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Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.
Suzuki, Ken; Hatzikotoulas, Konstantinos; Southam, Lorraine; Taylor, Henry J; Yin, Xianyong; Lorenz, Kim M; Mandla, Ravi; Huerta-Chagoya, Alicia; Rayner, Nigel W; Bocher, Ozvan; Arruda, Ana Luiza de S V; Sonehara, Kyuto; Namba, Shinichi; Lee, Simon S K; Preuss, Michael H; Petty, Lauren E; Schroeder, Philip; Vanderwerff, Brett; Kals, Mart; Bragg, Fiona; Lin, Kuang; Guo, Xiuqing; Zhang, Weihua; Yao, Jie; Kim, Young Jin; Graff, Mariaelisa; Takeuchi, Fumihiko; Nano, Jana; Lamri, Amel; Nakatochi, Masahiro; Moon, Sanghoon; Scott, Robert A; Cook, James P; Lee, Jung-Jin; Pan, Ian; Taliun, Daniel; Parra, Esteban J; Chai, Jin-Fang; Bielak, Lawrence F; Tabara, Yasuharu; Hai, Yang; Thorleifsson, Gudmar; Grarup, Niels; Sofer, Tamar; Wuttke, Matthias; Sarnowski, Chloé; Gieger, Christian; Nousome, Darryl; Trompet, Stella; Kwak, Soo-Heon.
Affiliation
  • Suzuki K; Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK.
  • Hatzikotoulas K; Department of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Southam L; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
  • Taylor HJ; Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Yin X; Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Lorenz KM; Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  • Mandla R; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Huerta-Chagoya A; Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
  • Rayner NW; Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
  • Bocher O; Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing City, China.
  • Arruda ALSV; Corporal Michael J Crescenz VA Medical Center, Philadelphia, PA, USA.
  • Sonehara K; Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
  • Namba S; Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
  • Lee SSK; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Preuss MH; Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Petty LE; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Schroeder P; Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Vanderwerff B; Consejo Nacional de Ciencia y Tecnología (CONACYT), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
  • Kals M; Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Bragg F; Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Lin K; Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Guo X; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
  • Zhang W; Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Yao J; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan.
  • Kim YJ; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan.
  • Graff M; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
  • Takeuchi F; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Nano J; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Lamri A; Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Nakatochi M; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Moon S; Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Scott RA; Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.
  • Cook JP; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
  • Lee JJ; Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • Pan I; Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK.
  • Taliun D; Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • Parra EJ; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Chai JF; Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
  • Bielak LF; Department of Cardiology, Ealing Hosptial, London NorthWest Healthcare NHS Trust, Middlesex, UK.
  • Tabara Y; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Hai Y; Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea.
  • Thorleifsson G; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Grarup N; Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan.
  • Sofer T; Institute of Epidemiology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Germany.
  • Wuttke M; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Sarnowski C; Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada.
  • Gieger C; Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Nousome D; Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, South Korea.
  • Trompet S; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK.
  • Kwak SH; Department of Health Data Science, University of Liverpool, Liverpool, UK.
medRxiv ; 2023 Mar 31.
Article in En | MEDLINE | ID: mdl-37034649
ABSTRACT
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. 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 previously unreported. We define eight non-overlapping clusters of T2D signals characterised 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, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: MedRxiv Year: 2023 Type: Article Affiliation country: United kingdom
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: MedRxiv Year: 2023 Type: Article Affiliation country: United kingdom