In a linear regression setting, the presence of interaction effects drives phenotypic variance heterogeneity by genotype . Exploiting variance heterogeneity as a signature of interactions is appealing because, unlike standard approaches for assessing G×E interactions, no explicit information about environmental exposures is needed  and multiple exposures can be simultaneously considered.