The trans-ancestral genomic architecture of glycemic traits
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30...
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| Vydané v: | Nature genetics Ročník 53; číslo 6; s. 840 - 860 |
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| Médium: | Journal Article |
| Jazyk: | English |
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New York
Nature Publishing Group US
01.06.2021
Nature Publishing Group |
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| ISSN: | 1061-4036, 1546-1718, 1546-1718 |
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| Abstract | Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel;
P
< 5 × 10
−8
), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets. |
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| AbstractList | Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10.sup.-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242loci (99 novel; P<5×10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10.sup.-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. Glycemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated hemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P<5x10-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10 −8 ), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets. Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10 ), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. |
| Audience | Academic |
| Author | Kumari, Meena Rasmussen-Torvik, Laura J. Sofer, Tamar Wang, Yujie Abecasis, Gonçalo R. Zafarmand, Mohammad Hadi Franks, Paul W. Sanna, Serena Pedersen, Oluf Nag, Abhishek Teslovich, Tanya M. Hartwig, Fernando P. Kentistou, Katherine A. Amin, Najaf Baldassarre, Damiano Vogel, Mandy Matsubara, Tatsuaki Alarcón-Riquelme, Marta E. Goodarzi, Mark O. Eiriksdottir, Gudny Aguilar-Salinas, Carlos Alberto Kim, Young Jin Peters, Annette Lin, Xu Takeuchi, Fumihiko Peyser, Patricia A. Palmer, Colin N. A. Njølstad, Inger Chen, Chien-Hsiun Qi, Lu Jørgensen, Marit E. Yokota, Mitsuhiro Liu, Ching-Ti Tönjes, Anke Barroso, Inês Boerwinkle, Eric Kutalik, Zoltan van Dam, Rob M. Lind, Lars Chang, Yi Cheng Wu, Peitao Frayling, Timothy M. Wang, Carol A. Timmers, Paul R. H. J. Zhao, Wei Evans, Michele K. Wood, Andrew R. Lindström, Jaana Li-Gao, Ruifang Gigante, Bruna Heckbert, Susan R. Boomsma, D. I. Rich, Stephen S. Jensen, Richard A. Kawaguchi, Takahisa Goel, Anuj Liu, Jianjun Small, Kerrin S. Duan, Qing Matsuda, Fumihiko Schurmann, Claudia März, Winfried de Haan, Hugo |
| AuthorAffiliation | 204 Medical Research Council Human Genetics Unit, Institute for Genetics and Cancer, University of Edinburgh, Edinburgh, UK 272 National Heart and Lung Institute, Imperial College London, London, UK 121 Genomics plc, Oxford, UK 93 German Center for Diabetes Research (DZD), Neuherberg, Bavaria, Germany 110 Icelandic Heart Association, Kopavogur, Iceland 105 Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA 246 Department of Medicine, Harvard Medical School, Boston, MA, USA 192 Gen-info LtD, Zagreb, Croatia 42 Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA 160 Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan 98 Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Monserrato, Italy 124 Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore 13 Laboratory for Genomics of Diabetes |
| AuthorAffiliation_xml | – name: 34 Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, Baden-Württemberg, Germany – name: 205 Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA – name: 255 Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford University, Stanford, CA, USA – name: 169 Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland – name: 317 Wellcome Sanger Institute, Hinxton, UK – name: 207 Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland – name: 53 NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, UK – name: 265 MRC/UVRI and LSHTM (Uganda Research Unit), Entebbe, Uganda – name: 115 National Center for Global Health and Medicine, Tokyo, Japan – name: 188 Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA – name: 83 Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA – name: 250 Department of Medicine, Division of Endocrinology, Diabetes & Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA – name: 315 Institute for Molecular Bioscience, The University of Queensland, Queensland, Australia – name: 264 Netherlands Heart Institute, Utrecht, The Netherlands – name: 151 Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China – name: 69 Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA – name: 105 Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA – name: 200 Department of Experimental Diabetology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany – name: 186 Department of Medicine and Pharmacology, New York Medical College School of Medicine, Valhalla, NY, USA – name: 102 Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA – name: 190 Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Bavaria, Germany – name: 263 Institute of Molecular and Clinical