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• Cincinnati Children's Hospital Medical Center (CCHMC) - eMERGE Phase IIIA Data

  This submission includes genotyping or sequencing data from separate cohorts, each is described in separate paragraphs below. Extreme early onset obesity Obesity is a serious epidemic condition and on the rise in the United States. Today, nearly one out of three children is overweight or obese in this country. According to the Center for Disease Control, 35.7% of American adults and 17% of American children are obese. The medical costs associated with obesity are estimated to be in the billions. Without a doubt, interplay of additive genetic effects and common environmental effects influence this complex disease. However, despite being exposed to so-called "obesogenic environment", a large proportion of the population remains of normal weight. These observations suggest that innate, non-environmental, factors make some individuals more susceptible to obesity providing support for biological mechanisms, and thus genetic factors, to underlie the individual's response to the obesogenic environment. In young children with severe obesity the relative role of genetics and in utero programming are likely to outweigh the short duration of environmental and lifestyle exposures. This group is therefore an ideal one to study as they are likely enriched for variants that influence the risk of developing obesity. The purpose of this project is to further study and understand obesity in childhood and to develop a repository of samples for future studies into obesity. Eosinophilic Esophagitis (EoE) Eosinophilic Esophagitis (EoE) is one of the manifestations of eosinophilic gastrointestinal inflammation which have profound effects on a patient's health and development. Results of epidemiologic studies performed through our center demonstrate that eosinophil-associated gastrointestinal disease is not an uncommon entity. While the epidemiology of eosinophilic esophagitis has not been thoroughly studied until recently, there appears to be a significant increase in the diagnosis of EoE in the last decade. Based on our research, this mainly reflects increased disease recognition, but there is also a bona-fide increase in disease incidence which coincides with the increasing incidence of asthma and allergic diseases in the industrialized world. In addition, many patients with intractable symptoms thought in the past to represent atypical GERD or other disorders are now being recognized as having EoE. Diagnosis of EoE requires endoscopy and biopsies to document the characteristic histologic findings of esophageal eosinophilia. In general, this study proposed to elucidate the mechanisms underlying eosinophil growth, survival, migration, and function, and to investigate and further characterize the pathophysiology of, clinical manifestations of, and spectrum of disease severity of eosinophilic esophagitis in humans. The de-identified genotyping and genome wide association data generated as part of this research will be used for further genome research. Familial Sample Repository (FSR) and Directed Sample Repository (DSR) De novo mutations could cause many diseases, which has been demonstrated in mental retardation, autism and many rare genetic disorders. Family-based studies have a variety of advantages over case/control studies, including the elimination of analysis artifacts related to population stratification, the detection of genes that act through a recessive mechanism of inheritance and validation that the trait is not transmitted from a parent, something not possible using a case/control design. Additionally, DNA from families can be used to identify de novo mutations suggesting strong candidate causal polymorphisms. For this project, samples will be collected from families on an on-going basis. Families may be recruited because the patient either has a disease which is thought to be of genetic origin or from the general patient population to serve as controls or future identified diseases. Some phenotypes under study include fibroblastic rheumatism, diaphragmatic hernia, polymicrogyria, severe congenital neutropenia, primary sclerosing cholangitis and staph infection. CLRR-Cincinnati Lupus Registry and Repository Systemic lupus erythematosus (SLE) is a complex, partially understood autoimmune disorder. Genetic origins for SLE are supported by high heritability (> 66%), familial aggregation, increased monozygotic twin concordance, genetic linkages, and candidate gene genetic association, including HLA genes, Fc receptors, and complement components. Relevant environmental factors likely include infections (Epstein-Barr virus), therapeutics, personal habits (smoking), and diet. To continue a research resource facility for collection of well-characterized pedigrees containing a proband with systemic lupus erythematosus we develop this repository. Juvenile Idiopathic Arthritis (JIA) Juvenile Idiopathic Arthritis (JIA) is a debilitating complex genetic disorder characterized by inflammation of the joints and other tissues and shares histopathological features with other autoimmune diseases. It is considered complex genetic traits. There are more than 50,000 children with JIA in the USA, approximately 1 per 1000 births, which is about the same incidence as juvenile diabetes. It is believed that genes in the major histocompatibility complex (MHC) play a role in defining genetic risk, and it can be hypothesized that loci in other chromosomal regions are involved in conferring risk in JIA. These candidate chromosomal regions can be identified using genome-wide association analyses. The long-term goal is a comprehensive understanding of the genetic basis of these disabling arthropathies for which the molecular basis is not presently understood. These data will contribute to a national resource for the study of autoimmunity in children. Better Outcomes for Children-Cytogenetics Since 2007, more than 4000 samples, enriched with various rare or common genetic diseases as well as specific chromosomal abnormalities such as deletions and duplications have been genotyped for the purpose of subsequent GWAS and Phewas analyses and uncovering main genetic effects.

