Dataset Information

T2D-GENES Multi-Ethnic Exome Sequencing Study: UK South Asian

ABSTRACT:

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.

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.

Table 1. T2D-GENES Whole Exome Sequencing Studies

Ancestry	Study	Countries of Origin	# Cases	# Controls
African American	Jackson Heart Study	US	502	527
African American	Wake Forest School of Medicine Study	US	518	532
East Asian	Korea Association Research Project	Korea	526	561
East Asian	Singapore Diabetes Cohort Study; Singapore Prospective Study Program	Singapore (Chinese)	486	592
European	Ashkenazi	US, Israel	506	352
European	Metabolic Syndrome in Men Study (METSIM)	Finland	484	498
European	Finland-United States Investigation of NIDDM Genetics (FUSION) Study	Finland	472	476
European	Kooperative Gesundheitsforschung in der Region Augsburg (KORA)	Germany	97	90
European	UK Type 2 Diabetes Genetics Consortium (UKT2D)	UK	322	320
European	Malmö-Botnia Study	Finland, Sweden	478	443
Hispanic	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	US	272	219
Hispanic	Starr County, Texas	US	749	704
South Asian	London Life Sciences Population Study (LOLIPOP)	UK (Indian Asian)	530	538
South Asian	Singapore Indian Eye Study	Singapore (Indian Asian)	563	585

The London Life Sciences Population Study (LOLIPOP) contributed 530 cases and 538 controls to T2D-GENES Project 1.

PROVIDER: phs001093 | dbGaP |

SECONDARY ACCESSION(S): PRJNA316527PRJNA316528

REPOSITORIES: dbGaP

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			Action	DRS
	GapExchange_phs001093.v1.p1.xml	Xml
	dbGaPEx2.1.5.xsd	Other
	Study_Report.phs001093.T2D_GENES_UK_SouthAsian.v1.p1.MULTI.pdf	Pdf
	manifest_phs001093.T2D_GENES_UK_SouthAsian.v1.p1.c1.DS-T2D-IRB-RD.pdf	Pdf
	phs001093.v1.pht005611.v1.T2D_GENES_UK_South_Asian_Sample.data_dict.xml	Xml

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Project description: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. 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. Table 1. T2D-GENES Whole Exome Sequencing Studies <table border="1"> <tr> <th>Ancestry</th> <th>Study</th> <th>Countries of Origin</th> <th># Cases</th> <th># Controls</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> The Singapore studies contributed 1049 cases and 1177 controls to T2D-GENES Project 1.

Project description: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. 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. Table 1. T2D-GENES Whole Exome Sequencing Studies <table border="1"> <tr> <th>Ancestry</th> <th>Study</th> <th>Countries of Origin</th> <th># Cases</th> <th># Controls</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> The Ashkenazi study contributed 506 cases and 352 controls to T2D-GENES Project 1.

Project description: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. 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. Table 1. T2D-GENES Whole Exome Sequencing Studies <table border="1"> <tr> <th>Ancestry</th> <th>Study</th> <th>Countries of Origin</th> <th># Cases</th> <th># Controls</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> The Korea Association Research Project (KARE) studies contributed 526 cases and 561 controls to T2D-GENES Project 1.

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: 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> 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. 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>. <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> The Diabetes in Mexico Study (DMS) study contributed 1,522 cases and 1,546 controls to the 52k T2D exome sequencing study.

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> 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. 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. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies <table border="1"> <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>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> The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

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> 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. 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. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies <table border="1"> <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 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> The research studies in Hong Kong contributed 493 cases and 485 controls to T2D-GENES Follow-Up study.

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> 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. 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. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies <table border="1"> <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>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> The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study.

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: <table> <tr> <td> Animal model </td> <td> Sample source </td> <td> Sample name </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> 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.

Project description:Description of Cohort: 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. Blood Collection: 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. Measurement of Breast Density: 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. 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. Table: 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> Measurement of Breast Density in Cohort: 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. SXA for Quantifying Breast Density: 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. 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. 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. Reproducibility of breast density measures: 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. 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. 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.

