Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 437-449 |
| Number of pages | 13 |
| Journal | Nature Genetics |
| Volume | 54 |
| Issue number | 4 |
| Early online date | 31 Mar 2022 |
| DOIs | |
| Publication status | Published - 1 Apr 2022 |
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In: Nature Genetics, Vol. 54, No. 4, 01.04.2022, p. 437-449.
Research output: Contribution to journal › Article › Academic › peer-review
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 - Abdellaoui, Abdel
AU - Watson, Chelsea
AU - Jala, Jonathan
AU - Conley, Dalton
AU - Koellinger, Philipp D.
AU - Johannesson, Magnus
AU - Laibson, David
AU - Meyer, Michelle N.
AU - Lee, James J.
AU - Kong, Augustine
AU - Yengo, Loic
AU - Cesarini, David
AU - Turley, Patrick
AU - Visscher, Peter M.
AU - Beauchamp, Jonathan P.
AU - Benjamin, Daniel J.
AU - Young, Alexander I.
AU - Peyrot, Wouter J.
AU - Evans, David M.
AU - Milaneschi, Yusplitri
AU - Penninx, Brenda W. J. H.
AU - Posthuma, Danielle
N1 - Funding Information: We thank E.M. Tucker-Drob for helpful comments and J. Zeng for help with the SBayesR software. This research was carried out under the auspices of the Social Science Genetic Association Consortium. The analyses reported in the paper fall under National Bureau of Economic Research institutional review board protocols 19_434, 19_465 and 20_041. This paper uses cohort-level data from Okbay et al.62, and information about studies participating in that study can be found in the Additional Acknowledgements Supplementary section of that paper. Per Social Science Genetic Association Consortium policy, we acknowledge the authors of that paper, listed below, as collaborators. 23andMe research participants provided informed consent and participated in the research online, under a protocol approved by the external Association for the Accreditation of Human Research Protection Programs-accredited institutional review board, Ethical & Independent Review Services. Participants were included in the analysis on the basis of consent status as checked at the time data analyses were initiated. We would like to thank the research participants and employees of 23andMe for making this work possible. We gratefully acknowledge the contributions of members of 23andMe’s Research Team, whose names are listed below. The research has also been conducted using the UKB Resource under application numbers 11425 and 12505. Informed consent was obtained from UKB subjects. Ethical approval for the GS: Scottish Family Health Study was obtained from the Tayside Committee on Medical Research Ethics (on behalf of the National Health Service). H.J, M.B., D. Cesarini and P.T. were supported by the Ragnar Söderberg Foundation (E42/15 to D. Cesarini); A.O. and P.K. by the European Research Council (consolidator grant 647648 EdGe to P.K.); H.J., M.B., S.M.N., T.G., C.W., J.J., M.N.M., D. Cesarini, P.T., J.P.B., D.J.B. and A.I.Y. by Open Philanthropy (grant 010623-00001 to D.J.B.); R.A. and S.O. by Riksbankens Jubileumsfond (grant P18-0782:1 to S.O.); N.W., G.G., C.W., L.Y. and D.J.B. by the National Institute on Aging (NIA)/National Institutes of Health (NIH) (grants R24-AG065184 and R01-AG042568 to D.J.B.); D.J.B. by the NIA/NIH (grant R56-AG058726 to T. Galama); P.T. by the NIA/National Institute on Mental Health (grants R01-MH101244-02 and U01-MH109539-02 to B. Neale); J.S. and P.M.V. by the Australian Research Council (grant FL180100072 to P.M.V.); and Y.W., L.Y. and P.M.V. by the National Health and Medical Research Council (grant GNT113400 to P.M.V.). The study was also supported by Netherlands Organisation for Scientific Research VENI (grant 016.Veni.198.058 to A.O.); the F.G. Meade Scholarship and UQ Research Training Scholarship from the University of Queensland Senate (Y.W.); the Swedish Research Council (grant 2019-00244 to S.O.); an MRC University Unit Programme Grant (MC_UU_00007/10, QTL in Health and Disease, to C.H.); the Swedish Research Council (grant 421-2013-1061 to M.J.); Pershing Square Fund of the Foundations of Human Behavior (D.L.); the Li Ka Shing Foundation (A.K.); the Australian Research Council (grant DE200100425 to L.Y.); the NIA/NIH (grant K99-AG062787-01 to P.T.); the