12160 results for "fc 26 coins pc Visit Buyfc26coins.com for latest FC 26 coins news..z7ux"

in 42.73 milliseconds.

• eIMPACT Trial: Modernized Collaborative Care to Reduce the Excess CVD Risk of Older Depressed Patients

  Cardiovascular disease (CVD) is the #1 killer of American men and women, and its economic burden is substantial and on the rise. Adults with depression are at elevated risk of CVD events and poor CVD prognosis. Unfortunately, past clinical trials of depression treatments have not observed the anticipated cardiovascular benefits. A novel explanation for these null results is that the depression interventions in these trials, which all involved patients with preexisting CVD, were delivered too late in the natural history of CVD. Accordingly, the objective of this single-center, parallel-group, assessor-blinded randomized controlled trial was to determine whether successful depression treatment before, versus after, the onset of clinical CVD reduces CVD risk in depression. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized 1:1 to 12 months of the eIMPACT intervention (a modernized collaborative stepped care program involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). The primary outcome was endothelial dysfunction (brachial flow-mediated dilation) at 12 months, and the secondary outcomes were self-reported depressive symptoms (Hopkins Symptom Checklist-20), autonomic dysfunction (high-frequency heart rate variability), systemic inflammation (interleukin-6 and high-sensitivity C-reactive protein), and platelet activation (β-thromboglobulin and platelet factor 4) at 12 months. The central hypothesis was that the eIMPACT intervention would improve endothelial dysfunction in depressed adults by decreasing depressive symptoms, autonomic dysfunction, systemic inflammation, and platelet activation. Primary results are posted to ClinicalTrials.gov at NCT02458690. The de-identified limited dataset available on BDC consists of only the individual phenotypic data needed to confirm this trial’s primary results – i.e., randomization status, primary and secondary outcome variables, and participant characteristics utilized in the hypothesis-testing models (age, sex, race, education, income, and systolic blood pressure). We also provide the SAS code to replicate the results of the hypothesis-testing models reported in Table 4 and Supplemental Tables 1-3 in the main outcomes paper (#2 in Selected Publications). Of note, the user will need to specify the file path for the dataset to run the SAS code. Instructions for requesting individual-level data are available on BDC at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BDC. For questions about availability, you may contact the BDC team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs003283

• 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

• Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

  We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

  Study phs003865

• 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

• Institute for Refractory Cancer Research (IRCR) Data Access Committee

  Dac EGAC00001000272

• DAC for study Hominin-specific NOTCH2 paralogs expand human cortical neurogenesis through regulation of Delta/Notch interactions.

  Dac EGAC00001000816

• Wargo Group Data Access Committee for Neodjuvant Immune Checkpoint Blockade in High-Risk Resectable Melanoma

  Dac EGAC00001001008

• DAC for study the impact of urbanization and diet on innate immune responses in healthy Tanzanians

  Dac EGAC00001001531

• Patient-derived tumor organoids for personalized medicine in a rare case of hepatocellular carcinoma with neuroendocrine differentiation.

  Dac EGAC00001002458

• Ultra-deep targeted sequencing for studying the accumulation of somatic mutations in cancer-free human skin

  Study EGAS00001004279

• Karolinska Institutet - Susanne Schlisio Lab

  DAC for Susanne Schlisio Lab, Department of Oncology-Pathology, Karolinska Institutet, Sweden

  Dac EGAC50000000603

• MutationalPatterns2: The one stop shop for the analysis of mutational processes: DNA repair deletions

  Study EGAS00001004789

• Preliminary Results from the Initiative for Molecular Profiling and Advanced Cancer Therapy 2 (IMPACT 2) Study

  Study EGAS00001004964

• Molecular evolution and clinical trajectories of prostate cancer identifies novel markers for risk stratification - additional data

  Study EGAS00001004884

• High coverage sequencing of a single sample can account for the problem of intratumor heterogeneity

  Study EGAS00001004200

• A capture-based next-generation sequencing panel for the molecular characterization of chronic lymphocytic leukemia

  Study EGAS00001006975

• CUPiD, a cfDNA methylation-based tissue-of-origin classifier for Cancers of Unknown Primary

  Study EGAS00001007445

• HC_genotyping

  HC genotyping data for lead SNPs using Illuminia Global Array V2.0

  Dataset EGAD00010002475

• WES of TGA

  Whole exome sequencing data for 381 TGA probands

  Dataset EGAD00001005809

• Genomic Sequencing of Triple Negative Breast Cancer - CUTseq data

  CUTseq data for study EGAS00001008261

  Dataset EGAD00001015684

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• DMET Genes, Nicotine Metabolism and Prospective Abstinence

  This study (DA033813; PI: Andrew W Bergen; PMID:26132489) includes samples from two laboratory studies of nicotine metabolism. The Pharmacokinetics of Nicotine Metabolism in Twins study (PKTWIN; PI: Gary E Swan; PMID: 15527659) was based on recruitment from a twin registry (PMID: 23084148). The Integrated Research Project on Tobacco Use and Dependence (IRP; PI: Gary E Swan; PMID: 14578134) was based on recruitment from a pedigree-based longitudinal study of risk factors for substance use, the Smoking in Families study (SMOFAM; DA03706; PI: Hy Hops). These two laboratory studies (PKTWIN and IRP/SMOFAM) served as the Stage I dataset to interrogate Drug Metabolizing Enzyme and Transporter genes with a targeted SNP array for association with the Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine), an established biomarker of nicotine metabolism. In addition to the laboratory studies, samples from eight RCTs (PMID: 23249876) with the NMR and smoking-related measures used to test SNPs identified in Stage I (PMID: 26132489). In a third stage, a lung cancer meta-analysis database (PMID: 24880342) was used to assess association of SNPs identified in Stage II with lung cancer. The objectives of the study were to identify novel genes and SNPs contributing to nicotine metabolism (Stage I), and to validate PK SNPs associated with the NMR from individuals participating in a clinical laboratory protocol with the NMR obtained from treatment-seeking smokers, and then to investigate association with prospective smoking cessation (Stage II). This study built upon existing studies of nicotine metabolism and randomized trials of smoking cessation therapies. Enhanced knowledge of the genes influencing nicotine metabolism and prospective abstinence may help personalize smoking cessation treatment and risk assessment for smoking-related diseases. For Stage I, both subject [fixed-dose NMR, covariates (age, BMI, ethnicity, sex, smoking status, and hormone use), and pedigree relationships] and sample (common DMET SNP genotype, genotyping quality control) data are available in this accession. The analysis protocol, quality control summaries, summary genotype, summary phenotype, and analysis results are available for Stage I, II and III samples (PMID: 26132489). Extensive discussion of the prior CYP2A6 association literature with the NMR, abstinence, smoking heaviness and lung cancer risk is available (PMID: 26132489). The NMR has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET) gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs) at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3). Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

  Study phs000931

• A Genome-Wide Association Analysis in Angiotensin-Converting Enzyme (ACE) Inhibitor-Associated Angioedema and ACE Inhibitor-Exposed Controls; A Collaboration between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Center for Genomic Medicine

