多组学解析动脉粥样硬化型缺血性卒中的免疫调控网络

doi:10.3969/j.issn.1673-5765.2025.10.007

摘要/Abstract

摘要： 目的基于多组学数据解析动脉粥样硬化型缺血性卒中的免疫特征。
方法通过孟德尔随机化联合转录组数据筛选动脉粥样硬化型缺血性卒中的相关基因。采用基因富集分析（gene set enrichment analysis，GSEA）和基因集变异分析（gene set variation analysis，GSVA）解析基因和通路功能。通过基因/蛋白质相互作用检索工具（search tool for the retrieval of interacting genes/proteins，STRING）数据库构建蛋白质-蛋白质相互作用网络，并通过Cytoscape软件筛选核心基因；使用单细胞测序（SingleR、CellChat包）分析细胞分化轨迹与通信网络；采用估算核糖核酸转录本相对子集细胞识别工具（cell-type identification by estimating relative subsets of ribonucleic acid transcripts，CIBERSORT）基于转录组数据推断免疫细胞组分与亚群丰度，并计算基因表达与免疫细胞浸润水平的相关性。
结果共筛选出133个动脉粥样硬化型缺血性卒中相关基因，功能富集显示其参与血管平滑肌发育（基因本体论：0097084）等生物过程。细胞通信分析显示，动脉粥样硬化型缺血性卒中相关基因通过分泌型磷蛋白1和半乳糖凝集素通路的8组配体-受体调控小胶质细胞、单核细胞等免疫细胞的细胞通信。蛋白质-蛋白质相互作用网络核心基因解旋酶（senataxin，SETX）、含缬酪肽蛋白（valosin containing protein，VCP）、Fcγ受体ⅡB（Fc fragment of IgG receptor Ⅱb，FCGR2B）、分化簇44（cluster of differentiation 44，CD44）与动脉粥样硬化型缺血性卒中呈正因果关系；CXC趋化因子受体2（C-X-C motif chemokine receptor 2，CXCR2）和自噬适配体蛋白1（sequestosome 1，SQSTM1）与动脉粥样硬化型缺血性卒中呈负因果关系。上述核心基因参与调控免疫细胞分化并影响辅助型T2细胞调节、抗原炎症反应抑制等生物过程。CIBERSORT评估显示CD8＋T细胞、活化自然杀伤（natural killer，NK）细胞、巨噬细胞M0、静息肥大细胞和中性粒细胞与动脉粥样硬化型缺血性卒中相关，其中SETX表达与中性粒细胞浸润呈正相关（ρ＝0.29）；CD44表达与活化NK细胞浸润呈正相关（ρ＝0.29），与中性粒细胞浸润呈负相关（ρ＝-0.41）。
结论 SETX、VCP、FCGR2B、CD44、CXCR2和SQSTM1等核心基因通过调控中枢与外周免疫细胞分化及血管平滑肌功能，参与动脉粥样硬化型缺血性卒中的病理过程，是其潜在的生物标志物。

文章导读： 本研究通过多组学整合分析，首次系统性揭示了动脉粥样硬化型缺血性卒中的免疫调控网络，明确了SETX、VCP、FCGR2B、CXCR2、CD44和SQSTM1 6个核心基因在免疫细胞分化和血管功能调控中的关键作用，强调了免疫失衡与神经损伤之间的内在联系。上述核心基因不仅是动脉粥样硬化型缺血性卒中潜在的分子标志物，还可能成为未来卒中治疗的重要靶点。

关键词: 动脉粥样硬化型缺血性卒中; 免疫微环境; 单细胞测序; 细胞分化; 细胞通信

Abstract: Objective To decipher the immune characteristics of atherosclerotic ischemic stroke using multi-omics data.
Methods Atherosclerotic ischemic stroke-related genes were identified by integrating Mendelian randomization with transcriptomic data. Pathway functions were elucidated through gene set enrichment analysis and gene set variation analysis. The protein-protein interaction networks were constructed using the search tool for the retrieval of interacting genes/proteins (STRING) database, and hub genes were subsequently screened with Cytoscape software. Cell differentiation trajectories and communication networks were analyzed by combining single-cell sequencing data (using the SingleR and CellChat packages). Based on transcriptome data, the cell-type identification by estimating relative subsets of ribonucleic acid transcripts (CIBERSORT) algorithm was used to infer immune cell composition and quantify the relative abundance of different immune cell subsets.
Results A total of 133 atherosclerotic ischemic stroke-related genes were identified, with functional enrichment analysis indicating their involvement in vascular smooth muscle development (gene ontology: 0097084). Cell communication analysis revealed that these genes regulate interactions among immune cells (such as microglia and monocytes) through eight ligand-receptor pairs of the secreted phosphoprotein 1 and galectin pathway. In the protein-protein interaction network, hub genes including senataxin (SETX), valosin containing protein (VCP), Fc fragment of IgG receptor Ⅱb (FCGR2B), cluster of differentiation 44 (CD44) (OR>1, positive causal relationship), C-X-C motif chemokine receptor 2 (CXCR2), and sequestosome 1 (SQSTM1) (OR<1, negative causal relationship) were found to regulate immune cell differentiation and influence biological processes such as T help cells 2 cell regulation and suppression of inflammatory antigen response. CIBERSORT evaluation showed that CD8+ T cells, activated natural killer (NK) cells, macrophages M0, resting mast cells, and neutrophils were associated with atherosclerotic ischemic stroke. Specifically, SETX expression was positively correlated with neutrophil infiltration (ρ=0.29), CD44 expression was positively correlated with infiltration of activated NK cells (ρ=0.29) and negatively correlated with neutrophil infiltration (ρ=–0.41).
Conclusions Hub genes such as SETX, VCP, FCGR2B, CD44, CXCR2, and SQSTM1 contribute to the pathological process of atherosclerotic ischemic stroke by regulating the differentiation of central and peripheral immune cells and vascular smooth muscle function, making them potential biomarkers.

Key words: Atherosclerotic ischemic stroke; Immune microenvironment; Single-cell sequencing; Cell differentiation; Cell communication

中图分类号:

迟骋, 华实, 车峰远. 多组学解析动脉粥样硬化型缺血性卒中的免疫调控网络[J]. 中国卒中杂志, 2025, 20(10): 1247-1260.

CHI Cheng, HUA Shi, CHE Fengyuan. Multi-Omics Approaches Decipher the Immune Regulatory Network in Atherosclerotic Ischemic Stroke[J]. Chinese Journal of Stroke, 2025, 20(10): 1247-1260.

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