We were unable to validate the individual association of previously reported genetic variants identified by GWAS with diabetes incidence in the DPP; however, when taken as an aggregate, we identified a nominally significant increase in diabetes incidence for those with a risk allele score of 7.5–9 compared with those with a score of <3.5 (P = 0.04). Given the higher prior probability of these diabetes-associated variants, this nominal P value is of interest even in the context of multiple hypotheses testing and illustrates a potential strategy for combining a full complement of diabetes-associated variants in risk prediction as additional loci are identified.
The DPP is a unique cohort that differs from the case-control design used in the prior GWAS studies detailed above. Participants in the DPP were at relatively high-risk at baseline (as evidenced by the 11% per year development of diabetes in the placebo group) and were presumably at a relatively late stage in the pathogenesis of disease. The DPP population is very homogeneous in their risk of type 2 diabetes: thus, as there is a smaller phenotypic difference between DPP participants who develop diabetes and those who do not (compared with the case-control designs of the published GWAS), the role of genetic variation is more difficult to ascertain. This limitation is supported by the apparently higher frequency of the risk alleles in the DPP white cohort compared with the reference groups from the HapMap CEU population and original GWAS cohorts.
The DPP is also limited in its ability to replicate the GWAS findings given its interventional design, in which a majority of participants received either a medication or lifestyle modification designed to prevent diabetes, again reducing the number of incident cases and thus our ability to observe the effect of genetic variation at multiple diabetes-related genes. In addition, the DPP cohort is multiethnic, introducing divergent allele frequencies and additional population differences that may increase population heterogeneity. The impact of these newly identified variants is quite modest, and our power calculations show that the cohort examined here only has marginal power to detect such effect sizes. Furthermore, positive gene-treatment interactions may have reduced our power even further. Nevertheless, in previous work, we have been able to convincingly replicate the association of relatively powerful genetic factors such as TCF7L2
with diabetes, illustrating that the DPP is an appropriate cohort to study genetic variants of high enough frequency and/or with strong effects (16
). The SNPs examined here were marker SNPs chosen from prior GWASs and are not known to represent causal mutations. Further fine mapping of these gene regions will be required in larger, better-powered studies to identify potential causal variants, because the current study is underpowered for such an analysis. Finally, the analysis of two of the genetic loci investigated, EXT2
and LOC387761, was largely exploratory because these loci have not been reproducibly associated with type 2 diabetes and associated traits in more recent studies.
Interestingly, in unadjusted analyses of variants at both LOC387761 and IGF2BP2
, carriers of the presumed high-risk genotypes had paradoxically higher insulin secretion levels at baseline and 1 year. The LOC387761 finding is consistent with results recently reported by Palmer et al. (15
) in the IRAS-FS, in which Hispanic Americans with the risk variant at LOC387761 had apparently higher acute insulin response (P
= 0.005) and disposition index (P
= 0.04) than low-risk genotype carriers (these results were not replicated in the African American cohort). When we adjusted for ethnicity, however, the associations of genotype at LOC387761 with insulin secretion were abolished, as were most of the IGF2BP2
associations (see below). The disparate results of our crude and adjusted analysis underscores the critical role ethnicity may play in confounding genetic association studies, particularly in admixed populations. Genetic loci with allele frequencies that diverge significantly across populations are particularly susceptible to confounding by ethnicity when tested for association with phenotypes whose prevalence also differs across populations. In such a scenario, a particular variant may simply be a marker for ancestry rather than truly associated with the trait under study. In the DPP, although diabetes incidence did not differ significantly across the five ethnic groups (19
), baseline quantitative glycemic traits did (26
). LOC387761 rs7480010 and IGF2BP2
rs1470579 SNPs have dramatically different allele frequencies in white and black populations (), which may allow genotype-phenotype associations to be confounded by genotype-ethnicity associations. Further studies, powered for stratified analyses of minority populations and adjusted for possible population substructure with the use of ancestry informative markers, will be required for investigators to fully understand the role genetic variants at these two loci play in individual ethnic groups. With regard to LOC387761, given the failure of other groups to replicate the association of this locus with type 2 diabetes (3
) and the disappearance of statistical significance in our results once ethnicity is taken into consideration, the role of this locus in disease pathogenesis remains unclear.
We identified significant differences in insulin secretion by genotype at HHEX
at baseline and 1-year follow-up; however, adjusting the results for BMI abolished the effect, emphasizing the role BMI plays in modulating the impact of this genetic variant. Other investigators have also identified differences in insulin secretion by genotype at HHEX
, including 1
) Pascoe et al. (12
), who found a significant decrease in 30-min insulin response in subjects with the HHEX
risk variant; 2
) Grarup et al. (13
), who found that the risk variant of HHEX
was associated with a decreased acute insulin response after OGTT or tolbutamide challenge; and 3
) Staiger et al. (14
), who showed that the risk variant of HHEX
was associated with decreased insulin secretion after OGTT or intravenous glucose challenge.
We did not replicate the associations of several other diabetes-related variants with insulin secretion documented by others (6
). We may have been underpowered to replicate these previous findings because of a smaller effect of these genes on insulin secretion and sensitivity when compared with those identified by the original GWAS investigations. An alternative explanation is that in these participants at high risk for diabetes, pathological changes had already taken place that obscured the effect of single genetic variants on these physiological parameters.
We identified a single genomic region with a possible genotype-intervention interaction. The previously reported impairment in β-cell function in carriers of the high-risk genotype at CDKN2A/B rs10811661 when compared with the alternative genotypes was augmented by treatments that improved insulin sensitivity: subjects with the low-risk genotype at CDKN2A/B improved β-cell function to a greater extent than those with the high-risk genotype after treatment with troglitazone and possibly lifestyle modification for 1 year, suggesting that they may have benefited more from these interventions. This interaction was identified in both crude and ethnically adjusted analysis. More scientific investigation on the biological consequences of genotypic variation at CDKN2A/B will be required to determine why subjects with the high-risk genotype, who had decreased insulin secretion, benefited less from metformin or lifestyle modification than low-risk genotype subjects. Although this is one of the first reports of a potential pharmacogenetic interaction with one of the newly identified type 2 diabetes gene regions, this finding is limited by the modest nominal P values obtained here, the multiple tests performed, and the unclear mechanism of action. Independent confirmation of these complex gene-environment interactions is needed.
In summary, although we were unable to replicate the findings of the original GWAS scans in our smaller, prediabetic population, our quantitative trait analysis confirms differences in insulin secretion by genotype at HHEX and CDKN2A/B. This study also emphasizes the important role ancestry may play at the diabetes-associated SNPs in LOC387761 and IGF2BP2, which have dramatically different allele frequencies in populations of European and African ancestry. Finally, we have identified a potential genotype-intervention interaction at CDKN2A/B; however, this hypothesis-generating finding needs to be confirmed by additional studies. Further studies are required to better understand the differences in insulin dynamics that result from variants at these and the other diabetes-associated genes identified to date.