Government of Canada through Genome Canada and the Ontario Genomics Institute (grant OGI-152 to J.P.B.); the Social Sciences and Humanities Research Council of Canada (J.P.B.); and the Australian Research Council (P.M.V.). Funding Information: We thank E.M. Tucker-Drob for helpful comments and J. Zeng for help with the SBayesR software. This research was carried out under the auspices of the Social Science Genetic Association Consortium. The analyses reported in the paper fall under National Bureau of Economic Research institutional review board protocols 19_434, 19_465 and 20_041. This paper uses cohort-level data from Okbay et al., and information about studies participating in that study can be found in the Additional Acknowledgements Supplementary section of that paper. Per Social Science Genetic Association Consortium policy, we acknowledge the authors of that paper, listed below, as collaborators. 23andMe research participants provided informed consent and participated in the research online, under a protocol approved by the external Association for the Accreditation of Human Research Protection Programs-accredited institutional review board, Ethical & Independent Review Services. Participants were included in the analysis on the basis of consent status as checked at the time data analyses were initiated. We would like to thank the research participants and employees of 23andMe for making this work possible. We gratefully acknowledge the contributions of members of 23andMe’s Research Team, whose names are listed below. The research has also been conducted using the UKB Resource under application numbers 11425 and 12505. Informed consent was obtained from UKB subjects. Ethical approval for the GS: Scottish Family Health Study was obtained from the Tayside Committee on Medical Research Ethics (on behalf of the National Health Service). H.J, M.B., D. Cesarini and P.T. were supported by the Ragnar Söderberg Foundation (E42/15 to D. Cesarini); A.O. and P.K. by the European Research Council (consolidator grant 647648 EdGe to P.K.); H.J., M.B., S.M.N., T.G., C.W., J.J., M.N.M., D. Cesarini, P.T., J.P.B., D.J.B. and A.I.Y. by Open Philanthropy (grant 010623-00001 to D.J.B.); R.A. and S.O. by Riksbankens Jubileumsfond (grant P18-0782:1 to S.O.); N.W., G.G., C.W., L.Y. and D.J.B. by the National Institute on Aging (NIA)/National Institutes of Health (NIH) (grants R24-AG065184 and R01-AG042568 to D.J.B.); D.J.B. by the NIA/NIH (grant R56-AG058726 to T. Galama); P.T. by the NIA/National Institute on Mental Health (grants R01-MH101244-02 and U01-MH109539-02 to B. Neale); J.S. and P.M.V. by the Australian Research Council (grant FL180100072 to P.M.V.); and Y.W., L.Y. and P.M.V. by the National Health and Medical Research Council (grant GNT113400 to P.M.V.). The study was also supported by Netherlands Organisation for Scientific Research VENI (grant 016.Veni.198.058 to A.O.); the F.G. Meade Scholarship and UQ Research Training Scholarship from the University of Queensland Senate (Y.W.); the Swedish Research Council (grant 2019-00244 to S.O.); an MRC University Unit Programme Grant (MC_UU_00007/10, QTL in Health and Disease, to C.H.); the Swedish Research Council (grant 421-2013-1061 to M.J.); Pershing Square Fund of the Foundations of Human Behavior (D.L.); the Li Ka Shing Foundation (A.K.); the Australian Research Council (grant DE200100425 to L.Y.); the NIA/NIH (grant K99-AG062787-01 to P.T.); the Government of Canada through Genome Canada and the Ontario Genomics Institute (grant OGI-152 to J.P.B.); the Social Sciences and Humanities Research Council of Canada (J.P.B.); and the Australian Research Council (P.M.V.). Publisher Copyright: © 2022, The Author(s).
PY - 2022/4/1
Y1 - 2022/4/1
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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85127422477&partnerID=8YFLogxK
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85127422477&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/35361970
U2 - https://doi.org/10.1038/s41588-022-01016-z
DO - https://doi.org/10.1038/s41588-022-01016-z
M3 - Article
C2 - 35361970
SN - 1061-4036
VL - 54
SP - 437
EP - 449
JO - Nature Genetics
JF - Nature Genetics
IS - 4
ER -