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

2013; American Diabetes Association; Volume: 63; Issue: 6 Linguagem: Inglês

10.2337/db13-0949

1939-327X

Antigone S. Dimas, Vasiliki Lagou, Adam Barker, Joshua W. Knowles, Reedik Mägi, Marie‐France Hivert, Andrea Benazzo, Denis Rybin, Anne Jackson, Heather M. Stringham, Ci Song, Antje Fischer-Rosinský, Trine Welløv Boesgaard, Niels Grarup, Fahim Abbasi, Themistocles L. Assimes, Ke Hao, Xia Yang, Cécile Lecœur, Inês Barroso, Lori L. Bonnycastle, Yvonne Böttcher, Suzannah Bumpstead, Peter S. Chines, Michael R. Erdos, J. Graessler, Péter Kovács, Mario A. Morken, Narisu Narisu, Felicity Payne, Alena Stančáková, 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, Torben Hansen, Oluf Pedersen, Mark Walker, A. Pfeiffer, Joachim Spranger, Michael Stümvoll, James B. Meigs, Nicholas J. Wareham, Johanna Kuusisto, Markku Laakso, Claudia Langenberg, Josée Dupuis, Richard M. Watanabe, José C. Florez, Erik Ingelsson, Mark I. McCarthy, Inga Prokopenko,

Pancreatic function and diabetes

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.