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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Vydané v:Nature genetics Ročník 50; číslo 2; s. 229 - 237
Hlavní autori: 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.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Nature Publishing Group US 01.02.2018
Nature Publishing Group
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631/208/205/2138
631/208/212
631/378
Accuracy
Agriculture
Algorithms
Animal Genetics and Genomics
Bioinformatics
Biomedical and Life Sciences
Biomedicine
Cancer Research
Comparative analysis
Computational biology
Data Interpretation, Statistical
Datasets as Topic - statistics & numerical data
Depression - epidemiology
Depression - genetics
Diagnostic Self Evaluation
Economic models
Gene Function
Genetic aspects
Genetic Association Studies - methods
Genetic Association Studies - statistics & numerical data
Genome-wide association studies
Genome-Wide Association Study - methods
Genome-Wide Association Study - statistics & numerical data
Genomes
Genomics
Health - statistics & numerical data
Human Genetics
Humans
Loci
Mental depression
Meta-analysis
Meta-Analysis as Topic
Multifactorial Inheritance
Neurosis
Neuroticism
Phenotype
Polygenic inheritance
Polymorphism, Single Nucleotide
Psychological factors
Quantitative Trait Loci - genetics
Statistical analysis
Statistical methods
Statistics
Well being
Sweden
ISSN:1061-4036, 1546-1718, 1546-1718
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Shrnutí: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