We investigated type 2 diabetes (T2D) genetic susceptibility via multi-ancestry meta-analysis of 228,499 cases and 1,178,783 controls in the Million Veteran Program (MVP), DIAMANTE, Biobank Japan and other studies. We report 568 associations, including 286 autosomal, 7 X-chromosomal and 25 identified in ancestry-specific analyses that were previously unreported. Transcriptome-wide association analysis detected 3,568 T2D associations with genetically predicted gene expression in 687 novel genes; of these, 54 are known to interact with FDA-approved drugs. A polygenic risk score (PRS) was strongly associated with increased risk of T2D-related retinopathy and modestly associated with chronic kidney disease (CKD), peripheral artery disease (PAD) and neuropathy. We investigated the genetic etiology of T2D-related vascular outcomes in the MVP and observed statistical SNP–T2D interactions at 13 variants, including coronary heart disease (CHD), CKD, PAD and neuropathy. These findings may help to identify potential therapeutic targets for T2D and genomic pathways that link T2D to vascular outcomes.
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The full summary-level association data from the trans-ancestry, European, African American, Hispanic and Asian meta-analysis from this report are available through dbGAP under accession number phs001672.v3.p1 (Veterans Administration Million Veteran Program Summary Results from Omics Studies). Source data are provided with this paper. More specifically, dbGaP accession number pha004943.1 refers to the African American–specific summary statistics, pha004944.1 to the Asian-specific summary statistics, pha004945.1 refers to the European-specific summary statistics, pha004946.1 refers to the Hispanic-specific summary statistics, and pha004947.1 refers to the trans-ancestry summary statistics.
Imputation was performed using MiniMac4 and EAGLE v2. Association analysis was performed using PLINK2A and XWAS v3.0. Post-GWAS processing software include: PRSice-2, LD Hub v1.9.3, FlashPCA v2.0, METAL v2011-03-25, GCTA-COJO v1.93, S-PrediXcan v0.6.1, SUGEN v8.9, DEPICT v140721, SIDER v4.1, DGIdb v3.0 and KING v2.1.6, as outlined in the Methods. Clear code for analysis is available at the associated website of each software package. Additional analyses were performed in R-3.2.
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This research is based on data from the MVP, Office of Research and Development, Veterans Health Administration and was supported by award no. MVP000. This publication does not represent the views of the VA, the US Food and Drug Administration, or the US Government. This research was also supported by funding from: the VA award I01-BX003362 (P.S.T. and K.-M.C.) and the VA Informatics and Computing Infrastructure (VINCI) VA HSR RES 130457 (S.L.D.). B.F.V. acknowledges support for this work from the National Institutes of Health (NIH) National Institute of Diabetes and Digestive and Kidney Diseases (DK101478), the NIH National Human Genome Research Institute (HG010067) and a Linda Pechenik Montague Investigator award. K.-M.C., S.M.D., J.M.G., C.J.O., L.S.P., J.S.L., and P.S.T. are supported by the VA Cooperative Studies Program. S.M.D. is supported by the Veterans Administration [IK2-CX001780]. D.K. is supported by the National Heart, Lung, and Blood Institute of the NIH (T32 HL007734). K.H.K. is supported by NIH award UC4-DK-112217. K.S. is supported by NIH R01 DK087635. L.S.P. is supported in part by VA awards I01-CX001025, and I01CX001737, NIH awards R21DK099716, U01 DK091958, U01 DK098246, P30DK111024 and R03AI133172, and a Cystic Fibrosis Foundation award PHILLI12A0. We thank all study participants for their contribution. Data on T2D were contributed by investigators from the DIAMANTE Consortium, Biobank Japan, Malmö Diet and Cancer Study, PennCath, MedStar, Pakistan Genomic Resource, Penn Medicine Biobank, and Regeneron Genetics Center. Data on stroke were provided by MEGASTROKE investigators, and data on CKD were contributed by CKDgen investigators. Data on islet α- and β-cells were contributed by the HPAP Consortium (RRID:SCR_016202 and https://hpap.pmacs.upenn.edu/). Data on coronary artery disease were contributed by the CARDIoGRAMplusC4D investigators. We thank Josep Maria Mercader and Aaron Leong for careful review and comments.