Ophthalmology Basel IOB, Basel, Switzerland – name: 77 Molecular Biology and Genomic Medicine Unit, National Institute of Medical Sciences and Nutrition, Mexico City, Mexico – name: 168 Institute of Biomedicine, Bioinformatics Center, Univeristy of Eastern Finland, Kuopio, Finland – name: 75 Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China – name: 209 Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands – name: 120 Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands – name: 159 Internal Medicine, Endocrinology, Diabetes & Metabolism, Diabetes and Metabolism Research Center, The Ohio State University Wexner Medical Center, Columbus, OH, USA – name: 269 Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland – name: 71 Department of Statistics, The University of Auckland, Science Center, Auckland, New Zealand – name: 127 Department of Community Medicine, Faculty of Health Sciences, UIT the Arctic University of Norway, Tromsø, Norway – name: 171 USC-Office of Population Studies Foundation, University of San Carlos, Cebu City, Philippines – name: 89 Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Malmo, Sweden – name: 293 Pirkanmaa Hospital District, Tampere, Finland – name: 318 TUM School of Medicine, Technical University of Munich and Klinikum Rechts der Isar, Munich, Germany – name: 303 Cardiovascular and Metabolic Disease Signature Research Program, Duke-NUS Medical School, Singapore, Singapore – name: 26 Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands – name: 119 Department of Biomedical Data Sciences, Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands – name: 176 Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan – name: 224 Aberdeen Centre for Health Data Science, 1:042 Polwarth Building, School of Medicine, Medical, Science and Nutrition, University of Aberdeen, Foresterhill, Aberdeen, UK – name: 305 Department of Public Health, University of Helsinki, Helsinki, Finland – name: 192 Gen-info LtD, Zagreb, Croatia – name: 197 Centre for Global Health, The Usher Institute, University of Edinburgh, Edinburgh, UK – name: 244 Intramural Research Program, National Institute of Aging, Baltimore, MD, USA – name: 325 Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK – name: 261 Department of Ophthalmology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany – name: 294 Department of Medicine, University of Cambridge, Cambridge, UK – name: 48 Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark – name: 309 Department of Medicine, Internal Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland – name: 237 Harvard Medical School, Boston, MA, USA – name: 220 Clinical and Health Services Research, National Institute on Minority Health and Health Disparities, Bethesda, MD, USA – name: 319 Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA, USA – name: 58 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, Taiwan – name: 18 Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA – name: 15 Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia – name: 266 Faculty of Medicine, Institute of Health Sciences, University of Oulu, Oulu, Finland – name: 129 Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam Universities Medical Center, Amsterdam, The Netherlands – name: 185 Department of Functional Pathology, Shimane University School of Medicine, Izumo, Japan – name: 231 Department of Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA – name: 46 Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UK – name: 221 Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA – name: 106 Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA – name: 20 Department of Epidemiology, Brown University School of Public Health, Brown University, Providence, RI, USA – name: 184 Department of Diabetes, Diabetes, & Nutritional Sciences, James Black Centre, King’s College London, London, UK – name: 93 German Center for Diabetes Research (DZD), Neuherberg, Bavaria, Germany – name: 211 Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands – name: 22 Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China – name: 73 Department of Medicine, Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA – name: 152 Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK – name: 81 Centre for Cardiovascular Sciences, Queen’s Medical Research Institute, University of Edinburgh, Edinburgh, Scotland – name: 187 Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK – name: 183 Department of Internal Medicine, Aichi Gakuin University School of Dentistry, Nagoya, Japan – name: 1 Exeter Centre of Excellence for Diabetes Research (EXCEED), Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK – name: 63 Department of Statistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA – name: 21 Department of Biomedical Sciences, City University of Hong Kong, Hong Kong SAR, China – name: 116 Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands – name: 101 Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA – name: 154 Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany – name: 166 Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, Japan – name: 247 Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweeden – name: 179 Center for Clinical Research and 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Behaviour and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands – name: 68 Bioinfosol, Sevilla, Spain – name: 157 Internal Medicine, Endocrine & Metabolism, Tri-Service General Hospital, Taipei, Taiwan – name: 316 Kurume University School of Medicine, Japan – name: 304 Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland – name: 230 Digital Health Center, Hasso Plattner Institut, University Potsdam, Potsdam, Germany – name: 29 CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China – name: 300 Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark – name: 139 Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institues of Health, Bethesda, MD, USA – name: 7 MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK – name: 296 Department of Psychology, University of Miami, Miami, FL, USA |
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Medicine – sequence: 107 givenname: Richa surname: Saxena fullname: Saxena, Richa organization: Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Program in Medical and Population Genetics, Broad Institute – sequence: 118 givenname: Peter J. surname: van der Most fullname: van der Most, Peter J. organization: Department of Epidemiology, University of Groningen, University Medical Center Groningen – sequence: 123 givenname: Nan surname: Wang fullname: Wang, Nan organization: Department of Preventive Medicine, Keck School of Medicine of University of Southern California, University of Southern California Diabetes and Obesity Research Institute, Keck School of Medicine of University of Southern California – sequence: 124 givenname: Helen R. surname: Warren fullname: Warren, Helen R. organization: Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London – sequence: 126 givenname: Tom surname: Wilsgaard fullname: Wilsgaard, Tom organization: Department of Community Medicine, Faculty of Health Sciences, UIT the Arctic University of Norway – sequence: 127 givenname: Andrew surname: Wong fullname: Wong, Andrew organization: MRC Unit for Lifelong Health and Ageing at University College London – sequence: 130 givenname: Mohammad Hadi surname: Zafarmand fullname: Zafarmand, Mohammad Hadi organization: Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam Public Health Research Institute, Amsterdam University Medical Center – sequence: 137 givenname: Damiano surname: Baldassarre fullname: Baldassarre, Damiano organization: Department of Medical Biotechnology and Translational Medicine, University of Milan, Centro Cardiologico Monzino, IRCCS – sequence: 138 givenname: Marian surname: Beekman fullname: Beekman, Marian organization: Department of Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center – sequence: 139 givenname: Richard N. surname: Bergman fullname: Bergman, Richard N. organization: Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center – sequence: 143 givenname: Stefan R. surname: Bornstein fullname: Bornstein, Stefan R. organization: Department for Prevention and Care of Diabetes, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden – sequence: 146 givenname: Archie surname: Campbell fullname: Campbell, Archie organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Usher Institute, University of Edinburgh – sequence: 148 givenname: Yi Cheng surname: Chang fullname: Chang, Yi Cheng organization: Institute of Biomedical Sciences, Academia Sinica, Department of Internal Medicine, National Taiwan University Hospital, Graduate Institute of Medical Genomics and Proteomics, National Taiwan University – sequence: 152 givenname: Gudny surname: Eiriksdottir fullname: Eiriksdottir, Gudny organization: Icelandic Heart Association – sequence: 159 givenname: Sohee surname: Han fullname: Han, Sohee organization: Division of Genome Science, Department of Precision Medicine, National Institute of Health – sequence: 160 givenname: Catharina A. surname: Hartman fullname: Hartman, Catharina A. organization: Department of Psychiatry, Interdisciplinary Center Psychopathy and Emotion Regulation, University of Groningen, University Medical Center Groningen – sequence: 165 givenname: Sahoko surname: Ichihara fullname: Ichihara, Sahoko organization: Department of Environmental and Preventive Medicine, Jichi Medical University School of Medicine – sequence: 173 givenname: Tomohiro surname: Katsuya fullname: Katsuya, Tomohiro organization: Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine – sequence: 174 givenname: Chiea Chuen surname: Khor fullname: Khor, Chiea Chuen organization: Genome Institute of Singapore, Agency for Science, Technology and Research – sequence: 176 givenname: Ivana surname: Kolcic fullname: Kolcic, Ivana organization: Department of Public Health, University of Split School of Medicine – sequence: 177 givenname: Teemu surname: Kuulasmaa fullname: Kuulasmaa, Teemu organization: Institute of Biomedicine, Bioinformatics Center, Univeristy of Eastern