Alzheimer's Disease Sequencing Project (ADSP)
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ABSTRACT: LOCATION CHANGE FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) DATA: Please go to NIAGADS DSS to apply for build 38 ADSP genetic and phenotypic data. See Background below for more details. For instructions on how to access the additional ADSP data that are shared through NIAGADS DSS, visit the Application Instructions page. Background: Additional sequencing data are continuously being generated by the ADSP. These data are mapped to the latest Genome Reference Consortium human genome build GRCh38 (hg38) and are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). As of May 1, 2020 there are 4,789 whole genomes and 19,922 whole exomes available to the research community. Later in 2020 there will be a total of ~17,000 whole genomes and 19,922 whole exomes available through NIAGADS DSS (ng00067). The total number of genomes from multi-ethnic cohorts is anticipated to exceed 50,000. Please see the ADSP Design page for the complete study description. ADSP whole exome and whole genome sequence data that were shared through dbGaP were mapped to the GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.
ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members.
SECONDARY ACCESSION(S): PRJNA205518PRJNA205516
REPOSITORIES: dbGaP
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Project description:GOAL: Identification of genes and/or pathways involved in the pathogenesis of animal models of Rheumatoid Arthritis (RA). Total RNA samples were extracted from synovial fibroblast ex vivo cultures or whole joints (J), isolated from arthritic mice (197, DARE) and their corresponding normal (F1, wt) littermates. Fluorescent-labeled cRNA probes were utilized to hybridize (in duplicates for 197, indicated by "new") the Affymetrix Mu11K oligonucleotide DNA chipset (A+B). In detail the samples are:<br> <table> <tr> <td> <u>Animal model</u> </td> <td> <u>Sample source</u> </td> <td> <u>Sample name</u> </td> </tr> <tr> <td> Tg197 </td> <td> Tg197 ex-vivo cultured synoviocyte populations </td> <td> 197 </td> </tr> <tr> <td> Tg197 </td> <td> Tg197 ex-vivo cultured synoviocyte populations </td> <td> 197new </td> </tr> <tr> <td> Tg197 </td> <td> wt ex-vivo cultured synoviocyte populations </td> <td> F1 </td> </tr> <tr> <td> Tg197 </td> <td> wt ex-vivo cultured synoviocyte populations </td> <td> F1new </td> </tr> <tr> </tr> <tr> <td> Tg197 </td> <td> Tg197 whole joints </td> <td> 197J </td> </tr> <tr> <td> Tg197 </td> <td> Tg197 whole joints </td> <td> 197Jnew </td> </tr> <tr> <td> Tg197 </td> <td> wt whole joints </td> <td> F1J </td> </tr> <tr> <td> Tg197 </td> <td> wt whole joints </td> <td> F1Jnew </td> </tr> <tr> </tr> <tr> <td> DARE </td> <td> DARE ex-vivo cultured synoviocyte populations </td> <td> DARE </td> </tr> <tr> <td> DARE </td> <td> wt ex-vivo cultured synoviocyte populations </td> <td> wt </td> </tr> <tr> <td> DARE </td> <td> DARE whole joints </td> <td> DAREJ </td> </tr> <tr> <td> DARE </td> <td> wt whole joints </td> <td> wtJ </td> </tr> </table> <br> Submitted files carry the extension A or B, corresponding to the subArrays of chipset Mu11K. Arthritic samples were always compared with the corresponding wt sample and not to a common reference chip.
