1217 results for ""initial+cohort"+"mid-2020s"+"consortium"+"scholarly+exchange"+"university""

in 17.61 milliseconds.

• NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)

  Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation "stable" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study.

  Study phs001927

• University of Miami Myeloma Genomics Lab

  Dac EGAC00001003337

• University of Florida Brain Cancer DAC

  Dac EGAC00001001035

• DAC Biobank Lab University of Lodz

  Dac EGAC00001001068

• Institute of Pathology, University Hospital Basel

  Dac EGAC00001001159

• Department for BioMedical Research, University of Bern

  Dac EGAC00001001457

• Department of Dermatology, Kyoto University

  Dac EGAC00001001770

• University of Ulsan College of Medicine

  Dac EGAC00001001947

• Newcastle University Male Infertility Genomics DAC

  Dac EGAC00001002043

• Medical University of Vienna - Nephrogene

  Dac EGAC00001002117

• University of Calgary Charbonneau Cancer Institute

  Dac EGAC00001002170

• Newcastle University Male Infertility Genomics DAC

  Dac EGAC00001002219

• Newcastle University Male Infertility Genomics DAC

  Dac EGAC00001002313

• Uppsala University (UU) Data Access Committee

  Dac EGAC00001003390

• snMultiome Studies of University of Copenhagen

  Dac EGAC50000000924

• Medical University of Vienna - AdameykoLab & Nephrogene

  Dac EGAC00001003383

• DAC University Hospital Cologne

  Dac EGAC00001000361

• Genetic predisposition to cancer, University of Tampere

  Dac EGAC00001000488

• Department of Immunology, University of Oslo

  Dac EGAC00001000877

• DAC of Biobank Lab, University of Lodz

  Dac EGAC00001001433

• Center for Technology Licensing at Cornell University

  Dac EGAC00001001587

• Urology lab, DBMR, University of Bern, Switzerland

  Dac EGAC00001001743

• Urology lab, DBMR, University of Bern, Switzerland

  Dac EGAC00001001744

• Urology lab, DBMR, University of Bern, Switzerland

  Dac EGAC00001001786

• DAC Tech Transfer - Ghent University

  Dac EGAC00001002060

• Radboud University Medical Centre FSHD Clinical Team

  Dac EGAC00001003305

• Malagasy Genomics University of Antananarivo (MGUA) committee

  Dac EGAC50000000320

• University Children`s Hospital Sarcoma Research

  Dac EGAC50000000260

• The BIOS Consortium: Biobank-based Integrative Omics Studies

  Dac EGAC00001000277

• MacTel_cohort_Omni5_genotypes

  MacTel Projet consortium case and control genotypes from Ilumina Omni5 chip

  Dataset EGAD00010001204

• NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

  Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

  Study phs001662

• DAC for Cornell-NCI DLBCL NGS Genomic Project

  Genome-wide sequencing experiments were conducted on 103 DLBCL biopsy samples, of which the datasets (called Cornell-NCI DLBCL cohort) are available for authorized scientists. The Center of Technology Licensing at Cornell University is in charge of this data access policy and approval. Particularly, Cornell University will email a DAA to each requestor to have their institution sign before access is granted

  Dac EGAC50000000704

• GWAS genotype data of Japanese

  GWAS genotype data of the Japanese population (N=2,380) were collected at Osaka University and the affiliated medical institutes. GWAS genotyping was performed using Infinium Asian Screening Array (Illumina, USA).

  Study EGAS00001006423

• Haplotype Reference Consortium Release 1.1

  Haplotype Reference Consortium Release 1.1 - subset for release via the EGA

  Dataset EGAD00001002729

• Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001227

• Fastq data for stranded mRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for stranded mRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001402

• Fastq data for whole genome shotgun sequencing for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for whole genome shotgun sequencing assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001400

• Fastq data for whole genome bisulfite sequencing for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for whole genome bisulfite sequencing assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001312

• ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001235

• Long-read sequencing of prostate adenocarcinoma metastatic to left axillary lymph node. Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Oxford Nanopore long-read sequencing of A17-LAxillaryLN2Met-23312 PELICAN sample, identified as D051965 un Pan-Cancer Analysis of Whole Genomes study, and identified as PD13412a by prior Gundem et al whole genome sequencing study (PMID 25830880). Data used to support Figure 6 in Pubmed ID 32025007 "Pan-Cancer Analysis of Whole Genomes Consortium." Nature 2020 578:8293.

