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通过系统生物信息学和单细胞转录组分析揭示的肥胖风险基因复杂网络。

A Complex Network of Obesity-Risk Genes Revealed by Systematic Bioinformatics and Single-Cell Transcriptomic Analyses.

作者信息

Liu Yuenan, Yuan Haolin, Hu Junhui, Xu Xu, Yin Shankai, Hu Yiming, Liu Feng

机构信息

Department of Otolaryngology Head and Neck Surgery, Shanghai Key Laboratory of Sleep Disordered Breathing, Otolaryngological Institute of Shanghai Jiaotong University, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai 200233, China.

出版信息

J Obes. 2025 Mar 31;2025:7821115. doi: 10.1155/jobe/7821115. eCollection 2025.

DOI:10.1155/jobe/7821115
PMID:40201036
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11976034/
Abstract

The development of obesity is closely linked to genetic factors. Despite the identification of numerous genes associated with an increased risk of obesity in humans, a comprehensive understanding of their biological roles has not been achieved. In our extensive bioinformatics study, we identified 802 core genes implicated in obesity. Our protein-protein interaction (PPI) network analysis revealed that these genes form a tightly connected functional network primarily involved in neurological and metabolic regulatory processes. Moreover, our in-depth analysis of single-cell transcriptomic datasets from the human hypothalamus, pancreatic islets, adipose tissue, and liver has shed light on the distinct expression profiles of these obesity-linked genes across various tissue and cell types. This analysis also highlighted the biological processes they influence and the upstream transcriptional regulatory networks involved. Our study not only uncovers the complicated regulatory role of genetic factors in the pathogenesis and progression of obesity but also establishes a close link between the expression patterns and functional roles of these obesity-associated genes. This study provides crucial insights for advancing our understanding of the genetic mechanisms underlying obesity.

摘要

肥胖的发展与遗传因素密切相关。尽管已经鉴定出许多与人类肥胖风险增加相关的基因,但尚未全面了解它们的生物学作用。在我们广泛的生物信息学研究中,我们鉴定出了802个与肥胖相关的核心基因。我们的蛋白质-蛋白质相互作用(PPI)网络分析表明,这些基因形成了一个紧密连接的功能网络,主要参与神经和代谢调节过程。此外,我们对来自人类下丘脑、胰岛、脂肪组织和肝脏的单细胞转录组数据集的深入分析,揭示了这些与肥胖相关的基因在各种组织和细胞类型中的不同表达谱。该分析还突出了它们影响的生物学过程以及涉及的上游转录调控网络。我们的研究不仅揭示了遗传因素在肥胖发病机制和进展中的复杂调控作用,还建立了这些与肥胖相关基因的表达模式和功能作用之间的紧密联系。这项研究为推进我们对肥胖潜在遗传机制的理解提供了关键见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2c/11976034/30128821895c/JOBE2025-7821115.006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2c/11976034/3fde64a8dbc9/JOBE2025-7821115.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2c/11976034/30128821895c/JOBE2025-7821115.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2c/11976034/6c0f5305ff3f/JOBE2025-7821115.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2c/11976034/1107d0a2a812/JOBE2025-7821115.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd2c/11976034/227ba432979b/JOBE2025-7821115.003.jpg
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本文引用的文献

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