title: Integration of disease-specific single nucleotide polymorphisms, expression quantitative trait loci and coexpression networks reveal novel candidate genes for type 2 diabetes.
abstract: OBJECTIVE
  While 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.
  
  
  METHODS
  We 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.
  
  
  RESULTS
  We 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
  We have devised a novel method, involving the integration of datasets of different modalities, to discover novel candidate genes for type 2 diabetes.
authors.affiliation: Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, 1265 Welch Road, Room X163, Stanford, CA 94305, USA.
authors.forename: H P
authors.initials: HP
authors.lastname: Kang
authors.forename: X
authors.initials: X
authors.lastname: Yang
authors.forename: R
authors.initials: R
authors.lastname: Chen
authors.forename: B
authors.initials: B
authors.lastname: Zhang
authors.forename: E
authors.initials: E
authors.lastname: Corona
authors.forename: E E
authors.initials: EE
authors.lastname: Schadt
authors.forename: A J
authors.initials: AJ
authors.lastname: Butte
mesh_terms: D000818:Animals; D016022:Case-Control Studies; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics*; D020869:Gene Expression Profiling; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D051379:Mice; D008810:Mice, Inbred C57BL; D009767:Obesity, Morbid / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D015203:Reproducibility of Results