  Study phs001011

• National Cancer Institute (NCI) TARGET: Therapeutically Applicable Research to Generate Effective Treatments

  The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative seeks to accelerate research in novel marker and drug development, along with understanding the molecular basis of pediatric malignancy, through identification of genomic changes associated with the following childhood cancers: Acute Lymphoblastic Leukemia (ALL) - A fast-growing type of blood cancer in which too many immature white blood cells are found in the blood and bone marrow. Acute Myeloid Leukemia (AML), including AML Induction Failure cases (AML-IF) - Another type of blood cancer marked by too many myeloblasts, an alternate type of immature white blood cell, are found in the blood and bone marrow. Upon diagnosis, AML patients without high-risk genetic markers undergo standard chemotherapy regimen, called the primary induction phase, to eliminate most cancer cells and induce a remission state. Clear Cell Sarcoma of the Kidney (CCSK) - A rare type of kidney cancer, in which the inside of the cells looks clear when viewed under a microscope. Clear cell sarcoma can spread from the kidney to other organs, most commonly the bone, but also including the lungs, brain, and soft tissues of the body. Neuroblastoma (NBL) - Cancer of cells of the sympathetic nervous system. Cancer Model Systems (MDLS), including PPTP - MDLS includes acute leukemia cell lines and xenografts with matched primary and/or relapsed tumor information, NBL cell lines and xenografts with matched controls, kidney tumor cell lines, normal brain tissues, and embryonic stem cell lines that were sequenced for some TARGET disease projects. Osteosarcoma (OS) - A cancer of the bone that primarily affects children and adolescents. Rhabdoid Tumor (RT) - A rare, fast-growing cancer that usually forms in the kidney or central nervous system (the brain and spinal cord) but can also form in soft tissues in other areas of the body. Rhabdoid tumors tend to spread quickly, are hard to treat, and have a poor prognosis. Wilms' Tumor (WT) - A cancer of cells in the kidney that can spread to the liver, lung and lymph nodes. More information can be found about each TARGET subproject by following the links on the top of this page. Together these cancers account for the majority of the more than 10,000 childhood cancer cases diagnosed in the United States each year. TARGET has employed a set of advanced and complementary genome analysis technologies, including large scale 2nd and 3rd generation genome sequencing, to strategically characterize alterations in both gene expression and in genomic structure (such as deletions and amplification) that are involved in childhood cancers. The goal of this coordinated effort has been to create a comprehensive genomic and transcriptomic profile of each cancer. Integrated analysis of the TARGET data has identified those genes that are either altered in their expression level or mapped to the chromosome regions of deletion/amplification/translocation, as these genes represent strong candidates for therapeutic targeting. To learn more about the TARGET project, which is now completed, visit the website at https://www.cancer.gov/ccg/research/genome-sequencing/target. TARGET data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the TARGET Publication Pages at the GDC (Please see the "Supplemental Links" section of any TARGET publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original TARGET research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data - gene expression, copy number variation, epigenetics, targeted sequencing), as well as higher level data generated by the GDC. Please see the TARGET Use and Publication Guidelines for updated details on the sharing of any TARGET substudy data, including how to cite TARGET.

