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

Aysu Okbay
•
Yeda Wu
•
Nancy Wang
altro
Alexander I. Young
2022
  • journal article

Periodico
NATURE GENETICS
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.
DOI
10.1038/s41588-022-01016-z
WOS
WOS:000776507800001
Archivio
http://hdl.handle.net/11368/3026010
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85127422477
https://www.nature.com/articles/s41588-022-01016-z
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005349/
Diritti
open access
license:creative commons
license:creative commons
license:creative commons
license:creative commons
license:creative commons
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
license uri:http://creativecommons.org/licenses/by/4.0/
license uri:http://creativecommons.org/licenses/by/4.0/
license uri:http://creativecommons.org/licenses/by/4.0/
license uri:http://creativecommons.org/licenses/by/4.0/
license uri:http://creativecommons.org/licenses/by/4.0/
FVG url
https://arts.units.it/bitstream/11368/3026010/1/s41588-022-01016-z.pdf
Soggetti
  • GWAS

  • educational attainmen...

  • genome-wide-significa...

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