will be reviewed from investigators to study the genetic or proteomic samples as well as the clinical and demographic information in the repository. Please note that this version of the dataset has a handful of mismatches between genotyped and provided sex. Data with the following IDs should be removed prior to analysis: 420252874213744142412243424569384245694642672223

  Study phs001616

• Center for Craniofacial and Dental Genetics: Study of Dental Caries and Cleft Lip/Palate in Guatemala

  This study provides an opportunity to investigate the genetics of both dental caries and orofacial clefts (OFCs) in one set of families ascertained in Guatemala. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). Furthermore this study brings together multiple research priorities of the University of Pittsburgh Center for Craniofacial and Dental Genetics (www.ccdg.pitt.edu). A genome-wide panel of 610,000 SNPs was genotyped at the Broad Institute to be comparable to our other pertinent GENEVA studies that are also part of dbGaP (dbGaP accession number phs000095, "Dental Caries: Whole Genome Association and Gene x Environment Studies" and dbGaP accession number phs000094, "International Consortium to Identify Genes and Interactions Controlling Oral Clefts"). The goal of this study is to investigate genetic determinants to dental caries and to OFCs in a novel study population. To date, most genetic studies of dental caries have been conducted in Caucasians, and of OFCs in Caucasians and Asians. The Guatemalan population under study is rural and ethnically mixed with a high proportion of Native-South-Americans. Thirty-six Guatemalans from this dataset were also part of the recent GWAS studies of cleft lip and cleft palate (Beaty et al., 2010 and 2011, dbGaP Study Accession: phs000094, "International Consortium to Identify Genes and Interactions Controlling Oral Clefts"). In addition to the families ascertained in Guatemala, some subjects were genotyped with this cohort to augment the data in the parent GENEVA study (Dental Caries: Whole Genome Association and Gene x Environment Studies, dbGaP accession number phs000095), in particular individuals from the IOWA and PITT GENEVA study sites. Their data are available with the parent study. Dental caries (also known as tooth decay) remains the most common chronic disease of childhood, five times more common than asthma and seven times more common than environmental allergies, with more than 40% of children exhibiting caries when they enter kindergarten. In 2005, it was estimated that dental health care costs were approximately $84 billion, of which 60% or about $50 billion were related to treatment of dental caries. The etiology of dental caries has been studied for many years. Multiple factors contribute to a person&#39;s risk for caries, including: 1) environmental factors such as diet, oral hygiene, fluoride exposure and the level of colonization of cariogenic bacteria and 2) host factors such as salivary flow, salivary buffering capacity, position of teeth relative to each other, surface characteristics of tooth enamel and depth of occlusal fissures on posterior teeth. In spite of all that is known about this disease, there are still individuals who appear to be more susceptible to caries and those who are extremely resistant, regardless of the environmental risk factors to which they are exposed, implying that genetic factors also play an important role in caries etiology. This conclusion is supported by studies in both humans and animals, with the most compelling evidence coming from studies of twins reared apart in which investigators found significant resemblance within monozygotic (MZ) but not dizygotic (DZ) twin pairs for percentage of teeth and surfaces restored or carious and estimated the genetic contribution to caries as 40%. Other recent studies of twins reared together estimated the heritability for caries, adjusted for age and gender, as ranging from 45-64%. In our study populations of families, we also estimated caries heritability as approximately 54%-70% of variation in primary dentition caries scores and 35%-55% in the permanent dentition (Wang et al., 2010). Orofacial clefts (OFCs), particularly cleft lip with or without cleft palate (CL/P) and isolated cleft palate (CP) are a major public health problem, affecting one in every 500-1000 births worldwide thus representing the most common facial birth defect and one of the most common of all congenital anomalies. CL/P is a major structural birth defect that is notable for significant lifelong morbidity and complex etiology. The extensive psychological, surgical, speech and dental involvement emphasize the importance of understanding the underlying causes of CL/P. Therefore, many research groups have attempted to elucidate the etiology of CL/P, with some recent success by our research group and others (see Beaty et al., 2010, 2011; Dixon et al., 2011). It is clear that CL/P can occur as part of Mendelian syndromes, that certain chromosomal abnormalities include CL/P in the phenotype, and that certain teratogens can increase the risk of having an offspring with CL/P. However, phenotypes of known etiology comprise only a small portion of all individuals with a CL/P or CP, and the major focus of research into OFCs is to develop an understanding of the etiology of nonsyndromic (NS) forms of clefting. A major focus of the University of Pittsburgh CCDG has been to study additional phenotypes within nonsyndromic OFC families in order to identify sub-clinical expressions of OFC risk genes or risk variants, e.g. SNPs (see Weinberg et al., 2006). A detailed oral exam is conducted as part of these extended phenotypic studies, including a dental caries exam. Note that although there are some reports in the literature of higher caries experience in individuals with clefts, the most recent meta-analysis of those literature reports concluded that individuals born with these defects do not have a higher frequency of caries (Hassl&#246;f and Twetman, 2007). Notably, we investigated the association of CL/P and caries in three of our study populations (including part of the Guatemalan population in this GWAS study) and also found no increase in caries rates of CL/P cases versus controls (Jindal et al., 2011). This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to dental caries and oral clefts through large-scale genome-wide association studies of well-characterized Guatemalan families and individuals. Genotyping was performed at the Broad Institute of MIT and Harvard. The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR, U01-DE018903). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000440

