Genome-Wide Association Analysis of 19,629 Individuals Identifies Variants Influencing Regional Brain Volumes and Refines Their Genetic Co-Architecture With Cognitive and Mental Health Traits
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CitationZhao, Bingxin, Tianyou Luo, Tengfei Li, Yun Li, Jingwen Zhang, Yue Shan, Xifeng Wang, Liuqing Yang, Fan Zhou, Ziliang Zhu, and Hongtu Zhu. 2019. Genome-wide Association Analysis of 19,629 Individuals Identifies Variants Influencing Regional Brain Volumes and Refines Their Genetic Co-architecture with Cognitive and Mental Health Traits. Nature Genetics 51, no. 11: 1637-644.
AbstractVolumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) and post-GWAS analyses of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding genome-wide significance threshold of 4.9*10-10, adjusted for testing multiple phenotypes. Gene-based association study found 157 associated genes (124 new) and functional gene mapping analysis linked 146 more genes. Many of the discovered genetic variants have previously been implicated with cognitive and mental health traits (such as cognitive performance, education, mental disease/disorders), and significant genetic correlations were detected for 22 pairs of traits. The significant genetic variants discovered in the UKB sample were supported by a joint analysis with four other independent studies (total sample size 2,192), and we performed a meta-analysis of five samples to provide GWAS summary statistics with sample size larger than 20,000. Using genome-wide polygenic risk scores prediction, more than 6% of phenotypic variance (p-value=3.13*10-24) in the four independent studies can be explained by the UKB GWAS results. In conclusion, our study identifies many new genetic associations at variant, locus and gene levels and advances our understanding of the pleiotropy and genetic co-architecture between brain volumes and other traits.
Citable link to this pagehttps://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37371860
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