Search Results - EGA European Genome-Phenome Archive

National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study

This is a case-control study of primary open angle glaucoma (POAG). POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. For this study we have formed a collaborative consortium contributing 2170 POAG cases and 2347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition has also been harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The NEIGHBOR consortium has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). The consortium includes eleven different centers where data collection and analysis take place. The eleven sites and investigators are: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman, D. Zack); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Eye Institute (X01HG005259).

Study phs000238

Lund HPI data access committee for Inspire

Phenotype data from human pancreatic islets from 191 donors, Lund University. Processed for the Inspire consortium.

Dataset EGAD00001005523

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

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

Study phs000558

Cellular and Molecular Characterization of Renal Cell Carcinoma

We are performing a comprehensive cellular and molecular characterization of renal cell carcinoma. This work includes an initial cohort of patients whose tumors (and adjacent normal tissue) underwent single cell analysis. Single-cell RNA sequencing (scRNA-seq) and TCR sequencing (scTCR-seq) analysis of untreated clear cell renal cell carcinoma tumor and adjacent normal tissue was performed across disease stages. This initial cohort includes 13 patients: 4 with early stage disease (stage I/II), 4 with locally advanced disease (stage III), and 5 with advanced/metastatic disease (stage IV). Whole exome sequencing on tumor and normal tissue was also performed. 

Study phs002252

Lund RNAseq data

RNAsequencing data from human pancreatic islets from 191 donors, Lund University. Processed for the Inspire consortium.

Dataset EGAD00001005512

Initial cohort of 500 solid tumors screened for Basket of Baskets

Study EGAS00001005893

NIDDK IBD Genetics Consortium Crohn's Disease Genome-Wide Association Study

This dataset contains data from a genome-wide association study performed with 968 Inflammatory Bowel Disease (IBD) affected cases and 995 unrelated controls using the Illumina HumanHap300 Genotyping BeadChip. Cases were selected to have Crohn's disease with ileal involvement, and controls were matched to cases based on sex and year of birth. Subjects were drawn from two cohorts: (1) persons with non-Jewish, European ancestry (561 cases and 563 controls), and (2) persons with Jewish ancestry (407 cases and 432 controls). Genotyping was performed at the Feinstein Institute for Medical Research. Seven-hundred fifty-four of the samples (468 cases and 286 controls) were taken from the NIDDK IBD Genetics Consortium cell line repository. These samples are identified in the IBD_Sample file. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are available, together with the Consortium's phenotyping manual and the forms used to collect the data. The remaining 1,209 samples were obtained from pre-existing collections ascertained through Cedars-Sinai Medical Center, Johns Hopkins University, University of Chicago, University of Montreal, University of Pittsburgh, University of Toronto, and the New York Health project (controls only). For these samples, only sex, cohort (Jewish vs. non-Jewish), and age at diagnosis (cases only) are available. Two-hundred three individuals from among the pre-existing samples did not provide consent to release their genotype data (designated as consent group 2 in the file IBD_Subject). Thus, individual genotype data are only provided for 1,760 samples. To compensate for this, we have provided summary results for each SNP. These are based on a stratified analysis testing case/control association. Fifty-one samples had a call rate less than 93% and were therefore excluded from this analysis, leaving an overall sample size of 1,963 - 51 = 1,912. X Chromosome Heterozygosity Nine samples have X chromosome heterozygosity that is neither consistent nor inconsistent with their phenotypic sex. One of these samples was found to have Turner Syndrome. The remaining 8 samples have heterozygosity ranging from 35-76%.