• Childhood Cancer Survivor Study (CCSS)

  Background and Rationale for the Childhood Cancer Survivor Study (CCSS) Over the last several decades, advances in treatments for childhood and adolescent cancer have substantially improved survival following diagnosis. These improvements gave rise to the responsibility for investigating long-term treatment-associated morbidity and mortality. Early efforts to describe late effects were largely conducted through single-institution and limited consortia studies. However, by the mid-1980s, it became increasingly clear that these approaches had inherent limitations, including small sample size, convenience sampling, incompletely characterized populations, and limited length of follow-up. To overcome these limitations, the CCSS was proposed and funded by the National Cancer Institute (NCI) as a U01 grant in 1994. Subsequently, the strengths of the CCSS, including an efficient and extensive infrastructure, plus expanding database and biorepository, were recognized and appreciated. Thus, in consultation with the NCI, the CCSS was converted to a U24 (resource grant) funding mechanism to serve the scientific community in 2000. The overarching goal of the CCSS resource is to increase the conduct of innovative and high impact research related to pediatric cancer survivorship. CCSS has been used extensively by researchers from a wide range of disciplines to address a broad spectrum of topics. Strengths of the resource include its large size, comprehensive annotation of treatment exposures, ongoing longitudinal follow-up with characterization of a wide array of participant characteristics and outcomes, and an established biorepository. Design of the Childhood Cancer Survivor Study The Childhood Cancer Survivor Study (CCSS) is a multi-institutional, multi-disciplinary collaborative research resource comprised of a retrospective hospital-based cohort of survivors of childhood cancer and a comparison sibling cohort. Eligible survivors from 31 participating institutions were diagnosed between 1970 and 1999, prior to age 21 years, with selected common pediatric cancers (leukemia, central nervous system tumors, Hodgkin lymphoma, non-Hodgkin lymphoma, kidney tumors, neuroblastoma, soft tissue sarcoma, or bone tumors). All patients who survived five years from the date of diagnosis were eligible, regardless of disease or treatment status. The baseline questionnaire was completed by 24,368 survivors and 5,039 siblings recruited to serve as a comparison group. To date, participants have completed three general follow-up surveys, as well as a number of specialized surveys on specific topics (e.g. health care, insurance, screening practices, men's and women's health issues, adolescent health, sleep and fatigue). In addition, biological samples (buccal cells, saliva and/or blood) have been collected for over 11,000 participants. Full descriptions of the design and characteristics of the CCSS have been previously published (Robison et al; Leisenring et al.), and available data and samples are described at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html. Treatment Data in the Childhood Cancer Survivor Study A key feature of CCSS is the availability of detailed treatment data, which were collected by abstraction of medical records for each individual member of the cohort. Detailed abstraction included dates of therapy, protocol information, and specific details regarding surgery, chemotherapy and radiation. Quantitative dose details were collected for 22 specific chemotherapeutic agents, including alkylating agents, anthracyclines, platinum compounds and epipodophyllotoxins. In addition to individual agent doses, algorithms have been created to calculate cumulative