Multi-trait analysis of genome-wide association summary statistics using MTAG

Patrick Turley; Raymond K. Walters; Omeed Maghzian; Aysu Okbay; James J. Lee; Mark Alan Fontana; Tuan Anh Nguyen-Viet; Robbee Wedow; Meghan Zacher; Nicholas A. Furlotte; Patrik Magnusson; Sven Oskarsson; Magnus Johannesson; Peter M. Visscher; David Laibson; David Cesarini; Benjamin M. Neale; Daniel J. Benjamin; Michelle Agee; Babak Alipanahi; Adam Auton; Robert K. Bell; Katarzyna Bryc; Sarah L. Elson; Pierre Fontanillas; Nicholas A. Furlotte; David A. Hinds; Bethann S. Hromatka; Karen E. Huber; Aaron Kleinman; Nadia K. Litterman; Matthew H. McIntyre; Joanna L. Mountain; Carrie A.M. Northover; J. Fah Sathirapongsasuti; Olga V. Sazonova; Janie F. Shelton; Suyash Shringarpure; Chao Tian; Joyce Y. Tung; Vladimir Vacic; Catherine H. Wilson; Steven J. Pitts; 23Andme Research Team; Social Science Genetic Association Consortium

doi:10.1038/s41588-017-0009-4

Multi-trait analysis of genome-wide association summary statistics using MTAG

Patrick Turley^*
, Raymond K. Walters
, Omeed Maghzian
, Aysu Okbay
, James J. Lee
, Mark Alan Fontana
, Tuan Anh Nguyen-Viet
, Robbee Wedow
, Meghan Zacher
, Nicholas A. Furlotte
, Patrik Magnusson
, Sven Oskarsson
, Magnus Johannesson
, Peter M. Visscher
, David Laibson
, David Cesarini
, Benjamin M. Neale
, Daniel J. Benjamin
, Michelle Agee
, Babak Alipanahi

Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Bethann S. Hromatka, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, Matthew H. McIntyre, Joanna L. Mountain, Carrie A.M. Northover, J. Fah Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Vladimir Vacic, Catherine H. Wilson, Steven J. Pitts, 23Andme Research Team, Social Science Genetic Association Consortium

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

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Abstract

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.

Original language	English
Pages (from-to)	229–237
Number of pages	15
Journal	Nature Genetics
Volume	50
Issue number	2
Early online date	1 Jan 2018
DOIs	https://doi.org/10.1038/s41588-017-0009-4
Publication status	Published - Feb 2018

Funding

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. 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.

Funders	Funder number
Broad Institute at Harvard
National Institutes of Health
Jan Wallander and Tom Hedelius Foundation
Pershing Square Fund of the Foundations of Human Behavior
Ragnar Söderbergs stiftelse
Massachusetts Institute of Technology
University of Southern California	5U01-MH109539-02, 1R01-MH107649-03, 1R01-MH101244-02
National Science Foundation	1144083
National Institute on Aging	R01AG042568, P30AG034532, P01AG005842, T32AG000186, P30AG012810
Medical Research Council	MR/N01104X/1, G1001799, MC_qA137853
Horizon 2020 Framework Programme	1144083, 647648
National Institute of Mental Health	R01MH107649, U01MH109539, R01MH101244
National Institute of Child Health and Human Development	R01HD060726
Engineering Research Centers	647648 EdGe
Eunice Kennedy Shriver National Institute of Child Health and Human Development	P01HD031921, R01HD073342
Ragnar Söderberg Foundation	E42/15, E9/11
Vetenskapsrådet	421-2013-1061

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10.1038/s41588-017-0009-4

Multi-trait analysis of genome-wide association summary statistics using MTAGFinal published version, 6.41 MBLicence: Article 25fa Dutch Copyright Act

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Turley, P., Walters, R. K., Maghzian, O., Okbay, A., Lee, J. J., Fontana, M. A., Nguyen-Viet, T. A., Wedow, R., Zacher, M., Furlotte, N. A., Magnusson, P., Oskarsson, S., Johannesson, M., Visscher, P. M., Laibson, D., Cesarini, D., Neale, B. M., Benjamin, D. J., Agee, M., ... Social Science Genetic Association Consortium (2018). Multi-trait analysis of genome-wide association summary statistics using MTAG. Nature Genetics, 50(2), 229–237. https://doi.org/10.1038/s41588-017-0009-4

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title = "Multi-trait analysis of genome-wide association summary statistics using MTAG",

abstract = "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 (Neff = 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.",

author = "Patrick Turley and Walters, \{Raymond K.\} and Omeed Maghzian and Aysu Okbay and Lee, \{James J.\} and Fontana, \{Mark Alan\} and Nguyen-Viet, \{Tuan Anh\} and Robbee Wedow and Meghan Zacher and Furlotte, \{Nicholas A.\} and Patrik Magnusson and Sven Oskarsson and Magnus Johannesson and Visscher, \{Peter M.\} and David Laibson and David Cesarini and Neale, \{Benjamin M.\} and Benjamin, \{Daniel J.\} 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 Hromatka, \{Bethann S.\} and Huber, \{Karen E.\} and Aaron Kleinman and Litterman, \{Nadia K.\} and McIntyre, \{Matthew H.\} and Mountain, \{Joanna L.\} and Northover, \{Carrie A.M.\} and Sathirapongsasuti, \{J. Fah\} and Sazonova, \{Olga V.\} and Shelton, \{Janie F.\} and Suyash Shringarpure and Chao Tian and Tung, \{Joyce Y.\} and Vladimir Vacic and Wilson, \{Catherine H.\} and Pitts, \{Steven J.\} and \{23Andme Research Team\} and \{Social Science Genetic Association Consortium\}",

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doi = "10.1038/s41588-017-0009-4",

language = "English",

volume = "50",

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issn = "1061-4036",

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Turley, P, Walters, RK, Maghzian, O, Okbay, A, Lee, JJ, Fontana, MA, Nguyen-Viet, TA, Wedow, R, Zacher, M, Furlotte, NA, Magnusson, P, Oskarsson, S, Johannesson, M, Visscher, PM, Laibson, D, Cesarini, D, Neale, BM, Benjamin, DJ, Agee, M, Alipanahi, B, Auton, A, Bell, RK, Bryc, K, Elson, SL, Fontanillas, P, Furlotte, NA, Hinds, DA, Hromatka, BS, Huber, KE, Kleinman, A, Litterman, NK, McIntyre, MH, Mountain, JL, Northover, CAM, Sathirapongsasuti, JF, Sazonova, OV, Shelton, JF, Shringarpure, S, Tian, C, Tung, JY, Vacic, V, Wilson, CH, Pitts, SJ, 23Andme Research Team & Social Science Genetic Association Consortium 2018, 'Multi-trait analysis of genome-wide association summary statistics using MTAG', Nature Genetics, vol. 50, no. 2, pp. 229–237. https://doi.org/10.1038/s41588-017-0009-4

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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.

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AU - Elson, Sarah L.

AU - Fontanillas, Pierre

AU - Furlotte, Nicholas A.

AU - Hinds, David A.

AU - Hromatka, Bethann S.

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AU - McIntyre, Matthew H.

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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

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AU - Pitts, Steven J.

AU - 23Andme Research Team

AU - Social Science Genetic Association Consortium

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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 (Neff = 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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DO - 10.1038/s41588-017-0009-4

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VL - 50

SP - 229

EP - 237

JO - Nature Genetics

JF - Nature Genetics

IS - 2

ER -

Multi-trait analysis of genome-wide association summary statistics using MTAG

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