实用老年医学 ›› 2026, Vol. 40 ›› Issue (3): 241-246.doi: 10.3969/j.issn.1003-9198.2026.03.005

• 基础研究 • 上一篇    下一篇

基于单细胞多组学分析的巨噬细胞衰老在动脉粥样硬化中的作用机制研究

陈徐冠, 夏玉东, 王璎瑛, 徐云凡, 吴军   

  1. 210029 江苏省南京市,南京医科大学第一附属医院老年心血管科
  • 收稿日期:2025-09-05 发布日期:2026-03-26
  • 通讯作者: 吴军,Email:wujun9989@njmu.edu.cn
  • 基金资助:
    江苏省社会发展-临床前沿技术项目(BE2023818);江苏省老年健康科研重点项目(LKZ2023001)

Mechanism of macrophage senescence-driven atherosclerosis based on single-cell multi-omics analysis

CHEN Xuguan, XIA Yudong, WANG Yingying, XU Yunfan, WU Jun   

  1. Department of Geriatric Cardiology,the First Affiliated Hospital with Nanjing Medical University,Nanjing 210029, China
  • Received:2025-09-05 Published:2026-03-26
  • Contact: WU Jun,Email:wujun9989@njmu.edu.cn

摘要: 目的 研究巨噬细胞衰老在动脉粥样硬化(AS)中的作用机制,筛选关键基因。 方法 从Gene Expression Omnibus(GEO)数据库获取数据,采用Seurat聚类分析细胞,通过UCell方法计算衰老评分,采用高维加权基因共表达网络分析(hdWGCNA)构建共表达网络,采用limma分析差异表达,采用Lasso回归和随机森林算法筛选核心基因,采用SHAP评估基因重要性,采用CIBERSORT分析免疫浸润。 结果 AS核心斑块组织(AC组)的巨噬细胞衰老评分高于斑块旁正常动脉组织(PA组)(P<0.001)。hdWGCNA鉴定了11个功能模块,其中Macrophages_NEW6与衰老评分正相关性最强。筛选出4个核心基因MAF、FILIP1L、PEBP1、SPRED1,随机森林模型预测效能较高(AUC=0.889);SHAP分析显示MAF基因重要性最高。免疫浸润分析显示,M2/M0巨噬细胞是AS斑块组织中占主导地位的浸润细胞,且与核心基因呈现显著相关性。 结论 巨噬细胞通过4个基因调控AS发展, 四基因诊断模型具有临床应用前景。

关键词: 巨噬细胞衰老, 动脉粥样硬化, 单细胞多组学, 四基因诊断模型

Abstract: Objective To investigate the role of macrophage senescence in atherosclerosis(AS) and identify the key genes. Methods The data were obtained from the Gene Expression Omnibus (GEO) database. Cell clusters were analyzed using Seurat, aging scores were calculated via the UCell method, co-expression networks were constructed through high-dimensional weighted gene co-expression network analysis (hdWGCNA), differential expression was analyzed with limma, core genes were screened using Lasso regression and random forest algorithms, gene significance was assessed by Shapley additive explanations(SHAP), and immune infiltration was evaluated by CIBERSORT. Results The senescence score of macrophages in the AS core plaques (AC group) was higher than that in the patient-matched proximal adjacent portions (PA group) of carotid artery tissue (P<0.001). hdWGCNA identified 11 functional modules, and Macrophages_NEW6 showed the strongest correlation with senescence scores. Four core genes (MAF、FILIP1L、PEBP1、SPRED1) were screened out, and the random forest model had high predictive efficacy (AUC=0.889). SHAP analysis revealed MAF as the most important gene in terms of feature importance. M2/M0 macrophages were the predominant infiltrating cells in atherosclerotic plaque tissues and showed a significant correlation with the core genes. Conclusions Macrophages regulate AS development through four genes, which has potential value for clinical application.

Key words: macrophage senescence, atherosclerosis, single-cell multi-omics analysis, four-gene diagnostic model

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