1. for the Diabetes Prevention Program Research Group
  1. 1 The Biostatistics Center, George Washington University, Rockville, Maryland, USA
  2. 2 Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
  3. 3 Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
  4. Departments of 4 Medicine and
  5. 10 Genetics, Harvard Medical School, Boston, Massachusetts, USA
  6. 5 Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
  7. 6 Genetic Epidemiology & Clinical Research Group, Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University Hospital, Umeå, Sweden and Department of Clinical Sciences, Lund University, Malmö, Sweden
  8. 7 Department of Medicine, Division of Endocrinology, Diabetes & Nutrition, University of Maryland School of Medicine, Baltimore, Maryland, USA
  9. 8 Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA
  10. 9 Geriatrics Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, Maryland, USA; and
  11. 11 Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA


Objective: Genome-wide association studies (GWAS) have begun to elucidate the genetic architecture of type 2 diabetes (T2D). We examined whether single nucleotide polymorphisms (SNPs) identified through targeted complementary approaches impact diabetes incidence in the at-risk population of the Diabetes Prevention Program (DPP), and whether they influence response to preventive interventions.

Research Design and Methods: We selected SNPs identified by prior GWAS for T2D and related traits, or capturing common variation in 40 candidate genes previously associated with T2D, implicated in monogenic diabetes, encoding T2D 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 (FDR).

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) kinase 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 non-overlapping SNPs, respectively. The lowest P-values were consistent with experiment-wide 33% FDR.

Conclusions: We have identified potential genetic determinants of metformin response. These results merit confirmation in independent samples.


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