observed interaction on choice of measurement scale (e.g. Jinks and Fulker, 1970) or, particularly in the case of binary phenotypes, the appropriateness of implicit modeling assumptions (e.g. Eaves, 2006; Heath et al., 2008). There is a more restrictive viewpoint that, since only true cross-over interactions cannot be removed by data-transformation, these alone should be the focus of research on gene-environment interaction. But if in biology first-order (main) effects are in general of greater magnitude than second-order interactive effects, such cross-over interactions are likely to be rare and atypical. However, it has recently been argued (Belsky et al., 2009) that such cross-over interactions are not as rare as typically assumed and are substantively meaningful. Specifically, such interactions suggest that a given genotype might be viewed as reflecting a general sensitivity to the environment, with resultant good or bad outcomes. Such cross-over interactions would therefore point to “plasticity” rather than “vulnerability.” Unfortunately, our ability to characterize the strength and form of statistical interactions with confidence is limited because most existing studies are based upon relatively small cohorts of individuals (by the standards of contemporary genetic research), only rarely enriched for specific environmental exposures.