  The purpose of this study is to identify genetic predictors of ACE inhibitor-associated angioedema. In addition to preventing the formation of the pressor angiotensin II, ACE inhibitors prevent the carboxyl-terminal degradation of the vasoactive substances bradykinin and substance P. Angioedema is hypothesized to result from defective amino-terminal degradation of bradykinin or substance P in patients in whom ACE is inhibited. For example, activity of dipeptidyl peptidase IV (DPP-IV), the enzyme responsible for the inactivation of substance P when ACE is inhibited, is decreased in patients with angioedema. In preliminary studies, we have identified SNPs in the DPP4 gene that associate with DPP-IV activity and, in blacks, with risk of angioedema. This project will use genome-wide genotyping to compare 250 cases and 568 ACE inhibitor-exposed control subjects (131 cases and 288 controls ascertained at Vanderbilt and 70 cases and 280 controls ascertained at the Marshfield Clinic). We plan a 2-stage analysis of associations between SNPs and angioedema - first, we will study DPP4 SNPs for association with angioedema and, second, we will explore associations using the full GWAS data set. Depending on the platform, additional DPP4 SNPs will be used to fully tag common genetic variants in both African American and European American samples. Based on the HapMap data, there are 14 tagging SNPs in people of European descent and 34 in Yoruba (selection criteria MAF>0.05 and r2>0.8). Cases were defined as having ACE inhibitor-associated angioedema if they had had swelling of the lips, throat, tongue or face while taking an ACE inhibitor but had never had angioedema while not taking an ACE inhibitor. For simplicity, intestinal edema was excluded. Control subjects were treated for at least 6 months with an ACE inhibitor without angioedema. Because black Americans are known to be overrepresented among patients with ACE inhibitor-associated angioedema, control subjects were prespecified to be 50% black American, 50% white American, and 50% female. At Vanderbilt, the medical history, including the history of angioedema, was confirmed by a research nurse or physician using a detailed case report form. Characteristics of Vanderbilt cases appear in the Table. At Marshfield, medical history will be confirmed by chart review. The Marshfield cohort is 98% white American and 57% female with a mean age of 47.2 years.

  Study phs000438

• 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

• Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE)

  The goal of this study was to identify SNPs and CNPs that are associated with development of normal tissue toxicities resulting from radiotherapy for prostate cancer. The study population includes approximately 1,400 men treated with brachytherapy, external beam radiation therapy, or a combination of the two treatments, and assessed for adverse effects at baseline and following radiotherapy. Three toxicity endpoints were investigated using a two-stage GWAS approach: urinary morbidity, rectal bleeding and erectile dysfunction. The study sample was split into a discovery set (N=367) and a replication set (N=417), and an additional 647 samples, which were not part of this original cohort, were also included as an independent replication set. The replication set was developed via collaboration developed under the framework of the Radiogenomics Consortium (RGC). The long-term goal of this project, and other radiogenomics projects lead by the RGC, is two-fold: 1) Develop an assay capable of predicting which cancer patients are most likely to develop radiation injuries resulting from treatment with a standard RT protocol, and 2) Obtain information to assist with the elucidation of the molecular pathways responsible for radiation-induced normal tissue toxicities. These studies focus on multiple cancer types including prostate, breast, lung, and head and neck cancers.

  Study phs000772

• Joslin Study on the Genetics of Type 2 Diabetes

  Between 1993 and 2003, families were recruited in the Joslin Study on the Genetics of Type 2 Diabetes for the presence of an autosomal dominant mode of inheritance of diabetes. Recruiting and screening of families occurred through probands who were receiving medical care at the Joslin Clinic (Boston, MA). Screening of families included 1) a proband and at least one sibling with type 2 diabetes, 2) diabetes occurring in at least three generations, 3) diabetes inherited on one side of the prospective family. Probands had to have a diabetes diagnosis between the age range from 10 to 60 years. Demographic data, clinical data, and family history were collected from participating family members, along with blood and urine samples. This study includes genetic and phenotypic data from one family examined in Simeone, Wilkerson, et. al. (NPJ Genomic Medicine 2022, PMID: 35869090). Genotype data for 14 family members and whole genome sequencing data for 6 individuals were generated with the goal of identifying a potential genetic cause of disease in this family. To de-identify this family and protect confidentiality, information on sex in phenotype data and variants identified in X, Y, and MT chromosomes have been removed in compliance with IRB guidelines.

  Study phs002959

• Multicenter AIDS Cohort Study (MACS)

  The Multicenter AIDS Cohort Study (MACS) - now part of the MACS-WIHS Combined Cohort Study (MWCCS) investigates the epidemiology of human immunodeficiency virus (HIV) infection among men who have sex with men. Over 7,000 participants volunteered for semiannual interview, physical examination, and laboratory testing across the 325 years of the study, in four metropolitan areas of Los Angeles, Chicago, Baltimore/Washington (DC) and Pittsburgh. The study aimed to identify risk factors for occurrence and clinical expression of the HIV infection, and to establish a repository of biologic specimens for future study. Study visits included detailed questions covering HIV-related symptoms and utilization of health services, demographic and psychosocial characteristics, a quality of life survey, a physical examination, a detailed form on medications used as prophylaxis and/or treatment, a neuropsychological screening and examination, blood samples to do measure hematologic variables including enumeration of T-cell subsets and HIV viral load and evaluate genetic risk factors via genome wide association studies using data generated using the Infinium Multi-Ethnic Global BeadChip genotyping array in all participants. Men who have sex with men, with and without HIV infection were enrolled in the MACS. MACS data continues to be available through the merged MWCCS cohort.

  Study phs002226

• CIP: Obesity-Diabetes Familial Risk, Viva La Familia Study

  The VIVA LA FAMILIA Study was designed to identify genetic variants influencing childhood obesity and its comorbidities in the Hispanic population. Family recruitment and phenotyping were conducted in 2000-2005 in Houston, TX. All enrolled children (n=1030) and parents gave written informed consent or assent. The protocol was approved by the Institutional Review Boards for Human Subject Research for Baylor College of Medicine and Affiliated Hospitals and for Texas Biomedical Research Institute. The VIVA LA FAMILIA study design and methodology have been described in detail (Butte NF, 2006). Each family was ascertained on an obese proband, defined as a BMI > 95th percentile, between the ages 4-19 y. The cross-sectional, longitudinal study design consisted of baseline measurements, with a one-year. GWAS was performed using the Illumina HumanOmni1 v1.0 BeadChips on 815 children from 263 Hispanic families and HumanOmni 2.5-8v1 on an additional 43 children. Exome sequencing is being performed on 822 children using NimbleGen capture, followed by Illumina DNA sequencing. Butte NF, Cai G, Cole SA, Comuzzie AG. Viva la Familia Study: genetic and environmental contributions to childhood obesity and its comorbidities in Hispanic population. Am J Clin Nutr 2006;84(3):646-54. PMID: 16960181

  Study phs000616

• Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

  The study is a retrospective transcriptomic profiling of oropharyngeal squamous cell carcinoma. The pathologic database was queried for squamous cell carcinoma tumors originating from the anatomic oropharynx (tonsil or tongue base) with available samples from surgical archives. This retrospective RNA sequencing cohort included cases dating prior to the routine implementation of p16 immunohistochemistry (IHC) testing at our institution, therefore, p16 status was not required for inclusion in this study. Formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center (LCCC) Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer's protocol (Promega 9FB167). After a pathology review of a hematoxylin and eosin (H&E) stained slides to identify tumor area, RNA was extracted from unstained slides using macrodissection. Total RNA quality was measured using a NanoDrop spectrophotometer (Thermo Scientific ND-2000C) and a TapeStation 4200 (Agilent G2991AA). Total RNA concentration was quantified using a Qubit 3.0 fluorometer (Life Technologies Q33216). Libraries were prepared with Illumina TruSeq Stranded Total RNA with Ribo-Zero protocol. Libraries were sequenced on an Illumina HiSeq2500 sequencer. Paired end read data, with read lengths of 75 were collected.

