Metabolic Reprogramming in Spinal Cord Injury and Analysis of Potential Therapeutic Targets - Chen, Xiangjun; Wang, Juan; Chan, Peiran; Zhu, Qian; Zhu, Ziyan; Zheng, Mingming; Chen, Xinyi; Wu, Haozhen; Cui, Min; Zhang, Yongjie (Journal of molecular neuroscience, 2025)
Spinal cord injury (SCI) is a critical neurological disorder that frequently leads to permanent disability, profoundly affecting the quality of life of individuals with SCI. In this research, we examined the varied expression of genes associated with metabolic reprogramming–related genes in SCI. By employing the Gene Expression Omnibus datasets GSE5296 and GSE47681, 1001 differentially expressed genes (DEGs) were identified through the limma R package. Among these, 871 and 130 genes were upregulated and downregulated, respectively. A subset of 10 metabolic reprogramming–related differentially expressed genes (MRRDEGs) was recognized as key players in metabolic reprogramming. Analyses of enrichment performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes indicated that the identified MRRDEGs predominantly participated in processes related to pyruvate metabolism and carbohydrate degradation. Nine hub genes were discerned using a protein–protein interaction network. Subsequently, an SCI mouse model was established using the LISA SCI modeling device, and preliminary validation was conducted through quantitative real-time PCR experiments at various time points after SCI, specifically on days 1, 3, and 7, suggesting their central role in SCI. Receiver operating characteristic curve analysis indicated that these MRRDEGs could be used to diagnose SCI. The CIBERSORT algorithm analysis of immune infiltration identified an inverse relationship between M0 and M2 macrophages. Furthermore, a positive relationship was observed between Ucp2 and M0 macrophages, underscoring their essential function in the immune response following SCI. These results highlight MRRDEGs’ importance in SCI and propose their potential roles as targets for therapeutic interventions. Graphical Abstract Using data from the public GEO database, we identified differentially expressed genes associated with metabolic reprogramming in spinal cord injury and successfully validated them through qPCR experiments.