  Study phs000218

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

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

  Study phs004055

• How to encrypt files with EGACryptor

  File preparation Due to the processes used at the EGA for file archival the use of non-alphanumeric characters in a filename will cause issues in archival. By convention whitespaces in filenames are to be avoided and should be replaced with the underscore character (_). Before encrypting your files please make sure that any files that will be uploaded to EGA do not use special characters such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &  Crypt4gh EGACryptor Files encrypted with EGACryptor must be uploaded via FTP EGACryptor The EGACryptor v.2.0.0 is a JAVA-based application which enables submitters to produce EGA compliant encrypted files along with files for the encrypted and unencrypted md5sum for each file to be submitted. The application will generate an output folder that will by default mirror the directory structure containing the original files. This output folder can subsequently be uploaded to the EGA FTP staging area via an FTP or Aspera client. Download EgaCryptor Download EgaCryptor Using the EgaCryptor Using the EgaCryptor Encrypting single file Encrypting multiple files Encrypting all files in folder Points to note Troubleshooting Troubleshooting Download EGACryptor The required jar files can be obtained by downloading EgaCrytptor jar file After the file has been downloaded, extraction of the zipped archive is required. The EGACryptor has been built to work with Java Runtime Environments from version 6 and above and with the OpenJDK Environment. Please refer to the relevant resources for installation guidance. Installing the latest version of the OpenJDK will include the JCE files. If your installation of Java JRE is less than 1.8.0_151 will require the manual installation of the JCE Policy Files. You can verify the version of the Java SE Runtime Environment (JRE) installed by using the command: $ java -version If you need to install the JCE please follow the instructions below: Installing the JCE policy files (due to licensing terms and conditions the required policy files must be downloaded direct from the ORACLE website) : Download the unlimited strength JCE policy files (JRE 6 / JRE 7/ JRE 8) Uncompress and extract the downloaded file. This will create a subdirectory called JCE. This directory contains the following files: README.txt, COPYRIGHT.html, local_policy.jar and US_export_policy.jar Install the two policy JAR files by replacing the existing ones in your java home directory. Install the two policy JAR files by replacing the existing ones in your directory. The standard place for JCE jurisdiction policy JAR files is: /lib/security [Unix] or \lib\security [Win32] Notes: refers to the directory where the Java SE Runtime Environment (JRE) was installed. Additional performance enhancements that have been included in the EGACryptor V2.0.0: The ability to parallelise the processing of datasets through the use of the resources on a system. Multicore systems will allow the user to specify n-1 cores for an n-core system. The use of this feature on clusters may speed up the processing of datasets that have large file numbers but consult your local cluster guide to ensure that there are not monopolising resources that are needed by other system users. The default for this process remains single threaded. 3 levels of system usage can be specified. Full usage within the limits detailed above. A limited mode that will ensure that 50% of the system resources are available for other tasks. Maximum mode is limited to 75% of system resources, this allows encryption to be prioritised but allows for the system to be usable for light alternate tasks. Finally there is a throttling mode that allows you to specify the exact number of computational threads to be used. the EGACryptor is able to ingest a structured directory and will output a directory with the same structure containing the encrypted files along with the md5checksums for the plain and encrypted files. The entire output directory can then be uploaded to the EGA for archival. as with the input path, it is now possible to specify the output path. the options have been updated inline with the upgraded functionality. The tool can only be used via the command line. The EGACryptor is designed to perform a single task, encrypting your data, for upload of these files please refer to our uploading guide Using the EgaCryptor Below are the three ways on how the EGACryptor tool can be used: Encrypting a single file : java -jar ../EGA-Cryptor_2_0_0.jar -i example1.bam Encrypting multiple files : java -jar ../EGA-Cryptor_2_0_0.jar -i "example1.bam,example2.bam" Encrypting all the files within a folder java -jar ../EGA-Cryptor_2_0_0.jar -i path/to/target/directory By default the EGACryptor v2 will create a new output directory containing all encrypted files and the relevant checksums within the target directory. If a specific directory is desired this can be specified by using the -o flag. This can be achieved in a similar manner to the following example: java -jar ../EGA-Cryptor_2_0_0.jar -i /path/to/target/directory -o /path/to/output/directory The tool will output three files per input file: file.gpg ( encrypted file ) file.md5( file md5 sum value file ) file.gpg.md5 ( encrypted file md5 sum value file ) All output files must then be uploaded to your submission account using Aspera or FTP. Further documentation on how to upload files: FTP and Aspera. Points to note Remember to provide the path to EgaCryptor.jar and run the command from within the directory the file/s are located. ECryptor writes files to the source directory of your local file system, as a result you must have write-access permissions for the source directory. Troubleshooting If in doubt about the function of the EGACryptor it is recommended to first consult the built-in documentation. This can be accessessed by using the -h flag as stated in the following table. Built-in Commands Table: list of the command line options built into EGA-Cryptor v2.0.0. Command line Option Action --------------------- ----------- -f Set this option to allow application to create maximum threads to utilise full capacity of cores/processors available on machine -h Use this option to view the bult-in help menu * -i File(s) to encrypt. Provide file/folder path or comma separated file path if multiple files in double quotes -l Set this option to allow application to create maximum threads equals to 50% capacity of cores/processors available on machine -m Set this option to allow application to create maximum threads equals to 75% capacity of cores/processors available on machine -o Path of the output file. This is optional. If not provided then output files will be generated in the same path as that of source file (default: output- files) -t Set this option if user wants to control application to create maximum threads as specified. Application will calculate no. of cores/processors available on machine & will create threads accordingly Encryption Errors UnixFileSystem.createFileExclusively (Native Method) The error is thrown by UNIX ("UnixFileSystem.createFileExclusively(Native Method)"). It appears that the user does not have write-access to the file system where the file to be uploaded is located. EGACryptor always writes MD5 checksums into files before uploading them to the server, and these files are created in the same location where the uploaded file itself resides.Solution: address your directory permission issue and re-run the command. Install JCE Unlimited Strength Jurisdiction Policy files The JCE policy unlimited strength jurisdiction files should be installed according to your current java version If you are still facing difficulty with the EGACryptor v.2 after having consulted the documentation please contact the EGA Helpdesk.