  Study phs002935

• Genomic Studies of Gilles de la Tourette Syndrome

  This study consists of three components. The first component includes genome-wide association study (GWAS) data on 695 TS cases and 198 ancestry matched controls from the first TS GWAS of 1285 TS cases and 4964 ancestry matched controls. The second component includes genome-wide association study (GWAS) data on 2106 TS cases from the second TS GWAS of 2716 TS cases and 3762 ancestry matched controls. The third component consists of 438 individuals representing 146 probands with DSM-IV-TR diagnosed Tourette Syndrome and their parents (146 complete parent-offspring trios). These individuals are part of the whole exome sequencing study, aiming to use whole exome sequencing of TS parent-offspring to identify de novo protein-truncating variants (PTVs) that are present in the child with TS but not in either parent. All subjects were collected by the Tourette Association of America International Consortium for Genetics (TAAICG) at seven sites in the United States and Canada. Both affected individuals and unaffected relatives were assessed for the presence of Tourette Syndrome and Chronic (Persistent) Tic Disorder (CTD) using a standardized, semi-structured interview, which has high clinical validity and reliability for the diagnoses of TS and CTD (TSAICG, Am J Hum Genet, 2007 (PMID: 17304708)); Darrow et al., Psychiatric Research, 2015 (PMID: 26054936)).

  Study phs001380

• NIDDK IBD Genetics Consortium Repository Immunochip

  The Immunochip is a custom Illumina Infinium chip comprising 196,524 SNPs and small indels selected primarily based on GWAS analysis of 12 autoimmune and inflammatory diseases. The chip has two purposes: fine mapping of 289 established associations corresponding to 187 distinct loci, and deep replication of suggestive, but not yet proven, associations. Fine-mapping regions were defined as 0.2cM centered on GWAS hit SNPs, and all SNPs and short indels in these regions from the 1000 Genomes Project low coverage pilot CEU samples, as well as variants discovered in resequencing experiments conducted by groups collaborating in the chip design were selected for inclusion. Replication of autoimmune and inflammatory GWAS (including Crohn's disease and ulcerative colitis) contributed the bulk of the remaining SNP lists. Approximately 25,000 SNPs were included as replication of unrelated diseases as part of the WTCCC2 project, which serve as useful null SNPs for these analyses. In total, approximately 240,000 SNPs were selected for inclusion, with an assay design success rate of ~80%. Reprinted from Jostins et al. (2012), with permission from Springer Nature (see https://www.nature.com/reprints/permission-requests.html). Jostins, L., et al. (2012) Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature, 491, 119-24. PMID: 23128233.

  Study phs001721

• Germline hypomorphic CARD11 mutations in severe atopic disease

  We described five patients from four unrelated families who had severe atopic dermatitis and susceptibility to mild skin viral infections. Some patients also exhibited other allergic symptoms such as asthma and food allergy. We performed targeted sequencing for affected patients A-I of family A and B-I of family B, whole exome sequencing for D-I, D-II.1 and healthy mother D-II.3 of family D, and whole genome sequencing for C-I and healthy mother C-II.2 of family C. We identified three different novel damaging missense mutations of CARD11 (GeneID:84433) in patients A-I (L194P), B-I (R975W), and C-I (E57D). In patients D-I and D-II.1, a dup183_196 (p.K196_V197insMKEERDSYNDELVK) mutation was found in the coil-coil domain of the protein. These mutations act as dominant negatives impeding the scaffolding function of the wild type protein, which leads to downstream NF-kB and mTORC1 signaling defects after TCR stimulation. Sanger sequencing later identified the corresponding CARD11 mutations in the affected family members (C-II.1, D-II.2) that are not included in the dbGaP submission. Hypomorphic CARD11 dominant negative mutants are novel causes of severe atopic disease.

  Study phs001369

• NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells

  Implement an efficient, highly reproducible and 'scalable' system for the production of large numbers of sickle cell anemia-specific iPS cells (iPSC). Derive and characterize a novel, in vitro system for the production of an unlimited supply of erythroid lineage cells from the directed differentiation of 'clinical grade' transgene-free iPS cells; use this system to recapitulate erythroid-lineage ontogeny in vitro with the sequential development of primitive and definitive erythropoiesis, accompanied by the appropriate expression of stage-specific globin genes. Identify developmental gene expression profile differences between erythroid precursors that produce primarily HbF and those that produce primarily HbA or HbS. Determine the effects of the three known HbF major quantitative trait loci (QTL) on globin gene expression in disease-specific iPS cells during in vitro erythropoiesis. Search for novel HbF genetic modifiers associated with markedly elevated HbF levels found in sickle cell anemia patients naturally, or in response to hydroxyurea treatment, by examining gene expression profiles and mRNA sequence of their iPSC-derived erythroid cells. Develop and use a CRISPR-based gene editing platform to study the effect of novel HbF genetic modifiers, explore globin switching, and correct the HbS mutation in sickle iPSC lines.

  Study phs001212

• Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

  This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

  Study phs002321

• A Large Data Resource of Genomic Copy Number Variation across Neurodevelopmental Disorders

  This study presents the first genome-wide copy number variation (CNV) analysis across autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), and obsessive-compulsive disorder (OCD). A total of 2,691 subjects diagnosed with a neurodevelopmental disorder (NDD), and a total of 1,769 unaffected family members from Ontario, Canada were assayed using the Affymetrix CytoScan HD array. We identified rare CNVs, (< 0.1% frequency in 10,851 population control samples), and found clinically relevant CNVs in 10.5% of total subjects. Among all NDD subjects, we identified 17 (0.63%) with aneuploidies and 115 (4.3%) with known genomic disorder variants. We searched further for genes impacted by different CNVs in multiple disorders. Examples of NDD-associated genes linked across more than one disorder (listed in order of occurrence) are NRXN1, SEH1L, LDLRAD4, GNAL, GNG13, MKRN1, DCTN2, KNDC1, PCMTD2, KIF5A, SYNM, and long non-coding RNAs: AK127244, NRON, and PTCHD1-AS. We demonstrated that identical CNVs or genes could potentially contribute to the etiology of multiple NDDs. The CNVs identified will serve as a useful resource for both research and diagnostic laboratories for prioritization of variants and clinical interpretations.CNV data from this study are available through dbVar at https://www.ncbi.nlm.nih.gov/dbvar/studies/nstd173/.

  Study phs001881

• Genetic Predictors of Ibrutinib-Related Cardiovascular Side Effects in Patients with Chronic Lymphocytic Leukemia

  The goal of this study was to identify genetic polymorphisms associated with ibrutinib-related cardiovascular side effects (CVSEs). This is an observational non-interventional pharmacogenomic study of 50 patients with newly diagnosed or relapsed refractory chronic lymphocytic leukemia (NDCLL or RRCLL) receiving ibrutinib 420 mg for at least six months. The ibrutinib-related CVSEs included atrial fibrillation and hypertension, which occurred in 20% of patients. DNA obtained from buccal swabs was genotyped for 40 single nucleotide polymorphisms (SNPs) in GATA4, SGK1, KCNQ1, KCNA5, NPPA, and SCN5A using a customized next generation sequencing panel. It was found that GATA4 rs804280 AA (P =.043), KCNQ1 rs163182 GG (P =.036) and KCNQ1 rs2237895 AA (P =.023) were associated with the ibrutinib-related CVSEs. Patients with a high-risk score had at least two of the three significant risk genotypes identified in univariate analysis for GATA4 rs804280 A>C, KCNQ1 rs162182 G>C and KCNQ1 rs2237895 A>C, and patients with a low-risk score had either one or none of these genotypes. In multivariate analysis, 18 patients with at least two of the three high-risk genotypes had an 11.5-fold higher odds of CVSEs (P =.019; 1.79-119.73 at 95% CI).

