Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning

作者：Wenyuan Zhang, Zhong‐Hua Chen, Xiaoxia An, Hui Li, Hualin Zhang, Shuijing Wu, Yu-Qian Guo, Kai Zhang, Congli Zeng, Xiangming Fang · 发表于：World Journal of Pediatrics · 年份：2023 · DOI：10.1007/s12519-023-00717-7 · 被引用次数：71 · 研究领域：Sepsis Diagnosis and Treatment、Inflammation biomarkers and pathways、Immune Response and Inflammation

BACKGROUND: Pediatric sepsis is a complicated condition characterized by life-threatening organ failure resulting from a dysregulated host response to infection in children. It is associated with high rates of morbidity and mortality, and rapid detection and administration of antimicrobials have been emphasized. The objective of this study was to evaluate the diagnostic biomarkers of pediatric sepsis and the function of immune cell infiltration in the development of this illness. METHODS: Three gene expression datasets were available from the Gene Expression Omnibus collection. First, the differentially expressed genes (DEGs) were found with the use of the R program, and then gene set enrichment analysis was carried out. Subsequently, the DEGs were combined with the major module genes chosen using the weighted gene co-expression network. The hub genes were identified by the use of three machine-learning algorithms: random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator. The receiver operating characteristic curve and nomogram model were used to verify the discrimination and efficacy of the hub genes. In addition, the inflammatory and immune status of pediatric sepsis was assessed using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). The relationship between the diagnostic markers and infiltrating immune cells was further studied. RESULTS: Overall, after overlapping key mo...