Abstract

Common genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.

Highlights

  • IntroductionThe Meta-Analysis of Glucose and Insulin-related traits Consortium (MAGIC) recently performed a global meta-analysis of 21 genome-wide association studies (GWAS) cohorts followed by replication in 26 studies, totaling .122,000 non-diabetic individuals for fasting glucose and .98,000 non-diabetic individuals for fasting insulin [8]

  • The Meta-Analysis of Glucose and Insulin-related traits Consortium (MAGIC) investigators reported a number of loci that influence fasting glucose and fasting insulin levels in nondiabetic populations of European descent; only a few of the loci were associated with type 2 diabetes at genome-wide levels of significance [8]

  • The authors speculated that it is not the mere elevation in fasting glucose, but how fasting glucose is raised, that determines overall b-cell dysfunction and future type 2 diabetes risk. Whether these loci exert their action on fasting glucose in the initial stages of diabetes progression or later is not known

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Summary

Introduction

The Meta-Analysis of Glucose and Insulin-related traits Consortium (MAGIC) recently performed a global meta-analysis of 21 GWAS cohorts followed by replication in 26 studies, totaling .122,000 non-diabetic individuals for fasting glucose and .98,000 non-diabetic individuals for fasting insulin [8] These efforts confirmed the GCK, G6PC2 and MTNR1B associations, and uncovered associations of fasting glucose with single nucleotide polymorphisms (SNPs) in or near DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B and the type 2 diabetes genes TCF7L2 and SLC30A8. SNPs in or near IGF1, GCKR and perhaps IRS1 have been found to influence fasting insulin concentrations, a surrogate for insulin resistance Of these loci, only GCK, MTNR1B, DGKB, GCKR, ADCY5 and PROX1 (besides TCF7L2 and SLC30A8) were associated with type 2 diabetes at genome-wide significance levels, with several others (but not all) showing a consistent trend but not meeting the same stringent statistical threshold. This work has illustrated that genetic associations with quantitative intermediate traits may lead to the discovery of type 2 diabetes loci, and that not all genetic loci that influence fasting glucose levels in healthy individuals necessarily contribute to type 2 diabetes pathogenesis

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