A study of analytical strategies to include X-chromosome in variance heterogeneity analysis: evidence for trait-specific polygenic variance structure

Genetic markers associated with variance of quantitative traits are considered promising candidates for follow-up including interaction analyses. However, as in studies of main effects, X-chromosome is routinely excluded from whole-genome scans due to analytical challenges. Specifically, as males carry only one copy of X-chromosome, the inherent sex-genotype dependency could bias the trait-genotype association, through sexual dimorphism in quantitative traits with sex-specific means or variances. Here we investigate phenotypic variance heterogeneity associated with SNPs on X-chromosome and propose robust strategies. Among those, a generalized Levene9s test, adjusting for sex and sex-genotype interaction effects, has adequate power and remains robust to sexual dimorphism. An alternative sex-stratified approach via Fisher9s method is the most robust at the cost of slightly reduced power. We applied both methods to an Estonian study of gene expression quantitative trait loci (eQTL; n=841), and two complex trait studies of height, hip and waist circumferences, and body mass index (BMI) collected on Caucasians in UK Biobank (UKB; n=132,968) and multi-ethnic study of atherosclerosis (MESA; n=2,073). Consistent with previous eQTL findings on mean, we found some but not conclusive evidence for cis regulators being enriched for variance association. Individual SNP rs148191803 was X-chromosome-wide significant for waist circumference (p=2.4E-6) and suggestive for BMI (p=1.2E-5) in UKB but not in MESA. However, a permutation study based on MESA showed a trait-specific polygenic model whereby multiple X-chromosome loci collectively influence variance of height (lambdaGC=1.14, p