  Dataset EGAD00001005974

• National Institute of Dental and Craniofacial Research (NIDCR) Sjögren's International Collaborative Clinical Alliance (SICCA): Center for Inherited Disease Research (CIDR) Genome-Wide Genotyping

  The Sjögren's International Collaborative Clinical Alliance (SICCA) is a multisite observational cohort study that recruited a large cohort of geographically diverse participants. Enrollment of participants began in late 2004 at five (one domestic and four international) sites, in which all groups used the same protocol-directed methods to provide uniform evaluations; collect oral, ocular, and rheumatologic data; and collect specimens. The sites were located at the University of Buenos Aires, Argentina; Peking Union Medical College, Beijing, China; Rigshopitalet (formerly at Glostrup Hospital), Copenhagen, Denmark; Kanazawa Medical University, Ishikawa, Japan; King's College, London, UK (joined in 2007); and the University of California, San Francisco (UCSF). In 2009, Aravind Eye Hospital, Madurai, India; Johns Hopkins University, Baltimore, MD; and University of Pennsylvania, Philadelphia, PA were added as additional SICCA sites. UCSF is the coordinating center for SICCA. All specimens and data collected for SICCA are housed at UCSF. To facilitate the research focused on understanding the genetics of Sjögren'sSjögren's syndrome, high-density SNP genotype data and SICCA clinical information are being made available to the research community. This includes participants recruited from all SICCA research groups (RG). These participants (3,382), blood relatives (439), and unrelated healthy controls (25) had their whole blood or saliva sample (Oragene) extracted for DNA for the GWAS at the UCSF DNA Bank. Eighty eight percent of the participants are women, most are of European or Asian ancestry and the median age is 55. To assess potential batch effects when doing case-control comparisons using planned external controls, 30 DNA samples from each of three studies were genotyped with SICCA DNA samples: The Genetic Architecture of Smoking and Smoking Cessation - Collaborative Genetic Study of Nicotine Dependence (COGEND) - PI: Laura Bierut. NEI-Age-related disease study (AREDS) - Genetic Variation in Refractive Error Substudy - PI: Dwight Stambolian. Controls from the National Institute of Mental Health's (NIMH's) Human Genetics Initiative. Genome-Wide Association Study of Schizophrenia - PI: Pablo V. Gejman. Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN) - PI: Pablo V. Gejman. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data quality control, dbGaP preparation and posting, and imputation to 1000 Genomes to increase SNP density was performed by the Center for Biomedical Statistics at the University of Washington. Data analysis was performed at UCSF using software PLINK, EIGENSOFT, and SNPTEST.

