Leveraging Hardy–Weinberg disequilibrium for association testing in case-control studies

Abstract

Modern genome-wide association studies (GWAS) remove single nucleotide polymorphisms (SNPs) that are in Hardy–Weinberg disequilibrium (HWD), despite limited rigor for this practice. In a case-control GWAS, although HWD in the control sample is an evidence for genotyping error, a truly associated SNP may be in HWD in the case and/or control populations. We, therefore, develop a new case-control association test that: (i) leverages HWD attributed to true association to increase power, (ii) is robust to HWD caused by genotyping error, and (iii) is easy-to-implement at the genome-wide level. The proposed robust allele-based joint test incorporates the difference in HWD between the case and control samples into the traditional association measure to gain power. We provide the asymptotic distribution of the proposed test statistic under the null hypothesis. We evaluate its type 1 error control at the genome-wide significance level of $5\times {10}^{-8}$ in the presence of HWD attributed to factors unrelated to phenotype-genotype association, such as genotyping error. Finally, we demonstrate that the power of the proposed allele-based joint test is higher than the standard association test for a variety of genetic models, through derivations of the noncentrality parameters of the tests, as well as simulation and application studies.