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Transethnic insight into the genetics of glycaemic traits: fine-mapping results from the Population Architecture using Genomics and Epidemiology (PAGE) consortium.
Bien, Stephanie A; Pankow, James S; Haessler, Jeffrey; Lu, Yinchang; Pankratz, Nathan; Rohde, Rebecca R; Tamuno, Alfred; Carlson, Christopher S; Schumacher, Fredrick R; Buzková, Petra; Daviglus, Martha L; Lim, Unhee; Fornage, Myriam; Fernandez-Rhodes, Lindsay; Avilés-Santa, Larissa; Buyske, Steven; Gross, Myron D; Graff, Mariaelisa; Isasi, Carmen R; Kuller, Lewis H; Manson, JoAnn E; Matise, Tara C; Prentice, Ross L; Wilkens, Lynne R; Yoneyama, Sachiko; Loos, Ruth J F; Hindorff, Lucia A; Le Marchand, Loic; North, Kari E; Haiman, Christopher A; Peters, Ulrike; Kooperberg, Charles.
Afiliação
  • Bien SA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, WA, 98109-1024, USA. sbien@fredhutch.org.
  • Pankow JS; Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA.
  • Haessler J; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, WA, 98109-1024, USA.
  • Lu Y; Department of Biological Sciences, Vanderbilt University, Nashville, TN, USA.
  • Pankratz N; Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
  • Rohde RR; Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Tamuno A; The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Carlson CS; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, WA, 98109-1024, USA.
  • Schumacher FR; Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.
  • Buzková P; Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Daviglus ML; Department of Medicine, Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA.
  • Lim U; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
  • Fornage M; Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Fernandez-Rhodes L; Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Avilés-Santa L; Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  • Buyske S; Department of Genetics, Rutgers University, Piscataway, NJ, USA.
  • Gross MD; Department of Statistics, Rutgers University, Newark, NJ, USA.
  • Graff M; Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
  • Isasi CR; Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Kuller LH; Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
  • Manson JE; Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
  • Matise TC; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Prentice RL; Department of Genetics, Rutgers University, Piscataway, NJ, USA.
  • Wilkens LR; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, WA, 98109-1024, USA.
  • Yoneyama S; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
  • Loos RJF; Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.
  • Hindorff LA; Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
  • Le Marchand L; The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • North KE; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
  • Haiman CA; The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Peters U; The Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Kooperberg C; National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Diabetologia ; 60(12): 2384-2398, 2017 12.
Article em En | MEDLINE | ID: mdl-28905132
AIMS/HYPOTHESIS: Elevated levels of fasting glucose and fasting insulin in non-diabetic individuals are markers of dysregulation of glucose metabolism and are strong risk factors for type 2 diabetes. Genome-wide association studies have discovered over 50 SNPs associated with these traits. Most of these loci were discovered in European populations and have not been tested in a well-powered multi-ethnic study. We hypothesised that a large, ancestrally diverse, fine-mapping genetic study of glycaemic traits would identify novel and population-specific associations that were previously undetectable by European-centric studies. METHODS: A multiethnic study of up to 26,760 unrelated individuals without diabetes, of predominantly Hispanic/Latino and African ancestries, were genotyped using the Metabochip. Transethnic meta-analysis of racial/ethnic-specific linear regression analyses were performed for fasting glucose and fasting insulin. We attempted to replicate 39 fasting glucose and 17 fasting insulin loci. Genetic fine-mapping was performed through sequential conditional analyses in 15 regions that included both the initially reported SNP association(s) and denser coverage of SNP markers. In addition, Metabochip-wide analyses were performed to discover novel fasting glucose and fasting insulin loci. The most significant SNP associations were further examined using bioinformatic functional annotation. RESULTS: Previously reported SNP associations were significantly replicated (p ≤ 0.05) in 31/39 fasting glucose loci and 14/17 fasting insulin loci. Eleven glycaemic trait loci were refined to a smaller list of potentially causal variants through transethnic meta-analysis. Stepwise conditional analysis identified two loci with independent secondary signals (G6PC2-rs477224 and GCK-rs2908290), which had not previously been reported. Population-specific conditional analyses identified an independent signal in G6PC2 tagged by the rare variant rs77719485 in African ancestry. Further Metabochip-wide analysis uncovered one novel fasting insulin locus at SLC17A2-rs75862513. CONCLUSIONS/INTERPRETATION: These findings suggest that while glycaemic trait loci often have generalisable effects across the studied populations, transethnic genetic studies help to prioritise likely functional SNPs, identify novel associations that may be population-specific and in turn have the potential to influence screening efforts or therapeutic discoveries. DATA AVAILABILITY: The summary statistics from each of the ancestry-specific and transethnic (combined ancestry) results can be found under the PAGE study on dbGaP here: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000356.v1.p1.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Glicemia / Diabetes Mellitus Tipo 2 Tipo de estudo: Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male Idioma: En Revista: Diabetologia Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Glicemia / Diabetes Mellitus Tipo 2 Tipo de estudo: Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans / Male Idioma: En Revista: Diabetologia Ano de publicação: 2017 Tipo de documento: Article