Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity

Research output: Contribution to journalJournal articleResearchpeer-review

  • Antigone S Dimas
  • Vasiliki Lagou
  • Adam Barker
  • Joshua W Knowles
  • Reedik Mägi
  • Marie-France Hivert
  • Andrea Benazzo
  • Denis Rybin
  • Anne U Jackson
  • Heather M Stringham
  • Ci Song
  • Antje Fischer-Rosinsky
  • Trine Welløv Boesgaard
  • Grarup, Niels
  • Fahim A Abbasi
  • Themistocles L Assimes
  • Ke Hao
  • Xia Yang
  • Cécile Lecoeur
  • Inês Barroso
  • Lori L Bonnycastle
  • Yvonne Böttcher
  • Suzannah Bumpstead
  • Peter S Chines
  • Michael R Erdos
  • Jurgen Graessler
  • Peter Kovacs
  • Mario A Morken
  • Narisu Narisu
  • Felicity Payne
  • Alena Stancakova
  • Amy J Swift
  • Anke Tönjes
  • Stefan R Bornstein
  • Stéphane Cauchi
  • Philippe Froguel
  • David Meyre
  • Peter E H Schwarz
  • Hans-Ulrich Häring
  • Ulf Smith
  • Michael Boehnke
  • Richard N Bergman
  • Francis S Collins
  • Karen L Mohlke
  • Jaakko Tuomilehto
  • Thomas Quertemous
  • Lars Lind
  • Hansen, Torben
  • Pedersen, Oluf Borbye
  • Mark Walker
  • on behalf of the MAGIC investigators
Patients with established type 2 diabetes display both beta-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 non-diabetic subjects with basal measures, and 17,327 with dynamic measures. We employed 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 (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 (including TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without detectable change in fasting glucose. The final group contained twenty 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.
Original languageEnglish
JournalDiabetes
Volume63
Issue number6
Pages (from-to)2158-2171
Number of pages14
ISSN0012-1797
DOIs
Publication statusPublished - 2 Dec 2013

ID: 91907390