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

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  = ...

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Published inNature genetics Vol. 50; no. 2; pp. 229 - 237
Main Authors Turley, Patrick, Walters, Raymond K., Maghzian, Omeed, Okbay, Aysu, Lee, James J., Fontana, Mark Alan, Nguyen-Viet, Tuan Anh, Wedow, Robbee, Zacher, Meghan, Furlotte, Nicholas A., Magnusson, Patrik, Oskarsson, Sven, Johannesson, Magnus, Visscher, Peter M., Laibson, David, Cesarini, David, Neale, Benjamin M., Benjamin, Daniel J.
Format Journal Article
LanguageEnglish
Published New York Nature Publishing Group US 01.02.2018
Nature Publishing Group
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ISSN1061-4036
1546-1718
1546-1718
DOI10.1038/s41588-017-0009-4

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Summary: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. MTAG is a new method for joint analysis of summary statistics from genome-wide association studies of different traits. Applying MTAG to summary statistics for depressive symptoms, neuroticism and subjective well-being increased discovery of associated loci as compared to single-trait analyses.
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A list of members of the Social Science Genetic Association Consortium can be found in section 10 of Supplementary Note.
A list of members of the 23andMe Research Team can be found at the end the paper.
CONTRIBUTOR LIST FOR THE 23andMe RESEARCH TEAM: 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, and Steven J. Pitts.
These authors contributed equally
ISSN:1061-4036
1546-1718
1546-1718
DOI:10.1038/s41588-017-0009-4