Project description:This pharmacogenomic study focused on the response of patients with MDD to an 8-week course of treatment with citalopram or escitalopram. Briefly, clinical assessments and research assessments were performed at each study visit as summarized in Table 1. Many patients continued on antidepressant medication after the 8 week study. Table 1: Study timeline and patient contacts. <table border="1"> <tr> <th>Week</th> <th>Consent/Med Hx</th> <th>Write Rx</th> <th>SI Qx</th> <th>SCID</th> <th>HRS-D17</th> <th>QIDSC16</th> <th>CGI-I</th> </tr> <tr> <td>0</td> <td>SC</td> <td>RC</td> <td>RC</td> <td>SC</td> <td>SC</td> <td>SC</td> <td></td> </tr> <tr> <td>4</td> <td></td> <td>RC</td> <td>RC</td> <td></td> <td>SC</td> <td>SC</td> <td>RC</td> </tr> <tr> <td>8</td> <td></td> <td>RC</td> <td>RC</td> <td></td> <td>SC</td> <td>SC</td> <td>RC</td> </tr> </table> HRS-D17=Hamilton Rating Scale for Depression, QIDS-C16=Quick Inventory of Depressive Symptomatology, CGI-I=Clinical Global Impression-Improvement, SCID=Structured Clinical Interview for DSM-IV, SC=Study Coordinator, RC=Research Clinician. Enrollment and baseline assessment. Upon initial intake, the Study Coordinator (SC) obtained informed consent as well as clinical and demographic information, including history of bone marrow or liver transplant or blood transfusion within the previous 6 weeks, and prior history of treatment during the current major depressive episode. The SC completed the Structured Clinical Interview for DSM-IV (SCID), the HRS-D17 (17-item Hamilton Rating Scale for Depression) and the QIDS-C16 (Quick Inventory of Depressive Symptomatology) and reviewed the inclusion/exclusion criteria. After review with the Research Clinician (RC) and when appropriate, after a negative pregnancy test, the SC invited the subject to participate in the study if entry criteria were met. If the subject agreed, he/she received treatment according to the study protocol. Treatment schedule. Participants selected for inclusion in the study were seen at weeks 0, 4, and 8. The appropriate treatment antidepressant (citalopram or escitalopram) was determined following discussion between the patient and RC concerning medical, financial, and insurance considerations. The study medication citalopram was given in tablet or liquid form, depending on the patient's need. A fixed-flexible dose schedule was employed with the possibility of a dose escalation. In particular, the initial dose of citalopram was 20 mg and escitalopram was 10 mg. This dose was increased to 40 mg and 20 mg, respectively, after 4 weeks if the subject had a score of >/= 6 on the QIDS-C16 and the RC concluded that the subject could tolerate the increase. If necessary, dose was reduced at the discretion of the RC. The importance of medication compliance was discussed with the subject, and subjects were asked to bring in the medication at each visit for the purpose of counting remaining pills to assess compliance. Participants may have had an abbreviated course of therapy if they were clearly intolerant of the drug or failed to respond to a 40 mg dose of citalopram or a 20 mg dose of escitalopram. They then received standard treatment from a primary physician or psychiatrist with different medications and/or therapeutic modalities (e.g. psychotherapy). Special attention was given to subjects with suicidal ideation. Those subjects were offered additional appointments as needed to ensure their safety. Participants were also contacted by telephone at week 1 and week 2 by the Clinical Nurse Specialist (CNS) or other study personnel to ensure medication compliance and patient safety. The CNS was supervised by the study psychiatrist and principal investigator and deferred to the physician's judgment as needed. The SC was trained to notify the RC at the time of the clinical visits or the phone interviews if the subject endorsed any suicidal ideation or plans. For those subjects who were unable to attend the follow-up visits as scheduled, the patient was contacted by phone to complete the HRS-D17/QIDS-C16. The participant was also asked to return to the clinic to complete a final blood draw for the study. Adjunctive and concurrent medications. Adjunctive treatments were those used to manage transient associated symptoms (e.g., insomnia) or transient or longer-term medication side effects (e.g., sexual dysfunction). Adjunctive treatments that were not used to treat depression were allowed during the study. However, drugs in the exclusion criteria for this study were not used as adjunctive therapies. Subjects were allowed to participate in the study while receiving concurrent medications for general medical conditions as long as there was no contraindication to use while taking citalopram or escitalopram. Drug efficacy phenotype evaluation. The change in QIDS-C16 score and change in HRS-D17 score were used as the major research outcome measures to assess drug response. At each clinical research visit, the RC also completed the Clinician Global Impression of Improvement (CGI-I) scale. For the primary genome-wide association analyses, dichotomous outcome variables, remission and response, were defined based on the QIDS-C16 last visit score. Remission was defined as a QIDS-C16 score of 5 or less, while response was defined as at least a 50% reduction in the QIDS-C16 score from baseline. Specimen collection. Specimen collections were obtained by the General Clinical Research Center (GCRC) at St. Mary's Hospital (SMH). Subjects had blood drawn on an outpatient basis at GCRC-SMH on three separate occasions - baseline (0), week 4 and week 8 visits. Prior to sample collection, date and time of last dose of study medication was gathered at the 4 and 8 week visits. For those patients who were unable to complete the regularly scheduled visits, a dismissal blood draw was requested. GCRC then shipped samples to Mayo Clinic's Biospecimens Accessioning and Processing Lab. Genotyping and biomarker assays. DNA from 529 patients was genotyped by the RIKEN Center for Genomic Medicine (Yokohama, Japan) using Illumina Human610-Quad BeadChips (Illumina, San Diego, CA). The study also included the determination of plasma drug levels at weeks 4 and 8, and metabolite levels at baseline and weeks 4 and 8 for a subset of subjects. The primary genome-wide association study based on these data, which includes a summary of the protocol, subject description, selection of subjects for genetic analyses, and definitions of clinical outcomes, was published in the Pharmacogenomics Journal (<a href="http://www.ncbi.nlm.nih.gov/pubmed/22907730">Ji et al., 2012</a>).

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T2D-GENES Multi-Ethnic Exome Sequencing Study: UK South Asian

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