Returning to Fig. 1 helps to illustrate the difficulty. Differentiating between the models requires information on the magnitude and sign of the following three components: (1) the main effect of the SNP (G); (2) the main effect of education (E); and (3) the interaction term (GxE). Although some researchers have made the case that “regions of significance” tests, such as the Johnson-Neyman approach (Preacher et al. 2007), can help us evaluate the diathesis-stress model versus the differential susceptibility model (Simons et al. 2011), this test is more relevant when one measured genotype is interacted with one measured environment. When hundreds of thousands of interactions are performed, the most significant p values for the interaction parameter estimates will be for those SNPs that have different signs for the two groups. These results conform to the differential susceptibility model but will not tell us anything meaningful about the way in which environments systematically moderate genetic factors related to BMI because they will likely be a statistical artifact.
