Classification and functional analysis of disulfidptosis-associated genes in sepsis

Abstract

Sepsis represents a critical condition characterized by multiple-organ dysfunction resulting from inflammatory response to infection. Disulfidptosis is a newly identified type of programmed cell death that is intimately associated with the actin cytoskeleton collapse caused by glucose starvation and disulfide stress, but its role in sepsis is largely unknown. The study was to adopt a diagnostic and prognostic signature for sepsis with disulfidptosis based on the differentially expressed genes (DEGs) between sepsis and healthy people from GEO database. The disulfidptosis hub genes associated with sepsis were identified, and then developed consensus clustering and immune infiltration characteristics. Next, we evaluated disulfidptosis-related risk genes by using LASSO and Random Forest algorithms, and constructed the diagnostic sepsis model by nomogram. Finally, immune infiltration, GSVA analysis and mRNA-miRNA networks based on disulfidptosis-related DEGs were screened. There are five upregulated disulfidptosis-related genes and seven downregulated genes were filtered out. The six intersection disulfidptosis-related genes including LRPPRC, SLC7A11, GLUT, MYH9, NUBPL and GYS1 exhibited higher predictive ability for sepsis with an accuracy of 99.7%. In addition, the expression patterns of the critical genes were validated. The study provided a comprehensive view of disulfidptosis-based signatures to predict the prognosis, biological features and potential treatment directions for sepsis.

Keywords: bioinformatics; disulfidptosis; gene expression; immune infiltration; sepsis.