IDENTIFICATION AND VERIFICATION OF FEATURE BIOMARKERS ASSOCIATED WITH CHOLINE METABOLISM IN SEPSIS-INDUCED CARDIOMYOPATHY.

Background: Sepsis-induced cardiomyopathy ( SIC ), one of the most common complications of sepsis, seriously affects the prognosis of critically ill patients. Choline metabolism is an important biological process in the organism, and the mechanism of its interaction with SIC is unclear. The aim of this study was to reveal the choline metabolism genes (CMGs) associated with SIC and to provide effective targets for the treatment of SIC . Methods: Through a comprehensive analysis of the microarray dataset GSE79962 (comprising 20 SIC patients and 11 healthy controls) from the GEO database, suspected co-expression modules and differentially expressed genes (DEGs) in SIC were identified. Hub CMGs were obtained by intersecting choline metabolism database with DEGs and key model genes. Afterward, hub CMGs most significantly involved in prognosis were further analyzed for the verification of major pathways of enrichment analysis. Finally, the expression of hub CMGs in in vivo and in vitro SIC model was verified by immunohistochemistry staining and quantitative real-time polymerase chain reaction analysis (qPCR). Results: Weighted gene co-expression network analysis identified 1 hub gene panel and 3,867 hub genes, which were intersected with DEGs and CMGs to obtain the same 3 hub CMGs:HIF-1α, DGKD, and PIK3R1. Only HIF-1α shows significant association with mortality ( P = 0.009). Subsequent differential analysis based on the high and low HIF-1α expression yielded 63 DEGs and then they were uploaded into Cytoscape software to construct a protein-protein interaction network and 6 hub genes with the highest priority were obtained (CISH, THBS1, IMP1, MYC, SOCS3, and VCAN). Finally, a multifactorial COX analysis revealed a significant correlation between HIF-1α and survival in SIC patients, which was further validated by in vitro and in vivo experiments. Conclusion: Our findings will provide new insights into the pathogenesis of SIC , and HIF-1α may have important applications as a potential biomarker for early detection and therapeutic intervention in SIC .