2005-06-30 | E-MEXP-255 | biostudies-arrayexpress
Project description:<p>The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: <ul> <li>Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES)</li> <li>Genetics of Type 2 Diabetes (GoT2D)</li> <li>Exome Sequencing Project (ESP)</li> <li>Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D)</li> <li>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP)</li> <li>Progress in Diabetes Genetics in Youth (ProDIGY)</li> </ul> </p> <p>This data generated from the SIGMA Diabetes in Mexico Study (DMS) was part of the Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D), which is an international research consortium funded by the Carlos Slim Foundation that seeks to identify the genetic risk factors for type 2 diabetes (T2D) in Mexico and Latin America and translate those findings into improved treatment and prevention of diabetes. The SIGMA T2D project has sequenced and genotyped more than 13,000 samples from Mexican and Mexican Americans.</p> <p>The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: <a href="https://esp.gs.washington.edu/drupal/dbGaP_Releases">https://esp.gs.washington.edu/drupal/dbGaP_Releases</a>. </p> <p><table style="width:100%" border="1"> <caption>Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies</caption> <tr> <th>Ancestry</th> <th>Consortia</th> <th>Study</th> <th>Countries of Origin</th> <th># Cases</th> <th># Controls</th> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Jackson Heart Study</td> <td>US</td> <td>500</td> <td>526</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>530</td> </tr> <tr> <td>African American</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>467</td> <td>1374</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Follow up study</td> <td>BioMe Biobank Program (BioMe)</td> <td>US</td> <td>1297</td> <td>1256</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1& Follow up Study</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>1486</td> <td>1568</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow up study</td> <td>Korea SNUH</td> <td>South Korea</td> <td>450</td> <td>475</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow up study</td> <td>Research Studies in Hong Kong (Hong Kong)</td> <td>Hong Kong</td> <td>493</td> <td>485</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>355</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Malmo-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>European</td> <td>LuCamp</td> <td>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp)</td> <td>Denmark</td> <td>997</td> <td>997</td> </tr> <tr> <td>European</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>390</td> <td>2843</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow up study</td> <td>Genetics of Diabetes and Audit Research Tayside Study (GoDARTS)</td> <td>Scotland, UK</td> <td>960</td> <td>966</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow up study</td> <td>Framingham Heart Study (FHS)</td> <td>US</td> <td>396</td> <td>596</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>218</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1 & SIGMAv2</td> <td>Starr County, Texas</td> <td>US</td> <td>1762</td> <td>1738</td> </tr> <tr> <td>Hispanic</td> <td>SIGMAv1</td> <td>Mexico City Diabetes Study</td> <td>Mexico</td> <td>281</td> <td>549</td> </tr> <tr> <td>Hispanic</td> <td>SIGMAv1 & v2</td> <td>Multiethnic Cohort (MEC)</td> <td>US</td> <td>1476</td> <td>1443</td> </tr> <tr> <td>Hispanic</td> <td>SIGMAv1 & v2</td> <td>UNAM/INCMNSZ Diabetes Study (UIDS)</td> <td>Mexico</td> <td>1998</td> <td>1977</td> </tr> <tr> <td>Hispanic</td> <td>SIGMAv1 & v2</td> <td>Diabetes in Mexico Study (DMS)</td> <td>Mexico</td> <td>1522</td> <td>1546</td> </tr> <tr> <td>Multi ethnic</td> <td>ProDIGY</td> <td>Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY)</td> <td>US</td> <td>3097</td> <td>0</td> </tr> <tr> <td>Multi ethnic</td> <td>ProDIGY</td> <td>SEARCH for Diabetes in Youth (SEARCH)</td> <td>US</td> <td>553</td> <td>0</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>531</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1 & Follow up study</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>1640</td> <td>1478</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Follow up study</td> <td>Pakistan Genomic Resource (PGR)</td> <td>Pakistan</td> <td>914</td> <td>932</td> </tr> </table> </p> <p>The Diabetes in Mexico Study (DMS) study contributed 1,522 cases and 1,546 controls to the 52k T2D exome sequencing study.</p>
| phs001388 | dbGaP
