publication . Article . Other literature type . 2019

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls

Flannick, Jason; Mercader, Josep M.; Fuchsberger, Christian; Udler, Miriam S.; Mahajan, Anubha; Wessel, Jennifer; Teslovich, Tanya M.; Caulkins, Lizz; Koesterer, Ryan; Barajas-Olmos, Francisco; ...
Open Access
  • Published: 01 Jun 2019
  • Publisher: eScholarship, University of California
Abstract
<p>Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10<sup>−3</sup>) and candidate genes from knockout mice (P = 5.2 × 10<sup>−3</sup>). ...
Subjects
free text keywords: Broad Genomics Platform, DiscovEHR Collaboration, CHARGE, LuCamp, ProDiGY, GoT2D, ESP, SIGMA-T2D, T2D-GENES, AMP-T2D-GENES, Animals, Mice, Knockout, Humans, Diabetes Mellitus, Type 2, Case-Control Studies, Gene Frequency, Decision Support Techniques, Female, Male, Genome-Wide Association Study, Exome, Whole Exome Sequencing, General Science & Technology, MD Multidisciplinary, Article, Diabetes Mellitus, Type 2/genetics, Exome/genetics, Mice, Knockout, /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Journal Article, GENOME-WIDE ASSOCIATION, COMMON GENETIC-VARIATION, LOW-FREQUENCY, RARE VARIANTS, MUTATIONS, RISK, IDENTIFICATION, HERITABILITY, ARCHITECTURE, METAANALYSIS, 3121 Internal medicine, Multidisciplinary, Allele frequency, Medical genetics, medicine.medical_specialty, medicine, Minor allele frequency, Allele, Candidate gene, Genetics, Exome sequencing
Funded by
NIH| IMMUNOCOMPETENCY &NUTRITIVE STATUS IN INPATIENT GEROREHABILITATION
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5M01RR014467-07
  • Funding stream: NATIONAL CENTER FOR RESEARCH RESOURCES
,
NIH| Exceptional aging: 12 year trajectories to function
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01AG023629-03
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| Diverse ancestry biobank to map biomedical traits and elucidate health disparitie
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 4U01HG007417-04
  • Funding stream: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
,
NIH| GENETICS OF GALLBLADDER DISEASE IN MEXICAN AMERICANS
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01DK053889-04
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
,
NIH| CHS Events Follow-up Study
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U01HL080295-01
  • Funding stream: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
80 references, page 1 of 6

1.Altshuler D., Daly M. J. & Lander E. S. Genetic mapping in human disease. Science 322, 881–888 (2008).18988837 [OpenAIRE] [PubMed]

2.Welter D.The NHGRI GWAS Catalog, a cu rated resource of SNP-trait associations. Nucleic Acids Res.42, D1001–D1006 (2014).24316577 [OpenAIRE] [PubMed]

3.Boyle E. A., Li Y. I. & Pritchard J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017).28622505 [OpenAIRE] [PubMed]

4.Grotz A. K., Gloyn A. L. & Thomsen S. K. Prioritising causal genes at type 2 diabetes risk loci. Curr. Diab. Rep. 17, 76 (2017).28758174 [OpenAIRE] [PubMed]

5.Cirulli E. T. & Goldstein D. B. Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat. Rev. Genet. 11, 415–425 (2010).20479773 [PubMed]

6.Mahajan A.Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat. Genet.50, 559–571 (2018).29632382 [OpenAIRE] [PubMed]

7.Flannick J.Loss-of-function mutations in SLC30A8 protect against type 2 diabetes. Nat. Genet.46, 357–363 (2014).24584071 [OpenAIRE] [PubMed]

8.Plenge R. M., Scolnick E. M. & Altshuler D. Validating therapeutic targets through human genetics. Nat. Rev. Drug Discov. 12, 581–594 (2013).23868113 [OpenAIRE] [PubMed]

9.Zuk O.Searching for missing heritability: designing rare variant association studies. Proc. Natl Acad. Sci. USA 111, E455–E464 (2014).24443550 [OpenAIRE] [PubMed]

10.Fuchsberger C.The genetic architecture of type 2 diabetes. Nature 536, 41–47 (2016).27398621 [OpenAIRE] [PubMed]

11.Moutsianas L.The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet.11, e1005165 (2015).25906071 [OpenAIRE] [PubMed]

12.Sveinbjornsson G.Weighting sequence variants based on their annotation increases power of whole-genome association studies. Nat. Genet.48, 314–317 (2016).26854916 [PubMed]

13.Mahajan A.Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat. Genet.46, 234–244 (2014).24509480 [OpenAIRE] [PubMed]

14.Tan K.Functional characterization and structural modeling of obesity associated mutations in the melanocortin 4 receptor. Endocrinology 150, 114–125 (2009).18801902 [OpenAIRE] [PubMed]

15.Wu M. C.Rare-variant association testing for sequencing data with the sequence kernel association test. Am. J. Hum. Genet.89, 82–93 (2011).21737059 [OpenAIRE] [PubMed]

