Skip to main content
Article thumbnail
Location of Repository

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

By 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, Niels Grarup, 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, Torben Hansen, Oluf Pedersen, Mark Walker, Andreas F.H. Pfeiffer, Joachim Spranger, Michael Stumvoll, James B. Meigs, Nicholas J. Wareham, Johanna Kuusisto, Markku Laakso, Claudia Langenberg, Josée Dupuis, Richard M. Watanabe, Jose C. Florez, Erik Ingelsson, Mark I. Mccarthy and Inga Prokopenko

Abstract

Patients with established type 2 diabetes display both b-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. © 2014 by the American Diabetes Association

Topics: Alleles, Cluster Analysis, Diabetes Mellitus, Type 2, Female, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Insulin-Secreting Cells, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Transcription Factors, Genetic Predisposition to Disease, Internal Medicine, Endocrinology, Diabetes and Metabolism, Medicine (all)
Year: 2014
DOI identifier: 10.2337/db13-0949
OAI identifier: oai:iris.unife.it:11392/2355912
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://diabetes.diabetesjourna... (external link)
  • http://hdl.handle.net/11392/23... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.