Dandan Zhao,1,2,* Jinqiang Zhuang,3,* Liping Wang,4 Lili Wu,5 Wangjie Xu,6 Lu Zhao,4 Jiang Hong,1 Wei Jin,1 Congliang Miao1 

1Department of Internal and Emergency Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Department of Emergency Medicine, Affiliated Hospital of Xuzhou Medical University, Xuzhou, People’s Republic of China; 3Department of Emergency Intensive Care Unit (EICU), Affiliated Hospital of Yangzhou University, Yangzhou, People’s Republic of China; 4Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, People’s Republic of China; 5Department of Cardiology, Shanghai Songjiang District Central Hospital, Shanghai, People’s Republic of China; 6Laboratory Animal Center, Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Congliang Miao; Wei Jin, Department of Internal and Emergency Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China, Email mcl15917908206@163.com; jw1230123@126.com

Purpose: Septic cardiomyopathy (SCM) is a significant global public health concern characterized by substantial morbidity and mortality, which has not been improved for decades due to lack of early diagnosis and effective therapies. This study aimed to identify hub biomarkers in SCM and explore their potential mechanisms.
Methods: We utilized the GSE53007 and GSE207363 datasets for transcriptome analysis of normal and SCM mice. Hub biomarkers were identified through a protein–protein interaction (PPI) network and validated using LPS-treated C57/BL6 mice. Functional enrichment analysis was performed to uncover relevant signaling pathways, while single-cell RNA sequencing was used to examine key genes and regulatory mechanisms associated with SCM.
Results: A total of 374 differentially expressed genes (DEGs) were identified, with 268 genes up-regulated and 106 genes down-regulated. Functional enrichment highlighted chemokine activity and receptor binding, with KEGG pathways revealing significant involvement of the TNF and IL-7 signaling pathways. Deterioration of cardiac function, elevated inflammatory markers such as IL-1β, IL-6, and increased cardiac injury biomarkers such as cTnI indicated the successful establishment of our SCM model. Subsequently, qPCR was conducted to validate the expression of the top 10 genes, through which we identified Cd40, Tlr2, Cxcl10, Ccl5, Cxcl1, Cd14, Gbp2, Ifit2, and Vegfa as key biomarkers. Single-cell sequencing indicated increased neutrophil and macrophage populations, with decreased B cells and cardiomyocytes. Additionally, transcription regulators Irf1 and Stat1 were found to potentially regulate the expression of Gbp2, Cxcl10, Ccl5, and Cd40, linking SCM to immune response, ferroptosis, pyroptosis, cuproptosis, and m6A RNA methylation modification.
Conclusion: This study identified nine hub biomarkers and two transcription regulators associated with SCM. Exploring the connections between SCM and immunity, ferroptosis, pyroptosis, cuproptosis, and m6A RNA methylation might provide insights into the underlying mechanisms. These findings enhanced our understanding of SCM’s underlying mechanisms and might pave the way for novel therapeutic strategies to improve clinical outcomes.

Keywords: septic cardiomyopathy, integrated bioinformatics analysis, hub biomarkers, single-cell data analysis, immunity