paperKB
coga / coga-kb
Help
Sign in

Chunk #10 — Materials and Methods — Analysis of WTCCC Type 1 and Type 2 Diabetes Data Under Heterogeneity

Source
The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases.
Embedded
yes

Text

To investigate the effect of heterogeneity, we examined the 20 SNPs most significantly associated with T1D or T2D, respectively. These SNPs are independent and in linkage equilibrium to each other, with the exception of rs9939609 and rs7193144 within the FTO gene which are in strong linkage disequilibrium (R2 = 0.97, D’ = 1) and are both associated with T2D. Further, we studied 21 and 16 polymorphisms found associated in subsequent large-scale meta-analyses for T1D [26]–[29] and T2D [30], respectively. The selected SNPs were genotyped in the WTCCC study and were required to have p<10−6 in at least one meta-analysis study. We created alternate phenotype files in order to simulate heterogeneity. Let N1 and N2 denote the respective totals of T1D and T2D cases. At each 10% increment of β, we removed N1*β subjects randomly selected from the T1D population and replaced them with N1*β subjects randomly chosen from the T2D population. Similarly, we analyzed T2D data, replacing N2*β T2D with T1D cases. For each of T1D and T2D, 100 alternate samples were created at each 10% increment of β. Association