Single-cell transcriptomics combined with bioinformatics for comprehensive analysis of macrophage subpopulations and hub genes in ischemic stroke.
- Author:
Jingyao XU
1
;
Xiaolu WANG
2
;
Shuai HOU
1
;
Meng PANG
2
;
Gang WANG
3
;
Yanqiang WANG
4
,
5
Author Information
1. Emergency Department, Affiliated Hospital of Shandong Second Medical University, Weifang 261031, China.
2. Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, Weifang 261031, China.
3. Emergency Department, Affiliated Hospital of Shandong Second Medical University, Weifang 261031, China. *Corresponding authors, E-mail: 381881579@qq.com.
4. Department of Neurology II, Affiliated Hospital of Shandong Second Medical University, Weifang 261031, China. *Corresponding authors, E-mail: wangqiangdoctor@
5. com.
- Publication Type:Journal Article
- MeSH:
Macrophages/metabolism*;
Computational Biology/methods*;
Single-Cell Analysis/methods*;
Transcriptome;
Ischemic Stroke/metabolism*;
Animals;
Gene Regulatory Networks;
Gene Expression Profiling;
Humans;
Male
- From:
Chinese Journal of Cellular and Molecular Immunology
2025;41(6):505-513
- CountryChina
- Language:Chinese
-
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.
