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Interrogating type 2 diabetes genome-wide association data using a biological pathway-based approach.

ABSTRACT: Recent genome-wide association studies have resulted in a dramatic increase in our knowledge of the genetic loci involved in type 2 diabetes. In a complementary approach to these single-marker studies, we attempted to identify biological pathways associated with type 2 diabetes. This approach could allow us to identify additional risk loci.We used individual level genotype data generated from the Wellcome Trust Case Control Consortium (WTCCC) type 2 diabetes study, consisting of 393,143 autosomal SNPs, genotyped across 1,924 case subjects and 2,938 control subjects. We sought additional evidence from summary level data available from the Diabetes Genetics Initiative (DGI) and the Finland-United States Investigation of NIDDM Genetics (FUSION) studies. Statistical analysis of pathways was performed using a modification of the Gene Set Enrichment Algorithm (GSEA). A total of 439 pathways were analyzed from the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and BioCarta databases.After correcting for the number of pathways tested, we found no strong evidence for any pathway showing association with type 2 diabetes (top P(adj) = 0.31). The candidate WNT-signaling pathway ranked top (nominal P = 0.0007, excluding TCF7L2; P = 0.002), containing a number of promising single gene associations. These include CCND2 (rs11833537; P = 0.003), SMAD3 (rs7178347; P = 0.0006), and PRICKLE1 (rs1796390; P = 0.001), all expressed in the pancreas.Common variants involved in type 2 diabetes risk are likely to occur in or near genes in multiple pathways. Pathway-based approaches to genome-wide association data may be more successful for some complex traits than others, depending on the nature of the underlying disease physiology.

SUBMITTER: Perry JR

PROVIDER: S-EPMC2682674 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature

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Interrogating type 2 diabetes genome-wide association data using a biological pathway-based approach.

Perry John R B JR McCarthy Mark I MI Hattersley Andrew T AT Zeggini Eleftheria E Weedon Michael N MN Frayling Timothy M TM

Diabetes 20090227 6

<h4>Objective</h4>Recent genome-wide association studies have resulted in a dramatic increase in our knowledge of the genetic loci involved in type 2 diabetes. In a complementary approach to these single-marker studies, we attempted to identify biological pathways associated with type 2 diabetes. This approach could allow us to identify additional risk loci.<h4>Research design and methods</h4>We used individual level genotype data generated from the Wellcome Trust Case Control Consortium (WTCCC) ...[more]

PMID: 19252133

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Project description:This study examined how differences in the BMI distribution of type 2 diabetic case subjects affected genome-wide patterns of type 2 diabetes association and considered the implications for the etiological heterogeneity of type 2 diabetes.We reanalyzed data from the Wellcome Trust Case Control Consortium genome-wide association scan (1,924 case subjects, 2,938 control subjects: 393,453 single-nucleotide polymorphisms [SNPs]) after stratifying case subjects (into "obese" and "nonobese") according to median BMI (30.2 kg/m(2)). Replication of signals in which alternative case-ascertainment strategies generated marked effect size heterogeneity in type 2 diabetes association signal was sought in additional samples.In the "obese-type 2 diabetes" scan, FTO variants had the strongest type 2 diabetes effect (rs8050136: relative risk [RR] 1.49 [95% CI 1.34-1.66], P = 1.3 x 10(-13)), with only weak evidence for TCF7L2 (rs7901695 RR 1.21 [1.09-1.35], P = 0.001). This situation was reversed in the "nonobese" scan, with FTO association undetectable (RR 1.07 [0.97-1.19], P = 0.19) and TCF7L2 predominant (RR 1.53 [1.37-1.71], P = 1.3 x 10(-14)). These patterns, confirmed by replication, generated strong combined evidence for between-stratum effect size heterogeneity (FTO: P(DIFF) = 1.4 x 10(-7); TCF7L2: P(DIFF) = 4.0 x 10(-6)). Other signals displaying evidence of effect size heterogeneity in the genome-wide analyses (on chromosomes 3, 12, 15, and 18) did not replicate. Analysis of the current list of type 2 diabetes susceptibility variants revealed nominal evidence for effect size heterogeneity for the SLC30A8 locus alone (RR(obese) 1.08 [1.01-1.15]; RR(nonobese) 1.18 [1.10-1.27]: P(DIFF) = 0.04).This study demonstrates the impact of differences in case ascertainment on the power to detect and replicate genetic associations in genome-wide association studies. These data reinforce the notion that there is substantial etiological heterogeneity within type 2 diabetes.

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Interrogating type 2 diabetes genome-wide association data using a biological pathway-based approach.

Publications

Interrogating type 2 diabetes genome-wide association data using a biological pathway-based approach.

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