An early and accurate diagnosis of septic cardiomyopathy is vital for improving the overall prognosis of sepsis. In our research, we aimed to identify signature genes and their immune connections in septic cardiomyopathy. By analyzing the mouse myocardial transcriptome from sepsis induced by cecum ligation and puncture (CLP), we identified four distinct k-means clusters. Further analysis of human myocardial datasets using Weighted Gene Co-expression Network Analysis (WGCNA) revealed a strong correlation between the MEturquoise module and septic cardiomyopathy (cor = 0.79, p < .001). Through the application of Cytoscape plug-in MCODE and comprehensive analysis, we pinpointed two signature genes, THBS1 and TIMP1. These genes demonstrated significant involvement in immune cell infiltration, as detected by CIBERSORT, and displayed promising prognostic potential as validated by external datasets. Our experimental validation confirmed the up-regulation of both THBS1 and TIMP1 in septic murine hearts, underscoring their positive association with septic cardiomyopathy.
Keywords: Septic cardiomyopathy; immune infiltration analysis; weighted gene co-expression network analysis.