  Study phs000672

• Tampere University Hospital Leukemia Research Data Access Committee

  Dac EGAC00001003278

• Ovarian Cancer Laboratory, University of Oxford

  Dac EGAC00001000518

• Tampere University Hospital Leukemia Research Data Access Committee

  Dac EGAC00001003137

• Leiden University Medical Center Adipose tissue RNA-seq

  Dac EGAC00001000503

• DAC for Department of Haematology, Aalborg University Hospital

  Dac EGAC00001000543

• Tel Aviv University Human BiPSC Data Access Committee

  Dac EGAC00001000735

• DAC University Hospital Cologne-Experimental Pediatric Oncology

  Dac EGAC00001001060

• Mannheim Liquid Biopsy Unit, Heidelberg University & DKFZ

  Dac EGAC00001001113

• Department for BioMedical Research (DBMR), University of Bern

  Dac EGAC00001001677

• Department of BioMedical Research (DBMR), University of Bern

  Dac EGAC00001002289

• DAC for Department of Hematology, University of Tsukuba

  Dac EGAC00001002378

• Tampere University Hospital Leukemia Reserach Data Access Committee

  Dac EGAC00001002445

• Tampere University Hospital Leukemia Research Data Access Committee

  Dac EGAC00001002489

• Institute of Pathology, University of Bern, Bern, Switzerland

  Dac EGAC00001002537

• Department of BioMedical Research (DBMR), University of Bern

  Dac EGAC00001002904

• Tampere University Hospital Leukemia Research Data Access Committee

  Dac EGAC00001003156

• Translational Genomics of Diabetes Lab at Stanford University

  Dac EGAC00001002542

• Endometrial Cancer Association Consortium - OncoArray Genotypes

  The data come from 9 studies participating in the Endometrial Cancer Association Consortium (ECAC). ECAC data included in this dbGaP submission include OncoArray data from 4486 endometrial cancer cases genotyped at the Center for Inherited Disease Research (CIDR). Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in O'Mara et al, Identification of nine new susceptibility loci for endometrial cancer. Nature Communications (PMID:30093612).

  Study phs001885

• Genome-Wide Association Study of Endometrial Cancer in the Epidemiology of Endometrial Cancer Consortium (E2C2)

  Endometrial cancer, the most common gynecological malignancy in the United States, has both an environmental and genetic component. To this end, we conducted a genome-wide association study to identify genes involved in endometrial cancer using studies from the NCI-supported Epidemiology of Endometrial Cancer Consortium (E2C2). For the discovery stage we included samples from 6 cohort and 7 case control studies through 2007. The total number of cases genotyped were 2,307, white women of European descent, and 2,307 matched controls using the Illumina HumanOmniExpress platform. We conducted the replication using the Infinium HumanExome BeadChip, which successfully genotyped 177,139 variants in 1055 cases and 1778 controls from four ethnically diverse studies that are part of the Epidemiology of Endometrial Cancer Consortium (E2C2). The overall goal is to determine whether certain genotypes are predictive of future endometrial cancer risk, and whether the genotypes interact with established endometrial risk factors.

  Study phs000893

• Reference epigenomes generated as part of the International Human Epigenomics Consortium (IHEC)

  The Centre for Epigenome Mapping Technologies (CEMT) is an epigenome sequencing platform funded by the Canadian Institutes of Health Research (CIHR) and Genome BC as part of the Canadian Epigenetics, Environment and Health Research Consortium (CEEHRC). CEMT aims to produce 100 human reference epigenomes, each comprising the following datasets: whole genome; whole genome bisulfite and oxidative bisulfite; transcriptome; microRNA; and chromatin immunoprecipitation (ChIP)-seq for the core chromatin marks (H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K36me3, and H3K27ac).CEEHRC is a full member of the International Human Epigenomics Consortium (IHEC), which aims to coordinate the production of 1,000 reference maps of human epigenomes for key cellular states relevant to health and diseases. As such, all datasets submitted by the CEMT platform conform to IHEC assay standards and metadata guidelines.

  Study EGAS00001000552

• The Cardiogenics study

  Cardiogenics is an European collaborative project, it started in January 2007 and was funded by the European Commission through its Sixth Framework Program (reference LSHM -CT-2006-037593) until 2011. It involved several laboratories from France (INSERM UMRS937), Germany (Lübeck University; Regensburg University), United Kingdom (the Welcome Trust Sanger Institute; University of Leicester) and Sweden (Uppsala University Hospital) and was coordinated by a management group composed of scientists from these different institutions. Under the coordination of the management group the laboratories are still developing projects using Cardiogenics data sets. As part of the Cardiogenics project, RNA from monocytes and macrophages of 363 patients with coronary artery disease and 395 healthy individuals was prepared and genome-wide expression was assessed in both cell types using the Illumina HumanRef 8 v3 Beadchip . The DNA of all these individuals was genotyped using the Human 610 Quad custom arrays. Both data sets were used to conduct eQTL analyses. A subsample of subjects included in an allelic-imbalance substudy were also genotyped using the Illumina Human Custom 1.2M array. Detailed description of these datasets can be found in Shah S et al. Circ Cardiovs Genet 2011; Rotival M et al. Plos Genet 2011, Almlöf et al. Plos One 2012 and Garnier S et al. Plos Genet 2013

