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对 500 万人的多变量基因组分析阐明了代谢综合征共享成分的遗传结构。

Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome.

机构信息

Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea.

Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea.

出版信息

Nat Genet. 2024 Nov;56(11):2380-2391. doi: 10.1038/s41588-024-01933-1. Epub 2024 Sep 30.

Abstract

Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (n = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse diseases beyond cardiometabolic diseases. Polygenic risk score analysis demonstrated better discrimination of MetS and predictive power in European and East Asian populations. Altogether, our findings will guide future studies aimed at elucidating the genetic architecture of MetS.

摘要

代谢综合征(Metabolic syndrome,MetS)是一种复杂的遗传性疾病,包含多种代谢特征作为风险因素。虽然通过大规模全基因组关联研究积极地研究了个别 MetS 成分的遗传学,但联合遗传结构尚未完全阐明。在这里,我们通过利用 MetS 成分之间的遗传相关性,在欧洲进行了迄今为止最大的多变量全基因组关联研究(n=4947860)。我们确定了 1307 个与 MetS 相关的遗传位点,这些位点主要富集在脑组织中。利用转录组数据,我们确定了 11 个与 MetS 密切相关的基因。我们的表型全基因组关联和孟德尔随机化分析强调了 MetS 与心脏代谢疾病以外的多种疾病的关联。多基因风险评分分析表明,在欧洲和东亚人群中,MetS 的区分度和预测能力更好。总的来说,我们的研究结果将为阐明 MetS 的遗传结构提供指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44d2/11549047/1b3d9a5d64f1/41588_2024_1933_Fig1_HTML.jpg

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