Project description:The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: <ul> <li>Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES)</li> <li>Genetics of Type 2 Diabetes (GoT2D)</li> <li>Exome Sequencing Project (ESP)</li> <li>Slim Initiative in Genomic Medicine for the Americas (SIGMA)</li> <li>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP)</li> <li>Progress in Diabetes Genetics in Youth (ProDIGY)</li> </ul> <p>This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. </p> <p><b>Table 1.</b> 52,000 sample T2D Case/Control Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th>Consortia</th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Jackson Heart Study</td> <td>US</td> <td>502</td> <td>527</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>532</td> </tr> <tr> <td>African American</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>467</td> <td>1374</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Follow-Up Study</td> <td>BioMe Biobank Program (BioMe)</td> <td>US</td> <td>1294</td> <td>1254</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1 and Follow-Up Study</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>1486</td> <td>1568</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Korea SNUH</td> <td>South Korea</td> <td>450</td> <td>475</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Research Studies in Hong Kong (Hong Kong)</td> <td>Hong Kong</td> <td>493</td> <td>485</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>355</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>European</td> <td>LuCamp</td> <td>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp)</td> <td>Denmark</td> <td>997</td> <td>997</td> </tr> <tr> <td>European</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>390</td> <td>2843</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow-Up Study</td> <td>Genetics of Diabetes and Audit Research Tayside Study (GoDARTS)</td> <td>Scotland, UK</td> <td>960</td> <td>966</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow-Up Study</td> <td>Framingham Heart Study (FHS)</td> <td>US</td> <td>396</td> <td>596</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>218</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1 and SIGMA v2</td> <td>Starr County, Texas</td> <td>US</td> <td>1762</td> <td>1738</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1</td> <td>Mexico City Diabetes Study</td> <td>Mexico</td> <td>281</td> <td>549</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>Multiethnic Cohort (MEC)</td> <td>US</td> <td>1476</td> <td>1443</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>UNAM/INCMNSZ Diabetes Study (UIDS)</td> <td>Mexico</td> <td>1998</td> <td>1977</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>Diabetes in Mexico Study (DMS)</td> <td>Mexico</td> <td>1522</td> <td>1546</td> </tr> <tr> <td>Multiethnic</td> <td>ProDIGY</td> <td>Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY)</td> <td>US</td> <td>3097</td> <td>0</td> </tr> <tr> <td>Multiethnic</td> <td>ProDIGY</td> <td>SEARCH for Diabetes in Youth (SEARCH)</td> <td>US</td> <td>553</td> <td>0</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>531</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1 and Follow-Up Study</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>1640</td> <td>1478</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Pakistan Genomic Resource (PGR)</td> <td>Pakistan</td> <td>914</td> <td>932</td> </tr> </table> <p>The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study. </p>
| phs001490 | dbGaP
Project description:The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: <ul> <li>Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES)</li> <li>Genetics of Type 2 Diabetes (GoT2D)</li> <li>Exome Sequencing Project (ESP)</li> <li>Slim Initiative in Genomic Medicine for the Americas (SIGMA)</li> <li>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP)</li> <li>Progress in Diabetes Genetics in Youth (ProDIGY)</li> </ul> <p>This data generated from the Hong Kong cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. </p> <p><b>Table 1.</b> 52,000 sample T2D Case/Control Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th>Consortia</th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Jackson Heart Study</td> <td>US</td> <td>500</td> <td>526</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>530</td> </tr> <tr> <td>African American</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>467</td> <td>1374</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Follow-Up Study</td> <td>BioMe Biobank Program (BioMe)</td> <td>US</td> <td>1297</td> <td>1256</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1 and Follow-Up Study</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>1486</td> <td>1568</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Korea SNUH</td> <td>South Korea</td> <td>450</td> <td>475</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Research