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Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. / Okbay, Aysu; Wu, Yeda; Wang, Nancy; Jayashankar, Hariharan; Bennett, Michael; Nehzati, Seyed Moeen; Sidorenko, Julia; Kweon, Hyeokmoon; Goldman, Grant; Gjorgjieva, Tamara; Jiang, Yunxuan; Hicks, Barry; Tian, Chao; Hinds, David A.; Ahlskog, Rafael; Magnusson, Patrik K.E.; Oskarsson, Sven; Hayward, Caroline; Campbell, Archie; Porteous, David J.; Freese, Jeremy; Herd, Pamela; Agee, Michelle; Alipanahi, Babak; Auton, Adam; Bell, Robert K.; Bryc, Katarzyna; Elson, Sarah L.; Fontanillas, Pierre; Furlotte, Nicholas A.; Hinds, David A.; Huber, Karen E.; Kleinman, Aaron; Litterman, Nadia K.; McCreight, Jennifer C.; McIntyre, Matthew H.; Mountain, Joanna L.; Northover, Carrie A.M.; Pitts, Steven J.; Sathirapongsasuti, J. Fah; Sazonova, Olga V.; Shelton, Janie F.; Pers, Tune H.; Timshel, Pascal; Ahluwalia, Tarunveer S.; Bønnelykke, Klaus; Bisgaard, Hans; Sørensen, Thorkild I.A.; 23andMe Research Team; Social Science Genetic Association Consortium; LifeLines Cohort Study.
In:
Nature Genetics, Vol. 54, No. 4, 2022, p. 437-449.
Research output: Contribution to journal › Journal article › peer-review
Harvard
Okbay, A, Wu, Y, Wang, N, Jayashankar, H, Bennett, M, Nehzati, SM, Sidorenko, J, Kweon, H, Goldman, G, Gjorgjieva, T, Jiang, Y, Hicks, B, Tian, C, Hinds, DA, Ahlskog, R, Magnusson, PKE, Oskarsson, S, Hayward, C, Campbell, A, Porteous, DJ, Freese, J, Herd, P, Agee, M, Alipanahi, B, Auton, A, Bell, RK, Bryc, K, Elson, SL, Fontanillas, P, Furlotte, NA, Hinds, DA, Huber, KE, Kleinman, A, Litterman, NK, McCreight, JC, McIntyre, MH, Mountain, JL, Northover, CAM, Pitts, SJ, Sathirapongsasuti, JF, Sazonova, OV, Shelton, JF
, Pers, TH, Timshel, P
, Ahluwalia, TS, Bønnelykke, K, Bisgaard, H
, Sørensen, TIA, 23andMe Research Team, Social Science Genetic Association Consortium & LifeLines Cohort Study 2022, '
Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals',
Nature Genetics, vol. 54, no. 4, pp. 437-449.
https://doi.org/10.1038/s41588-022-01016-zAPA
Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., Jiang, Y., Hicks, B., Tian, C., Hinds, D. A., Ahlskog, R., Magnusson, P. K. E., Oskarsson, S., Hayward, C., Campbell, A., ... LifeLines Cohort Study (2022).
Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals.
Nature Genetics,
54(4), 437-449.
https://doi.org/10.1038/s41588-022-01016-zVancouver
Okbay A, Wu Y, Wang N, Jayashankar H, Bennett M, Nehzati SM et al.
Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals.