None of the sponsors of the following authors had a role in the design and conduct of the study, in the collection, management, analysis and interpretation of the data, or in the preparation, review or approval of the manuscript. D.S. has received support from the British Heart Foundation, Pfizer, Regeneron, Genentech and Eli Lilly pharmaceuticals. L.S.P. has served on Scientific Advisory Boards for Janssen, and received research support from Abbvie, Merck, Amylin, Eli Lilly, Novo Nordisk, Sanofi, PhaseBio, Roche, Abbvie, Vascular Pharmaceuticals, Janssen, Glaxo SmithKline, Pfizer, Kowa and the Cystic Fibrosis Foundation. L.S.P. is a cofounder, officer, board member and stockholder of the diabetes management-related software company Diasyst. S.L.D. has received research grant support from the following for-profit companies through the University of Utah or the Western Institute for Biomedical Research (an affiliated non-profit of VA Salt Lake City Health Care System): AbbVie, Anolinx, Astellas Pharma, AstraZeneca Pharmaceuticals, Boehringer Ingelheim International, Celgene Corporation, Eli Lilly and Company, Genentech, Genomic Health, Gilead Sciences, GlaxoSmithKline, Innocrin Pharmaceuticals, Janssen Pharmaceuticals, Kantar Health, Myriad Genetic Laboratories, Novartis International and PAREXEL International Corporation. P.D.R. has received research grant support from the following for-profit companies: Bristol Myers Squib and Lysulin, and has consulted with Intercept Pharmaceuticals and Boston Heart Diagnostics. S.M.D. receives research support to the University of Pennsylvania from RenalytixAI and consults for Calico Labs.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
a–d, Each graph represents a Manhattan plot. The y-axis corresponds to –log10 (P) for association with T2D in the respective ancestral group (a, Europeans (148,726 T2D cases, 965,732 controls, λ = 1.21); b, African American (24,646 T2D cases, 31,446 controls, λ = 1.08); c, Hispanics (8,616 T2D cases, 11,829 controls, λ = 1.03); d, Asians (46,511 T2D cases, 169,776 controls, λ = 1.15)). The x-axis represents chromosomal position on the autosomal genome. The y-axis truncated at 1 × 10−300. Points that are color-coded blue correspond to a P-value between 5.0 × 10−8 and 1.0 × 10−6. Points color-coded red indicate genome-wide significance (P = 5.0 × 10−8).
a–d, Each graph represents a Manhattan plot. The y-axis corresponds to –log10 (P) for association with T2D in the respective ancestral group (a, Europeans (69,869 T2D cases, 127,197 controls); b, African American (23,305 T2D cases, 30,140 controls); c, Hispanics (8,616 T2D cases, 11,829 controls); d, Asians (893 T2D cases, 1,560 controls)). The x-axis represents chromosomal position on chromosome X. The blue line corresponds with a significance threshold of P = 5.0 × 10−8. The red line corresponds with genome-wide significance (P = 5.0 × 10−8).
This graph represents an inverted Manhattan plot based on the output from the European T2D GWAS (148,726 T2D cases, 965,732 controls). The y-axis corresponds to –log10 (P) for association with genetically predicted gene expression in the respective tissue type (color coding shown on the right). Data were analyzed using S-PrediXcan software. The x-axis represents chromosomal position on the autosomal genome. Source Data
Extended Data Fig. 4 Manhattan plots for T2D-related complications using interaction analysis in individuals of European ancestry.
a–f, Each graph represents a Manhattan plot. The y-axis corresponds to –log10 (P) for association of SNP×T2D on T2D-related vascular outcome (a, coronary heart disease (56,285 cases, 140,945 controls, λ = 1.06); b, chronic kidney disease (67,403 cases, 129,827 controls, λ = 1.02); c, neuropathy (40,475 cases, 110,331 controls, λ = 1.03); d, peripheral artery disease (5,882 cases, 161,348 controls, λ = 1.02); e, retinopathy (13,881 cases, 123,538 controls, λ = 1.02); f, acute ischemic stroke (11,796 cases, 178,481 controls, λ = 1.00)). The x-axis represents chromosomal position on the autosomal genome. Points that are color-coded blue correspond to a P-value between 5.0 × 10−8 and 1.0 × 10−6. Points color-coded red indicate genome-wide significance (P = 5.0 × 10−8).
A shape plot representing the risk of a T2D genome-wide PRS (gPRS) on the odds ratio of T2D in MVP participants of European ancestry (69,869 T2D cases, 127,197 controls). The weights for the PRS have been obtained from an external reference dataset, namely the DIAMANTE Consortium. The gPRS has been divided into 10 deciles based on gPRS values in MVP white participants without T2D. The reference group is the lowest decile (0-10%). Odds ratios are shown as red dots, with their respective 95th percent confidence intervals displayed as red vertical lines. Source Data
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Vujkovic, M., Keaton, J.M., Lynch, J.A. et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat Genet 52, 680–691 (2020). https://doi.org/10.1038/s41588-020-0637-y