Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

TLDR

We performed a genome‑wide association study of educational attainment in ~3 million individuals, identifying 3,952 largely independent genome‑significant SNPs. The resulting polygenic index explains 12–16 % of educational attainment variance, predicts risk for ten diseases, and shows that direct genetic effects account for roughly half its association; mate‑pair PGI correlations imply additional assortment, no significant dominance deviations were detected, and 57 X‑chromosome loci were identified.

Abstract

Abstract We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12–16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI’s magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.