doses of all drugs in a specific class, such as anthracyclines (doxorubicin, daunomycin and idarubicin) or platinum agents (cisplatinum and carboplatinum). Data abstracted for surgeries included dates and both the names and corresponding International Classification of Diseases (9th revision) code. For radiation treatment data, all relevant records were sent to the Radiation Physics Center at M.D. Anderson Cancer Center for detailed abstraction and dosimetry. Initial body region dosimetry was performed for all participants, followed by more detailed dosimetry as needed for specific studies. Genomics Data in the Childhood Cancer Survivor StudyThe NCI's Division of Cancer Epidemiology and Genetics and CCSS investigators collaborated to conduct genomics studies (SNP array genotyping and whole exome sequencing) using samples from the CCSS Biorepository. Studies included all cohort participants with available DNA regardless of sex or ancestry when the genomics studies were initiated. Phenotype Data in the Childhood Cancer Survivor Study Vital status and cause of death for both participants and non-participants is determined via linkage with the National Death Index (NDI). Identification of subsequent neoplasms is based on self-report, followed by validation using medical records, or via NDI. A wide array of additional health outcomes have been ascertained via a comprehensive set of questions on the CCSS questionnaires, covering potential adverse events across a range of organ systems (hearing/vision/speech, urinary, hormonal, heart and circulatory, respiratory, digestive, brain and nervous systems). In addition to health outcomes, longitudinal data have been collected on demographics, health behaviors, family history, screening practices, insurance status, and a range of psychosocial and neurocognitive factors. A full listing of available variables and copies of the CCSS questionnaires are available at http://ccss.stjude.org. Research Areas in the Childhood Cancer Survivor Study Extensive use by the research community has resulted in over 265 published manuscripts on a wide range of topics, including associations between treatment factors and mortality, subsequent neoplasms, chronic health conditions, cardiac events, neurocognitive sequelae, psychosocial factors, fertility, and health status. Additional topics have included health behaviors, screening practices, health care access and utilization, statistical and exposure assessment methodology, and development of risk prediction models. A full listing of published manuscripts using CCSS data is available on the CCSS website at https://ccss.stjude.org/published-research/publications.html. The Childhood Cancer Survivor Study as a Resource for Investigators The CCSS is an NCI-funded resource (U24 CA55727) to promote and facilitate research among long-term survivors of cancer diagnosed during childhood and adolescence. Interested investigators are encouraged to develop research ideas and propose projects within CCSS, whether or not they are from a participating CCSS institution. The CCSS is now accepting proposals to collaborate with CCSS and NCI investigators in the use of genomics data and corresponding outcomes-related data to address innovative research questions relating to potential genetic contributions to risk for treatment-related outcomes. Any researcher, or group of researchers, qualified to conduct genetic research can submit a proposal. There are no restrictions relative to country, institution, or prior involvement in CCSS. A full description of the process for developing a proposal for genetic research in CCSS can be found at https://ccss.stjude.org/develop-a-study/gwas-data-resource.html, along with listings of approved proposals.

