ArticleTranslational pediatrics2025
Identification of potential necroinflammation-associated necroptosis-related biomarkers in necrotizing enterocolitis based on bioinformatics analysis and machine learning.
Article in Translational pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Necrotizing enterocolitis (NEC) stands as one of the most lethal conditions afflicting premature infants. There is a close relationship between necroptosis, necroinflammation, and the potential mechanisms of NEC. The purpose of this study was to investigate the mechanism of necroinflammation-associated necroptosis-related genes (NiNRGs) in NEC, identify NiNRGs-related diagnostic markers for NEC, and construct a diagnostic model for NEC through bioinformatics analysis and machine learning. Methods: Differentially expressed NiNRGs (DE-NiNRGs) were identified through differential expression and correlation analysis, followed by gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network establishment. Three machine learning methods were used to find potential diagnostic biomarkers, evaluated through a receiver operating characteristic (ROC) curve and a nomogram model. Immune infiltration scores for 28 immune cell types in NEC were calculated, along with correlation coefficients for diagnostic marker genes. Various databases predicted interactions between these genes, small molecule drugs, microRNAs, and transcription factors. A single-gene GSEA (sgGSEA) identified significantly enriched signaling pathways associated with diagnostic marker genes in NEC. Results: A total of 29 DE-NiNRGs were identified, linked to 17 pathways, including tumor necrosis factor (TNF), interleukin (IL)-17, and cytosolic DNA-sensing pathways. The PPI network showed close interactions among DE-NiNRGs. Three biomarkers, Conclusions: Necroinflammation-induced necroptosis significantly contributes to the progression of NEC.
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