  Documentation submission/data/file-preparation/egacryptor

• CIDR: NCI Genome Wide Predictors of Survival in Colorectal Cancer

  CIDR/Molecular Correlates: This study genotyped archived blood samples from colorectal cancer cases participating in clinical trials. The goals of this project were to identify genetic variants associated with survival outcomes treatment and treatment-related severe adverse events among patients with colorectal cancer. Another goal was to examine the impact of adding information on germline genetic loci to existing prognostic models. MOSAIC: Multicenter International Study of Oxaliplatin/ 5FU-LV in the Adjuvant Treatment of Colon Cancer (MOSAIC). A randomized, open label efficacy trial to evaluate the FOLFOX regimen versus LV5FU2 in the adjuvant treatment of stage II and III colon cancer. The primary end point was disease-free survival. CPT.ES1.604: Randomized phase 3 study of weekly irinotecan plus high-dose 5-fluorouracil (FUIRI) versus biweekly irinotecan plus 5-fluorouracil/leucovorin (FOLFIRI) as first-line chemotherapy for patients with metastatic CRC. The aim of this study was to demonstrate that a regimen without leucovorin (LV) (FUIRI) is not inferior to the standard FOLFIRI (response rate). 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. N0147: Randomized phase III clinical trial for adjuvant therapy in stage III colon cancer patients enrolled at institutions across North America. Originally designed to compare three different chemotherapy regimens, and then later expanded to evaluate adding cetuximab to each original arm (leading to six total arms). Further modification later added pre-screening for KRAS mutation status, with the resulting goal to assess the potential benefit of cetuximab added to the modified sixth version of the FOLFOX regimen (mFOLFOX6) in patients with resected stage III wild-type KRAS colon cancer. Main outcome of interest is disease-free survival in patients with wild-type KRAS, while secondary end points included overall survival and toxicity. N9741: Randomized phase III trial to compare the effectiveness of various combination chemotherapy regimens in treating patients who have advanced, recurrent, or metastatic colorectal cancer that cannot be treated with surgery or radiation therapy. C-08: A Phase III Clinical Trial Comparing Infusional 5-Fluorouracil (5-FU), Leucovorin, and Oxaliplatin (mFOLFOX6) Every Two Weeks With Bevacizumab to the Same Regimen Without Bevacizumab For the Treatment of Patients With Resected Stages II and III Carcinoma of the Colon. The primary aim of the trial was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging disease-free survival and the secondary aim was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging survival.

  Study phs001290

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

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

  Study phs000833

• Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)

  Accessing Data Please refer to &#8220;Authorized Access&#8221; below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization.

  Study phs003599

• Neoadjuvant atezolizumab plus chemotherapy in gastric and gastroesophageal junction adenocarcinoma: the phase 2 PANDA trial

  Gastric and gastroesophageal junction (G/GEJ) cancers carry a poor prognosis, and despite recent advancements most patients die of their disease. While immune checkpoint blockade has become part of the standard of care for patients with metastatic G/GEJ cancers, its efficacy and impact on the tumor microenvironment in the early disease setting remain largely unknown. We hypothesized a higher efficacy of neoadjuvant immunotherapy plus chemotherapy in patients with non-metastatic G/GEJ cancer. In the phase 2 PANDA trial, patients with previously untreated resectable G/GEJ tumors (n=21) received neoadjuvant treatment with one cycle of atezolizumab monotherapy followed by 4 cycles of atezolizumab plus docetaxel, oxaliplatin and capecitabine. Treatment was well-tolerated, and all patients underwent resection without treatment-related delays, meeting the primary endpoint of safety and feasibility. Tissue was obtained at multiple time points, allowing analysis of the effects of single-agent PD-L1 blockade and the subsequent combination with chemotherapy on the tumor microenvironment. A total of 21 patients were included, of whom 20 patients underwent surgery and were evaluable for the secondary pathologic response and survival endpoints, while 19 were evaluable for exploratory translational analyses. A major pathologic response (MPR, ≤10% residual viable tumor) was observed in 14/20 (70%; 95% CI 46-88%) patients, including 9 (45%; 95% CI 23-68%) pathologic complete responses. At a median follow-up of 47 months, 13/14 responders were alive and disease-free, while 5/6 nonresponders had died due to disease recurrence. Notably, baseline PD-1+CD8+ T cell infiltration was significantly higher in responders than in nonresponders, and comparison of the tumor microenvironment alterations following anti-PD-L1 monotherapy versus the subsequent combination with chemotherapy revealed that increased immune activity was achieved upon single-agent PD-1/L1 axis blockade. Based on these data, anti-PD-L1 plus chemotherapy warrants further exploration in patients with non-metastatic G/GEJ cancer, and these results call for validation in a larger cohort.