Studies in Hong Kong (Hong Kong)</td> <td>Hong Kong</td> <td>493</td> <td>485</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>352</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>European</td> <td>LuCamp</td> <td>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp)</td> <td>Denmark</td> <td>997</td> <td>997</td> </tr> <tr> <td>European</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>390</td> <td>2843</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow-Up Study</td> <td>Genetics of Diabetes and Audit Research Tayside Study (GoDARTS)</td> <td>Scotland, UK</td> <td>960</td> <td>966</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow-Up Study</td> <td>Framingham Heart Study (FHS)</td> <td>US</td> <td>396</td> <td>596</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>218</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1 and SIGMA v2</td> <td>Starr County, Texas</td> <td>US</td> <td>1762</td> <td>1738</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1</td> <td>Mexico City Diabetes Study</td> <td>Mexico</td> <td>281</td> <td>549</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>Multiethnic Cohort (MEC)</td> <td>US</td> <td>1476</td> <td>1443</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>UNAM/INCMNSZ Diabetes Study (UIDS)</td> <td>Mexico</td> <td>1998</td> <td>1977</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>Diabetes in Mexico Study (DMS)</td> <td>Mexico</td> <td>1522</td> <td>1546</td> </tr> <tr> <td>Multiethnic</td> <td>ProDIGY</td> <td>Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY)</td> <td>US</td> <td>3097</td> <td>0</td> </tr> <tr> <td>Multiethnic</td> <td>ProDIGY</td> <td>SEARCH for Diabetes in Youth (SEARCH)</td> <td>US</td> <td>553</td> <td>0</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>531</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1 and Follow-Up Study</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>1640</td> <td>1478</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Pakistan Risk of Myocardial Infarction Study (PROMIS)</td> <td>Pakistan</td> <td>914</td> <td>932</td> </tr> </table> <p>The research studies in Hong Kong contributed 493 cases and 485 controls to T2D-GENES Follow-Up study.</p>
| phs001504 | dbGaP
Project description:The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: <ul> <li>Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES)</li> <li>Genetics of Type 2 Diabetes (GoT2D)</li> <li>Exome Sequencing Project (ESP)</li> <li>Slim Initiative in Genomic Medicine for the Americas (SIGMA)</li> <li>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP)</li> <li>Progress in Diabetes Genetics in Youth (ProDIGY)</li> </ul> <p>This data generated from the Pakistan Genomic Resource (PGR) cohort was part of the T2-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. </p> <p><b>Table 1.</b> 52,000 sample T2D Case/Control Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th>Consortia</th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Jackson Heart Study</td> <td>US</td> <td>502</td> <td>527</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Project 1</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>532</td> </tr> <tr> <td>African American</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>467</td> <td>1374</td> </tr> <tr> <td>African American</td> <td>T2D-GENES Follow-Up Study</td> <td>BioMe Biobank Program (BioMe)</td> <td>US</td> <td>1297</td> <td>1256</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Project 1 and Follow-Up Study</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>1486</td> <td>1568</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Korea SNUH</td> <td>South Korea</td> <td>450</td> <td>475</td> </tr> <tr> <td>East Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Research Studies in Hong Kong (Hong Kong)</td> <td>Hong Kong</td> <td>493</td> <td>485</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>355</td> </tr> <tr> <td>European</td> <td>T2D-GENES Project 1</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>GoT2D</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>European</td> <td>LuCamp</td> <td>Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp)</td> <td>Denmark</td> <td>997</td> <td>997</td> </tr> <tr> <td>European</td> <td>ESP</td> <td>Exome Sequencing Project (ESP)</td> <td>US</td> <td>390</td> <td>2843</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow-Up Study</td> <td>Genetics of Diabetes and Audit Research Tayside Study (GoDARTS)</td> <td>Scotland, UK</td> <td>960</td> <td>966</td> </tr> <tr> <td>European</td> <td>T2D-GENES Follow-Up Study</td> <td>Framingham Heart Study (FHS)</td> <td>US</td> <td>396</td> <td>596</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>218</td> </tr> <tr> <td>Hispanic</td> <td>T2D-GENES