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

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of similar to 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.

Automated summary

In this study, a genome-wide association study (GWAS) was conducted to investigate the genetic factors associated with educational attainment (EA). The results identified numerous single-nucleotide polymorphisms (SNPs) that are significantly correlated with EA. Furthermore, a polygenic predictor (PGI) was found to explain a substantial portion of the variation in EA and contribute to disease risk prediction. Intriguingly, the correlation between mate-pair PGIs suggests additional assortment mechanisms. However, no significant SNPs were identified in separate analyses of dominance deviations and the X-chromosome.