{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Suzuki K"],"funding":["NIDDK NIH HHS","Versus Arthritis","NIA NIH HHS","NHGRI NIH HHS","National Institute for Health Research (NIHR)"],"pagination":["347-357"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10937372"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["627(8003)"],"pubmed_abstract":["Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes<sup>1,2</sup> and molecular mechanisms that are often specific to cell type<sup>3,4</sup>. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10<sup>-8</sup>) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores<sup>5</sup> in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care."],"journal":["Nature"],"pubmed_title":["Genetic drivers of heterogeneity in type 2 diabetes pathophysiology."],"pmcid":["PMC10937372"],"funding_grant_id":["21754","R03 DK131249","U01 DK105535","L30 DK126146","R01 DK134575","K23 DK114551","UM1 DK126194","U01 HG011723","R00 AG066849","NIHR203308","R01 DK118011"],"pubmed_authors":["Psaty BM","Kardia SLR","Bowden DW","Lamri A","Jukema JW","Franco OH","Kawaguchi T","Vujkovic M","Luan J","van Dijk KW","Sonehara K","Canouil M","Lynch JA","Matsuda F","Stancakova A","Shin DM","Butterworth AS","Broadaway KA","Matsuda K","Nongmaithem SS","Sandow K","Kottgen A","de Silva HJ","Locke AE","Huerta-Chagoya A","Below JE","Ritchie MD","Strauch K","Cho YS","Wickremasinghe AR","Prins BP","Pankow JS","van Heel DA","Vanderwerff B","Hwu CM","Zeggini E","Lin K","Scott RA","Wang YX","Thorsteinsdottir U","Tuomi T","Collins FS","Gordon-Larsen P","Millwood IY","Chuang 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mechanisms that are often specific to cell type<sup>3,4</sup>. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10<sup>-8</sup>) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores<sup>5</sup> in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Mar","modification":"2025-04-18T20:15:39.884Z","creation":"2025-04-07T08:10:22.19Z"},"accession":"S-EPMC10937372","cross_references":{"pubmed":["38374256"],"doi":["10.1038/s41586-024-07019-6"]}}