Comprehensive analysis of macrophage-associated inflammatory genes in AMI based on bulk combined with single-cell sequencing data - Kong,Xugang; Jin,Guangjun (PeerJ, 2024)
Background Previous studies have highlighted the crucial role of macrophages in the post-acute myocardial infarction (AMI) inflammatory response. This study specifically focused on investigating macrophage-related targets involved in the inflammatory response after AMI. Methods Bioinformatics methods were applied for identifying differentially expressed genes (DEGs) in datasets GSE163465, GSE236374, and GSE183272 obtained from the Gene Expression Omnibus (GEO) database. Communication analysis was conducted to analyze macrophages in AMI. Subsequent analyses encompassed functional enrichment analysis of Co-DEGs using Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG). Gene set variation analysis (GSVA) and immune infiltration analysis were carried out for screening key genes. Validation of the bioinformatics analysis results involved original and GSE114695 datasets, supported by quantitative real time polymerase chain reaction (qRT-PCR). Animal experiments confirmed the upregulation of Saa3, Acp5, and Fcgr4 genes in AMI mouse myocardial tissues. Results A total of 80 and 1,907 DEGs were respectively identified by analyzing scRNA-seq and bulk RNA-seq data. The overlapping Co-DEGs were found to be closely associated with inflammation-associated pathways, specifically the PI3K-Akt-mTOR pathway. Screening based on GSVA scores and macrophage-associated scores highlighted four key genes (Saa3, Ms4a4c, Acp5, and Fcgr4). Immunoinfiltration analysis revealed their close association with macrophages. Dataset validation corroborated these findings. Experimental validation focused on Saa3, Ms4a4c, Acp5, and Fcgr4, demonstrating the upregulation of their expression in cardiac macrophages in the AMI group, consistent with previous reports. Conclusion This study provides new perspectives on AMI treatment. In addition, Saa3, Acp5, and Fcgr4 exhibit potential as biomarkers for improving cardiac repair and slowing down the development of heart failure after AMI.
Keywords: Acute myocardial infarction; Macrophage; Single-cell sequencing; Bioinformatics analysis; Inflammation