Biased tests of association: comparisons of allele frequencies when departing from Hardy-Weinberg proportions.

Abstract

Association studies of genetic markers or candidate genes with disease are often conducted using the traditional case-control design. Cases and controls are sampled from genetically unrelated subjects, and allele frequencies compared between cases and controls using Pearson's chi-square statistic. An assumption of this analysis method is that the two alleles within each subject are statistically independent, at least when no association exists. This is equivalent to assuming that the frequencies of the genotypes in the general population comply with Hardy-Weinberg Equilibrium proportions, which may not always be the case. However, deviations from Hardy-Weinberg Equilibrium can inflate the chance of a false-positive association. These results demonstrate that when comparing the frequencies of two alleles between cases and controls, the chance of a false-positive association can be substantially increased if homozygotes for the putative high-risk allele are more common in the general population than predicted by Hardy-Weinberg Equilibrium. In contrast, Pearson's chi-square statistic can be conservative if the frequency of homozygotes for the high-risk allele is less than that predicted. A statistically valid method that corrects for deviations from Hardy-Weinberg Equilibrium is presented, so that the chance of a false-positive association is not greater than the acceptable level.