In order to compare the relative strength of the DHS- and GW-scores, we fit a series of separate linear mixed-effects models incorporating each of the GW- and DHS-scores to predict ADsx and height. Each model also included sex (and, for height, age) as covariates. To account for clustering at the family level, we fit mixed models with random intercepts using the lmer function from the lme4 package (version 1.1.11) in R (version 3.2.3). Models were fit with risk scores calculated using SNPs at the p < .01 and p < .05 thresholds from the discovery GWAS. We examined the relative predictive ability of DHS- and GW-scores in two ways. First, we compared the significance of association and the overall variance accounted for (R2) by each score. However, because the number of SNPs included in the polygenic scores differed substantially between the GW-scores and DHS-scores, a direct comparison of the magnitudes of their association statistics may not be meaningful. Thus, as a second approach we calculated an average “per-SNP” effect to facilitate comparisons on the same metric. To do this, we divided the variance accounted for each by each score (R2) by the number of SNPs in that score.
