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.
Keywords: Complex trait, Genetic heterogeneity, Genetic relationship matrix, Genetic variance, Genome-wide association
study, Mixed model.
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