Supplementary Table 1 (available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db10-0543/DC1
) shows that we achieved adequate coverage of all 40 genes in the two targeted populations, with 37 genes reaching at least 80% of common variants captured at r2
≥ 0.8 in Europeans and all 40 reaching at least 70% of common variants captured at that level (comparable numbers were obtained in Africans). The average proportion of European ancestry among the DPP self-described white participants, as determined by ancestry-informative markers, was 98.9%, and the average proportion of West-African ancestry among DPP self-described African American participants was 89.3%. Given these results, we used self-described ethnicity as a covariate for these analyses. The full set of results is available in supplementary Table 2.
shows the candidate gene regions harboring variants nominally associated with diabetes incidence in the treatment-adjusted models for the full study (i.e., there was no evidence for interaction with either intervention); only the top SNP within each gene region (out of 85 nominal associations) is given. The most significant associations occurred at SNPs in the AMP kinase (AMPK) subunit gene PRKAG2 (hazard ratio [HR] 1.24, 95% CI 1.09–1.40, P = 7.0 × 10−4 for the top SNP rs5017427, which is consistent with an experiment-wide 34% FDR). Twelve other PRKAG2 SNPs were nominally associated with diabetes (five in the top ten). Although most of them are in moderate to high LD with the index SNP (r2 ranging from 0.49 to 1.0 in HapMap CEU), at least two of them (rs954482 and rs2727537) are only weakly correlated with rs5017427 (r2 0.07 and 0.05, respectively). Nevertheless, the consistency of the association signal in this region provides reassurance with regard to the absence of genotyping artifacts in our dataset. Of SNPs previously associated with type 2 diabetes in the 100K Amish, Framingham, or Pima GWASs, three (rs1422930 in ODZ2, rs1859441 near COL2A1 and SENP1, and rs385909 near SH3YL1) had consistent nominal associations with diabetes incidence in the DPP, and two had nominally significant associations (rs10520926 and rs3136279) in the opposite direction. On the other hand, none of the six SNPs selected from the DIAGRAM meta-analysis (original odds ratio [OR] ranging from 1.05 to 1.15) were nominally significant in the DPP. Fifteen SNPs in genes that cause either maturity-onset diabetes of the young or neonatal diabetes were nominally associated with diabetes incidence; one of them, rs11868513 in HNF1B (not in LD with the previously type 2 diabetes–associated SNP rs757210), was strongly associated with diabetes incidence in the placebo arm (HR 1.69, 95% CI 1.36–2.10, P = 2 × 10−6). Finally, 14 SNPs in genes that encode metformin transporters (SLC22A1, SLC22A2, and SLC47A1) were nominally associated with diabetes incidence. Of the 85 nominal associations with diabetes incidence in DPP, only two SNPs (rs651164 in SLC22A1 and rs3736265 in PPARGC1A) were nominally associated with type 2 diabetes in DIAGRAM in a consistent direction (OR 1.08, 95% CI 1.02–1.16, P = 0.01, and OR 1.15, 95% CI 1.01–1.31, P = 0.04, respectively), with 60 other SNPs not being nominally significantly associated in DIAGRAM and 23 SNPs not captured in that dataset.
Candidate gene variants nominally associated with diabetes incidence in the DPP
shows the candidate gene regions harboring variants that have a nominally significant genotype × metformin interaction; only the top SNP within each gene region is given (out of 91 nominal associations). The best result was consistent with a study-wide 33% FDR. At rs8065082 in SLC47A1, there was a nominal interaction with metformin (P = 0.006), with the minor allele associated with lower diabetes incidence in the metformin arm (HR 0.78, 95% CI 0.64–0.96, P = 0.02) but not in the placebo arm (1.15, 0.97–1.37, P = 0.11). At this locus, major allele homozygotes did not benefit from metformin with regard to diabetes prevention (HR 1.07, 95% CI 0.77–1.50, vs. placebo, P = 0.68), whereas minor allele carriers did (0.58, 0.46–0.73, vs. placebo, P < 0.001; ). We also noted a nominally significant interaction of a missense SNP in SLC22A1 (rs683369, encoding L160F) with metformin, with the major allele protecting from diabetes in the metformin arm (HR 0.69, 95% CI 0.53–0.89, P = 0.004) but not the placebo arm (1.01, 0.79–1.30, P = 0.91); the major allele is therefore associated with 31% risk reduction in diabetes incidence but only under the action of metformin. In this arm, the likelihood of developing diabetes depended on the number of phenylalanine alleles (HR 0.72, 95% CI 0.59–0.88, vs. placebo for LL homozygotes; 0.92, 0.66–1.28, for heterozygotes; and 1.44, 0.56–3.67, for FF homozygotes). There were five nominally significant interactions at SNPs encoding putative drug targets for metformin, in the gene encoding the AMPK kinase STK11 and the AMPK subunit genes PRKAA1, PRKAA2, and PRKAB2, respectively. A total of 22 SNPs in the ABCC8-KCNJ11 region also had nominally significant interactions with metformin, including rs5215, which is tightly linked to the widely replicated type 2 diabetes–associated missense SNP rs5219 (E23K) in KCNJ11.
Candidate gene variants showing a nominally significant interaction with the metformin intervention in the DPP
FIG. 1. Diabetes incidence in the DPP, by genotype at rs8065082 in the SLC47A1 gene. This SNP is in tight LD with rs2289669 (r2 ~0.8), whose major allele predicts a poorer response to metformin (5). In the DPP, major allele homozygotes at rs8065082 did (more ...)
shows the candidate gene regions harboring variants that have a nominally significant interaction with the lifestyle intervention; only the top SNP within each gene region is given (out of 69 nominal associations). The best result was consistent with an experiment-wide 84% FDR. Twelve of the top findings were in four AMPK subunit genes (PRKAA2, PRKAB2, PRKAG1, and PRKAG2), and 11 SNPs clustered around the peroxisome proliferator–associated receptor γ coactivators 1α and 1β (PPARGC1A and PPARGC1B, respectively).
Candidate gene variants showing a nominally significant interaction with the lifestyle intervention in the DPP
Review of 1,609 SNPs imputed in non-Hispanic white DPP participants (supplementary Table 3) revealed the nominal association of other PRKAG2 SNPs with diabetes incidence (best P = 5 × 10−5). Imputed SNPs in the PRKAA1, PRKAA2, and ABCC8-KCNJ11 regions also had nominally significant interactions with metformin.