[Single-cell transcriptomics combined with bioinformatics for comprehensive analysis of macrophage subpopulations and hub genes in ischemic stroke].

细胞与分子免疫学杂志 Pub Date : 2025-06-01
Jingyao Xu, Xiaolu Wang, Shuai Hou, Meng Pang, Gang Wang, Yanqiang Wang
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引用次数: 0

Abstract

Objective To explore macrophage subpopulations in ischemic stroke (IS) by using single-cell RNA sequencing (scRNA-seq) data analysis and High-Dimensional Weighted Gene Co-Expression Network Analysis (hdWGCNA). Methods Based on single-cell sequencing data, transcriptomic information for different cell types was obtained, and macrophages were selected for subpopulation identification. hdWGCNA, cell-cell communication, and pseudotime trajectory analysis were used to explore the characteristics of macrophage subpopulations following IS. Key genes related to IS were identified using microarray data and validated for diagnostic potential through Receiver Operating Characteristic (ROC) analysis. Gene Set Enrichment Analysis (GSEA) was conducted to investigate the potential functions of these genes. Results The scRNA-seq data analysis revealed significant changes in macrophage subpopulation composition after IS. A specific macrophage subpopulation enriched in the stroke group was identified and designated as MCAO-specific macrophages (MSM). Pseudotime trajectory analysis indicated that MSM cells were in an intermediate stage of macrophage differentiation. Cell-cell communication analysis uncovered complex interactions between MSM cells and other cells, with the CCL6-CCR1 signaling axis potentially playing a crucial role in neuroinflammation. Two gene modules associated with MSM were identified via hdWGCNA, significantly enriched in pathways related to NOD-like receptors and antigen processing. By integrating differentially expressed MSM genes with conventional transcriptomic data, three IS-related hub genes were identified: Arg1, CLEC4D, and CLEC4E. Conclusion This study reveals the characteristics and functions of macrophage subpopulations following IS and identifies three hub genes with potential diagnostic value, providing novel insights into the pathological mechanisms of IS.

[单细胞转录组学结合生物信息学综合分析缺血性卒中中巨噬细胞亚群和枢纽基因]。
目的通过单细胞RNA测序(scRNA-seq)数据分析和高维加权基因共表达网络分析(hdWGCNA),探讨巨噬细胞在缺血性卒中(IS)中的亚群。方法基于单细胞测序数据,获取不同细胞类型的转录组学信息,选择巨噬细胞进行亚群鉴定。采用hdWGCNA、细胞间通讯和伪时间轨迹分析来探讨IS后巨噬细胞亚群的特征。使用微阵列数据鉴定与IS相关的关键基因,并通过受试者工作特征(ROC)分析验证其诊断潜力。通过基因集富集分析(GSEA)研究这些基因的潜在功能。结果scRNA-seq数据分析显示IS后巨噬细胞亚群组成发生了显著变化。在卒中组中发现了一种特异性巨噬细胞亚群,并将其命名为mcao特异性巨噬细胞(MSM)。伪时间轨迹分析表明MSM细胞处于巨噬细胞分化的中间阶段。细胞间通讯分析揭示了MSM细胞与其他细胞之间复杂的相互作用,CCL6-CCR1信号轴可能在神经炎症中发挥关键作用。通过hdWGCNA鉴定出两个与MSM相关的基因模块,它们在nod样受体和抗原加工相关的途径中显著富集。通过将差异表达的MSM基因与常规转录组学数据整合,鉴定出三个与is相关的枢纽基因:Arg1、cle4d和cle4e。结论本研究揭示了IS后巨噬细胞亚群的特征和功能,并鉴定出3个具有潜在诊断价值的枢纽基因,为IS的病理机制提供了新的认识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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