  Study phs001327

• Genome-Wide Association Study of Leprosy and Dapsone Hypersensitivity Syndrome (DHS) in Chinese population

  Leprosy GWAS (1) Leprosy is a chronic infectious disease caused by Mycobacterium leprae (M. leprae). Due to M. leprae&#39;s narrow host range and an inability to be cultured in vitro, the biological investigation of this disease has been difficult. Host genetic factors have been suggested to play an important role in disease development, but few have been identified. In this study, we attempted to identify the host genetic factors by performing a two-stage genome-wide association study (GWAS) in Chinese population. The initial genome-wide scan was done by genotyping 706 patients and 1225 controls using the Illumina HumanHap610 BeadChip, and the follow-up study was performed by genotyping 93 SNPs in three independent samples consisting of 3254 cases and 5955 controls. We identified significant association (P &lt; 10-10) within six genes CCDC122 (13q14), C13orf31 (13q14), NOD2(16q12), TNFSF15 (9q32), HLA-DR (6p21) and RIPK2 (8q21), and suggestive association (P = 5.68x10-6) within LRRK2 (12q12). We also revealed suggestive evidence for C13orf31, LRRK2, NOD2 and RIPK2 to show stronger association in the multibacillary form than the paucibacillary form of leprosy. Our findings highlight the importance of the innate immune response, particularly NOD2-mediated signaling, in leprosy and suggests a new therapeutic target for leprosy. DHS GWAS Dapsone (DDS), as both an antibiotic and an anti-inflammatory agent, has been widely used for preventing and treating pathogen-caused infectious diseases and chronic inflammatory diseases. Currently, about 0.5-3.6% of individuals treated with DDS develop severe dapsone hypersensitivity syndrome (DHS) and the mortality rate is up to about 11-13%. However, until now, no tests are available to predict the risk of DHS. To identify the genetic risk factors of DHS, we performed a two-stage GWAS in Chinese population. In this study, the initial genome-wide scan was done by genotyping 39 DHS cases and 833 controls using Illumina Human 660W-Quad Beadchips and imputed human leukocyte antigen (HLA) molecules. Validation was performed by genotyping 24 SNPs using the Sequenom MassARRAY platform in additional 31 DHS cases and 1,089 controls through genotyping and 32 four-digit HLA-B alleles in an independent series of 37 DHS cases and 201 controls through Roche 454 sequencing. We identified significant association (OR =6.18, P = 3.84x10-13) with SNP rs2844573, which located between the HLA-B and MICA loci. HLA-B*13:01 was confirmed to be a strong risk factor for DHS (OR = 20.53, P = 6.84x10-25) and responsible for the association at rs2844573. The presence of HLA-B*13:01 had a sensitivity of 85.5% and specificity of 85.7% as a predictor for DHS, and its absence can reduce the risk by 7 fold (from 1.4% to 0.2%). HLA-B*13:01 is strongly associated with the development of DHS and can be used as a risk predictor of DHS in the individuals of Chinese and other Asian populations. Leprosy GWAS (2) This is a three-stage GWAS of leprosy in the Chinese population. The genome-wide discovery analysis involved two independent data sets: the new unpublished data set by genotyping 842 leprosy patients and 925 controls from northern and southern China using the Human660w-quad beadchips and a previously published GWAS