  Study EGAS50000000168

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api

• Security Overview

  Security Overview The European Genome-phenome Archive (EGA) houses consented human data under controlled access. Access decisions are handled by the relevant Data Access Committee (DAC), which autonomously manages requests through the DAC Portal. This document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. As security is a prime concern of the EGA, the EGA is a member of the Global Alliance for Genomics and Health (GA4GH) Data Security work stream. The EGA contributes and helps develop the recommendations outlined the GA4GH Security Technology Infrastructure document, which defines guidelines, best practices, and standards for building and operating an infrastructure that promotes responsible data sharing in accordance with the GA4GH Privacy and Security Policy. Explore the EGA dataflow to gain deeper insights! Accessing data in the EGA involves several steps. First, users need to create an EGA account. Once logged in, they can request access to data controlled by a DAC through the EGA website (see documentation). The DAC oversees these requests through the DAC Portal, and if approved, grants the necessary permissions to the user's EGA account, allowing them to access and download all relevant data and metadata for the requested dataset(s). The key points of EGA security strategy are: 1 Regular Risk Assessment The EGA regularly identifies and assesses risk related to the following: Breach of confidentiality,Breach of privacy or autonomy,Malicious or accidental corruption or destruction of data archived at EGA,Disruption of services provided by the EGA. 2 Risk mitigation The EGA implements and maintains safeguards to minimise the risks identified above in accordance with the 6 control objectives listed in Appendix 1 and outlined in the GA4GH Security and Infrastructure document.If a breach is discovered, the EGA applies a defined protocol to minimise damage. 3 Identity and authorisation management The EGA authenticates the identity of individuals or software accessing controlled access data held at the EGA.The EGA ensures an appropriate level of assurance (LoA) is applied to the identity consistent with the risk associated with that individual, such as multi-factor authentication for DACs.The EGA provides the minimum access rights and privileges consistent with the user’s identity, allowing access consistent with the GA4GH Privacy and Security Policy, as determined by the appropriate DAC. 4 Audit Logs The EGA maintains a set of logs recording: Changes to user access rights,Data access requests,Resource usage. 5 Cryptography, communication security, and data integrity The EGA ensures data transmission integrity using a hash function.All data transmitted to or from the EGA is end-to-end encrypted.All data at EGA is stored using strong encryption.Encryption keys are not stored in the same system as the encrypted data.All data archived at EGA must be accompanied by a signed submission statement ensuring appropriate consent or ethical approval has been obtained, and is in accordance with all applicable laws and regulations. The EGA has a defined protocol defining the response in the event of a security breach, and is continuing to work with the GA4GH Data Security Work Stream to help define best practice and associated standards for breach responses. Appendix 1 GA4GH Control Objectives Control Objective 1: Implement technology safeguards to minimise the risk of unauthorised access, use, or disclosure of confidential and private data.Control Objective 2: Implement technology safeguards to minimise the risk of discovery, access, and use of individuals’ clinical and genomic data, and individual identities, other than as authorised by applicable jurisdictional law, institutional policy, and individual consents.Control Objective 3: Implement technology safeguards to minimise the risk of accidental or malicious corruption or destruction of data.Control Objective 4: Implement technology safeguards to minimise the risk of disruption, degradation, and interruption of services enabling access to data.Control Objective 5: Implement technology safeguards to minimise the risk of potential security attacks and misuse of authorised accesses and privileges.Control Objective 6: Implement technology safeguards to promptly detect the failure to attain the above control objectives and to respond with proper countermeasures.Appendix 2Refer to the document below to learn more about EGA long-term data preservation policy and procedures at EMBL-EBI.Long-term data preservation

  Documentation about/security

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Tissue Biopsy Study

  The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Most of the variants associated with T2D and related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies (GWAS) occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to identify the appropriate cell type, regulatory elements, target genes, and causal variants(s) in T2D-relevant tissues. We hypothesize that a subset of T2D and related variants alter gene expression regulation in skeletal muscle and adipose tissue - two major insulin target tissues and play key roles in insulin resistance. To that end, our study contains a comprehensive survey of genomics, epigenomics and transcriptomics in skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D.For this FUSION Tissue Biopsy Study, we obtained RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. On the second visit, we obtained ~250mg vastus lateralis skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit. To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from vastus lateralis skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who consented to the use of their data.Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.Release phs001048.v3.p1 adds single-nucleus (sn) RNA-seq and ATAC-seq data in 287 skeletal muscle samples out of the original 331 individuals. Individual-level data is available here for the 265 subjects who consented to the use of their data. The frozen tissue biopsy samples were processed in ten batches, each consisting of 40-41 samples. These batches were organized using a randomized block design to protect against experimental contrasts of interest including cohort, age, sex, BMI among others. Samples in each batch were pulverized, pooled together followed by nuclei isolation. The nuclei were processed on the 10X Genomics Chromium platform separately for snATAC-seq and snRNA-seq (v. 3.1 chemistry for snRNA-seq).Release phs001048.v4.p1 adds additional phenotypes and provides some corrections to several previous phenotypes.