  Study phs003370

• Genomics and Epigenomics of the Elderly Response to Pneumococcal Vaccines

  Pneumococcal Vaccine Study: This is a study designed to develop a detailed transcriptional and cellular profile of the immune response to pneumococcal vaccination with conjugated and non-conjugated polysaccharide vaccines in the senescent immune system of older adults. In this study, 39 healthy adults ages 60 and older that have never received pneumococcal vaccination, have been randomized to receive Prevnar 13 (Pfizer), a conjugated 13-valent vaccine or Pneumovax 23 (Merck), a non-conjugated 23-valent vaccine. Four (4) study visits occurred over 70 days at Day -7 (baseline), day 1, day 10 and day 60 (± 5d) post vaccination.Bulk RNA-sequencing data are available on the 4 time points for 31 of the participants and 1 replicate. ATAC-Doublet Detector Study: We generated single nucleus ATAC-seq (snATAC-seq) data from PBMCs of 2 baseline blood samples from the pneumococcal study. Generated data was then used to benchmark a novel computational method for detecting multiplets in snATAC-seq data, namely, AMULET (https://github.com/UcarLab/AMULET). Multiplets confound downstream analyses by introducing combined epigenomic profiles from 2 or more cells/nuclei. AMULET detects multiplets by using unique snATAC-seq data features that allow it to reliably use read counts to detect multiplets for their removal from data analyses.

  Study phs002361

• Gene Expression and Biomarker Utility in Post-Mortem Samples

  The FAA Functional Genomics Team examined the feasibility of analyzing gene expression profiles using post-mortem brain, lung, muscle, and blood samples collected from aviation accident fatalities, with the goal of validating post-mortem extracted RNA for use in RNA sequencing. We compared the RNA sequencing results obtained from THC-positive and THC-negative samples to determine whether RNA sequencing on samples collected from aviation accident fatalities was possible and if any differences in gene expression associated with THC consumption were detectable post-mortem. The study population included 57 males of indeterminant age who perished in general aviation accidents and for whom post-mortem toxicological testing identified delta-9-THC or its primary or secondary metabolites, as well as negative controls. We determined that RNA sequencing on post-mortem aviation accident fatality samples is possible, and further identified genes showing differential expression in lung and muscle between THC-positive and THC-negative samples. We conclude that post-mortem tissue samples collected from aviation accident fatalities are suitable for gene expression profiling, but caution researchers that such samples have low RNA integrity numbers and some degree of microbial contamination is both probable and to be expected. Raw sequencing files (.fastq) from this study are available in dbGaP.

  Study phs003546

• Germline Mutations and Developmental Mosaicism Underlying EGFR-Mutant Lung Cancer

  We designed this study to examine the etiology of multiple lung tumors in EGFR-mutant non-small cell lung cancer patients who undergo surgical resection. Participants were 52-85 years old never or former smokers, who had at least 2 surgical lung tumor pathology specimens available in the Massachusetts General Hospital biobank, at least one of which had an EGFR mutation by routine clinical genotyping. 10 patients were selected, along with two patients from a family with an inherited EGFR-T790M mutation leading to multiple lung tumors. These patient tumor samples and matched normal lung samples were microdissected to collect DNA.In addition to obtaining clinical histories, we performed whole exome sequencing to evaluate the genetic profile of matched tumor and normal samples. The WES data are available on dbGaP. Our data showed increasing mutational burden and copy number alteration with increasing invasiveness, as compared to normal tissues, for the subset of samples that were assessed for tumor invasiveness. We also observed a range of numbers of shared mutations between tumors in a single patient, indicating different degrees of relatedness between lung tumors. We hope that this resource will help researchers understand non-small cell lung cancer presentations with multiple lung tumors. These data may aid in clinical decision making for such patients.

  Study phs003379

• Cardiovascular Health Study (CHS) - Imaging

  The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of coronary heart disease (CHD) and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication, and mortality.

  Study phs003639

• NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC)

  Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative.

  Study phs001211

• Melanoma Genome Sequencing Project

  Melanoma is the most prevalent cause of skin cancer morbidity and mortality. In order to characterize the full range of somatic mutations that may drive the growth of melanoma, we are sequencing tumor and normal DNA from a set of roughly 150 melanomas. For the majority of samples (approximately 90% of the cases), mutations in protein coding genes will be assessed in the exonic DNA of tumor-normal pairs using hybrid capture and paired-end DNA sequencing. For a few of DNA samples (approximately 10% of the cases), the entire genomes will be analyzed to assess the possible contribution of complex structural rearrangements contributing to oncogenesis. The sequencing data are supplemented by copy number profiling on the same tumors using high-density SNP arrays. Integration of these approaches will enable the unbiased and comprehensive characterization of both known and novel recurrent DNA alterations that arise in melanoma.Versions 1-4 contain whole exome and bulk RNA sequencing data for patients with melanoma.Version 5 - We compared somatic genomic profiles from matched pre-treatment and post-resistance tumor biopsies in patients with metastatic melanoma who exhibited heterogeneous responses to immune checkpoint inhibitors (ICIs). This version includes whole exome sequencing (WES) data from 14 patients.

  Study phs000452

• National Cancer Institute (NCI) Early Onset Malignancies Initiative (EOMI): Molecular profiling of Breast, Colon, Kidney, Liver, Multiple Myeloma, and Prostate among Racially and Ethnically Diverse Populations

  The Early Onset Malignancies Initiative (EOMI) is focused on collecting specimens from racially and ethnically diverse population groups with six different types of cancer (breast, prostate, colon, liver, kidney, and multiple myeloma). This initiative is a partnership between the Center for Research Strategy, the Center for Cancer Genomics and the Division of Cancer (DCP). DCP's NCI Community Oncology Research Program (NCORP) is a critical partner. The acquisition of the cancer and matching normal biospecimens in this initiative are from newly diagnosed early onset cancer patients who identify as Non-Hispanic Black, Hispanic, American Indian or Alaska Native, or Non-Hispanic White. The Minority/Underserved NCORPs sites will collect the samples for this project. By carrying out this initiative in the NCORP's national network of investigators, cancer care providers, and research institutions, the EOMI will harness the community-based partnerships to improve participation among these racial/ethnic groups. The NCORP investigators, as participants in NCI's clinical trials network, will annotate the biologic samples with clinical information that will enhance the ability to answer questions about molecular determinants of early disease, treatment response, and/or prognosis. The EOMI will be a step forward in addressing racial/ethnic disparities and in understanding cancer in underserved populations.

  Study phs001952

• Rapid detection of expanded short tandem repeats in personal genomics using hybrid sequencing.

  Long expansions of short tandem repeats (STRs); i.e., DNA repeats of 2-6 nucleotides, are associated with some genetic diseases. Cost-efficient high throughput sequencing can quickly produce billions of short reads that would be useful for uncovering disease-associated STRs. However, enumerating STRs in short reads remains largely unexplored because of the difficulty in elucidating STRs much longer than 100 bp, the typical length of short reads. We propose ab initio procedures for sensing and locating long STRs promptly by utilizing the frequency distribution of all STRs and paired-end read information. We validated the reproducibility of this method using biological replicates and used it to locate an STR associated with a brain disease (SCA31). Subsequently, we sequenced this STR site in eleven SCA31 samples using SMRT? sequencing (Pacific Biosciences), determined 2.3-3.1 kb sequences at nucleotide resolution, and revealed that (TGGAA)- and (TAAAATAGAA)-repeat expansions determined the instability of the repeat expansions associated with SCA31. Our method could also identify common STRs, (AAAG)- and (AAAAG)-repeat expansions, which are remarkably expanded at four positions in an SCA31 sample. This is the first proposed method for rapidly finding disease-associated long STRs in personal genomes using hybrid sequencing of short and long reads.

