Analytical Models For Genetics of Human Traits Influenced By Sex

Abstract

Analytical models usually assume an additive sex effect by treating it as a covariate to identify genetic associations with sex-influenced traits. Their underlying assumptions are violated by ignoring interactions of sex with genetic factors and heterogeneous genetic effects by sex. Methods to deal with the problems are compared and discussed in this article. Especially, heterogeneity of genetic variance by sex can be assessed employing a mixed model with genetic relationship matrix constructed from genome-wide nucleotide variant information. Estimating genetic architecture of each sex would help understand different prevalence, course, and severity of complex diseases between women and men in the era of personalized medicine.

Genetic Association of Diagnostic Traits of Metabolic Syndrome with Lysosomal Pathways: Insights from Target Gene Enrichment Analysis

“…To reduce the burden of such complexity, employing more rational methods would be helpful in accurately estimating eQTL effects; that is, mixed model-based methods that may avoid confounding polygenic effects [58,59]. Moreover, to explain heterogeneity by sex in precision medicine [60], the genetic covariance between males and females was estimated using a modified mixed model [61].…”

Genome-Wide Expression Quantitative Trait Loci Analysis Using Mixed Models

“…However, heterogeneous effects of sex are also important as an interaction between eQTLs and sex, especially for genes with hormone-dependent functions. Heterogeneous eQTLs by sex can be explained by separate analyses with partitioned data or by sex-stratified bivariate mixed models ( Lee, 2016a ). A straightforward sex-stratified model is the two-phenotype model in which male expression is treated as one phenotype and female expression as the other ( Lee et al, 1997 , 2012 ).…”