80 references, page 1 of 6
Abstract
<p>Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10<sup>−3</sup>) and candidate genes from knockout mice (P = 5.2 × 10<sup>−3</sup>). ...
Subjects
free text keywords: Broad Genomics Platform, DiscovEHR Collaboration, CHARGE, LuCamp, ProDiGY, GoT2D, ESP, SIGMA-T2D, T2D-GENES, AMP-T2D-GENES, Animals, Mice, Knockout, Humans, Diabetes Mellitus, Type 2, Case-Control Studies, Gene Frequency, Decision Support Techniques, Female, Male, Genome-Wide Association Study, Exome, Whole Exome Sequencing, General Science & Technology, MD Multidisciplinary, Article, Diabetes Mellitus, Type 2/genetics, Exome/genetics, Mice, Knockout, /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Journal Article, GENOME-WIDE ASSOCIATION, COMMON GENETIC-VARIATION, LOW-FREQUENCY, RARE VARIANTS, MUTATIONS, RISK, IDENTIFICATION, HERITABILITY, ARCHITECTURE, METAANALYSIS, 3121 Internal medicine, Multidisciplinary, Allele frequency, Medical genetics, medicine.medical_specialty, medicine, Minor allele frequency, Allele, Candidate gene, Genetics, Exome sequencing
Funded by
NIH| IMMUNOCOMPETENCY &NUTRITIVE STATUS IN INPATIENT GEROREHABILITATION
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5M01RR014467-07
  • Funding stream: NATIONAL CENTER FOR RESEARCH RESOURCES
,
NIH| Exceptional aging: 12 year trajectories to function
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01AG023629-03
  • Funding stream: NATIONAL INSTITUTE ON AGING
,
NIH| Diverse ancestry biobank to map biomedical traits and elucidate health disparitie
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 4U01HG007417-04
  • Funding stream: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
,
NIH| GENETICS OF GALLBLADDER DISEASE IN MEXICAN AMERICANS
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01DK053889-04
  • Funding stream: NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES
,
NIH| CHS Events Follow-up Study
Project
  • Funder: National Institutes of Health (NIH)
  • Project Code: 1U01HL080295-01
  • Funding stream: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE
80 references, page 1 of 6

1.Altshuler D., Daly M. J. & Lander E. S. Genetic mapping in human disease. Science 322, 881–888 (2008).18988837 [OpenAIRE] [PubMed]

2.Welter D.The NHGRI GWAS Catalog, a cu rated resource of SNP-trait associations. Nucleic Acids Res.42, D1001–D1006 (2014).24316577 [OpenAIRE] [PubMed]

3.Boyle E. A., Li Y. I. & Pritchard J. K. An expanded view of complex traits: from polygenic to omnigenic. Cell 169, 1177–1186 (2017).28622505 [OpenAIRE] [PubMed]

4.Grotz A. K., Gloyn A. L. & Thomsen S. K. Prioritising causal genes at type 2 diabetes risk loci. Curr. Diab. Rep. 17, 76 (2017).28758174 [OpenAIRE] [PubMed]

5.Cirulli E. T. & Goldstein D. B. Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nat. Rev. Genet. 11, 415–425 (2010).20479773 [PubMed]

6.Mahajan A.Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. Nat. Genet.50, 559–571 (2018).29632382 [OpenAIRE] [PubMed]

7.Flannick J.Loss-of-function mutations in SLC30A8 protect against type 2 diabetes. Nat. Genet.46, 357–363 (2014).24584071 [OpenAIRE] [PubMed]

8.Plenge R. M., Scolnick E. M. & Altshuler D. Validating therapeutic targets through human genetics. Nat. Rev. Drug Discov. 12, 581–594 (2013).23868113 [OpenAIRE] [PubMed]

9.Zuk O.Searching for missing heritability: designing rare variant association studies. Proc. Natl Acad. Sci. USA 111, E455–E464 (2014).24443550 [OpenAIRE] [PubMed]

10.Fuchsberger C.The genetic architecture of type 2 diabetes. Nature 536, 41–47 (2016).27398621 [OpenAIRE] [PubMed]

11.Moutsianas L.The power of gene-based rare variant methods to detect disease-associated variation and test hypotheses about complex disease. PLoS Genet.11, e1005165 (2015).25906071 [OpenAIRE] [PubMed]

12.Sveinbjornsson G.Weighting sequence variants based on their annotation increases power of whole-genome association studies. Nat. Genet.48, 314–317 (2016).26854916 [PubMed]

13.Mahajan A.Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat. Genet.46, 234–244 (2014).24509480 [OpenAIRE] [PubMed]

14.Tan K.Functional characterization and structural modeling of obesity associated mutations in the melanocortin 4 receptor. Endocrinology 150, 114–125 (2009).18801902 [OpenAIRE] [PubMed]

15.Wu M. C.Rare-variant association testing for sequencing data with the sequence kernel association test. Am. J. Hum. Genet.89, 82–93 (2011).21737059 [OpenAIRE] [PubMed]

80 references, page 1 of 6
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