Cui Changmeng, Xu Biao, Liu Hui, Wang Changshui, Zhang Tao, Jiang Pei, Feng Lei
Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, Shandong, 272000, People's Republic of China.
Translational Pharmaceutical Laboratory, Jining First People's Hospital, Shandong First Medical University, Jining, Shandong, 272000, People's Republic of China.
J Inflamm Res. 2024 Dec 11;17:10835-10848. doi: 10.2147/JIR.S491290. eCollection 2024.
Traumatic brain injury (TBI) is associated with disturbances in energy metabolism. This study aimed to construct a lncRNA-miRNA-mRNA network through bioinformatics methods to explore energy metabolism-related genes in the pathogenesis of TBI.
Data from datasets GSE171718, GSE131695, and GSE223245 obtained from the Gene Expression Omnibus, were analyzed to identify differentially expressed (DE) genes. Regulatory relationships were investigated through miRDB, miRTarBase, and TargetScan, thereby forming a lncRNA-miRNA-mRNA network. The Molecular Signatures Database (MSigDB) was utilized to identify energy metabolism-related genes, and a protein-protein interaction (PPI) network was established through the STRING database. Functional annotation and enrichment analysis were conducted using GO and KEGG. The TBI mouse model was established to detect the expression levels of , and in brain tissues.
emerged as the key DE gene linked to energy metabolism in TBI, demonstrating a negative correlation with miR-218-5p and being associated with moderate unconsciousness and female patients. The PPI network revealed interactions with proteins associated with cell death, sphingolipid metabolism, and neurodegenerative diseases such as Alzheimer's disease. In , and mRNA levels were significantly lower in TBI mice.
In summary, represents a crucial metabolic gene in the progression of TBI. It potentially provides a new therapeutic target for metabolic disorders caused by traumatic brain injury (TBI) and holds significant theoretical value for further research.
创伤性脑损伤(TBI)与能量代谢紊乱有关。本研究旨在通过生物信息学方法构建lncRNA-miRNA-mRNA网络,以探索TBI发病机制中与能量代谢相关的基因。
分析从基因表达综合数据库获得的数据集GSE171718、GSE131695和GSE223245的数据,以鉴定差异表达(DE)基因。通过miRDB、miRTarBase和TargetScan研究调控关系,从而形成lncRNA-miRNA-mRNA网络。利用分子特征数据库(MSigDB)鉴定与能量代谢相关的基因,并通过STRING数据库建立蛋白质-蛋白质相互作用(PPI)网络。使用GO和KEGG进行功能注释和富集分析。建立TBI小鼠模型以检测脑组织中 、 和 的表达水平。
成为与TBI中能量代谢相关的关键DE基因,与miR-218-5p呈负相关,且与中度昏迷和女性患者有关。PPI网络显示 与细胞死亡、鞘脂代谢以及阿尔茨海默病等神经退行性疾病相关的蛋白质存在相互作用。在 中,TBI小鼠的 和 mRNA水平显著降低。
总之, 在TBI进展中代表一个关键的代谢基因。它可能为创伤性脑损伤(TBI)引起的代谢紊乱提供新的治疗靶点,对进一步研究具有重要的理论价值。