Dataset Information

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.

ABSTRACT: Volumetric variations of the 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 sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding a significance threshold of 4.9?×?10-10, adjusted for testing multiple phenotypes. A 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. Through genome-wide polygenic-risk-score prediction, more than 6% of the phenotypic variance (P?=?3.13?×?10-24) in four other independent studies could be explained by the UK Biobank GWAS results. In conclusion, our study identifies many new genetic associations at the variant, locus and gene levels and advances our understanding of the pleiotropy and genetic co-architecture between brain volumes and other traits.

SUBMITTER: Zhao B

PROVIDER: S-EPMC6858580 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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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.

Zhao Bingxin B Luo Tianyou T Li Tengfei T Li Yun Y Zhang Jingwen J Shan Yue Y Wang Xifeng X Yang Liuqing L Zhou Fan F Zhu Ziliang Z Zhu Hongtu H

Nature genetics 20191101 11

Volumetric variations of the 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 sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding a significance threshold of 4.9 × 10<sup>-10</sup>, adjusted for testing multiple phenotypes. A gene-based association study found 157 associated genes (124 new), and functiona ...[more]

PMID: 31676860

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Project description:ObjectiveTo determine whether there is a correlation between obesity-related variants and regional brain volumes.MethodsBased on a mixed linear model (MLM), we analyzed the association between 1,498 obesity-related SNPs in the GWAS Catalog and 164 regional brain volumes from 29,420 participants (discovery cohort N = 19,997, validation cohort N = 9,423) in UK Biobank. The statistically significant brain regions in association analysis were classified into 6 major neural networks (dopamine (DA) motive system, central autonomic network (CAN), cognitive emotion regulation, visual object recognition network, auditory object recognition network, and sensorimotor system). We summarized the association between obesity-related variants (metabolically healthy obesity variants, metabolically unhealthy obesity variants, and unclassified obesity-related variants) and neural networks.ResultsFrom association analysis, we determined that 17 obesity-related SNPs were associated with 51 regional brain volumes. Several single SNPs (e.g., rs13107325-T (SLC39A8), rs1876829-C (CRHR1), and rs1538170-T (CENPW)) were associated with multiple regional brain volumes. In addition, several single brain regions (e.g., the white matter, the grey matter in the putamen, subcallosal cortex, and insular cortex) were associated with multiple obesity-related variants. The metabolically healthy obesity variants were mainly associated with the regional brain volumes in the DA motive system, sensorimotor system and cognitive emotion regulation neural networks, while metabolically unhealthy obesity variants were mainly associated with regional brain volumes in the CAN and total tissue volumes. In addition, unclassified obesity-related variants were mainly associated with auditory object recognition network and total tissue volumes. The results of MeSH (medical subject headings) enrichment analysis showed that obesity genes associated with brain structure pointed to the functional relatedness with 5-Hydroxytryptamine receptor 4 (5-HT4), growth differentiation factor 5 (GDF5), and high mobility group protein AT-hook 2 (HMGA2 protein).ConclusionIn summary, we found that obesity-related variants were associated with different brain volume measures. On the basis of the multiple SNPs, we found that metabolically healthy and unhealthy obesity-related SNPs were associated with different brain neural networks. Based on our enrichment analysis, modifications of the 5-HT4 pathway might be a promising therapeutic strategy for obesity.

Dataset Information

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.

Publications

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.

Similar Datasets

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