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探索体重指数与脑形态特征之间遗传相关性的分子基础。

Exploring the molecular basis of the genetic correlation between body mass index and brain morphological traits.

作者信息

Fusco Daniela, Marinelli Camilla, André Mathilde, Troiani Lucia, Noè Martina, Pizzagalli Fabrizio, Marnetto Davide, Provero Paolo

机构信息

Department of Neurosciences "Rita Levi Montalcini", University of Turin, Turin, Italy.

Center for Omics Sciences, IRCCS Ospedale San Raffaele, Milan, Italy.

出版信息

PLoS Genet. 2025 Apr 10;21(4):e1011658. doi: 10.1371/journal.pgen.1011658. eCollection 2025 Apr.

DOI:10.1371/journal.pgen.1011658
PMID:40209151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12048161/
Abstract

Several studies have demonstrated significant phenotypic and genetic correlations between body mass index (BMI) and brain morphological traits derived from structural magnetic resonance imaging (sMRI). We use the sMRI, BMI, and genetic data collected by the UK Biobank to systematically compute the genetic correlations between area, volume, and thickness measurements of hundreds of brain structures on one hand, and BMI on the other. In agreement with previous literature, we find many such measurements to have negative genetic correlation with BMI. We then dissect the molecular mechanisms underlying such correlations using brain eQTL data and summary-based Mendelian randomization, thus producing an atlas of genes whose genetically regulated expression in brain tissues is pleiotropic with brain morphology and BMI. Fine-mapping followed by colocalization analysis allows, in several cases, the identification of credible sets of variants likely to be causal for both the macroscopic phenotypes and for gene expression. In particular, epigenetic fine mapping identifies variant rs7187776 in the 5' UTR of the TUFM gene as likely to be causal of increased BMI and decreased caudate volume, possibly through the creation, by the alternate allele, of an ETS binding site leading to increased chromatin accessibility, specifically in microglial cells.

摘要

多项研究表明,体重指数(BMI)与源自结构磁共振成像(sMRI)的脑形态学特征之间存在显著的表型和遗传相关性。我们使用英国生物银行收集的sMRI、BMI和遗传数据,系统地计算了数百个脑结构的面积、体积和厚度测量值与BMI之间的遗传相关性。与先前的文献一致,我们发现许多此类测量值与BMI呈负遗传相关。然后,我们使用脑eQTL数据和基于汇总的孟德尔随机化分析来剖析这些相关性背后的分子机制,从而生成一个基因图谱,这些基因在脑组织中的遗传调控表达与脑形态和BMI具有多效性。在几种情况下,通过精细定位随后进行共定位分析,可以识别出可能对宏观表型和基因表达均具有因果关系的可靠变异集。特别是,表观遗传精细定位确定了TUFM基因5'UTR中的变异rs7187776可能是BMI增加和尾状核体积减小的原因,可能是由于替代等位基因产生了一个ETS结合位点,导致染色质可及性增加,特别是在小胶质细胞中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/bdc09e35e2aa/pgen.1011658.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/17f81136579e/pgen.1011658.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/4c14de618cd2/pgen.1011658.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/d433a1c80c12/pgen.1011658.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/6eb71c585601/pgen.1011658.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/bdc09e35e2aa/pgen.1011658.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/17f81136579e/pgen.1011658.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/4c14de618cd2/pgen.1011658.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/d433a1c80c12/pgen.1011658.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/6eb71c585601/pgen.1011658.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/770d/12048161/bdc09e35e2aa/pgen.1011658.g005.jpg

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本文引用的文献

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Nat Genet. 2024 Nov;56(11):2333-2344. doi: 10.1038/s41588-024-01951-z. Epub 2024 Oct 21.
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TUFM in health and disease: exploring its multifaceted roles.
线粒体延伸因子TUFM在健康与疾病中的作用:探索其多方面的角色
Front Immunol. 2024 May 29;15:1424385. doi: 10.3389/fimmu.2024.1424385. eCollection 2024.
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Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology.基因调控细胞类型特异性染色质可及性塑造大脑疾病病因。
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A comparative atlas of single-cell chromatin accessibility in the human brain.人类大脑单细胞染色质可及性比较图谱。
Science. 2023 Oct 13;382(6667):eadf7044. doi: 10.1126/science.adf7044.
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Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes.全基因组关联研究(GWAS)和多组学数量性状位点(QTL)汇总统计的联合分析揭示了很大一部分与分子表型共享的GWAS信号。
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Mendelian randomization.孟德尔随机化
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