TY - JOUR
T1 - Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals
AU - 23andMe Research Team
AU - COGENT (Cognitive Genomics Consortium)
AU - Social Science Genetic Association Consortium
AU - Lee, James J.
AU - Wedow, Robbee
AU - Okbay, Aysu
AU - Kong, Edward
AU - Maghzian, Omeed
AU - Zacher, Meghan
AU - Nguyen-Viet, Tuan Anh
AU - Bowers, Peter
AU - Sidorenko, Julia
AU - Karlsson Linnér, Richard
AU - Fontana, Mark Alan
AU - Kundu, Tushar
AU - Lee, Chanwook
AU - Li, Hui
AU - Li, Ruoxi
AU - Royer, Rebecca
AU - Timshel, Pascal N.
AU - Walters, Raymond K.
AU - Willoughby, Emily A.
AU - Yengo, Loïc
AU - Agee, Michelle
AU - Alipanahi, Babak
AU - Auton, Adam
AU - Bell, Robert K.
AU - Bryc, Katarzyna
AU - Elson, Sarah L.
AU - Fontanillas, Pierre
AU - Hinds, David A.
AU - McCreight, Jennifer C.
AU - Huber, Karen E.
AU - Litterman, Nadia K.
AU - McIntyre, Matthew H.
AU - Mountain, Joanna L.
AU - Noblin, Elizabeth S.
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 - Tian, Chao
AU - Vacic, Vladimir
AU - Wilson, Catherine H.
AU - Okbay, Aysu
AU - Beauchamp, Jonathan P.
AU - Lee, James J
AU - Rustichini, Aldo
AU - Iacono, William G
AU - Mc Gue, Matt
AU - Krueger, Robert
N1 - Funding Information:
This research was carried out under the auspices of the Social Science Genetic Association Consortium (SSGAC). The research has also been conducted using the UK Biobank Resource under application numbers 11425 and 12512. We acknowledge the Swedish Twin Registry for access to data. The Swedish Twin Registry is managed by the Karolinska Institutet and receives funding through the Swedish Research Council under the grant number 2017-00641. This study was supported by funding from the Ragnar Söderberg Foundation (E9/11, E42/15), the Swedish Research Council (421-2013-1061), The Jan Wallander and Tom Hedelius Foundation, an ERC Consolidator Grant (647648 EdGe), the Pershing Square Fund of the Foundations of Human Behavior, The Open Philanthropy Project (2016-152872), and the NIA/NIH through grants P01-AG005842, P01-AG005842-20S2, P30-AG012810 and T32-AG000186-23 to N.B.E.R. and R01-AG042568 to U.S.C. A full list of acknowledgments is provided in the Supplementary Note.
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/8/1
Y1 - 2018/8/1
N2 - Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
AB - Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
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U2 - 10.1038/s41588-018-0147-3
DO - 10.1038/s41588-018-0147-3
M3 - Article
C2 - 30038396
AN - SCOPUS:85050543338
SN - 1061-4036
VL - 50
SP - 1112
EP - 1121
JO - Nature Genetics
JF - Nature Genetics
IS - 8
ER -