Study phs000130

Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

Study phs000629

Genetic Discovery and Application in a Clinical Setting: Continuing a Partnership (eMERGE Phase II)

The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites funded by the NHGRI to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. The eMERGE Network brings together researchers with a wide range of expertise in genomics, statistics, ethics, informatics, and clinical medicine from leading medical research institutions across the country. Each center participating in the consortium is uniquely situated to provide critical resources to this highly collaborative and productive network. Each site combines a biobank or study cohort with extensive genomic data and access to clinical data derived from electronic medical records. Sites are geographically dispersed and have diverse patient populations, including two sites focusing specifically on pediatrics. The eMERGE Network is comprised of 9 sites and one coordinating center. Each site maintains its own biorepository where DNA specimens are linked to phenotypic data contained within EMRs. Children's Hospital of Pennsylvania, PI: Hakon Hakonarson, MD, PhD Cincinnati Children's Medical Center with Boston Children's Hospital, PI: John Harley, MD, PhD - CCHMC and Ingrid Holm, MD, MPH - BCH Geisinger Health System, PI: David Carey, PhD and Marc Williams, MD Group Health Cooperative with University of Washington, PI: Eric Larson, MD, MPH - GHC and Gail Jarvik, MD, PhD - UW Marshfield Clinic with Essentia Institute of Rural Health, PI: Catherine McCarty, PhD, MPH - Essentia and Murray Brilliant, PhD - Marshfield Mayo Clinic, PI: Christopher Chute, MD, DrPH and Iftikhar Kullo, MD Icahn School of Medicine at Mount Sinai, PI: Erwin Bottinger, MD Northwestern University, PI: Rex Chisholm, PhD and Maureen Smith, MS Vanderbilt University, PI: Dan Roden, MD eMERGE Coordinating Center - Vanderbilt University, PI: Paul Harris, PhD Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes.

Study phs000948

National Human Genome Research Institute Tumor Sequencing Project (TSP) - Lung Adenocarcinoma

The Tumor Sequencing Project (TSP) Consortium is a collaboration among participants at the Baylor College of Medicine Human Genome Sequencing Center, the Broad Institute Genome Sequencing Platform, the Dana Farber Cancer Institute, the Memorial Sloan-Kettering Cancer Center, the Genome Sequencing Center and Siteman Cancer Center at Washington University, the M.D. Anderson Cancer Center and the University of Michigan Medical Center. The TSP Part A will pilot approaches to large-scale identification of genomic changes in tumors by sequencing the exonic regions of 623 genes in 188 specimens of adenocarcinoma of the lung, as well as using high density SNP genotyping arrays for high resolution identification of changes in chromosomal copy number. The TSP Part B will pilot approaches to tumor characterization of lung adenocarcinoma samples using next-generation sequencing technologies and benchmark those results against Part A data generated with ABI3730 instruments.

Study phs000144

Pancreatic Cancer Case Control Association Study

Pancreatic cancer is the fourth leading cause of cancer death in the United States. This is in large part due to the rapidly fatal course of this disease, as the vast majority of patients die within months of diagnosis and the five-year survival rate is less than 5. We have brought together over 8000 participants from 9 studies of pancreatic cancer, to conduct a GWAS of pancreatic cancer. The studies were drawn from the Pancreatic Cancer Case-Control consortium and include case-control studies from the United States, Europe and Australia. Sites include: Johns Hopkins National Familial Pancreas Tumor Registry, Mayo Clinic Biospecimen Resource for Pancreas Research, Ontario Pancreas Cancer Study (OPCS), Yale University, MD Anderson Case Control Study, Queensland Pancreatic Cancer Study, University of California San Francisco Molecular Epidemiology of Pancreatic Cancer Study, International Agency of Cancer Research and Memorial Sloan Kettering Cancer Center.

Study phs000648

Autism Sequencing Consortium (ASC)

