Abstract
Aims/hypothesisWhile genome-wide association studies (GWASs) have been successful in identifying novel variants associated with various diseases, it has been much more difficult to determine the biological mechanisms underlying these associations. Expression quantitative trait loci (eQTL) provide another dimension to these data by associating single nucleotide polymorphisms (SNPs) with gene expression. We hypothesised that integrating SNPs known to be associated with type 2 diabetes with eQTLs and coexpression networks would enable the discovery of novel candidate genes for type 2 diabetes.MethodsWe selected 32 SNPs associated with type 2 diabetes in two or more independent GWASs. We used previously described eQTLs mapped from genotype and gene expression data collected from 1,008 morbidly obese patients to find genes with expression associated with these SNPs. We linked these genes to coexpression modules, and ranked the other genes in these modules using an inverse sum score.ResultsWe found 62 genes with expression associated with type 2 diabetes SNPs. We validated our method by linking highly ranked genes in the coexpression modules back to SNPs through a combined eQTL dataset. We showed that the eQTLs highlighted by this method are significantly enriched for association with type 2 diabetes in data from the Wellcome Trust Case Control Consortium (WTCCC, p = 0.026) and the Gene Environment Association Studies (GENEVA, p = 0.042), validating our approach. Many of the highly ranked genes are also involved in the regulation or metabolism of insulin, glucose or lipids.Conclusions/interpretationWe have devised a novel method, involving the integration of datasets of different modalities, to discover novel candidate genes for type 2 diabetes.
Highlights
Genome-wide association studies (GWASs) of common complex or multifactorial diseases have proliferated enormouslyDiabetologia (2012) 55:2205–2213 over the last few years
Type 2 diabetes expression traits We started with 32 single nucleotide polymorphisms (SNPs) that have been associated with type 2 diabetes in multiple studies (Table 1) [17,18,19,20,21,22]
The expression of TCF7L2 is not associated with any of the SNPs studied, but there are several genes, including VTI1A, PDCD4 and CASP7, whose expression is associated with SNPs in TCF7L2
Summary
Diabetologia (2012) 55:2205–2213 over the last few years They have been successful in identifying a large number of loci at extraordinary levels of significance, given the large cohort sizes. This success has presented a new challenge: translating these findings into a full understanding of how the loci affect complex disease traits. Variations in DNA affecting the expression of a gene begs the question of whether such genetic variants, commonly known as expression quantitative trait loci (eQTLs), are an important factor in disease susceptibility [2]
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