Identification and validation of autophagy-related genes in sepsis based on bioinformatics studies

Abstract

Abstract We identified 14 key genes associated with mitochondrial autophagy in sepsis through differential analysis of the dataset and then analysed the identified genes for functional enrichment. The analysis of key genes and deeper analysis of key genes by molecular typing, Weighted Gene Correlation Network Analysis (WGCNA) and ceRNA were also carried out. We have also validated these key genes with clinical data. Finally, sepsis diagnostic models are constructed by combining key genes with machine learning methods. In addition, we discuss the importance of the immune system in sepsis and its relationship with signature genes, which opens up new directions for studying the role of the immune system in sepsis. Overall, our study adds new ideas to the diagnosis and treatment of sepsis.

Keywords

• Sepsis
• Autophagy
• Weighted gene correlation Network analysis
• Gene expression omnibus dataset