  Study JGAS000002

• Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

  The standard treatment for stage III colorectal cancer (CRC) is surgery, followed by adjuvant chemotherapy (AC). However, the efficacy of AC is limited, and approximately 30% of patients experience recurrence. Therefore, easily assessable molecular biomarkers that can predict response to AC are needed. Here, we aimed to identify predictive biomarkers of response to AC using tumor transcriptomic data. Tumor specimens from 253 patients who underwent surgery for stage III CRC between 1997 and 2019 were analyzed using RNA sequencing. Transcriptional subtyping and analyses of gut microbiome, immune cell fractions, and T-cell receptor (TCR) were performed to identify factors associated with recurrence-free survival (RFS) in patients treated with or without AC. Of 253 patients, 118 (46.6%) received AC. Twenty phyla and 799 species of the microbiomes were identified, among which Fusobacteria were identified in 247 patients (97.6%). Multivariable Cox proportional hazards regression analysis of patients who received AC showed that intratumoral Fusobacterium and M1 macrophage abundance and diversity of TCR alpha and delta (TRAD) were independently associated with RFS. Fusobacterium and M1 macrophage abundance, and TRAD diversity were associated with the response to AC, suggesting that these factors could serve as biomarkers for personalized treatment in stage III CRC.

  Study JGAS000875

• Molecular characteristics in Burkitt lymphoma over age groups

  Treatment optimization has improved the overall survival in Burkitt lymphoma (BL) patients but there are still relevant outcome differences between pediatric and adult patients. In both age groups survival remains poor for patients who suffer relapse. Therefore, new treatment approaches are warranted to improve survival. Thus, we conducted a comparative study in the largest pediatric cohort to date including 191 cases and 97 samples from adult patients and analyzed the mutational landscape. We detected overlapping molecular profiles but also significant differences in the mutational pattern. Samples from pediatric patients show a higher frequency of mutations in ID3, DDX3X and BAF-complex components ARID1A and SMARCA4, while YY1AP1 and BCL2 are more frequently mutated in cases from adult BL patients. Correlation of the mutational profile with clinical data was available for the pediatric cohort and identified TP53 mutations to be highly significantly associated with the incidence of relapse thus identifying the first molecular marker to be associated with the incidence of relapse in pediatric BL. As the hotspot analysis of TP53 mutations showed mostly gain of function mutations, it is tempting to speculate that drugs decreasing the amount of malignant TP53 or increase the abundance of wildtype TP53 could be a promising approach for future treatment regimens to further improve prognosis.

  Study EGAS00001005270

• Genentech Colon Cancer Screen

  Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.

  Study EGAS00001000288

• Allele Balance Bias Identifies Systematic Genotyping Errors and False Disease Associations

  In recent years, Next Generation Sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the allele balance distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies (RVAS).

  Study EGAS00001003027

• 3D tissue engineered human skeletal muscle modelling Facioscapulohumeral Muscular Dystrophy

  acioscapulohumeral muscular dystrophy (FSHD) is caused by sporadic misexpression of the transcription factor double homeobox 4 (DUX4) in skeletal muscles. So far, monolayer cultures and animal models have been used to study the FSHD disease mechanism and for FSHD therapy development, but these models do not fully recapitulate the disease and there is a lack of knowledge on how DUX4 misexpression leads to skeletal muscle dysfunction. To overcome these barriers, we have developed a 3D tissue engineered skeletal muscle (3D-TESM) model by generating genetically matched myogenic progenitors (MPs) from human induced pluripotent stem cells of three mosaic FSHD patients. 3D-TESMs derived from genetically affected MPs recapitulate pathological features including DUX4 and DUX4 target gene expression, smaller myofiber diameters, and reduced absolute forces upon electrical stimulation. RNA sequencing data illustrates increased expression of DUX4 target genes in 3D-TESMs compared to 2D myotubes, and cellular differentiation was improved by 3D culture conditions. Treatment of 3D-TESMs with small molecules identified in drug development screens in 2D muscle culture showed no improvements in contractile force and sarcomere organization, highlighting the potential benefit of 3D-TESMs for preclinical drug potency screening by eliminating false-positive compounds for FSHD research and drug development.

  Study EGAS50000000502

• Developmental_Dysplasia_of_the_Hip__DDH_

  The National Joint Registry for England and Wales (NJR) has become established as one of the largest repositories of clinical information about patients undergoing hip and knee replacement. The primary aim of this proposal is to examine the feasibility of adding value to that clinical information by partnering it with a DNA dataset to allow its use to be extended to the study of the underlying pathogenesis of diseases of the hip and knee, and the complications of their treatment. We will do this 1) by establishing a mechanism for accessing and linking pseudo-anonymised demographic and phenotype data between the NJR database and the proposed DNA Biobank; 2) by validating the collection of postal DNA samples from consenting NJR patients; and 3) by genotyping genome-wide 900 patients with the condition developmental dysplasia of the hip (DDH) to find variants that play a role in this heritable condition. The successful demonstration that the NJR can be used to establish a DNA Biobank will provide a powerful platform to examine the genetic basis for a wide range of joint diseases, and the complications of their treatment. This proposal is to carry out the genotyping portion of this project on the current CoreExome array

  Study EGAS00001000916

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• Whole genome sequencing of tumour and normal paired samples of diffuse intrinsic pontine gliomas

  Diffuse intrinsic pontine glioma (DIPG) have a universally dismal prognosis (median 9-12 months), with neither chemotherapeutic nor targeted agents showing any substantial survival benefit in clinical trials in children with these tumours. DIPG are highly infiltrative malignant glial neoplasms of the ventral pons, which due to their location within the brain, make them unsuitable for surgical resection and consequently have a universally dismal clinical outcome. Recent high-throughput sequencing approaches have revealed a striking prevalence of K27M mutations in the genes encoding the histone variants H3.3 (H3F3A) or H3.1 (HIST1H3B) in the childhood brain tumour DIPG. This K-to-M substitution confers a trans-dominant ablation of global H3K27 trimethylation, which likely profoundly alters gene expression through de-repression of polycomb repressive complex 2 (PRC2) target genes. Despite these advances in our understanding of the distinct biology of these tumours, approaches for specific novel therapeutic interventions are not clear, and little has been reported of the secondary mutations accompanying these changes. We carried out whole genome sequencing on a series of 20 tumour normal pairs of pre-treatment biopsy samples of DIPG, for which the patients underwent a safe stereotactic procedure, and whole exome sequencing on a further six tumour normal pairs obtained at autopsy.

