학술논문

Multi-trait analysis of genome-wide association summary statistics using MTAG
Document Type
article
Source
Nature Genetics. 50(2)
Subject
Biological Sciences
Genetics
Human Genome
Algorithms
Data Interpretation
Statistical
Datasets as Topic
Depression
Diagnostic Self Evaluation
Genetic Association Studies
Genome-Wide Association Study
Health
Humans
Meta-Analysis as Topic
Multifactorial Inheritance
Neuroticism
Phenotype
Polymorphism
Single Nucleotide
Quantitative Trait Loci
23andMe Research Team
Social Science Genetic Association Consortium
Medical and Health Sciences
Developmental Biology
Agricultural biotechnology
Bioinformatics and computational biology
Language
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.