We have presented evidence that examining factors jointly, including SNPs displaying little to no univariate association to the phenotype, may uncover interactions and other synergistic effects that account for a sizable portion of the “missing” genetic variance remaining after univariate analyses of well-powered GWAS (Goldstein 2009; Hirschhorn 2009; Kraft and Hunter 2009). Although this study on the genetics of nicotine dependence focused on only a small portion of the genome, we found that examining nicotinic receptor variants in a pair-wise manner increased the proportion of variation explained. The challenge with such an approach, particularly if applied to data with 1,000,000 genotyped polymorphisms, is the number of tests. Even if limited to all pair-wise models, such analyses would be computationally expensive and statistically intractable. The problem becomes more extreme if analyses involve more than two factors at a time.
