Decoding immune cell dynamics in ischemic stroke: Insights from single-cell RNA sequencing analysis

Yating Lan Chun Zou Feiyu Nong Qi Huang Jingyi Zeng Wenyi Song Guining Liang Qingyan Wei Mika Pan Donghua Zou ^* Yaobin Long ^*

• The Second Affiliated Hospital of GuangXi Medical University, Nanning, Guangxi Zhuang Region, China

Background: Ischemic stroke (IS) is a leading cause of adult disability worldwide. The inflammatory processes involved are complex, making it challenging to fully understand the pathological mechanisms of IS. Phagocytosis plays an important role in eliminating neurotoxic or damaged neurons resulting from inflammatory responses. This study employed bioinformatics methods to analyze single-cell RNA sequencing (scRNA-seq) data to investigate the cell types and molecular biological processes involved in IS. Methods: scRNA-seq data for IS were obtained from the Gene Expression Omnibus (GEO). Following sample screening and reprocessing, 5,582 single cells were identified from healthy controls and patients with IS. Uniform manifold approximation and projection (UMAP) was utilized to further explore the cellular composition in IS. Functional enrichment analysis of differentially expressed genes was conducted to identify transcriptional regulators, whereas cell developmental trajectories were predicted to uncover potential cell fate decisions. iTALK was employed to identify potential ligand-receptor axes within the cell-type immune microenvironment of IS. Results: Based on scRNA-seq data analysis, we identified four cell types and their associated subclusters, along with genes exhibiting significant differential expression within these subclusters. Phagocytosis was significantly enriched in cell types linked to IS, while the differentiation trajectories of subpopulations in IS were different.Additionally, multiple receptor-ligand axes were identified, indicating diverse interactions within the immune microenvironment of IS. Conclusion: This study demonstrated that phagocytosis in IS cell types critically influences disease progression. It also predicted the trajectories of infarct cells. These findings provide valuable insights into the molecular and cellular mechanisms underlying IS and highlight potential pathways for therapeutic intervention.