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Common Variants in 40 Genes Assessed for Diabetes Incidence and Response to Metformin and Lifestyle Intervention in the Diabetes Prevention Program

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2010

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American Diabetes Association
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Jablonski, Kathleen A., Jarred B. McAteer, Paul I.W. de Bakker, Paul W. Franks, Toni I. Pollin, Robert L. Hanson, Richa Saxena, et al. 2010. Common variants in 40 genes assessed for diabetes incidence and response to metformin and lifestyle intervention in the diabetes prevention program. Diabetes 59(10): 2672-2681.

Abstract

OBJECTIVE: Genome-wide association studies have begun to elucidate the genetic architecture of type 2 diabetes. We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches affect diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP) and whether they influence a response to preventive interventions. RESEARCH DESIGN AND METHODS: We selected SNPs identified by prior genome-wide association studies for type 2 diabetes and related traits, or capturing common variation in 40 candidate genes previously associated with type 2 diabetes, implicated in monogenic diabetes, encoding type 2 diabetes drug targets or drug-metabolizing/transporting enzymes, or involved in relevant physiological processes. We analyzed 1,590 SNPs for association with incident diabetes and their interaction with response to metformin or lifestyle interventions in 2,994 DPP participants. We controlled for multiple hypothesis testing by assessing false discovery rates. RESULTS: We replicated the association of variants in the metformin transporter gene (SLC47A1) with metformin response and detected nominal interactions in the AMP kinase (AMPK) gene (STK11), the AMPK subunit genes (PRKAA1) and (PRKAA2), and a missense SNP in (SLC22A1), which encodes another metformin transporter. The most significant association with diabetes incidence occurred in the AMPK subunit gene (PRKAG2) (hazard ratio 1.24, 95% CI 1.09–1.40, P = 7 × 10(^{−4})). Overall, there were nominal associations with diabetes incidence at 85 SNPs and nominal interactions with the metformin and lifestyle interventions at 91 and 69 mostly nonoverlapping SNPs, respectively. The lowest (P) values were consistent with experiment-wide 33% false discovery rates. CONCLUSIONS: We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.

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