The effects of 32 BMI-associated SNPs were incorporated via an aggregate risk score and accounted for up to 3.1% of the variance in BMI. Comparison of SNP-GRSS methodology indicated that a weighted score resulted in a 0.6-0.9% increase in the amount of variance accounted for. Furthermore, in the EA sample incorporating the probability of risk alleles from imputation further increased the amount of variance accounted for in BMI. The effect of the score tended to be lower in the AA sample. Due to the limited sample size of the AA group it could not be determined with confidence if indeed the effect of the score on BMI differed by ancestry. However, a study by Belsky et al. report that a genetic score of BMI-associated SNPs tended to be less significant in an AA sample compared to those from the EA sample [50]. These findings highlight the value of large-scale meta-analysis validation efforts to characterize effect sizes for genetic variants. Future research should test these methods for improved risk prediction in other complex traits and diseases and in diverse populations.
