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Genet Epidemiol. 2019 Oct;43(7):815-830. doi: 10.1002/gepi.22247. Epub 2019 Jul 22.

Analytical strategies to include the X-chromosome in variance heterogeneity analyses: Evidence for trait-specific polygenic variance structure.

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Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, Canada.
Department of Pathology and Molecular Medicine, Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Canada.
Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.
Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts.
Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada.
Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.


Genotype-stratified variance of a quantitative trait could differ in the presence of gene-gene or gene-environment interactions. Genetic markers associated with phenotypic variance are thus considered promising candidates for follow-up interaction or joint location-scale analyses. However, as in studies of main effects, the X-chromosome is routinely excluded from "whole-genome" scans due to analytical challenges. Specifically, as males carry only one copy of the 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 X-chromosome single nucleotide polymorphisms (SNPs) and propose valid and powerful strategies. Among those, a generalized Levene's test has adequate power and remains robust to sexual dimorphism. An alternative approach is a sex-stratified analysis but at the cost of slightly reduced power and modeling flexibility. 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 from Multi-Ethnic Study of Atherosclerosis (MESA; n = 2,073) and UK Biobank (UKB; n = 327,393). Consistent with previous eQTL findings on mean, we found some but no conclusive evidence for cis regulators being enriched for variance association. SNP rs2681646 is associated with variance of waist circumference (p = 9.5E-07) at X-chromosome-wide significance in UKB, with a suggestive female-specific effect in MESA (p = 0.048). Collectively, an enrichment analysis using permutated UKB (p < 0.1) and MESA (p < 0.01) datasets, suggests a possible polygenic structure for the variance of human height.


X-chromosome association; complex traits; eQTL; gene-environment interaction; variance heterogeneity

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