Project 1 and SIGMA v2</td> <td>Starr County, Texas</td> <td>US</td> <td>1762</td> <td>1738</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1</td> <td>Mexico City Diabetes Study</td> <td>Mexico</td> <td>281</td> <td>549</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>Multiethnic Cohort (MEC)</td> <td>US</td> <td>1476</td> <td>1443</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>UNAM/INCMNSZ Diabetes Study (UIDS)</td> <td>Mexico</td> <td>1998</td> <td>1977</td> </tr> <tr> <td>Hispanic</td> <td>SIGMA v1 and SIGMA v2</td> <td>Diabetes in Mexico Study (DMS)</td> <td>Mexico</td> <td>1522</td> <td>1546</td> </tr> <tr> <td>Multiethnic</td> <td>ProDIGY</td> <td>Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY)</td> <td>US</td> <td>3097</td> <td>0</td> </tr> <tr> <td>Multiethnic</td> <td>ProDIGY</td> <td>SEARCH for Diabetes in Youth (SEARCH)</td> <td>US</td> <td>553</td> <td>0</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>531</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Project 1 and Follow-Up Study</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>1640</td> <td>1478</td> </tr> <tr> <td>South Asian</td> <td>T2D-GENES Follow-Up Study</td> <td>Pakistan Genomic Resource (PGR)</td> <td>Pakistan</td> <td>903</td> <td>930</td> </tr> </table> <p>The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study. </p>
| phs001552 | dbGaP
Project description:<p><u>Description of Cohort</u>: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density.</p> <p><i>Blood Collection</i>: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women.</p> <p><i>Measurement of Breast Density</i>: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below.</p> <p>The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women.</p> <p><b>Table</b>: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. <table border="1"> <tr> <th>Variable</th> <th>Median/Percentage</th> </tr> <tr> <td>Age (Median/IQR)</td> <td align="center">52 (46-59)</td> </tr> <tr> <td>Ethnicity</td> <td></td> </tr> <tr> <td align="right">Caucasian/White</td> <td align="center">0.76</td> </tr> <tr> <td align="right">Asian/Pacific Islander</td> <td align="center">0.141</td> </tr> <tr> <td align="right">Hispanic</td> <td align="center">0.029</td> </tr> <tr> <td align="right">Mixed Race/Ethnicity</td> <td align="center">0.039</td> </tr> <tr> <td align="right">African American/Black</td> <td align="center">0.022</td> </tr> <tr> <td align="right">American Indian</td> <td align="center">0.001</td> </tr> <tr> <td align="right">Other</td> <td align="center">0.009</td> </tr> <tr> <td>First degree relative with breast cancer</td> <td align="center">0.17</td> </tr> <tr> <td>Age at first birth</td> <td></td> </tr> <tr> <td>Nulliparous</td> <td align="center">0.39</td> </tr> <tr> <td align="right">Age<20</td> <td align="center">0.043</td> </tr> <tr> <td align="right">Age>40</td> <td align="center">0.032</td> </tr> <tr> <td align="right">Age<30, ≥20</td> <td align="center">0.251</td> </tr> <tr> <td align="right">Age>30, ≤40</td> <td align="center">0.282</td> </tr> </table> </p> <p><u>Measurement of Breast Density in Cohort</u>: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk.</p> <p><i>SXA for Quantifying Breast Density</i>: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC.</p> <p>Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels.</p> <p>The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram.</p> <p><i>Reproducibility of breast density measures</i>: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9.</p> <p>In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density.</p> <p>Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: <a href="http://www.ncbi.nlm.nih.gov/pubmed/21610220" target="_blank">21610220</a>). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.</p>
| phs000395.v1.p1 | EGA
Project description:<p>T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP.</p> <p> <p><b>Table 1.</b> T2D-GENES Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>Jackson Heart Study</td> <td>US</td> <td>502</td> <td>527</td> </tr> <tr> <td>African American</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>532</td> </tr> <tr> <td>East Asian</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>486</td> <td>592</td> </tr> <tr> <td>European</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>352</td> </tr> <tr> <td>European</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>Hispanic</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>219</td> </tr> <tr> <td>Hispanic</td> <td>Starr County, Texas</td> <td>US</td> <td>749</td> <td>704</td> </tr> <tr> <td>South Asian</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>530</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>563</td> <td>585</td> </tr> </table> <p>The Ashkenazi study contributed 506 cases and 352 controls to T2D-GENES Project 1.</p> </p>
