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Chunk #14 — Results — Application to WTCCC Type 1 and Type 2 Diabetes Data

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The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases.
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To further test the validity of the results identified in the computer simulation we analyzed the WTCCC T1D and T2D data [24]. In both datasets we examined the 20 most significantly associated SNPs. Of these, 7 loci for T1D and 3 for T2D reached genome-wide significance and an additional 13 and 17 loci, respectively, showed moderate association. The results of this analysis are outlined in Figure 3. The strength of the association for T1D decreased substantially as the proportion of T2D cases in the sample was increased. Most of the significantly associated SNPs became equivocal at a relatively low degree of β (between 20% and 30%). Only the association of HLA-DRB1 with T1D [31] was robust to the effects of heterogeneity, with a significant effect present with up to 90% of the sample made up of T2D cases. Similarly, the strength of the association signals for T2D progressively diminished as T1D cases gradually replaced the “true” cases of T2D. Further support came from the analysis of loci found associated in subsequent meta-analyses of T1D and T2D (Figures S1 and S2). Again, with increasing degree of β the magnitude of association of the SNPs declined substantially.