data set of 706 leprosy cases, 1,225 healthy controls and 4,362 individuals with immune-related diseases as population controls from northern China of Chinese Han descent. Further validation studies were performed in two stages in a total of 6,765 cases and 9,505 controls from Chinese Han and minority descent in multiple areas of China, similar to the discovery stage. From this study, we discovered six new susceptibility loci with a combined P-value from discovery and validation stage surpassing genome-wide significance, including BATF3 at 1q32.3, CDH18 at 5p14.3, DEC1 at 9q32, EGR2 at 10q21.3, CCDC88B at 11q13.1 and CIITA at 16p13.13. Our current study has advanced the genetic understanding of leprosy by substantially increasing the number of confirmed genetic susceptibility loci. Leprosy GWAS (3) To discover additional leprosy susceptibility loci, we carried out a large-scale three-stage GWAS analysis of leprosy in Chinese population. The genome-wide discovery analysis (Stage 1) involved a new GWAS data set of 1,197 leprosy cases and 1,426 controls from northern and southern China conducted by using Illumina Omni Zhonghua chips with 900,015 single-nucleotide polymorphisms (SNPs), two published GWAS dataset (GWAS2 data set including 706 leprosy cases, 1,225 healthy controls genotyped by Illumina HumanHap610 beadchips, GWAS3 data set including 842 leprosy patients and 925 controls from northern and southern China genotyped by the Human660w-quad beadchips). Further validation studies were performed in two stages in a total of 5,413 cases and 9,771 controls from Chinese Han descent in multiple areas of China. In this study, we identified four novel associations at genome-wide significance (P &lt; 5 x 10-8), all of which can indicate candidate genes within the susceptibility loci, SYN2 (3p25.2), BBS9 (7p14.3), CTSB (8p23.1) and MED30 (8q24.11), through a differential gene expression and eQTL analysis. Altogether, these findings have provided new insight and significantly expanded our understanding of the genetic basis of leprosy. Leprosy GWAS (4) In this study, we attempted to systematically investigate the contribution of protein-coding variants to leprosy susceptibility by performing a three-stage genome-wide association study (GWAS) of protein-coding variants in Chinese population. The initial genome-wide scan was done by genotyping 1,670 persons affected by leprosy and 2,321 controls using the Illumina Infinium Human Exome Beadchips (v1.0).The validation study was performed by genotyping 39 SNPs in an additional 3,169 leprosy patients and 9,814 healthy controls from the northern region of China, and the replication study was performed by genotyping eight SNPs in three independent samples from the southern regions of China consisting of 2,231 cases and 2,266 controls. We identified significant association (P &lt; 1.23 x 10-6) within seven genes FLG (Gene ID: 2312), IL23R (Gene ID: 149233), CARD9 (Gene ID: 64170), NCKIPSD (Gene ID: 51517), TYK2 (Gene ID: 7297), SLC29A3 (Gene ID: 55315), IL27 (Gene ID: 246778). Our findings discover novel involvement of skin barrier and endocytosis/phagocytosis/autophagy, besides known innate and adaptive immunity, in the pathogenesis of leprosy, highlight the merits of protein coding variant studies for complex diseases. Here, the summary statistics from the five genome-wide association analyses were published.