Finland – sequence: 183 givenname: Rozenn N. surname: Lemaitre fullname: Lemaitre, Rozenn N. organization: Department of Medicine, Cardiovascular Health Research Unit, University of Washington – sequence: 186 givenname: Shih-Yi surname: Lin fullname: Lin, Shih-Yi organization: Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, National Defense Medical Center, National Yang-Ming University – sequence: 188 givenname: Allan surname: Linneberg fullname: Linneberg, Allan organization: Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen – sequence: 192 givenname: Fumihiko surname: Matsuda fullname: Matsuda, Fumihiko organization: Center for Genomic Medicine, Kyoto University Graduate School of Medicine – sequence: 195 givenname: Sanghoon surname: Moon fullname: Moon, Sanghoon organization: Division of Genome Science, Department of Precision Medicine, National Institute of Health – sequence: 202 givenname: Yasumasa surname: Ohyagi fullname: Ohyagi, Yasumasa organization: Department of Geriatric Medicine and Neurology, Ehime University Graduate School of Medicine – sequence: 206 givenname: Qibin surname: Qi fullname: Qi, Qibin organization: Department of Epidemiology and Population Health, Albert Einstein College of Medicine – sequence: 214 givenname: Kevin surname: Sandow fullname: Sandow, Kevin organization: The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center – sequence: 221 givenname: Betina surname: Thuesen fullname: Thuesen, Betina organization: Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital – sequence: 226 givenname: Rob M. surname: van Dam fullname: van Dam, Rob M. organization: Saw Swee Hock School of Public Health, National Univeristy of Singapore and National University Health System, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Department of Nutrition, Harvard T. H. Chan School of Public Health – sequence: 233 givenname: Ko surname: Willems van Dijk fullname: Willems van Dijk, Ko organization: Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Department of Human Genetics, Leiden University Medical Center – sequence: 236 givenname: Linda S. surname: Adair fullname: Adair, Linda S. organization: Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Carolina Population Center, University of North Carolina – sequence: 246 givenname: Michael surname: Boehnke fullname: Boehnke, Michael organization: Center for Statistical Genetics, University of Michigan, Department of Biostatistics, School of Public Health, University of Michigan – sequence: 249 givenname: Klaus surname: Bønnelykke fullname: Bønnelykke, Klaus organization: COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen – sequence: 250 givenname: D. I. surname: Boomsma fullname: Boomsma, D. I. organization: Department of Biological Psychology, Faculty of Behaviour and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam University Medical Center – sequence: 252 givenname: Thomas A. surname: Buchanan fullname: Buchanan, Thomas A. organization: University of Southern California Diabetes and Obesity Research Institute, Keck School of Medicine of University of Southern California, Department of Medicine, Keck School of Medicine of University of Southern California, Department of Physiology and Neuroscience, Keck School of Medicine of University of Southern California – sequence: 255 givenname: John C. surname: Chambers fullname: Chambers, John C. organization: Department of Epidemiology and Biostatistics, Imperial College London, Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Lee Kong Chian School of Medicine, Nanyang Technological University, Imperial College Healthcare NHS Trust, Imperial College London, MRC-PHE Centre for Environment and Health, Imperial College London – sequence: 256 givenname: Daniel I. surname: Chasman fullname: Chasman, Daniel I. organization: Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School – sequence: 257 givenname: Yii-Der Ida surname: Chen fullname: Chen, Yii-Der Ida organization: The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center – sequence: 259 givenname: Francis S. surname: Collins fullname: Collins, Francis S. organization: Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institues of Health – sequence: 261 givenname: Francesco surname: Cucca fullname: Cucca, Francesco organization: Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR) – sequence: 262 givenname: H. Janaka surname: de Silva fullname: de Silva, H. Janaka organization: Department of Medicine, Faculty of Medicine, University of Kelaniya – sequence: 267 givenname: Luigi surname: Ferrucci fullname: Ferrucci, Luigi organization: Intramural Research Program, National Institute of Aging – sequence: 268 givenname: Jose C. surname: Florez fullname: Florez, Jose C. organization: Program in Medical and Population Genetics, Broad Institute, Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Department of Medicine, Harvard Medical School – sequence: 269 givenname: Paul W. surname: Franks fullname: Franks, Paul W. organization: Department of Clinical Sciences, Lund University Diabetes Centre, Lund University, Department