The purpose of this study was to quantify the impact of heterogeneity in the analysis and interpretation of GWAS findings. We showed that the presence of heterogeneity (presence of “non-cases”) reduced both the statistical power as well as the observed risks attributed to susceptibility alleles or genotypes. These findings were supported by the analysis of both simulated case-control and GWAS data from WTCCC T1D and T2D cohorts [24]. We also tested our hypothesis by analyzing loci replicated and validated in large-scale meta-analyses irrespective of their association strength in the WTCCC study, as these are more likely to represent true associations. The same pattern was observed for these loci: the magnitude of association declined substantially with increasing heterogeneity.
