Integrating Bulk RNA and Single-Cell Sequencing Data Unveils Efferocytosis Patterns and ceRNA Network in Ischemic Stroke

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 (Ky oto 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 employ ed 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 res ponse and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related gen...
Source: Translational Stroke Research - Category: Neurology Source Type: research