Revealing novel pyroptosis-related therapeutic targets for sepsis based on machine learning.

ABSTRACT:

Background

Sepsis is one of the most lethal diseases worldwide. Pyroptosis is a unique form of cell death, and the mechanism of interaction with sepsis is not yet clear. The aim of this study was to uncover pyroptosis genes associated with sepsis and to provide early therapeutic targets for the treatment of sepsis.

Methods

Based on the GSE134347 dataset, sepsis-related genes were mined by differential expression analysis and weighted gene coexpression network analysis (WGCNA). Subsequently, the sepsis-related genes were analysed for enrichment, and a protein‒protein interaction (PPI) network was constructed. We performed unsupervised consensus clustering of sepsis patients based on 33 pyroptosis-related genes (PRGs) provided by prior reviews. We finally obtained the PRGs mos

SUBMITTER: Chen Y 

PROVIDER: S-EPMC9912626 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature