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

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.
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.
Publication Year :
2018

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.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1235175533
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1038.s41588-017-0009-4