genetic risk and may be useful for examining the impact of prevention or intervention efforts across the biological risk spectrum. Inclusion of polygenic risk as the lone genetic predictor, or in addition to a single SNP, in association testing is a valid strategy for jointly testing association. The growth of large scale curated databases of gene function, tissue specific and developmental timing of expression, methylation sensitive sites, and genomic functional annotations provide relevant prior information that can be used in weighted hypothesis testing approaches such as the weighted FDR. The increased availability of arrays to provide genome-wide indicators of baseline and change in site-specific methylation is a boon to those interested in exploring the mechanisms by which intervention may serve to impact the genome. As with genotype data, great care must be taken with methylation array data to ensure that technical artefacts are removed and data are properly normalized before conducting association tests. Since methylation signals can change over time, a new set of mechanistic hypotheses, including whether or not a particular site mediates the impact of an intervention, are possible. Lastly, GxE testing is at the core of inclusion of genetic measures in intervention and prevention studies (i.e., does
