Multilocus heterozygosity and coronary heart disease: nested case-control studies in men and women

Unbalanced Sample Size Introduces Spurious Correlations to Genome-Wide Heterozygosity Analyses

Excess of heterozygosity (H) is a widely used measure of genetic diversity of a population. As high-throughput sequencing and genotyping data become readily available, it has been applied to investigating the associations of genome-wide genetic diversity with human diseases and traits. However, these studies often report contradictory results. In this paper, we present a meta-analysis of five whole-exome studies to examine the association of H scores with Alzheimer's disease. We show that the mean H score of a group is not associated with the disease status, but ot is associated with the sample size. Across all five studies, the group with more samples has a significantly lower H score than the group with fewer samples. To remove potential confounders in empirical data sets, we perform computer simulations to create artificial genomes controlled for the number of polymorphic loci, the sample size, and the allele frequency. Analyses of these simulated data confirm the negative correlation between the sample size and the H score. Furthermore, we find that genomes with a large number of rare variants also have inflated H scores. These biases altogether can lead to spurious associations between genetic diversity and the phenotype of interest. Based on these findings, we advocate that studies shall balance the sample sizes when using genome-wide H scores to assess genetic diversities of different populations, which helps improve the reproducibility of future research.

Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk

Greater genetic variability in an individual is protective against recessive disease. However, existing quantifications of autozygosity, such as runs of homozygosity (ROH), have proved highly sensitive to genotyping density and have yielded inconclusive results about the relationship of diversity and disease risk. Using genotyping data from three data sets with >43,000 subjects, we demonstrated that an alternative approach to quantifying genetic variability, the heterozygosity ratio, is a robust measure of diversity and is positively associated with the nondisease trait height and several disease phenotypes in subjects of European ancestry. The heterozygosity ratio is the number of heterozygous sites in an individual divided by the number of nonreference homozygous sites and is strongly affected by the degree of genetic admixture of the population and varies across human populations. Unlike quantifications of ROH, the heterozygosity ratio is not sensitive to the density of genotyping performed. Our results establish the heterozygosity ratio as a powerful new statistic for exploring the patterns and phenotypic effects of different levels of genetic variation in populations.