  Study EGAS00001000572

• Recurrent intra-tumour heterogeneity is a hallmark of metastatic prostate cancer

  The evolution of cancers from low grade to metastatic disease is a major determinant of cancer mortality. Cancer evolution involves a complex interplay between cell intrinsic genetics and transcriptional alterations and the extrinsic microenvironment. To define the key mechanisms underpinning metastatic development, we focused on the most lethal form of prostate cancer, metastatic castration-resistant prostate cancer, and employed single-cell multi-omics and whole-genome sequencing to deeply profile 34 metastatic lesions from 9 patients obtained from rapid autopsy. We found that intra-tumour heterogeneity is an indicator of key evolutionary processes, characterised by recurrent tumour populations acting as critical functional components of the tumour ecosystem, irrespective of clonal and microenvironmental backgrounds. Unexpectedly, microenvironments across metastatic sites played a limited role while clonal evolution primarily promoted transcriptional noise. Intra-patient functional convergence of tumour ecosystems was observed across metastatic sites, pointing towards system-level selection pressures that drive the heterogeneity landscape of mCRPC. Our findings reveal functional evolutionary convergence of metastatic disease into units of intra-tumour heterogeneity identifying critical determinants of metastatic progression for therapeutic targeting. Note: matched WGS for some tumour single-cell experiments, as well as germline WGS for patients CA0027, CA0034, CA0035, CA0043, and CA0076, can be found in EGAS00001006598.

  Study EGAS50000001312

• The evolutionary trajectory of a highly recurrent paediatric high grade neuroepithelial tumour with MN1:BEND2 fusion

  Astroblastomas are rare brain tumours which predominate in children and young adults, and have a controversial claim as a distinct entity, with no established WHO grade. Reports suggest a better outcome than high grade gliomas, though they frequently recur. Recently, they have been described to overlap with a newly-discovered group of tumours described as ’high grade neuroepithelial tumour with MN1 alteration’ (CNS HGNET-MN1), defined by global methylation patterns and strongly associated with gene fusions targeting MN1. We have studied a unique case of astroblastoma arising in a 6 year old girl, with multiple recurrences over a period of 10 years, with the pathognomonic MN1:BEND2 fusion. Exome sequencing allowed for a phylogenetic reconstruction of tumour evolution, which when integrated with clinical, pathological and radiological data provide for a thorough understanding of disease progression, with initial treatment driving tumour dissemination along four distinct trajectories. Infiltration of distant sites was associated with a later genome doubling, whilst there was evidence of convergent evolution of different lesions acquiring distinct alterations targeting NF-κB. These data represent an usual opportunity to understand the evolutionary history of a highly recurrent childhood brain tumour, and provide novel therapeutic targets for astroblastoma / CNS HGNET-MN1.

  Study EGAS00001002432

• UK10K_RARE_NEUROMUSCULAR

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The neuromuscular disorder samples are part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Francesco Muntoni (f.muntoni@ucl.ac.uk).

  Study EGAS00001000101

• UK10K_RARE_FIND

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Raymond samples will be part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Lucy Raymond (flr24@cam.ac.uk).

  Study EGAS00001000128

• UK10K_RARE_CILIOPATHIES

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Ciliopathies samples will be part of the rare disease group, and will undergo exome sequencing. For further information with regard to this cohort please contact Phil Beales (p.beales@ich.ucl.ac.uk).

  Study EGAS00001000126

• UK10K_RARE_SIR

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes.Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The SIR (Severe Insulin Resistance) samples are part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Robert Semple (rks16@cam.ac.uk).

  Study EGAS00001000130

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR02

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Paired DNA samples – isolated from the tumour tissue and from the blood of fifty six patients – have been analyzed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored.Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumour tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Exome capture and deep resequencing are being performed at the National Institute of Biomedical Genomics, Kalyani. We have analyzed the exomes of paired blood and tumour DNA samples using exome capture by Illumina TrueSeq Exome Enrichment kit followed by sequencing on Illumina HiSeq-2000. Each exome is being sequenced at a mean depth of 70x for Tumour and 40x for Blood. In addition, we have used Illumina Omni 2.5 SNP-chips to generate genotype data.

  Study EGAS00001001028

• CRUK-ICGC Prostate Cancer Group Study

  Prostate cancer somatic genomic sequencing data generated from 2011 onwards under auspices of the International Cancer Genome Consortium Prostate Cancer UK consortium (CRUK-ICGC Prostate Group), co-led by Colin Cooper and Ros Eeles, with other Principal Investigators (Brewer, Neal, Bova, McDermott, Wedge, Lynch, Massie, and Foster) and others as listed in study publications. Funded by Cancer Research UK and other funders as listed in study publications. Contents and publications related to each dataset are described with each dataset (EGAD) entry. Our study was funded with the ambition of collecting Whole Genome DNA sequence data from 250 prostate cancers, with matching transcriptome and methylome data. The original aims of the project were: 1.To understand the significance of multifocal prostate cancer. 2.To understand the clinical heterogeneity of prostate cancer to devise markers for predicting outcome and for drug targeting. 3.To understand the molecular basis of development and spread of castration-resistant and metastatic disease 4.To understand the aetiology of prostate cancer particularly the large variation in incidences that occur in different populations and ethnic groups. Please see https://doi.org/10.5281/zenodo.4022439 for links between sample IDs reported in literature and EGA IDs.

  Study EGAS00001000262

• Identifying New Genetic Subtypes in Follicular Lymphoma

  Follicular lymphoma (FL) exhibits considerable variability in biological features and clinical trajectories across patients. To dissect the diversity of FL, we utilized a Bernoulli mixture model to identify genetic subtypes in 713 pre-treatment tumor tissue samples. Our analysis revealed the existence of five subtypes with unique genetic profiles that correlated with clinicopathological characteristics. The clusters were enriched in specific mutations as follows: CS (CREBBP and STAT6), TT (TNFAIP3 and TP53), GM (GNA13 and MEF2B), Q (quiescent, for low mutation burden), and AR (mutations of mTOR pathway-related genes). The subtype Q was enriched for patients with stage I disease and was associated with a lower proliferative history compared to the other subtypes. The AR subtype was unique in its enrichment for IgM-expressing FL cases and was associated with advanced-stage and more than 4 nodal sites. The existence of subtypes was validated in an independent cohort of 418 samples from the GALLIUM trial. Notably, patients assigned to the TT subtype consistently experienced inferior progression-free survival when treated with immunochemotherapy. Collectively, our findings offer insight into core pathways distinctly linked with each FL cluster and are expected to be informative in the era of targeted therapies.

  Study EGAS50000000435

• Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is the leading cause of death from gynecological cancers worldwide. No effective screening methods exist, and tumors are commonly detected at advanced stages where treatment is much less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we detected ovarian cancer with high specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach distinguished benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Study EGAS50000000484

• Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

  In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

  Study EGAS50000000701

• Exploring the role of mtDNA variation in Multiple Sclerosis in a large cohort of discordant monozygotic twins

  Several lines of evidence indicate that mitochondrial DNA (mtDNA) variants might predispose to multiple sclerosis (MS). We examined this in 49 monozygotic (MZ) twin pairs clinically discordant for MS at study entry. Since the nuclear DNA of MZ twins is identical, our study provides a unique setting to functionally associate unique mtDNA variants and skewed heteroplasmy with MS development. In order to identify mtDNA variants in the twin cohort, we deeply sequenced the mitochondrial genome in blood of all 49 MZ twin pairs using next generation sequencing (Illumina, HiSeq or MiSeq) with an average coverage depth of ~25,000 sequences per base. Heteroplasmic variants were validated using targeted deep sequencing (TDS) (Illumina, MiSeq) in DNA isolated from blood and buccal swabs. In addition, whole blood was also available of 5 additional MS-affected or healthy siblings and 1 dizygotic twin pair discordant for MS, comprising in total 6 non-identical sib pairs. Moreover, all cases were screened for pathogenic mtDNA polymerase gamma (POLG) mutations. The data provides valuable insights in the possible involvement of mtDNA variants in the pathogenesis of MS, and gives information on the segregation of heteroplasmic variants within MZ twins and non-identical siblings and across different tissues.