  Study phs001048

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235

• eMERGE Network Imputed GWAS for 41 Phenotypes

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites (Cincinnati Children&#39;s Hospital Medical Center/Boston Children&#39;s Hospital, Children&#39;s Hospital of Philadelphia, Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University, Geisinger Clinic, Group Health Cooperative/University of Washington, Mayo Clinic, Icahn School of Medicine at Mount Sinai, Northwestern University, Vanderbilt University Medical Center) funded by the NHGRI to investigate the use of electronic medical record (EMR) systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 55,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of over forty phenotypes, including Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection, as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. Sites and participants include: Children&#39;s Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children&#39;s Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children&#39;s Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic medical records (EMRs). EMRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children&#39;s Hospital Medical Center/Boston&#39;s Children&#39;s Hospital (CCHMC/BCH): Cincinnati Children&#39;s Hospital Medical Center (CCHMC) and Boston Children&#39;s Hospital (BCH) are pediatric institutions dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. The CCHMC/BCH site has been built on a five-year history of collaboration, particularly in patient electronic record (ERM)-related informatics, the basis of much of eMERGE II. CCHMC and BCH together bring an extraordinary faculty to eMERGE II who are committed to diseases that afflict children, specifically phenotypes that focus upon diseases of children in ways that will leverage the available eMERGE adult GWAS and EMRs to discover meaningful use results. CCHMC/BCH plans to demonstrate real-time execution of phenotypic selection across their two distinct pediatric institutions as a model for ensuring phenotypic standardization and for national scalability. They will also look carefully at parents&#39; responses to results and use of their children&#39;s research results and better understand the factors that influence their decisions about learning incidental findings. In addition to patient and parent perceptions CCHMC/BCH will also explore clinician perceptions of pharmacogenetic research results after EMR integration. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Group Health(GH)/University of Washington (UW): GH participants for the PGx project were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~6300.) Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in GH&#39;s integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at Group Health: 1. Demographics - participants with self-reported race as Asian or African ancestry were prioritized and selected to enrich for non-European ancestry; 2. Diagnosis and procedure codes - participants were selected if found to have a history of hypertension, atrial fibrillation (AF), or congestive heart failure (CHF). Participants with a history of arrhythmia were added if the entire selection algorithm did not generate 900 individuals. We also enriched for participants with EHR evidence of actionable indications related to PGRNSeq genes. Participants were selected if found to have an ICD9 code for malignant hyperthermia, hypertension, atrial fibrillation, congestive heart failure or long QT syndrome (LQTS); 3. Laboratory values - if participants had any laboratory event of creatine kinase (CK) &#62;1000, and were dispensed statins within 6 months of the event, then they were selected; and 4. Medications - participants were excluded if ever on carbamazepine or had a current regimen of warfarin. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was &#60;1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants&#39; DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University: BioVU, Vanderbilt&#39;s DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt&#39;s EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations.

  Study phs000888

• National Cancer Institute (NCI) Biospecimen Pre-analytical Variables (BPV) Analysis

  The Biospecimen Pre-analytical Variables (BPV) Program is a National Cancer Institute-sponsored study to systematically assess the effects of pre-analytical factors on the molecular profile of biospecimens. A robust biospecimen collection infrastructure was established to prospectively collect biospecimens using rigorous standard operating procedures to control for most variables while introducing experimental conditions to study specific biospecimen handling issues, including the cold ischemic time (delay to formalin fixation), time in formalin, freezing methods, and storage temperatures and durations. RNA and DNA from biospecimens collected under these conditions was analyzed on multiple molecular platforms. The potential effects of these pre-analytical conditions on protein integrity and detection of metabolites were also examined. Data from this study will be used to develop evidence-based biospecimen standard operating procedures and best practices for fit-for-purpose collection, processing, and storage of biospecimens. The BPV Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following sub-studies below or in the &#34;Substudies&#34; box located on the right hand side of this top-level study page phs001304 BPV Cohort. The substudy links will be active once they are released by dbGaP. Preanalytical Impacts on Global Metabolite Profiling - plasma (MassSpec by Metabolon) This study was to evaluate the impact of the storage temperature (s) (-80&#176;C and LN2 vapor) and the length of storage on human plasma quality using LC-MS/MS (liquid-chromatography-mass spectrometry/mass spectrometry) based global metabolite profiling. The study includes 240 plasma samples collected from 40 donors. Investigate the effect of the delay to fixation on the proteome and phosphoproteome -FFPE (MassSpec by Caprion). The study is to do proteome and phosphoproteome analysis on Delay to fixation was carried out using FFPE tumor samples from colon and ovarian cancer patients comparing 2, 3, and 12hr delay to fixation to the 1hr time point. The study includes 100 samples 20 donors. Investigate the effect of storage conditions of tumor specimens on the proteome and phosphoproteome profiling- Frozen tissue and plasma (MassSpec by Caprion). The study was to evaluate the effects of storage conditions on tumor specimens. Plasma samples from 40 cancer patients stored at two different temperatures (-80&#176;C and LN2) for a given period (0-2, 6-8, and 12-14 months) were evaluated. Frozen kidney tumor samples from 20 patients were compared for effects of different snap frozen (dry ice vs. LN2) and storage temperatures (-80&#176;C and LN2). The study includes 100 tissue and 240 plasma samples from 60 donors. Preanalytical Impacts on Genomic Sequencing by Next Generation Sequencing (NGS) technology (mRNA/miRNA and WES by Expression Analysis). The goal of the study is to determine the effects of cold ischemic delay-to-fixation (4 time points) and formalin preservation (FFPE) on the nature and quality of genomic profiles using the matched freshly frozen sample as the gold standard, which including WES, RNAseq. The study includes 395 samples from 37 donors. Preanalytical Impacts on Copy Number Variation (CNV) Detection by aCGH technology (aCGH by Georgetown University). This study was to use aCGH to evaluate the effect of variation in cold ischemia time and time in formalin fixation on CNV in DNA extracted from kidney cancer specimens. The study includes 235 samples from 40 donors. Evaluation of frozen conditions on mRNA profiling by TaqMan assay (mRNA expression by Georgetown University). This study was to utilize gene expression profiling, using custom TaqMan arrays, to compare the molecular profiles of RNA from frozen tumor samples collected using two freezing methods (dry ice or LN2), two storage temperatures (-80&#176;C or LN2 vapor), as well as Optimal Cutting Temperature (OCT) compound and non-OCT embedded. The study includes 100 samples from 20 donors. mRNA signature for stratification by cold ischemia time (mRNA expression by IBBL). The study was to determine the effects of cold ischemic time (delay-to-fixation) and formalin preservation (FFPE) on mRNA detection by Taqman assay using tumor tissue specimens from kidney, colon and ovarian cancer patients. There are160 samples from 40 donors. The Biospecimen PV cohort is utilized in the following dbGaP individual studies. To view molecular data, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001304 Biospecimen PV cohort. phs001634 CIT mRNA phs001635 CNV aCGH phs001636 Fixation Delay phs001637 Global Metabolite Profiling phs001638 mRNA TaqMan phs001639 NGS phs001640 Tumor Storage

