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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
Volumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 365 independent g...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858580/ https://www.ncbi.nlm.nih.gov/pubmed/31676860 http://dx.doi.org/10.1038/s41588-019-0516-6 |
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author | Zhao, Bingxin Luo, Tianyou Li, Tengfei Li, Yun Zhang, Jingwen Shan, Yue Wang, Xifeng Yang, Liuqing Zhou, Fan Zhu, Ziliang Zhu, Hongtu |
author_facet | Zhao, Bingxin Luo, Tianyou Li, Tengfei Li, Yun Zhang, Jingwen Shan, Yue Wang, Xifeng Yang, Liuqing Zhou, Fan Zhu, Ziliang Zhu, Hongtu |
author_sort | Zhao, Bingxin |
collection | PubMed |
description | Volumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding 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 additional genes. Many of the discovered genetic variants and genes have previously been implicated in cognitive and mental health traits. Using genome-wide polygenic risk score prediction, more than 6% of phenotypic variance (P = 3.13 × 10(−24)) in four other independent studies could 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. |
format | Online Article Text |
id | pubmed-6858580 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
record_format | MEDLINE/PubMed |
spelling | pubmed-68585802020-05-01 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 Zhao, Bingxin Luo, Tianyou Li, Tengfei Li, Yun Zhang, Jingwen Shan, Yue Wang, Xifeng Yang, Liuqing Zhou, Fan Zhu, Ziliang Zhu, Hongtu Nat Genet Article Volumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding 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 additional genes. Many of the discovered genetic variants and genes have previously been implicated in cognitive and mental health traits. Using genome-wide polygenic risk score prediction, more than 6% of phenotypic variance (P = 3.13 × 10(−24)) in four other independent studies could 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. 2019-11-01 2019-11 /pmc/articles/PMC6858580/ /pubmed/31676860 http://dx.doi.org/10.1038/s41588-019-0516-6 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Zhao, Bingxin Luo, Tianyou Li, Tengfei Li, Yun Zhang, Jingwen Shan, Yue Wang, Xifeng Yang, Liuqing Zhou, Fan Zhu, Ziliang Zhu, Hongtu 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858580/ https://www.ncbi.nlm.nih.gov/pubmed/31676860 http://dx.doi.org/10.1038/s41588-019-0516-6 |
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