RESUMEN
Excessive inflammatory response following ischemic stroke (IS) injury is a key factor affecting the functional recovery of patients. The efferocytic clearance of apoptotic cells within ischemic brain tissue is a critical mechanism for mitigating inflammation, presenting a promising avenue for the treatment of ischemic stroke. However, the cellular and molecular mechanisms underlying efferocytosis in the brain after IS and its impact on brain injury and recovery are poorly understood. This study explored the roles of inflammation and efferocytosis in IS with bioinformatics. Three Gene Expression Omnibus Series (GSE) (GSE137482-3 m, GSE137482-18 m, and GSE30655) were obtained from NCBI (National Center for Biotechnology Information) and GEO (Gene Expression Omnibus). Differentially expressed genes (DEGs) were processed for GSEA (Gene Set Enrichment Analysis), GO (Gene Ontology Functional Enrichment Analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Efferocytosis-related genes were identified from the existing literature, following which the relationship between Differentially Expressed Genes (DEGs) and efferocytosis-related genes was examined. The single-cell dataset GSE174574 was employed to investigate the distinct expression profiles of efferocytosis-related genes. The identified hub genes were verified using the dataset of human brain and peripheral blood sample datasets GSE56267 and GSE122709. The dataset GSE215212 was used to predict competing endogenous RNA (ceRNA) network, and GSE231431 was applied to verify the expression of differential miRNAs. At last, the middle cerebral artery (MCAO) model was established to validate the efferocytosis process and the expression of hub genes. DEGs in two datasets were significantly enriched in pathways involved in inflammatory response and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related genes (Abca1, C1qc, Ptx3, Irf5, and Pros1) and key transcription factors (Stat5). The scRNA-seq analysis showed that these hub genes were mainly expressed in microglia and macrophages which are the main cells with efferocytosis function in the brain. We then identified miR-125b-5p as a therapeutic target of IS based on the ceRNA network. Finally, we validated the phagocytosis and clearance of dead cells by efferocytosis and the expression of hub gene Abca1 in MCAO mice models.
RESUMEN
Objective: This study is aimed at identifying the potential diagnostic markers for circulating endothelial cells (CECs) for acute myocardial ischemia (AMI) and exploring the regulatory mechanisms of the selected biomarker in mitochondrial oxidative damage and vascular inflammation in AMI pathology. Methods: Utilizing the Gene Expression Omnibus dataset GSE66360, we scanned for differentially expressed genes (DEGs) in 49 AMI patients and 50 healthy subjects. To discover possible biomarkers, LASSO regression and support vector machine recursive feature elimination examinations were conducted. Using the GSE60993 and GSE123342 datasets and AMI rat models, the expression levels and diagnostic accuracy of the biomarkers in AMI were thoroughly verified. CIBERSORT was employed to evaluate the compositional patterns of 22 distinct immunological cell percentages in AMI according to combined cohorts. The oxidative-damaged mitochondria were detected by confocal microscopy observation of MitoTracker, ROS-DCFH-DA, and mCherry-GFP-LC3B. Results: In total, 122 genes were identified. The identified DEGs primarily contributed in arteriosclerosis, arteriosclerotic cardiovascular disorders, bacterial infectious disorder, coronary artery disease, and myocardial infarction. Nine features (NR4A2, GABARAPL1 (GEC1), CLEC4D, ITLN1, SNORD89, ZFP36, CH25H, CCR2, and EFEMP1) of the DEGs were shared by two algorithms, and GABARAPL1 (GEC1) was identified and verified as a diagnostic mitochondrial biomarker for AMI. Confocal results showed that there existed mitochondrial damage and oxidative stress in cardiac CMECs after AMI, and the blocked autophagy flux could be released by exosome burst in cardiac CMECs and blood CECs. Immune cell infiltration testing declared that elevated GEC1 expression in blood CECs was linked to the rise of monocytes and neutrophils. Functional tests revealed that high GEC1 expression in CMECs and CECs could activate the vascular inflammatory response by stimulating NLRP3 inflammasome production after AMI. Conclusion: Oxidative-damaged mitochondria in cardiac CMECs activate GEC1-mediated autophagosomes but block autophagy flux after AMI. The exfoliated cardiac CMECs evolve into abnormal blood CECs, and the undegraded GEC1 autophagosomes produce a large number of NLRP3 inflammasomes by exosome burst, stimulating the increase in monocytes and neutrophils and ultimately triggering vascular inflammation after AMI. Therefore, GEC1 in blood CECs is a highly specific diagnostic mitochondrial biomarker for AMI.