生物
全基因组关联研究
计算生物学
特质
遗传关联
遗传学
进化生物学
汇总统计
神经质
基因组
单核苷酸多态性
统计
基因
人格
基因型
心理学
社会心理学
计算机科学
数学
程序设计语言
作者
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 K. E. Magnusson,Sven Oskarsson,Magnus Johannesson,Peter M. Visscher,David Laibson,David Cesarini,Benjamin M. Neale,Daniel J. Benjamin
出处
期刊:Nature Genetics
[Springer Nature]
日期:2017-12-22
卷期号:50 (2): 229-237
被引量:861
标识
DOI:10.1038/s41588-017-0009-4
摘要
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. 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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