Abstract
Sepsis often leads to unpredictable consequences. The prognosis of sepsis has not been largely improved. We tried to construct a prognostic gene model related to the 28-day mortality of sepsis to identify the risk of mortality and improve the outcome early. We identified the modules associated with 28-day mortality by weighted gene co-expression network analysis from the microarray data of GSE65682. Protein-protein interaction network analysis and univariate Cox regression were conducted to identify hub genes for constructing a prognostic model. Finally, the model was evaluated for robustness. The correlation between the model and immune cells was investigated. The cyan module has a significant negative relationship with 28-day mortality. A risk model was developed to predict prognosis, utilizing macrophage expressed gene 1, CX3C chemokine receptor 1, and human leukocyte antigen-DRB1. The model's expression was found to be higher in the group with lower risk, while the group with higher risk had a higher 28-day mortality rate. These findings were validated using both the test and whole sets. Three genes were positively associated with monocyte expression. We constructed a septic prognostic model with 3 genes, including macrophage expressed gene 1, CX3C chemokine receptor 1, and human leukocyte antigen-DRB1. The expression of them had a significant negative relationship with the 28-day mortality and may influenced monocyte function.