Development of macrophage-associated genes prognostic signature predicts clinical outcome and immune infiltration for sepsis.

ABSTRACT: Sepsis is a major global health problem, causing a significant burden of disease and death worldwide. Risk stratification of sepsis patients, identification of severe patients and timely initiation of treatment can effectively improve the prognosis of sepsis patients. We procured gene expression datasets for sepsis (GSE54514, GSE65682, GSE95233) from the Gene Expression Omnibus and performed normalization to mitigate batch effects. Subsequently, we applied weighted gene co-expression network analysis to categorize genes into modules that exhibit correlation with macrophage activity. To pinpoint macrophage-associated genes (MAAGs), we executed differential expression analysis and single sample gene set enrichment analysis. We then established a prognostic model derived from four MAAGs that

SUBMITTER: Ma G 

PROVIDER: S-EPMC10805801 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature