This point is important because it reminds us that genome-wide data continue to hold a great deal of information for the respondents of our studies. Genome-wide analysis (in the SNP-by-SNP approach) is simply one use of these data; candidate SNPs with clearly hypothesized links to environmental sensitivity via biologically plausible networks (Duncan et al. 2010) can be used in a comparable manner to construct a priori genetic profiles. We are skeptical that any one SNP will hold sufficient information to shed light on individual differences in environmental sensitivity, but summary information across a number of different loci may prove to be useful. For example, Belsky and colleagues (2012) examined 29 SNPs that have been linked to body mass phenotypes from published GWAS studies. They summed the number of risk alleles for these 29 SNPs from an independent sample to form a genetic risk score (GRS). BMI was then regressed on the GRS, and they were able to explain roughly 2 % of the variance of BMI in their study. This is a very useful approach that uses existing genome-wide data
