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Multi-trait analysis of genome-wide association summary statistics using MTAG
- 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;
- 23andMe Research Team;
- Social Science Genetic Association Consortium;
- Magnusson, Patrik;
- Oskarsson, Sven;
- Johannesson, Magnus;
- Visscher, Peter M;
- Laibson, David;
- Cesarini, David;
- Neale, Benjamin M;
- Benjamin, Daniel J
- et al.
Published Web Location
https://doi.org/10.1038/s41588-017-0009-4Abstract
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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