title: Association testing to detect gene-gene interactions on sex chromosomes in trio data.
abstract: Autism Spectrum Disorder (ASD) occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to the X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the significant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratification. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.
authors: Department of Statistics, Penn State University, University Park PA, USA.
authors: Yeonok
authors: Y
authors: Lee
authors: Debashis
authors: D
authors: Ghosh
authors: Yu
authors: Y
authors: Zhang
keywords: binary traits; generalized linear mixed effect model; gene–gene interaction; logistic model; sex chromosomes; trio data