  Study EGAS00001001240

• Single cell sequencing of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis

  The quantity of tumor infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival particularly in triple negative and HER2-overexpressing BC subtypes. Whilst T cells are the predominant TIL population, the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6311 T cells isolated from human BCs, and show for the first time that significant heterogeneity exists in the infiltrating T cell population. We demonstrated that high TIL BCs contained significant numbers of CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple negative breast cancer (TNBC) and provided better prognostication compared with CD8 expression alone. Our data suggests that CD8+ TRM contribute to BC immunosurveillance and are the key targets of modulation through immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.

  Study EGAS00001002845

• The Prediction and Prevention of Preeclampsia

  The Prediction and Prevention of Preeclampsia (PREDO) is a prospective birth cohort study of Finnish women who were pregnant between 2005 and 2010 and their children. The PREDO study cohort was set up to identify novel risk factors and biomarkers in pregnant women associated with the development of preeclampsia and intrauterine growth restriction (IUGR). Two groups of pregnant women were enrolled during the first trimester of their pregnancy: first, pregnant women with a known clinical risk factor status for preeclampsia and IUGR (N=1079; 969 of these women had at least one and 110 had none of the known risk factors for preeclampsia and IUGR), and second, pregnant women who volunteered to participate regardless of their risk factor status for preeclampsia and IUGR (N=3698). Both samples were monitored during pregnancy with four clinical visits and bi-weekly self-reports. The post-delivery follow-up has taken place at approximately 2 weeks, 6 months, and 3.5 years after the delivery. The most recent follow-up started in 2016 and is ongoing. In the high-risk sample, cord blood samples were collected and genome-wide genotyping has been conducted with Illumina OmniExpressExome 1.2 and genome-wide methylation status has been analysed with Illumina 450k HM array.

  Study EGAS00001001898

• Whole Exome Sequencing PPGL

  Whole exome sequencing (WES) libraries were prepared with the SureSelectXT Human All Exon V6+COSMIC target enrichment system (Agilent, 5190-9307) by following kit manufacturer`s instructions. 200 ng of genomic DNA from FFPE tumoral samples and 1 µg from FF or germline samples were used as starting material. SureSelectXT HS (Agilent, G9704A) and SureSelectXT2 (Agilent, G9621A) reagent kits were alternatively used for FFPE derived and good quality samples, respectively. DNAs were fragmented on a Covaris S2 sharing instrument based on initial sample’s integrity. Fragmented DNA samples were processed through subsequent enzymatic treatments of end-repair, dA-tailing, and ligation to Illumina's adapters. Adapter-ligated libraries were PCR amplified with Illumina PE primers and subsequently hybridized to SureSelect Oligo Capture Library Mix. Biotinylated hybrids were captured and the enriched fraction eluted. Libraries were completed by limited-cycle PCR with Illumina TruSeq primers and KAPA HiFi HotStart DNA pol (Roche KK2501). Sample-specific libraries were combined into equimolarly balanced pools and applied to Illumina flow cells for cluster generation. Sequencing was performed on either the Illumina HiSeq2500 or NovaSeq6000 in a paired-end 100bp reads mode to a median target coverage of ~200x and ~100x for tumors and germline, respectively.

  Study EGAS00001006043

• Whole genome sequencing delineates regulatory, structural, and cryptic splice variants in early onset cardiomyopathy

  Cardiomyopathy (CMP) is a heritable disorder. Over 50% cases are gene-elusive on clinical gene panel testing. The contribution of variants in non-coding DNA elements that result in cryptic splicing and regulate gene expression has not been explored. We analyzed whole genome sequencing (WGS) data in a discovery cohort of 209 pediatric CMP patients and 1,953 independent replication genomes and exomes. We searched for protein-coding variants, and non-coding variants predicted to affect the function or expression of genes. Thirty-nine % cases harbored pathogenic coding variants in known CMP genes, and 5% harbored high-risk loss-of-function (LoF) variants in additional candidate CMP genes. Fifteen % harbored high-risk regulatory variants in promoters and enhancers of CMP genes (Odds ratio 2.25, p=6.70×10-7 versus controls). Genes involved in α-dystroglycan glycosylation (FKTN, DTNA) and desmosomal signaling (DSC2, DSG2) were most highly enriched for regulatory variants (Odds ratio 6.7-58.1). Functional effects were confirmed in patient myocardium and reporter assays in human cardiomyocytes, and in zebrafish CRISPR knockouts. We provide strong evidence for the genomic contribution of functionally active variants in new genes and in regulatory elements of known CMP genes to early-onset CMP.

  Study EGAS00001004929

• Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing

  Abstract Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternate RNA-seq methodologies. It is currently unclear how RNA degradation impacts DRS or if it can be corrected for. To assess the impact of RNA integrity on DRS we performed a degradation time-series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than nanopore cDNA-PCR sequencing. Overall, we find samples with RIN > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilised for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in-vivo clinical and post-mortem samples, whilst limiting the confounding effect of degradation on expression quantification.

  Study EGAS00001006542

• FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003508

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• Natural genetic variation of the cardiac transcriptome in non-diseased donors and patients with dilated cardiomyopathy

  Background: Genetic variation is an important determinant of RNA transcription and splicing, which in turn contributes to variation in human traits including cardiovascular diseases.Results: Here we report the first in-depth survey of heart transcriptome variation using RNA-sequencing in 149 (97)* patients with dilated cardiomyopathy and 113 (108)* non-diseased controls. We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls, affecting known as well as novel dilated cardiomyopathy genes. Moreover, we show a widespread effect of genetic variation on the regulation of transcription, isoform usage and allele specific expression. Systematic annotation of genome wide association SNPs identifies 60 functional candidate genes for heart phenotypes, representing 20% of all published heart genome wide association loci. Focusing on the dilated cardiomyopathy phenotype we found that eQTL variants are also enriched for dilated cardiomyopathy genome wide association signals in two independent cohorts.Conclusions: RNA transcription, splicing and allele specific expression are each important determinants of the DCM phenotype and are controlled by genetic factors. Our results represent a powerful resource for the field of cardiovascular genetics. (*) numbers in parentheses represent samples that the publication is based on.

  Study EGAS00001002454

• Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

  Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

  Study EGAS00001006798

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! 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! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal

• DAC - Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  Dac EGAC00001002549

• Data Access Committee for data from EGAS00001002864: Genome analysis of oesophageal cancer and Barretts oesophagus

  Dac EGAC00001000863

• This DAC is to control access to data contained within dataset EGAS00001001147, for Myeloma XI clinical trial patients.

  Dac EGAC00001000307

• Centre for Genomic Regulation - Beta Cell Genome Regulation Lab

  Dac EGAC00001000853

• DAC for Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

  Dac EGAC00001002644

• ITER-FIISC Data Access Committee (microbiome)

  DAC for Metagenomic characterization of tracheal aspirates from non-pulmonary sepsis patients

  Dac EGAC50000000230

• DAC Fondazione Michelangelo

  This is the DAC responsible for granting access to sequencing data generated by Fondazione Michelangelo

  Dac EGAC50000000179

• Uni_Wue_Chair of Microbiology

  Dual RNA seq datasets of M2 sequenced macrophages after chlamydia infection for 30 hours.

  Dac EGAC50000000577

• South African Blood Regulatory (SABR) Resource Committee

  Data access committee for the South African Blood Regulatory (SABR) Resource.