| phs001095 | dbGaP
Project description:<p>T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP.</p> <p> <p><b>Table 1.</b> T2D-GENES Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>Jackson Heart Study</td> <td>US</td> <td>502</td> <td>527</td> </tr> <tr> <td>African American</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>532</td> </tr> <tr> <td>East Asian</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>486</td> <td>592</td> </tr> <tr> <td>European</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>352</td> </tr> <tr> <td>European</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>Hispanic</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>219</td> </tr> <tr> <td>Hispanic</td> <td>Starr County, Texas</td> <td>US</td> <td>749</td> <td>704</td> </tr> <tr> <td>South Asian</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>530</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>563</td> <td>585</td> </tr> </table> <p>The Korea Association Research Project (KARE) studies contributed 526 cases and 561 controls to T2D-GENES Project 1.</p> </p>
| phs001096 | dbGaP
Project description:<p>T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP.</p> <p> <p><b>Table 1.</b> T2D-GENES Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>Jackson Heart Study</td> <td>US</td> <td>502</td> <td>527</td> </tr> <tr> <td>African American</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>532</td> </tr> <tr> <td>East Asian</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>486</td> <td>592</td> </tr> <tr> <td>European</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>352</td> </tr> <tr> <td>European</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>Hispanic</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>219</td> </tr> <tr> <td>Hispanic</td> <td>Starr County, Texas</td> <td>US</td> <td>749</td> <td>704</td> </tr> <tr> <td>South Asian</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>530</td> <td>538</td> </tr> <tr> <td>South Asian</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>563</td> <td>585</td> </tr> </table> <p>The Singapore studies contributed 1049 cases and 1177 controls to T2D-GENES Project 1.</p> </p>
| phs001097 | dbGaP
Project description:<p>T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples) is a NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. </p> <p>The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a sub study, as it is not consented to be deposited in dbGAP.</p> <p> <p><b>Table 1.</b> T2D-GENES Whole Exome Sequencing Studies</p> <table border="1"> <tr> <th><b>Ancestry</b></th> <th><b>Study</b></th> <th><b>Countries of Origin</b></th> <th><b># Cases</b></th> <th><b># Controls</b></th> </tr> <tr> <td>African American</td> <td>Jackson Heart Study</td> <td>US</td> <td>502</td> <td>527</td> </tr> <tr> <td>African American</td> <td>Wake Forest School of Medicine Study</td> <td>US</td> <td>518</td> <td>532</td> </tr> <tr> <td>East Asian</td> <td>Korea Association Research Project</td> <td>Korea</td> <td>526</td> <td>561</td> </tr> <tr> <td>East Asian</td> <td>Singapore Diabetes Cohort Study; Singapore Prospective Study Program</td> <td>Singapore (Chinese)</td> <td>486</td> <td>592</td> </tr> <tr> <td>European</td> <td>Ashkenazi</td> <td>US, Israel</td> <td>506</td> <td>352</td> </tr> <tr> <td>European</td> <td>Metabolic Syndrome in Men Study (METSIM)</td> <td>Finland</td> <td>484</td> <td>498</td> </tr> <tr> <td>European</td> <td>Finland-United States Investigation of NIDDM Genetics (FUSION) Study</td> <td>Finland</td> <td>472</td> <td>476</td> </tr> <tr> <td>European</td> <td>Kooperative Gesundheitsforschung in der Region Augsburg (KORA)</td> <td>Germany</td> <td>97</td> <td>90</td> </tr> <tr> <td>European</td> <td>UK Type 2 Diabetes Genetics Consortium (UKT2D)</td> <td>UK</td> <td>322</td> <td>320</td> </tr> <tr> <td>European</td> <td>Malmö-Botnia Study</td> <td>Finland, Sweden</td> <td>478</td> <td>443</td> </tr> <tr> <td>Hispanic</td> <td>San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component</td> <td>US</td> <td>272</td> <td>219</td> </tr> <tr> <td>Hispanic</td> <td>Starr County, Texas</td> <td>US</td> <td>749</td> <td>704</td> </tr> <tr> <td>South Asian</td> <td>London Life Sciences Population Study (LOLIPOP)</td> <td>UK (Indian Asian)</td> <td>530</td> <td>538</td> </tr> <td>South Asian</td> <td>Singapore Indian Eye Study</td> <td>Singapore (Indian Asian)</td> <td>563</td> <td>585</td> </table> <p>The London Life Sciences Population Study (LOLIPOP) contributed 530 cases and 538 controls to T2D-GENES Project 1. </p> </p>
| phs001093 | dbGaP