Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

  1. on behalf of the MAGIC Investigators
  1. 1Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K.
  2. 2Alexander Fleming, Biomedical Sciences Research Center, Vari, Athens, Greece
  3. 3Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, U.K.
  4. 4Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, U.K.
  5. 5Department of Medicine and Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA
  6. 6Estonian Genome Center, University of Tartu, Tartu, Estonia
  7. 7Department of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
  8. 8General Medicine Division, Massachusetts General Hospital, Boston, MA
  9. 9Department of Biology and Evolution, University of Ferrara, Ferrara, Italy
  10. 10Boston University Data Coordinating Center, Boston, MA
  11. 11Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI
  12. 12Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
  13. 13Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
  14. 14Charité-Universitätsmedizin Berlin, Department of Endocrinology and Metabolism, Berlin, Germany
  15. 15Steno Diabetes Center, Gentofte, Denmark
  16. 16The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
  17. 17Department of Genetics and Genomic Sciences, Institute of Genomics and Multiscale Biology, Mount Sinai School of Medicine, New York, NY
  18. 18Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA
  19. 19CNRS UMR8199-Institute of Biology, Pasteur Institute, Lille 2-Droit et Santé University, Lille, France
  20. 20Wellcome Trust Sanger Institute, Hinxton, U.K.
  21. 21University of Cambridge Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, U.K.
  22. 22Genome Technology Branch, National Human Genome Research Institute, Bethesda, MD
  23. 23IFB AdiposityDiseases, Leipzig University Medical Center, Leipzig, Germany
  24. 24Department of Medicine III, Division of Prevention and Care of Diabetes, University of Dresden, Dresden, Germany
  25. 25Interdisciplinary Center for Clinical Research Leipzig, Leipzig, Germany
  26. 26Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
  27. 27Department of Medicine, University of Leipzig, Leipzig, Germany
  28. 28Department of Genomics of Common Disease, Imperial College London, London, U.K.
  29. 29Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada
  30. 30Department of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Medicine, Nephrology and Clinical Chemistry, University of Tübingen, Tübingen, Germany
  31. 31Lundberg Laboratory for Diabetes Research, Center of Excellence for Metabolic and Cardiovascular Research, Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
  32. 32Department of Physiology & Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, CA
  33. 33Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, NC
  34. 34Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
  35. 35Centre for Vascular Prevention, Danube University Krems, Krems, Austria
  36. 36King Abdulaziz University, Jeddah, Saudi Arabia
  37. 37Department of Medical Sciences, Akademiska Sjukhuset, Uppsala University, Uppsala, Sweden
  38. 38Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
  39. 39Hagedorn Research Institute, Copenhagen, Denmark
  40. 40Institute of Biomedical Science, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
  41. 41Faculty of Health Sciences, University of Aarhus, Aarhus, Denmark
  42. 42Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, U.K.
  43. 43Department of Clinical Nutrition, German Institute of Human Nutrition, Nuthetal, Germany
  44. 44Department of Medicine, Harvard Medical School, Boston, MA
  45. 45Department of Biostatistics, Boston University School of Public Health, Boston, MA
  46. 46The National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA
  47. 47Departments of Preventive Medicine and Physiology & Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, CA
  48. 48Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA
  49. 49Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
  50. 50Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hospital, Oxford, U.K.
  1. Corresponding authors: Inga Prokopenko, i.prokopenko{at}imperial.ac.uk; Mark I. McCarthy, mark.mccarthy{at}drl.ox.ac.uk; Erik Ingelsson, erik.ingelsson{at}medsci.uu.se; Jose C. Florez, jcflorez{at}partners.org; and Richard M. Watanabe, rwatanab{at}usc.edu.
  1. A.S.D., V.L., A.Ba., J.W.K., R.M.W., J.C.F., E.I., M.I.M., and I.P. contributed equally to this work.

Abstract

Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

Footnotes

  • Received June 18, 2013.
  • Accepted November 23, 2013.

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  1. Diabetes vol. 63 no. 6 2158-2171
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