The ARRA Autism Sequencing Collaboration was created in 2010 bringing together expert large-scale sequencing center (at the Baylor College of Medicine, PI Richard Gibbs and the Board Institute of MIT and Harvard, PI Mark J. Daly) and a collaborative network of research labs focused on the genetics of autism (brought together by the Autism Genome Project and the Autism Consortium). These groups worked together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes. The Autism Sequencing Consortium (ASC) was founded by Joseph D. Buxbaum and colleagues as an international group of scientists who share autism spectrum disorder (ASD) samples and genetic data. The PIs are Drs. Joseph D. Buxbaum (Icahn School of Medicine at Mount Sinai), Mark J. Daly (Broad Institute of MIT and Harvard), Bernie Devlin (University of Pittsburgh School of Medicine), Kathryn Roeder (Carnegie Mellon University, Matthew State and Stephan Sanders (University of California, San Francisco). The rationale for the ASC is described in Buxbaum et al. 2012, and this paper should be cited when referencing the data set. All shared data and analysis is hosted at a single site, which enables joint analysis of large-scale data from many groups. The ASC was first supported by a cooperative agreement grant to four lead sites funded by the National Institute of Mental Health (U01MH100233, U01MH100209, U01MH100229, U01MH100239), with additional support from the National Human Genome Research Institute. The NIMH recently renewed their support with a second grant (U01MH111661, U01MH111660, U01MH111658 and U01MH111662) to expand the project from 29,000 genomes to more than 50,000 exomes over the next 5 years. NHGRI provides ongoing sequencing support for the ASD through the Broad Center for Common Disease Genomics (UM1HG008895, Mark Daly, PI).

Study phs000298

ARDSnet and the iSPAAR Consortium: Genomic Basis of Susceptibility and Outcomes in Patients with the Acute Respiratory Distress Syndrome (ARDS)

Acute Respiratory Distress Syndrome (ARDS)/ Acute Lung Injury (ALI) is a syndrome defined by the presence of acute hypoxemic respiratory failure, bilateral pulmonary infiltrates on chest radiograph, a known clinical risk factor (e.g. sepsis, pneumonia, trauma, gastric fluid aspiration, pancreatitis, massive transfusion), and the absence of physiologic or clinical evidence of congestive heart failure. The Identification of SNPs Predisposing to Altered ALI Risk (iSPAAR) study is a multi-institutional cooperative study, funded through the NHLBI Recovery Act, that assembled samples and phenotype information from existing cohorts. The consortium included samples from patients with ARDS from the NIH NHLBI ARDS Clinical Trials Network (ARDSNet). Samples were obtained from 3 interventional treatment trials in patients with ARDS, including the Fluid and Catheter Treatment Trial (FACTT), the Albuterol to Treat Acute Lung Injury (ALTA) trial, and the Omega-3 Fatty Acid/Antioxidant Supplementation for ALI trial (Omega). In addition to ARDSnet samples, samples from the other cohorts included cases of established ARDS but also controls: critically ill patients who were at-risk for ARDS but who did not develop ARDS during their hospital course. These cohorts included the Molecular Epidemiology of Acute Respiratory Distress (MEA) Study enrolled at the Harvard University/Massachusetts General Hospital, the Systemic Inflammatory Immune Response Syndrome (SIRS) Patient Database and ICU Traumatic Injury cohorts from Harborview Medical Center, and cohorts collected from the ALI research programs at the University of Pennsylvania and the University of California, San Francisco. The Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000631 ARDSnet iSPAAR Consortium. phs000334 ESP_LungGO_ALI phs000686 ALI_GeneticRisk

Study phs000631

Aggregated panel-seq VCF for initial cohort screened for BoB

Aggregated VCF file from cancer genes panel seq for the initial (n=500) cohort of solid tumors screened for the Basket of Baskets study

Dataset EGAD00001008437

COVID_19_UK_CIC_Spatial

Understanding the immune response to SARS-CoV-2 is critical to our ability to control the coronavirus pandemic. Spatial transcriptomics will be performed on COVID-19 post-mortem tissues in collaboration with the UK - Coronavirus Immunology Consortium (UK-CIC). UK-CIC encompasses a concerted effort by the UK's world-leading immunology community to deliver a co-ordinated and agile national research programme to increase our understanding of how the immune system interacts with SARS-CoV-2. UK-CIC is led by Professor Paul Moss (University of Birmingham) and brings together 20 UK immunology centres of excellence, with support from the British Society for Immunology.

Study EGAS00001005817

McGill Epigenomics Mapping Centre

The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

Study EGAS00001000995

DNA Methylation in Prostate Tumor and Paired Benign Tissue for African and European Ancestry Men

We recruited prostate cancer (PCa) patients undergoing robotic-assisted laparoscopic radical prostatectomy at the University of Chicago Medical Center Urology Clinic between 2011 and 2017. Our study includes 76 African American (AA) and 75 European American (EA) men with PCa of Gleason Score (GS) ≥7, recruited by the Epidemiology Research Recruitment Core at the University of Chicago. All patients consented to the collection of questionnaire data, prostate tissue, and medical records. The study was approved by the Institutional Review Board of the University of Chicago. Following prostatectomy, prostate tissue was sent to the Human Tissue Research Center (HTRC) at the University of Chicago. Each sample underwent histological examination and Gleason scoring by University of Chicago genitourinary pathologists. The presence of adenocarcinoma was confirmed by overexpression of alpha-methylacyl-coenzyme-A racemase (AMACR) and areas for DNA extraction were marked. Tissue samples used for DNA extraction were obtained using with either a 1mm biopunch or laser microdissection of a 100 µm2 area of tissue. Genome-wide DNA methylation profiles were generated using Illumina's Infinium MethylationEPIC BeadChip array kit. Genome-wide SNP data was generated (from benign tissue DNA) using the Illumina Infinium Multi-Ethnic Global-8 v1.0 array at the University of Chicago Genomics Core Facility. We performed imputation using the Haplotype Reference Consortium (HRC, Version r1.1 2016) panel, which includes all samples from the 1,000 Genomes Project (Phase 3), using the Michigan Imputation Server. The imputed SNP data for mQTL analysis was imputed based on genotype SNP data which was all from benign tissue DNA and the methylation data was identified in both tumor and benign tissue, both AA and EA men, and identified QTLs co-occuring with prostate cancer susceptibility loci.Data including SNP genotypes, DNA methylation, tissue type, and participant characteristics will be available in dbGaP.

Study phs003516

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

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

Study phs003047

Center Common Disease Genomics [CCDG] - CVD - TAICHI

The TaiChi consortium consists of 6 studies that collaborated initially in a large scale metabochip study, and became an ongoing consortium for studies of cardiometabolic disease in the Chinese population in Taiwan. The six studies included the following: 1) SAPPHIRe (Stanford-Asian Pacific Program in Hypertension and Insulin Resistance), a family based study established in 1995 with an initial goal of identifying major genetic loci underlying hypertension and insulin resistance in East Asian populations, with Taiwan subjects participating in the TaiChi consortium; 2) TCAGEN (Taiwan Coronary Artery Disease GENetic), a cohort study that the enrolled patients undergoing coronary angiography or percutaneous intervention at the National Taiwan University Hospital (NTUH) in the setting of either stable angina pectoris or prior myocardial infarction; 3) TACT (TAiwan Coronary and Transcatheter intervention), a cohort study enrolled patients with angina pectoris and objective documentation of myocardial ischemia who underwent diagnostic coronary angiography and/or revascularization any time after October 2000 at the National Taiwan University Hospital (NTUH) (similar to TCAGEN but recruitment was independent of TCAGEN); 4) Taiwan DRAGON (Taiwan Diabetes and RelAted Genetic COmplicatioN), a cohort study of Type 2 diabetes at Taichung Veterans General Hospital (Taichung VGH) in Taiwan, with participants including individuals with either newly diagnosed or established diabetes (subjects with hyperglycemia who did not meet diagnostic criteria for Type 2 DM were not included); 5) TCAD (Taichung CAD study), includes patients with a variety of cardiovascular diseases who received care at the Taichung Veterans General Hospital (Taichung VGH), i.e. specifically individuals who were hospitalized for diagnostic and interventional coronary angiography examinations and treatment; 6) TUDR (Taiwan US Diabetic Retinopathy) enrolled subjects with Type 2 diabetes who received care at Taichung Veteran General Hospital (Taichung VGH), and a small number of subjects from Taipei Tri-Service General Hospital (TSGH); TUDR subjects underwent a complete ophthalmic and fundus examination to carefully document the presence and extent of retinopathy. From these 6 studies, subjects were selected based on completeness of standard metabolic phenotyping and knowledge of cardiac disease status (early onset coronary disease), to undergo whole genome sequencing at the Broad.