  Study phs000217

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (&lt; 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value &lt; 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (T&#246;rn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, &gt;90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age&lt;20 0.043 Age&gt;40 0.032 Age&lt;30, &#8805;20 0.251 Age&gt;30, &#8804;40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd&#39;s group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient&#39;s breast and the reference materials have the same thickness as the patient&#39;s breast, then the breast&#39;s grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson&#39;s R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be &gt;0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• What is a DAC?

  What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant.  For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source.  Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions.  You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks.  Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

  Documentation access/data-access-committee/what-is-dac

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• How to upload GPG files

  Uploading files Users that holds an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. In order to manage the available resources, we enforce a limit of 10Tb per submission account at any one time. Please do not exceed this limit. INBOX FTP The FTP is only compatible with files encrypted using the EGACryptor tool Before uploading Once your submission files have been prepared using the EGAryptor, the resulting encrypted files and associated md5sum files can be uploaded to your submission account using Aspera or FTP. The EGA is a shared, public service with limited resources. In order to manage the available resources, EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. If you are approaching this limit please contact contact EGA Helpdesk so that we can advise on how to register the associated metadata and trigger the archiving of files, so that you can continue with your submission. If we note that your submission account increases above 10Tb on a consistent base your password will be changed until metadata is associated. Aspera Download Aspera Using Aspera FTP FTP windows FTP Linux / Unix FTP client (Filezilla) FTP and TLS Troubleshooting Troubleshooting Aspera Download Aspera is a commercial file transfer protocol that may provide faster transfer speeds than ftp especially over longer distances. The Aspera ascp command line client. Please select Aspera Connect. The ascp command line client is distributed as part of the aspera connect highperformance transfer browser plugin and is free to use, without registration. The minimum required version of the IBM Aspera Cli is V4. Further instructions. Using the Aspera ascp command line program The location of the ascp program in the filesystem: Mac: on the desktop go cd /Applications/Aspera\ Connect.app/Contents/Resources/ there you'll see the command line utilities where you're going to use ascp. Windows: the downloaded files are a bit hidden. For instance, in Windows 7 the ascp.exe is located in the users home directory in: AppData\Local\Programs\Aspera\Aspera Connect\bin\ascp.exe Linux: should be in your user's home directory, cd /home/username/.aspera/connect/bin/ there you'll see the command line utilities where you're going to use ascp. Your command should look similar to this: ascp -P33001 -O33001 -QT -l300M -L- /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path If you wish to upload several files without being requested the password, please use the below command : ASPERA_SCP_PASS=ega-box-password ascp -P33001 -O33001 -QT -l300M /path/file ega-box-N@fasp.ega.ebi.ac.uk:/path/ Explanation of parameters l300M option sets the upload speed limit to 30MB/s. You may wish to lower this value to increase the reliability of the transfer. L option is for printing logs out while transferring files to upload can be a file mask (e.g. '/homes/submitter/*.srf) or a list of files. ega-box-N is your submission account login. Add k2 switch for transfer restarts Check the command line transfer usage for more configuration details. Using FTP to upload your prepared files Use your preferred ftp client. For example, lftp is a popular choice for Linux and Mac users. Use binary mode for file transfers. Use ftp.ega.ebi.ac.uk as the target host. Login with your ega-box username and password. Upload files to your private ega-box upload area. Depending on your network setting you might wish to start FTP in passive or active mode. Using default FTP command line client in Windows Start the command line interpreter: press WinR, type cmd, hit enter Enter ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Use exit command to exit the command line interpreter. Using default FTP command line client in Linux / Unix Open a terminal and type ftp ftp.ega.ebi.ac.uk Enter your submission username Enter your submission password Type binary to enter binary mode for transfer To see a list of available ftp commands type help. Type ls command to check the content of your submission account. Type prompt to switch off confirmation for each file uploaded. Use mput command to upload files: mput *.bam* Use bye command to exit the ftp client. Using FTP client FileZilla We recommend the use of FileZilla, a free FTP client . FileZilla is open source software distributed free of charge under the terms of the GNU General Public License. Use the following connection details (File - Site Manager) and add yoursubmission account username and password: Using FTP client FileZilla Select the files you wish to upload and then select upload: Using FTP client Filezilla Using LFTP with TLS We recommend the following to force the use of a secure connection. lftp > set ftp:ssl-force yes We also recommend setting the following for not encrypting the bulk data itself for performance reasons (theauthentication will still be encrypted): lftp > ftp:ssl-protect-data no In order to verify the certificate,the recommended way would be to use the CA certificates from your machine. To do that use this command in lftp adjusting the path to your ca-certificates location. lftp > ssl:ca-file "/etc/ssl/certs/ca-certificates.crt" If that is not possible or certificates are old and you can't update them, you can download the certificates needed from Quo Vadis Digital Repository The two certificates to download in PEM format are: QuoVadis Root CA2 G3 QuoVadis EV SSL ICA G3 Then you can concatenate them in a file one after the other and save it as lftp-certificates.pem Once this is done you have to point the ssl:ca-file variable to the path lftp > set ssl:ca-file "/path/to/lftp-certificates.pem" Also note that you can save this configuration at ~/.lftp/rc Another option is to download the certificates and add them to the ca-certificates of your machine. For example: In RHEL7 and cenots and others box the process to add the certificates globally is: Download the two certificates (in PEM or DER format, doesn't matter) and save them to "/etc/pki/ca-trust/source/anchors/" Run "update-ca-trust extract" Another less secure option is to turn off certificate verification with the following command: lftp > set ssl:verify-certificate false Troubleshooting If you are having problems with Aspera connection timeouts, it can be down to either one of the following. Transfers cannot start the connection fails instantly. Ensure that TCP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewall. The connection is made, transfers are started, but 0 bytes (0%) are uploaded for each file. Ensure that UDP traffic on port 33001 is allowed (open) for outbound connections through your computer's firewall and network's firewal

  Documentation submission/data/uploading-files/ftp