Nature Genetics. 2022;54(4):437-449.
https://doi.org/10.1038/s41588-022-01016-zAuthor
Okbay, Aysu ; Wu, Yeda ; Wang, Nancy ; Jayashankar, Hariharan ; Bennett, Michael ; Nehzati, Seyed Moeen ; Sidorenko, Julia ; Kweon, Hyeokmoon ; Goldman, Grant ; Gjorgjieva, Tamara ; Jiang, Yunxuan ; Hicks, Barry ; Tian, Chao ; Hinds, David A. ; Ahlskog, Rafael ; Magnusson, Patrik K.E. ; Oskarsson, Sven ; Hayward, Caroline ; Campbell, Archie ; Porteous, David J. ; Freese, Jeremy ; Herd, Pamela ; Agee, Michelle ; Alipanahi, Babak ; Auton, Adam ; Bell, Robert K. ; Bryc, Katarzyna ; Elson, Sarah L. ; Fontanillas, Pierre ; Furlotte, Nicholas A. ; Hinds, David A. ; Huber, Karen E. ; Kleinman, Aaron ; Litterman, Nadia K. ; McCreight, Jennifer C. ; McIntyre, Matthew H. ; Mountain, Joanna L. ; Northover, Carrie A.M. ; Pitts, Steven J. ; Sathirapongsasuti, J. Fah ; Sazonova, Olga V. ; Shelton, Janie F. ; Pers, Tune H. ; Timshel, Pascal ; Ahluwalia, Tarunveer S. ; Bønnelykke, Klaus ; Bisgaard, Hans ; Sørensen, Thorkild I.A. ; 23andMe Research Team ; Social Science Genetic Association Consortium ; LifeLines Cohort Study. / Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. In: Nature Genetics. 2022 ; Vol. 54, No. 4. pp. 437-449.
Bibtex
@article{8e8e0cd75ac64b0bbde214b5bc12e3ed,
title = "Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals",
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{\textquoteright}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.",
author = "Aysu Okbay and Yeda Wu and Nancy Wang and Hariharan Jayashankar and Michael Bennett and Nehzati, {Seyed Moeen} and Julia Sidorenko and Hyeokmoon Kweon and Grant Goldman and Tamara Gjorgjieva and Yunxuan Jiang and Barry Hicks and Chao Tian and Hinds, {David A.} and Rafael Ahlskog and Magnusson, {Patrik K.E.} and Sven Oskarsson and Caroline Hayward and Archie Campbell and Porteous, {David J.} and Jeremy Freese and Pamela Herd and Michelle Agee and Babak Alipanahi and Adam Auton and Bell, {Robert K.} and Katarzyna Bryc and Elson, {Sarah L.} and Pierre Fontanillas and Furlotte, {Nicholas A.} and Hinds, {David A.} and Huber, {Karen E.} and Aaron Kleinman and Litterman, {Nadia K.} and McCreight, {Jennifer C.} and McIntyre, {Matthew H.} and Mountain, {Joanna L.} and Northover, {Carrie A.M.} and Pitts, {Steven J.} and Sathirapongsasuti, {J. Fah} and Sazonova, {Olga V.} and Shelton, {Janie F.} and Pers, {Tune H.} and Pascal Timshel and Ahluwalia, {Tarunveer S.} and Klaus B{\o}nnelykke and Hans Bisgaard and S{\o}rensen, {Thorkild I.A.} and {23andMe Research Team} and {Social Science Genetic Association Consortium} and {LifeLines Cohort Study}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
doi = "10.1038/s41588-022-01016-z",
language = "English",
volume = "54",
pages = "437--449",
journal = "Nature Genetics",
issn = "1061-4036",
publisher = "nature publishing group",
number = "4",
}
RIS
TY - JOUR
T1 - Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals
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 - Pers, Tune H.
AU - Timshel, Pascal
AU - Ahluwalia, Tarunveer S.
AU - Bønnelykke, Klaus
AU - Bisgaard, Hans
AU - Sørensen, Thorkild I.A.
AU - 23andMe Research Team
AU - Social Science Genetic Association Consortium
AU - LifeLines Cohort Study
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
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.
U2 - 10.1038/s41588-022-01016-z
DO - 10.1038/s41588-022-01016-z
M3 - Journal article
C2 - 35361970
AN - SCOPUS:85127422477
VL - 54
SP - 437
EP - 449
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
IS - 4
ER -
