Results from linear regression analyses are presented in Table 2. Standard covariates known to influence BMI (ancestry, sex and age) were included in the models. Described previously (Sanders et al. 2008; Shi et al. 2009), 224 ancestry informative markers were used to construct 10 PC scores designed to discriminate between European, African, Ameri-Indian and Asian ancestry. PC1 (distinguishes European from African ancestry) and PC4 (distinguishes Eastern and Western European ancestry) were significantly associated with BMI and therefore included as covariates. Interactions between the covariates were tested and significant interactions were found between PC1 and sex and PC4 and sex. No other interactions between the covariates were significant. Model 1, the base model, included the standard covariates and the significant interactions between ancestry PCs and sex and accounted for 3.5% of the variance in BMI. Model 2, which added the GRSS to the base model, fits significantly better [F (1,3027) = 21.8, p = 3.2E−06] and accounted for an additional 0.66% of phenotypic variance in BMI for a total of 4.1%. We note that the GRSS accounted for more of the
