Imagine your body as a bustling city, with different cells playing different roles. In acute ischemic stroke (AIS), the city is under attack! Immune cells rush to the scene, triggering an intense inflammatory response. But what about circular RNA (circRNA)? These special molecules have been found to influence AIS, yet their role in the immune response remains unclear. In this study, scientists examined the distribution of immune cells in AIS patients using a nifty algorithm called CIBERSORT. They then analyzed gene data to identify 668 target genes involved in immune regulation and activation. Further analysis revealed key hub genes like TOM1, STAT3, RAB3D, MDM2, and FOS that were strongly linked to neutrophils, a type of immune cell. Using this information, they constructed a network of circRNA-mediated competitive endogenous RNAs (ceRNAs) that interacted with the immune system. The findings suggest a potential regulatory relationship between circRNA and the immune mechanism in AIS. This study not only enhances our understanding of AIS but also paves the way for new therapeutic approaches. Intrigued? Dive into the research to uncover more!

Acute ischemic stroke (AIS) is a common neurological disease that seriously endangers both the physical and mental health of human. After AIS, activated immune cells are recruited to the stroke site, where inflammatory mediators are released locally, and severe immune inflammatory reactions occur within a short time, which affects the progress and prognosis of IS. Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a closed-loop structure and high stability. Studies have found that circRNA can affect the course of IS. However, there is no report on ceRNA’s pathogenesis in AIS that is mediated by circRNA. In this study, the CIBERSORT algorithm was used to analyze the distribution of immune cells in patients with AIS. mRNA dataset was downloaded from the GEO database, and the weighted gene co-expression network analysis (WGCNA) method was used to construct weighted gene co-expression to determine 668 target genes, using GO, KEGG enrichment analysis, construction of protein-protein interaction (PPI) network analysis, and molecular complex detection (MCODE) plug-in analysis. The results showed that the biological function of the target gene was in line with the activation and immune regulation of neutrophils; signal pathways were mostly enriched in immune inflammation-related pathways. A Venn diagram was used to obtain 52 intersection genes between target genes and disease genes. By analyzing the correlation between the intersection genes and immune cells, we found that the top 5 hub genes were TOM1, STAT3, RAB3D, MDM2, and FOS, which were all significantly positively correlated with neutrophils and significantly negatively correlated with eosinophils. A total of 52 intersection genes and the related circRNA and miRNA were used as input for Cytoscape software to construct a circRNA-mediated ceRNA competition endogenous network, where a total of 18 circRNAs were found. Further analysis of the correlation between circRNA and immune cells found that 4 circRNAs are positively correlated with neutrophils. Therefore, we speculate that there may be a regulatory relationship between circRNA-mediated ceRNA and the immune mechanism in AIS. This study has important guiding significance for the progress, outcome of AIS, and the development of new medicine.

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