  Study phs001304

• Women's Health Initiative Clinical Trial and Observational Study

  The Women&#39;s Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are: Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo. The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to &#39;WHI dbGaP Cohort Data Release Data Preparation Guide May 2018&#39; for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" box located on the right hand side of this top-level study page phs000200 WHI Cohort. phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS

  Study phs000200

• Gene Expression and Regulatory Networks in Human Leukocytes - Immunological Variation Consortium

  Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified naive CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal data group, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, NanoString technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome&#39;s expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies. Additionally, over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, in a second study we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (ATAC-QTLs). ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression. In another study we analyzed RNA-seq profiles from primary CD4+ T cells of two healthy donors at six time points from 0 to 72 hours after stimulation with bead-bound antibodies against CD3 and CD28.

  Study phs000815

• Single cell eQTL map of T cell activation

  We isolated naive and memory CD4+ T cells from 119 healthy individuals and stimulated the cells using anti-CD3/anti-CD28 coated beads. We profiled gene expression using single cell RNA-seq (10X-Genomics 3’ v2 kit) at resting state and three time points of activation (16h, 40h and 5 days post stimulation) and mapped expression quantitative trait loci.

  Dataset EGAD00001008197

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1&#215;1&#215;6 mm3, 320&#215;320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations &#215; 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002

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

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

  Study phs003470

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

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

  Study phs003824

• Privacy Notice for Helpdesk service

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

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

• Contextual and Health Behavior Effects on Epigenetic Aging Among Africans in the Family and Community Health Studies

  The Family and Community Health Studies (FACHS) is a longitudinal examination of health and health related behaviors in African American families. The original study cohort consisted of 867 African American parent-child dyads from Georgia and Iowa who were ascertained in cooperation with local school districts. The key inclusion criteria for participating in the study were the presence of an adolescent in the 5th grade (approximately 10-11 years old) who self-identified as African American (i.e., the Target) and the participation of a primary caretaker (PC) for the Target. The clinical and biological data included in this collection are from the Target (i.e., FACHS-T) portion of these studies of these African American parent-child dyads. The initial wave of behavioral assessments of the FACHS-T subjects was conducted in 1997-98 (Wave 1), with seven subsequent ascertainments, Wave 2 (1999&#8211;2000), Wave 3 (2002&#8211;2003), Wave 4 (2005&#8211;2006), Wave 5 (2007&#8211;2009), Wave 6 (2010&#8211;2011), Wave 7 (2014&#8211;2016) and Wave 8 (2019-2021). Full interviews were obtained at each wave of the study with the exact content of the wave varying as a function of developmental age. These interviews of the FACHS-T subjects collected a wide variety of data including the following: perceived discrimination; socioeconomic status; substance use exposure; common internalizing and externalizing disorders such as depression, substance use, and conduct disorder; school efficacy; peer support and perceived parenting practices. Biological sampling of the FACHS-T subjects was conducted at three time points. Saliva DNA was collected at Wave 5 while full phlebotomy was conducted at Waves 7 and 8. The genome wide methylation data listed below is derived from the whole blood DNA samples collected at Wave 8 and Wave 9. The genome wide genotyping data was determined using DNA from the Wave 7 samples. The clinical and biological data available herein are those from 309 FACHS-T subjects who participated in both Wave 7 and Wave 8, and who consented for deposition of their data in dbGAP.

