Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology · SciRah

^aCentre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
^bDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
^cDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
^dInstitute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. konstantinos.hatzikotoulas@helmholtz-munich.de
^eInstitute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
^fBritish Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
^gCenter for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
^hHeart and Lung Research Institute, University of Cambridge, Cambridge, UK
ⁱDepartment of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
^jDepartment of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
^kCorporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
^lDepartment of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
^mDepartment of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
ⁿDiabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
^oPrograms in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
^pTIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
^qWilliam Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
^rGraduate School of Experimental Medicine, Technical University of Munich, Munich, Germany
^sMunich School for Data Science, Helmholtz Munich, Neuherberg, Germany
^tDepartment of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
^uIntegrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
^vLaboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
^wCharles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
^xDepartment of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
^yEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
^zMedical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
^aaNuffield Department of Population Health, University of Oxford, Oxford, UK
^abInstitute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
^acDepartment of Cardiology, Ealing Hospital, London NorthWest Healthcare NHS Trust, London, UK
^adDepartment of Epidemiology and Biostatistics, Imperial College London, London, UK
^aeDivision of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea
^afDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
^agDepartment of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
^ahInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
✉Corresponding author

Abstract

Abstract Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes 1,2 and molecular mechanisms that are often specific to cell type 3,4 . 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 −8 ) 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 5 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.

TL;DRA meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype. (Semantic Scholar)

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Abstract

Plain-language summary

Discussion