Study phs001487

African American Multiple Myeloma GWAS

The case set is from a case-control study designed to identify common genetic risk factors for multiple myeloma in African Americans, the population with the highest risk for this cancer. We conducted two GWAS and combined each of these with convenience controls consisting of unaffected African American participants in cohorts with existing GWAS data. We then conducted a meta-analysis of the two sets. Cases were persons of African ancestry with smoldering or active multiple myeloma identified at participating oncology clinics or through SEER registries, as part of the African American Multiple Myeloma Study (AAMMS) diagnosed from Jan 1, 1988 through July 31, 2016. The majority of the samples were collected from incident and prevalent cases diagnosed since Jan 1, 2008 (80.9%), with a minority obtained from biobanks from cases diagnosed prior to 2008 (19.1%). Additional samples were obtained from the Multiethnic Cohort (USC and University of Hawaii) (n=40), the University of California at San Francisco Multiple Myeloma Study (n=27), and from the Multiple Myeloma Research Consortium for secondary analysis (samples originally provided to MMRC by 8 additional sites (n=84)). We have identified the phenotype (smoldering myeloma, plasma cell multiple myeloma, or myeloma not otherwise specified (myeloma NOS) when myeloma phenotype was not known), sex and age at diagnosis in this data set. The initial GWAS set consisted of 1308 (1,305 passed QC) cases with DNA samples, with a GWAS performed on the Illumina Human Core. Controls consisted of 7,078 unaffected African American subjects who were participants in the African American Prostate and Breast Consortium, with existing GWAS data from the Illumina1M Duo BeadChip. The second GWAS set consisted of 529 African American multiple myeloma patients with samples (406 from University of Arkansas, results not contained in this dataset because NCI funds were not used for the collection and genotyping) with GWAS data resulting from the Illumina Mega-BeadChip v1.1. Controls were 2,390 unaffected African American participants in the Multiethnic Cohort with existing GWAS data from the same array. After QC and removal of duplicates within sets, sex mismatches, and removal of plasmacytoma cases (ICD-0 code 9731), this deposited data set contains the typed GWAS data for the Illumina Human Core (set 1) (n=1298), and for the MegaBead Chip v1.1 (set 2) (n=123), with the University of Arkansas samples removed, for a total of 1,421 case genotypes. Note that 13 samples that overlap set 1 and set 2 were included.

Study phs001632

Whole Genome Association Study of Systemic Lupus Erythematosus

The goal of this collaborative study was to identify new genetic risk factors for Systemic Lupus Erythematosus (SLE). To do this we conducted a genome-wide scan by combining the resources and expertise from a number of SLE researchers to establish a large sample set comprising 1311 SLE cases and 3340 controls. The SLE case samples were genotyped from the following collections: 338 subjects from the Autoimmune Biomarkers Collaborative Network (ABCoN), an NIH/NIAMS funded repository, 141 subjects from the Multiple Autoimmune Disease Genetics Consortium (MADGC), 613 subjects from the University of California San Francisco (UCSF) Lupus Genetics, and 335 subjects from the University of Pittsburgh Medical Center (UPMC), plus 8 samples collected at The Feinstein Institute for Medical Research. A total of 3583 control samples were examined in the association analyses. As part of this project, 1861 control samples were selected and then genotyped from the New York Cancer Project (NYCP), based on self-described ethnicity, gender and age. In addition, genotype data from 1722 control samples (all self-described North Americans of European descent) were obtained from the publicly available iControlDB database (http://www.illumina.com/pages.ilmn?ID=231).