  Dac EGAC50000000501

• OICR-DAC, Ontario Institute for Cancer Research; Biliary Tract Cancer

  Next Gen Sequencing data from Biliary Tract Cancers

  Dac EGAC50000000528

• DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

  Dac EGAC00001003514

• Breast Cancer Association Consortium Data Access Coordinating Committee

  Data access committee for the Breast Cancer Association Consortium (BCAC).

  Dac EGAC50000000824

• Synthetic modeling reveals HOXB genes are critical for the initiation and maintenance of human leukemia

  Study EGAS00001003627

• Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA

  Study EGAS00001003849

• Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Study EGAS00001008218

• Methylation data for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  Study EGAS00001008175

• Molecular Classification of Lymph Node Metastases Subtypes Predict for Survival in Head and Neck Cancer

  Study EGAS00001003233

• The INFORM Precision Medicine Study for High-Risk Pediatric Malignancies

  Study EGAS00001005112

• DNA methylation and Panel sequencing for pancreatic neuroendocrine carcinomas (PanNECs) and pancreatic neuroendocrine tumors (PanNETs)

  Study EGAS00001005731

• Shallow nanopore RNA sequencing enables transcriptome profiling for precision cancer medicine (Hipo_021)

  Study EGAS00001006317

• The genomic diversity of Taiwanese Austronesian groups: implications for the ‘Into and Out of Taiwan’ models

  Study EGAS00001006911

• CLUC complete genomics dataset

  Complete genomics data for VCaP and PC346c.

  Dataset EGAD00001002069

• GFD viral enrichment sequencing

  sequencing of libraires enriched for viral particles

  Dataset EGAD00001007638

• Genome-Wide Association Study of Breast Cancer in the African Diaspora - the ROOT study

  The paucity of data on the genetic epidemiology of breast cancer for racial/ethnic groups other than those of European ancestry hinders the development of innovative interventions to reduce health disparities. Women in the African Diaspora experience a disproportionate burden of pre-menopausal breast cancer in comparison to all other races for reasons that remain unknown and understudied. This higher proportion of early-onset breast cancer might suggest a stronger genetic component in these populations. Genome-wide association studies (GWAS) have revealed several genetic loci that confer risk of breast cancer. Because all GWAS started the discovery stage in women of European ancestry and replicated mainly in women of European ancestry, we propose a novel approach for a GWAS in indigenous African women to identify alleles associated with breast cancer risk which will then be replicated in other populations. This innovative design builds on our current understanding of the etiologic heterogeneity in breast cancer and the distribution of breast cancer molecular subtypes which differ between women of African ancestry and women of European ancestry. The major objective of the proposed studies is to get to the "root" causes of breast cancer by identifying breast cancer risk alleles in a pooled sample of women of African ancestry and to replicate our findings in other populations. To achieve this objective, we conducted a case control study of breast cancer in women of African ancestry, including Africans living in Nigeria, African Americans and African Barbadians. We will genotype ~3800 individuals using the Illumina HumanOmni2.5-Quad platform. We will conduct both standard and novel genetic analyses of the data to map genes associated with breast cancer susceptibility, verify genotyping and carry out fine-mapping studies in genes or regions showing association with breast cancer risk, and replicate in other African American and non-African American populations. By pooling unique resources from studies throughout the African Diaspora, this study has the potential to identify risk alleles in several genes that contribute to increased breast cancer risk and may have implications for early detection, prognosis and treatment of breast cancer in ALL women. This should ultimately lead to improved outcomes for those who suffer a disproportionate burden of early-onset breast cancer.

  Study phs000383

• Cooperative Study of Sickle Cell Disease (CSSCD)

  The Cooperative Study of Sickle Cell Disease was initiated in 1977 to determine the natural history of sickle cell disease (SCD) from birth to death in order to identify those factors contributing to the morbidity and mortality of the disease. Specific objectives included: 1) to study the effect of sickle cell disease on growth and development from birth through adolescence 2) to study the conditions or events that may be related to the onset of painful crises 3) to obtain data on the nature, duration, and outcome of major complications of SCD 4) determine the nature, prevalence, and age- related incidence of organ damage due to SCD, and 5) study the role of SCD and its interaction with selected health events.Phases 2 and 3 of the study involved followup of the infant cohort. A total of 709 infants (age less than 6 months) were enrolled during Phase 1 of the Cooperative Study of Sickle Cell Disease (CSSCD), and Phases 2 and 3 of the CSSCD was designed to follow these children for an additional 10 years. The study objectives included: 1) define prospectively the natural history of sickle cell disease; 2) determine the relationships between cognitive and academic functioning and brain status as determined by MRI; 3) determine the cognitive or behavioral markers of silent infarct; 4) determine the relationship of family functioning on the Family Environment Scale (FES) to brain status, cognitive functioning, and social and demographic factors; 5) continue studies that will enhance the state of knowledge on the influence of sickle cell disease on the psychosocial adjustment of children and adolescents. Phase 2A of the study sought to examine the progression of organ damage in the heart, lung, kidney, and liver in adult cohort patients (born before 1/1/56) enrolled in phase 1 of the study between 3/79 and 5/81. A total of 620 patients from 11 centers were eligible for phase 2A.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 phs002362

• Mayo-Perlegen LEAPS (Linked Efforts to Accelerate Parkinson's Solutions) Collaboration

  We performed a two-tiered, whole-genome association study of Parkinson disease (PD). For tier 1, we individually genotyped 198,345 uniformly spaced and informative single-nucleotide polymorphisms (SNPs) in 443 sibling pairs discordant for PD. For tier 2a, we individually genotyped 1,793 PD-associated SNPs (P<.01 in tier 1) and 300 genomic control SNPs in 332 matched case-unrelated control pairs. We identified 11 SNPs that were associated with PD (P<.01) in both tier 1 and tier 2 samples and had the same direction of effect. For these SNPs, we combined data from the case-unaffected sibling pair (tier 1) and case-unrelated control pair (tier 2) samples and employed a liberalization of the sibling transmission/disequilibrium test to calculate odds ratios, 95% confidence intervals, and P values. A SNP within the semaphorin 5A gene (SEMA5A) had the lowest combined P value (P=7.62E-6). The protein encoded by this gene plays an important role in neurogenesis and in neuronal apoptosis, which is consistent with existing hypotheses regarding PD pathogenesis. A second SNP tagged the PARK11 late-onset PD susceptibility locus (P=1.70E-5). In tier 2b, we also selected for genotyping additional SNPs that were borderline significant (P<.05) in tier 1 but that tested a priori biological and genetic hypotheses regarding susceptibility to PD (n=941 SNPs). In analysis of the combined tier 1 and tier 2b data, the two SNPs with the lowest P values (P=9.07E-6; P=2.96E-5) tagged the PARK10 late-onset PD susceptibility locus. Independent replication across populations will clarify the role of the genomic loci tagged by these SNPs in conferring PD susceptibility. Note: The following instruments were used: 1)clinical assessments form and manual; 2) sibling screening form and manual; 3) unrelated control screening and manual; and 4) risk factors questionnaire and manual. All cases underwent #1, as did sibling controls screening positive (see below). Unrelated controls were not examined. All siblings underwent #2. All unrelated controls underwent #3. All subjects (cases, sibling controls, and unrelated controls) underwent #4. Any publications using the data are to cite the original American Journal of Human Genetics article (Maraganore et al., 2005). Investigators using the data collection instruments are to acknowledge Drs. Maraganore and Rocca, and cite grants ES-10751 and NS-33978.

  Study phs000048