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

23andMe Research Team, Social Science Genetic Association Consortium, LifeLines Cohort Study

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)437-449
Number of pages13
JournalNature Genetics
Volume54
Issue number4
DOIs
StatePublished - Apr 2022

All Science Journal Classification (ASJC) codes

  • Genetics

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