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

ABSTRACT: Patients with established type 2 diabetes display both ?-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.

SUBMITTER: Dimas AS

PROVIDER: S-EPMC4030103 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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

Dimas Antigone S AS Lagou Vasiliki V Barker Adam A Knowles Joshua W JW Mägi Reedik R Hivert Marie-France MF Benazzo Andrea A Rybin Denis D Jackson Anne U AU Stringham Heather M HM Song Ci C Fischer-Rosinsky Antje A Boesgaard Trine Welløv TW Grarup Niels N Abbasi Fahim A FA Assimes Themistocles L TL Hao Ke K Yang Xia X Lecoeur Cécile C Barroso Inês I Bonnycastle Lori L LL Böttcher Yvonne Y Bumpstead Suzannah S Chines Peter S PS Erdos Michael R MR Graessler Jurgen J Kovacs Peter P Morken Mario A MA Narisu Narisu N Payne Felicity F Stancakova Alena A Swift Amy J AJ Tönjes Anke A Bornstein Stefan R SR Cauchi Stéphane S Froguel Philippe P Meyre David D Schwarz Peter E H PE Häring Hans-Ulrich HU Smith Ulf U Boehnke Michael M Bergman Richard N RN Collins Francis S FS Mohlke Karen L KL Tuomilehto Jaakko J Quertemous Thomas T Lind Lars L Hansen Torben T Pedersen Oluf O Walker Mark M Pfeiffer Andreas F H AF Spranger Joachim J Stumvoll Michael M Meigs James B JB Wareham Nicholas J NJ Kuusisto Johanna J Laakso Markku M Langenberg Claudia C Dupuis Josée J Watanabe Richard M RM Florez Jose C JC Ingelsson Erik E McCarthy Mark I MI Prokopenko Inga I

Diabetes 20131202 6

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 adju ...[more]

PMID: 24296717

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Project description:ObjectiveShared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits.MethodsWe estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 × 10). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases.ResultsThe SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes).ConclusionsWe found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.

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

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

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