  Study EGAS00001000411

• DAC for IGMM / Usher Institute, University of Edinburgh

  Dac EGAC00001000365

• DAC for Dave Lab, Duke University

  Dac EGAC00001000538

• DAC for AA HCC patient from National Taiwan University

  Dac EGAC00001000708

• University Hospital of Basel - Novartis collaboration Data Access Committee

  Dac EGAC00001000747

• Harbin Medical University Cancer Hospital Data Access Commitee

  Dac EGAC00001000948

• Tampere University Hospital Leukemia Reserach Data Access Committee

  Dac EGAC00001001551

• Department of Clinical Genetics of Maastricht University Medical Center

  Dac EGAC00001002259

• Department of BioMedical Research (DBMR), University of Bern

  Dac EGAC00001002274

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001003071

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001003083

• Kyoto Prefectural University of Medicine Data Access Commitee

  Dac EGAC00001003411

• NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish

  The Amish Complex Disease Research Program includes a set of large community-based studies focused largely on cardiometabolic health carried out in the Old Order Amish (OOA) community of Lancaster, Pennsylvania (http://medschool.umaryland.edu/endocrinology/amish/research-program.asp). The OOA population of Lancaster County, PA immigrated to the Colonies from Western Europe in the early 1700's. There are now over 30,000 OOA individuals in the Lancaster area, nearly all of whom can trace their ancestry back 12-14 generations to approximately 700 founders. Investigators at the University of Maryland School of Medicine have been studying the genetic determinants of cardiometabolic health in this population since 1993. To date, over 7,000 Amish adults have participated in one or more of our studies. Due to their ancestral history, the OOA may be enriched for rare variants that arose in the population from a single founder (or small number of founders) and propagated through genetic drift. Many of these variants have large effect sizes and identifying them can lead to new biological insights about health and disease. The parent study for this WGS project provides one (of multiple) examples. In our parent study, we identified through a genome-wide association analysis a haplotype that was highly enriched in the OOA that is associated with very high LDL-cholesterol levels. At the present time, the identity of the causative SNP - and even the implicated gene - is not known because the associated haplotype contains numerous genes, none of which are obvious lipid candidate genes. A major goal of the WGS that will be obtained through the NHLBI TOPMed Consortium will be to identify functional variants that underlie some of the large effect associations observed in this unique population.

  Study phs000956

• Exome Sequencing to Identify Medically Relevant Associations in Finnish Sub-Isolate Samples from the FINRISK Cohort

  We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago. Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: 23912948). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (www.nationalbiobanks.fi) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.

  Study phs000756

• Lung Cancer Genetic Study Among Asian Never Smokers

  The Lung Cancer Genetic Study Among Asian Never Smokers includes data from four population-based studies conducted among Asian women: the Shanghai Women's Health Study (SWHS), the Hwasun Cancer Epidemiology Study (HCES1 and HCES2), the Female Lung Cancer Consortium in Asia (FLCCA, including sFLCA), and the Guangzhou Lung Cancer Study (GLCS). Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Lung cancer patients identified in the SWHS and non-cases were included in the current study.Hwasun Cancer Epidemiology Study-Lung Cancer (HCES1 and HCES2): The HCES is a hospital-based case-control study whose goal is to identify factors of the cancer development and clinical progression in a Korean population. Included in this project were 299 female lung cancer cases from HCES2, who were diagnosed between April 2004 and February 2013 at Chonnam National University Hwasun Hospital, a cancer specified hospital in Jeollanam-do province, South Korea. Controls were randomly selected from women with no previous cancer diagnosis at enrollment in the Namwon Study and the Dong-gu study, ongoing community-based cohort studies in South Korea. A total of 1,103 controls (273 from HCES1 and 830 from HCES2) were genotyped by MEGA. Guangzhou Lung Cancer Study (GLCS): The GLCS is a case-control study including never-smoking women lung cancer cases and controls from Guangzhou, China.In this study, the DNA samples of 1,195 subjects from SWHS and GLCS were genotyped using whole exome sequencing (WES), and the DNA samples of 7,174 subjects from SWHS, HCES1, HCES2, FLCCA, and sFLCA were genotyped using the Multi-Ethnic Global Array (MEGA).