of Public Health and Clinical Medicine, Umeå University – sequence: 277 givenname: Sameline surname: Grimsgaard fullname: Grimsgaard, Sameline organization: Department of Community Medicine, Faculty of Health Sciences, UIT the Arctic University of Norway – sequence: 280 givenname: Xiuqing surname: Guo fullname: Guo, Xiuqing organization: The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center – sequence: 286 givenname: Wei surname: Huang fullname: Huang, Wei organization: Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai (CHGC) and Shanghai Academy of Science & Technology (SAST) – sequence: 295 givenname: Norihiro surname: Kato fullname: Kato, Norihiro organization: National Center for Global Health and Medicine – sequence: 299 givenname: Heikki A. surname: Koistinen fullname: Koistinen, Heikki A. organization: Department of Public Health Solutions, Finnish Institute for Health and Welfare, Department of Medicine, University of Helsinki and Helsinki University Central Hospital, Minerva Foundation Institute for Medical Research – sequence: 303 givenname: Diana surname: Kuh fullname: Kuh, Diana organization: MRC Unit for Lifelong Health and Ageing at University College London – sequence: 304 givenname: Meena surname: Kumari fullname: Kumari, Meena organization: Institute for Social and Economic Research, University of Essex – sequence: 308 givenname: Lenore J. surname: Launer fullname: Launer, Lenore J. organization: Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health – sequence: 319 givenname: Dennis O. surname: Mook-Kanamori fullname: Mook-Kanamori, Dennis O. organization: Department of Clinical Epidemiology, Leiden University Medical Center, Department of Public Health and Primary Care, Leiden University Medical Center – sequence: 329 givenname: Oluf surname: Pedersen fullname: Pedersen, Oluf organization: Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen – sequence: 332 givenname: Peter P. surname: Pramstaller fullname: Pramstaller, Peter P. organization: Institute for Biomedicine, Eurac Research – sequence: 333 givenname: Michael A. surname: Province fullname: Province, Michael A. organization: Department of Genetics, Division of Statistical Genomics, Washington University School of Medicine – sequence: 334 givenname: Bruce M. surname: Psaty fullname: Psaty, Bruce M. organization: Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Department of Epidemiology, Cardiovascular Health Research Unit, University of Washington, Department of Health Services, Cardiovascular Health Research Unit, University of Washington – sequence: 340 givenname: Frits R. surname: Rosendaal fullname: Rosendaal, Frits R. organization: Department of Clinical Epidemiology, Leiden University Medical Center – sequence: 349 givenname: Xiao-ou surname: Shu fullname: Shu, Xiao-ou organization: Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center – sequence: 362 givenname: E. Shyong surname: Tai fullname: Tai, E. Shyong organization: Saw Swee Hock School of Public Health, National Univeristy of Singapore and National University Health System, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Cardiovascular and Metabolic Disease Signature Research Program, Duke-NUS Medical School – sequence: 363 givenname: Nicholas J. surname: Timpson fullname: Timpson, Nicholas J. organization: MRC Integrative Epidemiology Unit, University of Bristol, Department of Population Health Sciences, Bristol Medical School, University of Bristol – sequence: 366 givenname: Teresa surname: Tusie fullname: Tusie, Teresa organization: Molecular Biology and Genomic Medicine Unit, National Institute of Medical Sciences and Nutrition, Department of Genomic Medicine and Environmental Toxicology, Instituto de Investigaciones Biomedicas, Universidad Nacional Autonoma de Mexico – sequence: 367 givenname: Matti surname: Uusitupa fullname: Uusitupa, Matti organization: Department of Public Health and Clinical Nutrition, University of Eastern Finland – sequence: 372 givenname: Tanja G. M. surname: Vrijkotte fullname: Vrijkotte, Tanja G. M. organization: Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Center – sequence: 379 givenname: Wen B. surname: Wei fullname: Wei, Wen B. organization: Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University – sequence: 381 givenname: Gonneke surname: Willemsen fullname: Willemsen, Gonneke organization: Department of Biological Psychology, Faculty of Behaviour and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam University Medical Center – sequence: 383 givenname: Tien-Yin surname: Wong fullname: Wong, Tien-Yin organization: Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School – sequence: 385 givenname: Anny H. surname: Xiang fullname: Xiang, Anny H. organization: Department of Research and Evaluation, Kaiser Permanente of Southern California – sequence: 388 givenname: Mitsuhiro surname: Yokota fullname: Yokota, Mitsuhiro organization: Kurume University School of Medicine – sequence: 389 givenname: Eleftheria surname: Zeggini fullname: Zeggini, Eleftheria organization: Department of Human Genetics, Wellcome Sanger Institute, Institute of Translational Genomics, Helmholtz Zentrum München–German Research Center for Environmental Health, TUM School of Medicine, Technical University of Munich and Klinikum Rechts der Isar – sequence: 394 givenname: Mark I. surname: McCarthy fullname: McCarthy, Mark I. organization: Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Wellcome Centre for Human Genetics, University of Oxford, Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Genentech – sequence: 395 givenname: Josée surname: Dupuis fullname: Dupuis, Josée organization: Department of Biostatistics, Boston University School of Public Health – sequence: 401 givenname: Stephen C. J. orcidid: 0000-0001-8122-0117 surname: Parker fullname: Parker, Stephen C. J. organization: Department of Computational Medicine and Bioinformatics, University of Michigan, Department of Human Genetics, University of Michigan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34059833$$D View this record in MEDLINE/PubMed https://hal.science/hal-04535845$$DView record in HAL https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185083$$DView record from Swedish Publication Index (Umeå universitet) https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-454592$$DView record from Swedish Publication Index (Uppsala universitet) http://kipublications.ki.se/Default.aspx?queryparsed=id:146730751$$DView record from Swedish Publication Index (Karolinska Institutet) |
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| ContentType | Journal Article |
| Contributor | van der Harst, Pim de Haan, Hugoline G van Hylckama Vlieg, Astrid van den Akker, Erik van der Most, Peter J van Willems van Dijk, Ko de Geus, Eco J C van Dam, Rob M van Heemst, Diana de Silva, H Janaka van Duijn, Cornelia |
| Contributor_xml | – sequence: 1 givenname: Hugoline G surname: de Haan fullname: de Haan, Hugoline G – sequence: 2 givenname: Erik surname: van den Akker fullname: van den Akker, Erik – sequence: 3 givenname: Peter J surname: van der Most fullname: van der Most, Peter J – sequence: 4 givenname: Eco J C surname: de Geus fullname: de Geus, Eco J C – sequence: 5 givenname: Rob M surname: van Dam fullname: van Dam, Rob M – sequence: 6 givenname: Diana surname: van Heemst fullname: van Heemst, Diana – sequence: 7 givenname: Astrid surname: van Hylckama Vlieg fullname: van Hylckama Vlieg, Astrid – sequence: 8 givenname: Ko surname: van Willems van Dijk fullname: van Willems van Dijk, Ko – sequence: 9 givenname: H Janaka surname: de Silva fullname: de Silva, H Janaka – sequence: 10 givenname: Pim surname: van der Harst fullname: van der Harst, Pim – sequence: 11 givenname: Cornelia surname: van Duijn fullname: van Duijn, Cornelia |
| Copyright | The Author(s), under exclusive licence to Springer Nature America, Inc. 2021 COPYRIGHT 2021 Nature Publishing Group Copyright Nature Publishing Group Jun 2021 licence_http://creativecommons.org/publicdomain/zero |
| Copyright_xml | – notice: The Author(s), under exclusive licence to Springer Nature America, Inc. 2021 – notice: COPYRIGHT 2021 Nature Publishing Group – notice: Copyright Nature Publishing Group Jun 2021 – notice: licence_http://creativecommons.org/publicdomain/zero |
| CorporateAuthor | The Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) Lifelines Cohort Study Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) Genetic and Molecular Epidemiology Lunds universitet Profile areas and other strong research environments Translational Muscle Research Department of Clinical Sciences, Malmö Lund University Translationell muskelforskning Strategiska forskningsområden (SFO) EpiHealth: Epidemiology for Health Genetisk och molekylär epidemiologi EXODIAB: Excellence of Diabetes Research in Sweden Faculty of Medicine Strategic research areas (SRA) Medicinska fakulteten Profilområden och andra starka forskningsmiljöer Institutionen för kliniska vetenskaper, Malmö Geriatrik Geriatrics |
| CorporateAuthor_xml | – name: The Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) – name: Lifelines Cohort Study – name: Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC) – name: Faculty of Medicine – name: Medicinska fakulteten – name: Strategiska forskningsområden (SFO) – name: Translationell muskelforskning – name: Geriatrik – name: EpiHealth: Epidemiology for Health – name: Institutionen för kliniska vetenskaper, Malmö – name: Strategic research areas (SRA) – name: Genetisk och molekylär epidemiologi – name: Lunds universitet – name: Translational Muscle Research – name: Profilområden och andra starka forskningsmiljöer – name: Lund University – name: EXODIAB: Excellence of Diabetes Research in Sweden – name: Profile areas and other strong research environments – name: Genetic and Molecular Epidemiology – name: Geriatrics – name: Department of Clinical Sciences, Malmö |
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| DOI | 10.1038/s41588-021-00852-9 |
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| Title | The trans-ancestral genomic architecture of glycemic traits |
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