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

Research output: Contribution to JournalArticleAcademicpeer-review

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
Pages (from-to)437-449
Number of pages31
JournalNature genetics
Volume54
Issue number4
Early online date31 Mar 2022
DOIs
Publication statusPublished - 1 Apr 2022

Bibliographical note

Publisher Copyright:
© 2022. The Author(s).

Cohort Studies

  • Netherlands Twin Register (NTR)

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