TY - JOUR
T1 - Multi-trait analysis of genome-wide association summary statistics using MTAG
AU - Turley, Patrick
AU - Walters, Raymond K.
AU - Maghzian, Omeed
AU - Okbay, Aysu
AU - Lee, James J.
AU - Fontana, Mark Alan
AU - Nguyen-Viet, Tuan Anh
AU - Wedow, Robbee
AU - Zacher, Meghan
AU - Furlotte, Nicholas A.
AU - Magnusson, Patrik
AU - Oskarsson, Sven
AU - Johannesson, Magnus
AU - Visscher, Peter M.
AU - Laibson, David
AU - Cesarini, David
AU - Neale, Benjamin M.
AU - Benjamin, Daniel J.
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 - Hromatka, Bethann S.
AU - Huber, Karen E.
AU - Kleinman, Aaron
AU - Litterman, Nadia K.
AU - McIntyre, Matthew H.
AU - Mountain, Joanna L.
AU - Northover, Carrie A.M.
AU - Sathirapongsasuti, J. Fah
AU - Sazonova, Olga V.
AU - Shelton, Janie F.
AU - Shringarpure, Suyash
AU - Tian, Chao
AU - Tung, Joyce Y.
AU - Vacic, Vladimir
AU - Wilson, Catherine H.
AU - Pitts, Steven J.
N1 - Funding Information:
We thank J. Beauchamp, P. Koellinger, Ö. Sandewall, C. Shulman, and R. de Vlaming for helpful comments and P. Bowers, E. Kong, T. Kundu, S. Lee, H. Li, R. Li, and R. Royer for research assistance. This research was carried out under the auspices of the Social Science Genetic Association Consortium (SSGAC). The study was supported by the Ragnar Söderberg Foundation (E9/11, M.J.; E42/15, D.C.), the Swedish Research Council (421-2013-1061, M.J.), the Jan Wallander and Tom Hedelius Foundation (M.J.), an ERC Consolidator Grant (647648 EdGe, P. Koellinger), the Pershing Square Fund of the Foundations of Human Behavior (D.L.), the National Science Foundation’s Graduate Research Fellowship Program (DGE 1144083, R.W.), and the NIA/NIH through grants P01-AG005842, P01-AG005842-20S2, and T32-AG000186-23 to D. Wise at NBER; P30-AG012810 (D.L.) to NBER; R01-AG042568-02 (D.J.B.) to the University of Southern California; and 1R01-MH107649-03 (B.M.N.), 1R01-MH101244-02 (B.M.N.), and 5U01-MH109539-02 (B.M.N.) to the Broad Institute at Harvard and MIT. This research has also been conducted using the UK Biobank Resource under application number 11425. We thank the research participants and employees of 23andMe for making this work possible. We also thank K. Mullan Harris and Add Health for early access to the data used in our replication and prediction analyses. A full list of acknowledgements is provided in the Supplementary Note.
Funding Information:
This research was carried out under the auspices of the Social Science Genetic Association Consortium (SSGAC). The study was supported by the Ragnar S?derberg Foundation (E9/11, M.J.; E42/15, D.C.), the Swedish Research Council (421-2013-1061, M.J.), the Jan Wallander and Tom Hedelius Foundation (M.J.), an ERC Consolidator Grant (647648 EdGe, P. Koellinger), the Pershing Square Fund of the Foundations of Human Behavior (D.L.), the National Science Foundation's Graduate Research Fellowship Program (DGE 1144083, R.W.), and the NIA/NIH through grants P01-AG005842, P01-AG005842-20S2, and T32-AG000186-23 to D. Wise at NBER; P30-AG012810 (D.L.) to NBER; R01-AG042568-02 (D.J.B.) to the University of Southern California; and 1R01-MH107649-03 (B.M.N.), 1R01-MH101244-02 (B.M.N.), and 5U01-MH109539-02 (B.M.N.) to the Broad Institute at Harvard and MIT.
Publisher Copyright:
© 2017 The Author(s).
PY - 2018/2/1
Y1 - 2018/2/1
N2 - We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
AB - We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.
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U2 - 10.1038/s41588-017-0009-4
DO - 10.1038/s41588-017-0009-4
M3 - Article
C2 - 29292387
AN - SCOPUS:85039801269
VL - 50
SP - 229
EP - 237
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
IS - 2
ER -