  Study phs002366

• NHLBI TOPMed - NHGRI CCDG: Groningen Genetics of Atrial Fibrillation (GGAF) Study

  Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. The Groningen Genetics of Atrial Fibrillation (GGAF) cohort is a cohort composed from 5 different sources of individuals with atrial fibrillation (AF) and age and sex-matched controls. Written informed consent was provided from all participating individuals, and all 5 studies were approved by the ethical committee at the University Medical Center (www.atrialfibrillationresearch.nl) and Maastricht University. All samples selected for TOPMed WGS are from individuals with atrial fibrillation.

  Study phs001725

• Clinical Genetics Pediatric Brain Tumor (CGPBT)-group at Gothenburg University.

  Dac EGAC00001000572

• University Hospital of Copenhagen, Laboratory of Molecular Cardiology

  Dac EGAC00001000785

• Peking University BIOPIC Data Access Committee (PUBDAC)

  Dac EGAC00001000902

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001002266

• Lymphoma Biology and Survival / Applied Tumor Genomics / University of Helsinki

  Dac EGAC00001002849

• Data access committee for sequencing data at Kyoto University

  Dac EGAC50000000045

• MARCH Study DAC, Vyas Group, University of Oxford

  Dac EGAC00001003303

• Lyon University Hospital Molecular Endocrinology Laboratory Data Access Committee

  Dac EGAC00001003363

• University of Melbourne Centre for Cancer Research (UMCCR) Data Access Committee

  Dac EGAC00001003567

• This DAC is the list of persons that, on behalf of the UKBEC consortium, manage the access to the UKBEC data.

  Dac EGAC00001000314

• This agreement governs the terms on which access will be granted to the data generated by the United Kingdom Brain Expression Consortium.

  Dac EGAC00001001408

• Study of Addiction: Genetics and Environment (SAGE)

