TY - JOUR
T1 - Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals
AU - 23andMe Research Team
AU - Social Science Genetic Association Consortium
AU - Lifelines Cohort Study
AU - Okbay, Aysu
AU - Wu, Yeda
AU - Wang, Nancy
AU - Jayashankar, Hariharan
AU - Bennett, Michael
AU - Nehzati, Seyed Moeen
AU - Sidorenko, Julia
AU - Kweon, Hyeokmoon
AU - Goldman, Grant
AU - Gjorgjieva, Tamara
AU - Jiang, Yunxuan
AU - Hicks, Barry
AU - Tian, Chao
AU - Hinds, David A.
AU - Ahlskog, Rafael
AU - Magnusson, Patrik K.E.
AU - Oskarsson, Sven
AU - Hayward, Caroline
AU - Campbell, Archie
AU - Porteous, David J.
AU - Freese, Jeremy
AU - Herd, Pamela
AU - Agee, Michelle
AU - Alipanahi, Babak
AU - Auton, Adam
AU - Bell, Robert K.
AU - Bryc, Katarzyna
AU - Elson, Sarah L.
AU - Fontanillas, Pierre
AU - Furlotte, Nicholas A.
AU - Hinds, David A.
AU - Huber, Karen E.
AU - Kleinman, Aaron
AU - Litterman, Nadia K.
AU - McCreight, Jennifer C.
AU - McIntyre, Matthew H.
AU - Mountain, Joanna L.
AU - Northover, Carrie A.M.
AU - Pitts, Steven J.
AU - Sathirapongsasuti, J. Fah
AU - Sazonova, Olga V.
AU - Shelton, Janie F.
AU - Shringarpure, Suyash
AU - Tung, Joyce Y.
AU - Vacic, Vladimir
AU - Wilson, Catherine H.
AU - Fontana, Mark Alan
AU - Pers, Tune H.
AU - Rietveld, Cornelius A.
AU - Hottenga, Jouke Jan
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/4
Y1 - 2022/4
N2 - 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.
AB - 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.
KW - Biobank
KW - Cohort profile
KW - Genetics
KW - Gwas
KW - Health
KW - Human complex traits
KW - Loci
KW - Models
UR - https://www.scopus.com/pages/publications/85127422477
U2 - 10.1038/s41588-022-01016-z
DO - 10.1038/s41588-022-01016-z
M3 - Article
C2 - 35361970
AN - SCOPUS:85127422477
SN - 1061-4036
VL - 54
SP - 437
EP - 449
JO - Nature Genetics
JF - Nature Genetics
IS - 4
ER -