Demonstrating genotype–sex interaction effects on human diseases has been challenging because, until recently, most study designs did not allow a systematic search for sex-specific genetic contribution to quantitative variation or disease risk47. Moreover, in most linkage and association studies that address sex-specific architecture, analyses are performed in each sex separately (usually in addition to studies in the combined sample), adding to the number of statistical tests and increasing the likelihood of a type i error if multiple testing is not properly taken into account when assessing significance. On the other hand, the roughly halving of the sample size to conduct sex-specific analysis reduces the power to detect an effect. For example, a study with 80% power for a main effect will have only 29% power to detect an interaction of the same magnitude48, making replication of genotype–sex interactions particularly challenging.
