Diagnostic and predictive values of pyroptosis-related genes in sepsis - Wang, Xuesong; Guo, Zhe; Wang, Ziyi; Liao, Haiyan; Wang, Ziwen; Chen, Feng; Wang, Zhong (Frontiers in Immunology, 2023)
Background: Sepsis is an organ dysfunction syndrome caused by the body's dysregulated response to infection, which often occurs during infection. Existing methods for early diagnosis of sepsis have low specificity and cannot fully meet the urgent need to reduce mortality from sepsis. Methods: We screened the pediatric sepsis microarray dataset from the GEO database and analyzed the differentially expressed genes (DEGs) associated with pyroptosis. In this paper, these DEGs were subjected to multiple bioinformatics analyses. The differential immune landscape between sepsis and healthy controls was explored by screening diagnostic genes using various machine-learning models. In addition, this paper verified the diagnostic value of these diagnosis-related genes in with sepsis, identified miRNAs that have regulatory relationships with them, and related drugs that have regulatory relationships, respectively, in the internal test set and external test. Results: The results showed that eight genes (CLEC5A, MALT1, NAIP, NLRC4, SERPINB1, SIRT1, STAT3 and TLR2) related to sepsis diagnosis were screened by multiple machine learning algorithms. The CIBERSORT algorithm confirmed that these genes were significantly correlated with the infiltration abundance of some immune cells and immune checkpoint sites (P<0.05). SIRT1, STAT3 and TLR2 were identified by DGIdb database as potentially regulated by multiple drugs. Finally, 7 genes were verified to have significant differences in expression between the sepsis group and the control group (P<0.05). Conclusion: The diagnostic genes identified and verified in this study can provide reference for clinical diagnosis.