Autosomal genes contributing to variation in many complex traits are influenced by male or female physiological 'environments.' Accounting for such genotype-by-sex (GxS) interactions has been shown to be important in quantitative genetic, segregation, and linkage analyses of a number of sexually dimorphic traits. In analyses of data simulated for GAW10, we showed that incorporating sex-specific variance components into a variance components-based linkage method increased the power to detect linkage in a trait that exhibited GxS interaction. The goals of this study of data from the Collaborative Study on the Genetics of Alcoholism (COGA) were to screen the event-related brain potential (ERP) data from COGA participants for GxS interaction, and then to conduct variance components linkage analysis of ERP phenotypes showing evidence of GxS interaction using models incorporating sex-specific variance components. Significant GxS interaction was found in four ERP phenotypes: N100 measured at occipital leads 1 and 2, and P300 measured at occipital leads 1 and 2. In linkage analyses of these traits, the most significant lod score found was that between N100 occipital lead 1 amplitude and marker D7S490. The peak lod score at the D7S490 locus was 2.45 without sex-specific variance components, and 3.25 with sex-specific marker and residual polygenic components.
- Genotype x sex interaction
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