Background: Immune dysregulation is central to the pathogenesis of sepsis, yet the underlying immunomodulatory mechanisms in pediatric sepsis remain insufficiently defined. This study aimed to elucidate key immune-related gene signatures and cellular features associated with pediatric sepsis. Methods: Integrated bioinformatic analyses were applied to identify immunomodulatory-related differentially expressed genes (IRDEGs). Immune modulation was further characterized by computing immunomodulatory scores (IMSs) using single-sample gene set enrichment analysis (ssGSEA), followed by subgroup stratification and immune cell infiltration analysis. Results: Five hub IRDEGs—MAPK14, S100A9, HP, SERPINB1, and SIGLEC5—were identified. Among these, MAPK14 exhibited a strong association with myeloid-derived suppressor cells (MDSCs), which were significantly enriched in patients with high IMSs. Conclusion: These findings reveal novel immunomodulatory axes in pediatric sepsis, emphasizing the role of MAPK14 and MDSCs. This work provides potential biomarkers and therapeutic targets for improving the clinical management of pediatric sepsis. Keywords: pediatric sepsis, immunomodulation, machine learning, least absolute shrinkage and selection operator, myeloid-derived suppressor cells
Shi et al. (Sun,) studied this question.