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.
Genet Epidemiol. 2019 Oct;43(7):815-830. doi: 10.1002/gepi.22247. Epub 2019 Jul 22.
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 染色体上的单核苷酸多态性（SNP）与表型方差的关联存在遗传与环境的相互作用，因此，与表型方差相关的遗传标记被认为是后续相互作用或联合位置-尺度分析的有希望的候选者。然而，与主效应研究一样，由于分析上的挑战，X 染色体通常被排除在“全基因组”扫描之外。具体来说，由于男性只携带一条 X 染色体，因此性别-基因型的固有依赖性可能会通过具有性别特异性均值或方差的数量性状的性别二态性来偏置性状-基因型的关联。在这里，我们研究了与 X 染色体单核苷酸多态性（SNP）相关的表型方差异质性，并提出了有效且强大的策略。其中，广义 Levene 检验具有足够的功效，并且对性别二态性具有稳健性。另一种方法是性别分层分析，但代价是略微降低了功效和建模灵活性。我们将这两种方法应用于爱沙尼亚基因表达数量性状基因座（eQTL；n=841）的研究，以及三项复杂性状研究，包括来自动脉粥样硬化多民族研究（MESA；n=2073）和英国生物库（UKB；n=327393）的身高、臀部和腰围以及体重指数。与之前关于均值的 eQTL 发现一致，我们发现一些但没有确凿的证据表明顺式调控因子富集了方差关联。SNP rs2681646 与 UKB 全 X 染色体范围内显著的腰围方差（p=9.5E-07）相关，在 MESA 中具有女性特异性效应（p=0.048）。总体而言，使用置换的 UKB（p<0.1）和 MESA（p<0.01）数据集进行的富集分析表明，人类身高方差可能存在多基因结构。
