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The trans-ancestral genomic architecture of glycemic traits.
Chen, Ji; Spracklen, Cassandra N; Marenne, Gaëlle; Varshney, Arushi; Corbin, Laura J; Luan, Jian'an; Willems, Sara M; Wu, Ying; Zhang, Xiaoshuai; Horikoshi, Momoko; Boutin, Thibaud S; Mägi, Reedik; Waage, Johannes; Li-Gao, Ruifang; Chan, Kei Hang Katie; Yao, Jie; Anasanti, Mila D; Chu, Audrey Y; Claringbould, Annique; Heikkinen, Jani; Hong, Jaeyoung; Hottenga, Jouke-Jan; Huo, Shaofeng; Kaakinen, Marika A; Louie, Tin; März, Winfried; Moreno-Macias, Hortensia; Ndungu, Anne; Nelson, Sarah C; Nolte, Ilja M; North, Kari E; Raulerson, Chelsea K; Ray, Debashree; Rohde, Rebecca; Rybin, Denis; Schurmann, Claudia; Sim, Xueling; Southam, Lorraine; Stewart, Isobel D; Wang, Carol A; Wang, Yujie; Wu, Peitao; Zhang, Weihua; Ahluwalia, Tarunveer S; Appel, Emil V R; Bielak, Lawrence F; Brody, Jennifer A; Burtt, Noël P; Cabrera, Claudia P; Cade, Brian E.
Afiliação
  • Chen J; Exeter Centre of Excellence for Diabetes Research (EXCEED), Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK.
  • Spracklen CN; Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK.
  • Marenne G; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Varshney A; Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, USA.
  • Corbin LJ; Department of Human Genetics, Wellcome Sanger Institute, Cambridge, UK.
  • Luan J; Inserm, Univ Brest, EFS, UMR 1078, GGB, Brest, France.
  • Willems SM; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
  • Wu Y; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
  • Zhang X; Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Horikoshi M; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
  • Boutin TS; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
  • Mägi R; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Waage J; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
  • Li-Gao R; Department of Biostatistics, School of Public Health, Shandong University, Jinan, China.
  • Chan KHK; Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
  • Yao J; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
  • Anasanti MD; Laboratory for Genomics of Diabetes and Metabolism, RIKEN Centre for Integrative Medical Sciences, Yokohama, Japan.
  • Chu AY; Medical Research Council Human Genetics Unit, Institute for Genetics and Molecular Medicine, Edinburgh, UK.
  • Claringbould A; Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.
  • Heikkinen J; COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark.
  • Hong J; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
  • Hottenga JJ; Department of Epidemiology, Brown University School of Public Health, Brown University, Providence, RI, USA.
  • Huo S; Department of Biomedical Sciences, City University of Hong Kong, Hong Kong SAR, China.
  • Kaakinen MA; Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China.
  • Louie T; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • März W; Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
  • Moreno-Macias H; Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA.
  • Ndungu A; Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  • Nelson SC; Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
  • Nolte IM; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
  • North KE; Department of Biological Psychology, Faculty of Behaviour and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Raulerson CK; Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Amsterdam, the Netherlands.
  • Ray D; 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.
  • Rohde R; Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
  • Rybin D; Section of Statistical Multi-omics, Department of Clinical and Experimental Research, University of Surrey, Guildford, UK.
  • Schurmann C; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Sim X; SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany.
  • Southam L; Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University Graz, Graz, Austria.
  • Stewart ID; Vth Department of Medicine (Nephrology, Hypertensiology, Rheumatology, Endocrinology, Diabetology), Medical Faculty Mannheim, Heidelberg University, Mannheim, Baden-Württemberg, Germany.
  • Wang CA; Department of Economics, Metropolitan Autonomous University, Mexico City, Mexico.
  • Wang Y; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
  • Wu P; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Zhang W; Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  • Ahluwalia TS; CVD Genetic Epidemiology Computational Laboratory, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
  • Appel EVR; Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
  • Bielak LF; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Brody JA; CVD Genetic Epidemiology Computational Laboratory, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
  • Burtt NP; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
  • Cabrera CP; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Cade BE; HPI Digital Health Center, Digital Health and Personalized Medicine, Hasso Plattner Institute, Potsdam, Germany.
Nat Genet ; 53(6): 840-860, 2021 06.
Article em En | MEDLINE | ID: mdl-34059833
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Glicemia / Característica Quantitativa Herdável / População Branca Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Glicemia / Característica Quantitativa Herdável / População Branca Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article