Bioinformatics-driven exploration of key genes and mechanisms underlying oxidative stress in traumatic brain injury.

BACKGROUND: Oxidative stress is a pivotal mechanism implicated in the onset of traumatic brain injury (TBI), yet its precise role remains elusive. This study aims to elucidate the potential molecular interactions between key genes associated with oxidative stress and their influence on TBI pathogenesis. METHODS: TBI dataset and oxidative stress-related genes sourced from Public databases. Differential expression analysis and machine learning models were executed to select key genes, which were further validated using receiver operating characteristic (ROC) curves. A nomogram was constructed for diagnostic prediction, and enrichment analysis explored pathways associated with key genes. Immune infiltration analysis and regulatory network construction were conducted. Molecular validation included RT-qPCR and Western blotting using rat brain tissue to assess gene and protein expression levels. RESULTS: In our study, we identified 400 differentially expressed genes (DEGs) between TBI and normal samples, including 20 oxidative stress-related genes. Machine learning analysis highlighted AKR1C2, QDPR, CYP3A5, CNTF, and PNPT1 as key genes with diagnostic potential (AUC > 0.6). Functional analysis revealed significant involvement of these genes in immune processes and metabolic regulation. Further, immune cell infiltration analysis showed notable differences in effector memory CD8 T cells. Molecular validation through RT-qPCR and Western blot confirmed the overexpression of key genes PNPT1 and QDPR in TBI models, substantiating their potential role in TBI pathology. CONCLUSION: Our study revealed the potential mechanisms of action for PNPT1 and QDPR in TBI, offering valuable insights into their roles in TBI pathology. These findings opened new avenues for future therapeutic strategies in TBI treatment.