as a novel biomarker for sepsis diagnosis: Evidence from integrative WGCNA analysis.

Sepsis is a dysregulated immune response to infection that comes with multiple organ dysfunction and high mortality. The management of sepsis relies heavily on early recognition and diagnosis, but current diagnostic methods have limitations in timeliness, sensitivity, and discriminability. This study aims to discover novel biomarkers for sepsis diagnosis. Four datasets from different regions were analyzed using weighted gene co-expression network analysis (WGCNA), and genes with high Gene Significance values across these datasets were overlapped. Finally, two genes, and , were identified. was validated as a potential sepsis biomarker by checking multiple datasets and Receiver Operating Characteristic (ROC) Curve Analysis. Of note, could distinguish not only between adult and child sepsis patients and healthy controls, but also between septic shock and cardiogenic shock. Moreover, a murine sepsis model was established and the results showed that the transcription of in peripheral blood of septic mice was significantly higher than that of healthy controls, while infection alone did not significantly increase the transcription level of this gene. Subsequent studies of sepsis in mice revealed that the predictive effect of on sepsis could be observed as early as 6 h post-modeling. Interestingly, ANXA3 expression was predominantly up-regulated in myeloid cells, up-regulated in spleen, down-regulated in lung, and not detected in liver after sepsis modeling. Taken together, this study provides a way for the discovery of biomarkers and finds that may be a novel diagnostic biomarker for sepsis.