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Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals.
Liu, Ching-Ti; Merino, Jordi; Rybin, Denis; DiCorpo, Daniel; Benke, Kelly S; Bragg-Gresham, Jennifer L; Canouil, Mickaël; Corre, Tanguy; Grallert, Harald; Isaacs, Aaron; Kutalik, Zoltan; Lahti, Jari; Marullo, Letizia; Marzi, Carola; Rasmussen-Torvik, Laura J; Rocheleau, Ghislain; Rueedi, Rico; Scapoli, Chiara; Verweij, Niek; Vogelzangs, Nicole; Willems, Sara M; Yengo, Loïc; Bakker, Stephan J L; Beilby, John; Hui, Jennie; Kajantie, Eero; Müller-Nurasyid, Martina; Rathmann, Wolfgang; Balkau, Beverley; Bergmann, Sven; Eriksson, Johan G; Florez, Jose C; Froguel, Philippe; Harris, Tamara; Hung, Joseph; James, Alan L; Kavousi, Maryam; Miljkovic, Iva; Musk, Arthur W; Palmer, Lyle J; Peters, Annette; Roussel, Ronan; van der Harst, Pim; van Duijn, Cornelia M; Vollenweider, Peter; Barroso, Inês; Prokopenko, Inga; Dupuis, Josée; Meigs, James B; Bouatia-Naji, Nabila.
Afiliación
  • Liu CT; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, 02118, USA. ctliu@bu.edu.
  • Merino J; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Rybin D; Programs in Metabolism and Medical & Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • DiCorpo D; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Benke KS; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, 02118, USA.
  • Bragg-Gresham JL; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, MA, 02118, USA.
  • Canouil M; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
  • Corre T; Kidney Epidemiology and Cost Center, Department of Internal Medicine - Nephrology, University of Michigan, Ann Arbor, MI, 48109, USA.
  • Grallert H; CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, 59000, Lille, France.
  • Isaacs A; Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland.
  • Kutalik Z; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
  • Lahti J; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
  • Marullo L; Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.
  • Marzi C; German Center for Diabetes Research (DZD), Neuherberg, Germany.
  • Rasmussen-Torvik LJ; Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • Rocheleau G; CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio) and Department of Biochemistry, Maastricht University, Maastricht, The Netherlands.
  • Rueedi R; Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland.
  • Scapoli C; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
  • Verweij N; Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki, Finland.
  • Vogelzangs N; Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland.
  • Willems SM; Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy.
  • Yengo L; Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.
  • Bakker SJL; German Center for Diabetes Research (DZD), Neuherberg, Germany.
  • Beilby J; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Hui J; CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, 59000, Lille, France.
  • Kajantie E; Preventive and Genomic Cardiology, McGill University Health Centre and Research Institute, Montreal, Quebec, Canada.
  • Müller-Nurasyid M; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Rathmann W; The Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Balkau B; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Bergmann S; Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
  • Eriksson JG; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
  • Florez JC; Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy.
  • Froguel P; University Medical Center Groningen, Department of Cardiology, University of Groningen, Groningen, The Netherlands.
  • Harris T; Maastricht University, Department of Epidemiology, Cardiovascular Research Institute Maastricht (CARIM) & Maastricht Centre for Systems Biology (MaCSBio), Maastricht, The Netherlands.
  • Hung J; Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • James AL; CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, 59000, Lille, France.
  • Kavousi M; University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Groningen, The Netherlands.
  • Miljkovic I; PathWest Laboratory Medicine of Western Australia, Nedlands WA, 6009, Australia.
  • Musk AW; School of Pathology and Laboratory Medicine, The University of Western Australia, Nedlands WA, 6009, Australia.
  • Palmer LJ; Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands WA, Australia.
  • Peters A; PathWest Laboratory Medicine of Western Australia, Nedlands WA, 6009, Australia.
  • Roussel R; School of Pathology and Laboratory Medicine, The University of Western Australia, Nedlands WA, 6009, Australia.
  • van der Harst P; Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Nedlands WA, Australia.
  • van Duijn CM; School of Population and Global Health, The University of Western Australia, Nedlands WA, 6009, Australia.
  • Vollenweider P; National Institute for Health and Welfare, Helsinki, Finland.
  • Barroso I; Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
  • Prokopenko I; Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-Universität, Munich, Germany.
  • Dupuis J; Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.
  • Meigs JB; DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
  • Bouatia-Naji N; Institute for Biometrics and Epidemiology, German Diabetes Centre, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.
Sci Rep ; 9(1): 9439, 2019 07 01.
Article en En | MEDLINE | ID: mdl-31263163
ABSTRACT
Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P < 5 × 10-8) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P < 0.05) associated with fasting glucose change over time. Limited power influences unambiguous interpretation, but these data suggest that genetic effects on fasting glucose change over time are likely to be small. A public version of the data provides a genomic resource to combine with future studies to evaluate shared genetic links with T2D and other metabolic risk traits.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Glucemia / Población Blanca / Estudio de Asociación del Genoma Completo Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Glucemia / Población Blanca / Estudio de Asociación del Genoma Completo Tipo de estudio: Observational_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos