The polygenic scoring method uses results from a GWAS to aggregate the effects of genetic variants across the genome into a single continuous score for individuals in an independent sample. We used estimates from the Social Science Genetic Association Consortium (SSGAC) GWAS of educational attainment (Lee et al., 2018), the largest published GWAS of educational attainment to date, to calculate education polygenic scores for all participants in our sample. We used PRS-CS (Ge et al., 2019) to calculate the education polygenic score. This approach employs a Bayesian regression and continuous shrinkage method to correct for the non-independence among nearby SNPs in the genome (i.e., linkage disequilibrium, or LD), and includes SNPs in the construction of Edu-PGS regardless of their p-value. In order to account for population stratification, we regressed education polygenic score on the first 10 genetic ancestry principal components (PC1–10) and used the standardized, residualized education polygenic score in all subsequent analysis.
