Implications of the Co-Dominance Model for Hardy-Weinberg Testing in Genetic Association Studies.

INTRODUCTION: The standard way of using tests for compatibility of genetic markers with the Hardy-Weinberg equilibrium (HWE) assumptionvas a means of quality control in genetic association studies (GAS) is to vcarry out this step of preliminary data analysis with the sample of non-diseased vindividuals only. We show that this strategy has no rational basis whenever the genotype--phenotype relation for avmarker under consideration satisfies the assumption of co-dominance. METHODS/RESULTS: The justification of this statement is the fact rigorously shown here that under co-dominance, the genotype distribution of a diallelic marker is in HWE among the controls if and only if the same holds true for the cases. CONCLUSION: The major practical consequence of that theoretical result is that under the co-dominance model, testing for HWE should be done both for cases and controls aiming to establish the combined (intersection) hypothesis of compatibility of both underlying genotype distributions with the HWE assumption. A particularly useful procedure serving this purpose is obtained through applying the confidence-interval inclusion rule derived by Wellek, Goddard and Ziegler (Biom J. 2010; 52:253-270) to both samples separately and combining these two tests by means of the intersection-union principle.

Gene-gene Interaction Analyses for Atrial Fibrillation.

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27-1.65, P = 4.3 × 10-8). Eight additional gene-gene interactions were also marginally significant (P < 5 × 10-7). However, none of the top interactions were replicated. In summary, we did not find significant interactions that were associated with AF susceptibility. Future increases in sample size and denser genotyping might facilitate the identification of gene-gene interactions associated with AF.