Study phs000122

Genome wide association study for early onset coronary disease and related phenotypes (ADVANCE)

ADVANCE (Atherosclerotic Disease, VAscular functioN, and genetiC Epidemiology) is a large epidemiological study of genetic and non-genetic determinants of coronary artery disease (CAD) that started in 2000 as a collaborative effort between researchers at Stanford University and Kaiser Permanente of Northern California. The overarching goal of the study is to improve our ability to prevent, diagnose and treat CAD. The initial study included recruitment of over 3600 subjects (including 1873 subjects with incident clinically significant coronary disease and 1745 control subjects) from multiple race/ethnic backgrounds. A subset of ~ 500 subjects with very early onset coronary disease (men < 45 and women < 55) and ~ 500 similar aged controls were genotyped using the Illumina 550K platform as part of an NIH funded effort within the STAMPEED consortium.

Study phs000423

Multi-Omic Microbiome Study-Pregnancy Initiative (MOMS-PI)

The Vaginal Microbiome Consortium team at Virginia Commonwealth University has conducted the Multi-Omic Microbiome Study: Pregnancy Initiative (MOMS-PI) in collaboration with the Global Alliance to Prevent Prematurity and Stillbirth (GAPPS) to better understand how microbiome and host profiles change throughout pregnancy and influence the establishment of the nascent microbiome in neonates. The team particularly focused on elucidation of the role of the microbiome and its components in the etiology of preterm birth, which occurs in over 10% of pregnancies and which is the leading cause of death in neonates. Samples from 1594 women and their neonates were collected throughout pregnancy, at delivery and postpartum. The group has generated a comprehensive dataset of multiple omics technologies. This longitudinal, large-scale effort was designed to provide a large-scale resource for the scientific community. The study also permits characterization of temporal dynamics of the microbiome in pregnancy and factors associated with preterm birth.

Study phs001523

Proteogenomic Characterization Unveils Biomarkers Associated With Chemoresistance in Muscle Invasive Bladder Cancer

Cisplatin-based neoadjuvant chemotherapy (NAC) combined with radical cystectomy has been used as a standard of care for patients with clinically non-metastatic muscle invasive urothelial bladder cancer, but 40-50% patients will benefit from the treatment. Molecular subtypes of muscle invasive bladder cancer (MIBC) provide a possible biomarker roadmap that may help identify patients who may or may not respond to NAC. Recently, by integrating Mass Spectrometry-based proteomics, proteogenomic studies from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) have demonstrated the potential of this approach in prioritizing candidate driver genes and facilitating understanding of the chemotherapy resistance mechanisms. To demonstrate the proteogenomic workflow for investigating the mechanisms underlying chemotherapy resistance in MIBC, we conducted proteogenomic characterization of 46 pre- and 14 post- treatment tumors, including whole exome sequencing (WES), mRNA sequencing, Tandem Mass Tag (TMT)-proteomics, or TMT-phosphoproteomic. These samples were selected from an initial cohort of 143 MIBC tissues and filtered by tumor purity, clinical history, pathological response, and proteomic quality control metrics. The final cohort comprised samples from 53 patients, including 45 with both genomic and proteomic data and 8 with genomic data only.Our multi-omics-based clustering reveals subtypes associated with chemotherapy sensitivity. Protein abundance of a short isoform of ATAD1 and RAF family proteins were identified as biomarkers of chemosensitivity which highlights the importance of proteomics data. Integration of proteomic and phosphoproteomic data reveals Wnt signaling via GSK3B-S9 phosphorylation and the JAK/STAT pathway as potential targets to overcome chemoresistance. Correlations between PD-L1 and TROP-2/NECTIN-4 indicate an additive benefit of combination therapy targeting these proteins. Our data analysis clearly demonstrates that proteogenomic plays an important role in uncovering potential resistance mechanisms that operate only at protein and Post-Translational Modification (PTM) levels. Proteomics data can be accessed through PRIDE with ID PXD060290. RNA-seq and whole-exome sequencing (WES) FASTQ files are archived in the dbGaP database.

Study phs004049

Myocardial Infarction Genetics Exome Sequencing Consortium: University of Lubeck

MI cases were recruited from the German MI Family Study and the Angio-Lub study. Controls were recruited from the German MI Family Study and the Angio-Lub study. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

Study phs000990

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

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