In order to evaluate whether or not modeling of rAOS interactions would improve the predictive utility of multiple SNPs, we constructed multi-locus genetic models to predict case-control status from either : 1.) multiple SNPs; or 2.) multiple SNPs paired with their respective SNP x rAOS interaction terms. For the former model, the top 30 SNPs were entered into the model, and a backward elimination procedure was applied until all remaining SNPs in the model were independently associated with p<0.15 (a commonly used threshold for multiple regression model building). A similar procedure was done for the model that included SNP x rAOS interaction except in this case, interactions were only entered into the initial model if they were significant in single-locus analyses, and SNPs were eliminated until all remaining SNPs exhibited either a main effect or interaction with p<0.15.