  This study is part of the Gene Environment Association Studies initiative (GENEVA) funded by the National Human Genome Research Institute. The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. The focus of this proposal is a case-control design of unrelated individuals for a genetic association study of addiction. Cases are defined as individuals with DSM-IV alcohol dependence (lifetime) and potentially other illicit drug dependence. In addition to the categorical diagnosis, we have data on ordinal measurements of number of DSM-IV symptoms for alcohol, nicotine, marijuana, cocaine, opiates and other drugs so that we will able to construct quantitative measurements of addiction severity over a wide range of substances. Controls are defined as individuals who have been exposed to alcohol (and possibly to other drugs), but have never met lifetime diagnosis for alcohol dependence or dependence on other illicit substances. Analyses that include refinement of the phenotype and incorporation of important demographic and environmental factors into association studies will be pursued. Cases and controls were selected from three large, complementary datasets: the Collaborative Study on the Genetics of Alcoholism (COGA), the Family Study of Cocaine Dependence (FSCD), and the Collaborative Genetic Study of Nicotine Dependence (COGEND). COGA: COGA was initiated in 1989 and is a large-scale family study that has had as its primary aim the identification of genes that contribute to alcoholism susceptibility and related characteristics. COGA is funded through the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Subjects were recruited from 7 sites across the U.S. Alcohol dependent probands were recruited from treatment facilities and assessed by personal interview. After securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through the alcohol dependent probands. Assessment involved a comprehensive personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Families with three or more first-degree relatives who were alcohol dependent were invited for more extensive testing, including neurophysiology evaluations (ERPs and EEGs) and a battery of neuropsychological assessments. Blood was obtained for genetic studies. Institutional Review Boards at all sites approved the protocols, including sharing in the NIAAA national repository. COGA has four Co-Principal Investigators Bernice Porjesz, Victor Hesselbrock, Howard Edenberg, and Laura Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-investigators are: University of Connecticut (Victor Hesselbrock); Indiana University (Howard Edenberg, John Nurnberger, Jr., Tatiana Foroud); University of Iowa (Samuel Kuperman); SUNY Downstate (Bernice Porjesz); Washington University in St. Louis (Laura Bierut, Alison Goate, John Rice); University of California at San Diego (Marc Schuckit); Howard University (Robert Taylor); Rutgers University (Jay Tischfield); Southwest Foundation (Laura Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Family Study of Cocaine Dependence (FSCD): This project was initiated in 2000 as a case-control family study of cocaine dependence funded through the National Institute on Drug Abuse (NIDA; PI: Laura Bierut). The primary goal was to increase the understanding of the familial and non-familial antecedents and consequences of cocaine dependence. Cocaine dependent individuals were systematically recruited from chemical dependency treatment units (both public and private; residential and outpatient) in the greater St. Louis metropolitan area. Community based control subjects were identified through a Missouri Driver's License Registry (maintained at Washington University for research purposes) and matched by age, race, gender, and residential zip code. As a supplement to this project, blood samples were collected for future genetic analysis and were included in the NIDA Genetics Consortium. Phenotypic data, DNA, and cell lines are in the NIDA Center for Genetics Studies. Collaborative Genetic Study of Nicotine Dependence (COGEND): COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. All subjects were recruited from Detroit and St. Louis. Nicotine dependent cases and non-dependent smoking controls were identified and recruited. In addition, one sibling for each case and control subject was recruited in a subset of the sample. Over 56,000 subjects aged 25-44 years were screened by telephone, over 3,100 subjects were personally interviewed, and over 2,900 donated blood samples for genetic studies. All three studies (COGA, COGEND, FSCD) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, educational attainment, religious participation, and family structure. Other important covariates and/or potential moderators of genetic effects include comorbid addictions and age at initiation of use for cigarettes, alcohol and drugs. The assessments also include measures of various life stressors, such as physical and sexual abuse, which have been implicated in gene-environment interactions for several disorders. Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Note for Publications Related to Study: The Study of Addiction: Genetics and Environment (SAGE) has not yet generated publications. Below is a listing of publications related to the three studies from which the SAGE sample was selected. COGA has over 228 publications listed at www.niaaagenetics.org This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000092

• Data Access Commitee of Nanjing Medical University Affiliated Jiangsu Cancer Hospital

  Dac EGAC00001003206

• Department of Pediatrics, The University of Tokyo Data Access Committee

  Dac EGAC00001000207

• Department of Pathology and Tumor Biology, Kyoto University Data Access Committee

  Dac EGAC00001000327

• K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Norway

  Dac EGAC00001000848

• University Clinic Erlangen/ German Cancer Research Center rare tumors data access committee

  Dac EGAC00001001053

• Department of Pathology and Tumor Biology, Kyoto University Data Access Committee

  Dac EGAC00001001140

• Guangzhou Medical University LAM Data Access Committee

  Dac EGAC00001001148

• Department of Pathology and Tumor Biology, Kyoto University Data Access Committee

  Dac EGAC00001001232

• Department of Pathology and Tumor Biology, Kyoto University Data Access Committee

  Dac EGAC00001001235

• Department of Pathology and Tumor Biology, Kyoto University Data Access Committee

  Dac EGAC00001001292

• Department of Pathology and Tumor Biology, Kyoto University Data Access Committee

  Dac EGAC00001001299