  Study phs003723

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

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

  Study phs001442

• Privacy Notice for the Account User

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

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

• eMERGE Network Phase III: HRC SNV and 1000 Genomes SV Imputed Array Data of 105,000 Participants

  The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in June 2007 and began its third phase in September 2015. eMERGE Phase III (June 2015 - June 2020) consists of 10 study sites, two central sequencing and genotyping facilities, and a coordinating center. Included in this study are: Human Reference Consortium (HRC) single nucleotide variants and 1000 Genomes structural variants imputed array data of 105,108 eMERGE participants from nine Phase III study sites and three Phase II study site collaborators. Corresponding demographics, body mass index measurements. Case/control status for the following phenotypes: Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection. Study sites and participants include: Boston Children&#39;s Hospital: The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children&#39;s Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants&#39;preferences;results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children&#39;s Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP. Children&#39;s Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children&#39;s Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children&#39;s Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic health records (EHRs). EHRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children&#39;s Hospital Medical Center/Boston&#39;s Children&#39;s Hospital (CCHMC/BCH): Cincinnati Children&#39;s Hospital Medical Center (CCHMC) is a pediatric institution dedicated to improving health and welfare of children and to the discovery and practical application of new genomic information to the ordinary care of children. CCHMC brings an extraordinary faculty to eMERGE III who are committed to gain a better understanding of the genesis of disease and to elucidate the mechanisms of diseases that afflict children, specifically pediatric disease phenotypes that will leverage the available eMERGE adult genomic data and electronic medical records (EMRs) to discover meaningful use results. Generation of EMR phenotype algorithms, informed by natural language processing, using heuristic and machine learning methods is ongoing. CCHMC has developed tools to evaluate adolescent return of results preferences, examined the ethical and legal obligations and potential to reanalyze results, and developed clinical decision support for phenotyping, test ordering, and returning sequencing results. The success of these eMERGE III studies is enhanced by the ongoing institutional investment made in the CCHMC Biobank, the comprehensive EMR (EPIC), the i2b2 de-identified medical record data warehouse, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. Columbia University: Columbia University Medical Center/New York Presbyterian (CUMC/NYP) Hospital system is one of the nation&#39;s largest and most comprehensive hospital systems with over 2 million inpatient and outpatient yearly visits that serves a racially and ethnically diverse urban patient population. The Columbia University GENomic Integration with EHR (GENIE) research study contributed and shared phenotype and genotype data for individuals who were recruited as part of a diverse array of initiatives within the hospital, including Northern Manhattan Study (NOMAS), Pediatric Cardiac Genomic Consortium (PCGC), Caribbean Hispanics with Familial and Sporadic Late Onset Alzheimer&#39;s disease (AD), Alzheimer&#39;s Disease Sequencing Project (ADSP), and Genetics of Chronic Kidney Disease study. Some of these individuals had kidney or neurological problems, some were healthy adult volunteers with self-reported health status information from the medically underserved Northern Manhattan community, and others were pediatric patients with cardiac conditions. For the kidney disease cohort, patients with the diagnosis of Chronic Kidney Disease (CKD) and healthy controls were recruited to the Columbia University CKD biobank. For the NOMAS cohort, eligible participants were stroke-free, were 40 years old, and resided for at least 3 months in a Northern Manhattan household with a telephone. The PCGC study recruited parent-offspring trios with pediatric probands diagnosed with congenital heart defects (CHD). For the Caribbean Hispanics with Alzheimer&#39;s disease project, individuals from families affected by AD and with sporadic AD were recruited, along with unrelated controls. Samples for the ADSP study have been selected from well-characterized cohorts of individuals with AD diagnosis. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Partners Health Care (Harvard): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people&#39;s health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women&#39;s Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women&#39;s Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 60,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 100 million dollars in NIH research. Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center: KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~8,073.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA&#39;s integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes n=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (n=1,002), in order to allow us to enrich germline pathogenic variants. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo Vascular Disease Biorepository is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval;this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was &#60;1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Case control study of venous thromboembolism (PI John Heit) Controls from a case control study of pancreatic cancer (PI Gloria Petersen) Mayo Clinic Biobank. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants&#39;DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University Medical Center: BioVU, Vanderbilt&#39;s DNA databank, was designed as an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt&#39;s EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. BioVU is currently the largest single site DNA collection world-wide, at &#62;235,000 samples as of spring 2017.

  Study phs001584