ObjectiveExplore the mechanism of action of Kruppel-like factor 4 (KLF4) in the oxidative damage model of hippocampal neurons in mice induced by glutamate. MethodsTo clarify the role of KLF4 and glutamate in the oxidative toxicity of epilepsy, the mouse hippocampal neuron cell line (HT22) was adopted, and a neuronal death excitotoxicity cell model was formed by induction with glutamate as the in vitro epilepsy experimental model. The expression level of KLF4 was detected by Real-Time PCR. HT22 cells were transfected with KLF4-specific siRNA, and the experiments were grouped as follows: Ctrl group, Glu group, Glu + siKLF4-1 group, and Glu + siKLF4-2 group. The cell viability of each group was detected by the CCK8 method. ResultsKLF4 was significantly increased in the epilepsy model of HT22 cells induced by glutamate, while downregulation of KLF4 improved the proliferation and viability of neurons in the epilepsy model of HT22 cells induced by glutamate. ConclusionIn the hippocampal neuron cells of epileptic mice, KLF4 is highly expressed. The downregulation of KLF4 improves the proliferation function and vitality of glutamate-induced HT22 cells, indicating that KLF4 may contribute to the occurrence and development of epilepsy by participating in the regulation of oxidative stress responses.
ObjectiveUbiquitination-mediated disruption of protein homeostasis can affect neuronal excitability and synaptic function, processes that are closely linked to the pathogenesis of epilepsy. The study aims to identify ubiquitination-related genes and explore their potential molecular mechanisms and diagnostic value. MethodsPeripheral blood transcriptome data of epilepsy patients and healthy controls were obtained from the Gene Expression Omnibus (GEO). The limma package was used to identify differentially expressed genes (DEGs). These DEGs were then intersected with a set of ubiquitination-related genes (URGs) to obtain differentially expressed ubiquitination-related genes (DE-URGs). Enrichment analyses of these genes were performed to explore their potential biological functions and underlying molecular mechanisms. The Least Absolute Shrinkage and Selection Operator (LASSO) regression and Receiver Operating Characteristic (ROC) curve analysis were used to identify key genes with diagnostic potential. A combined diagnostic index model was constructed based on the selected genes, and its cross-tissue generalizability was validated in a brain tissue transcriptome dataset. The hTFtarget database was used to predict transcription factors that may interact with DE-URGs, and a visualized regulatory network was constructed. ResultsDifferential expression analysis identified 930 DEGs, and after intersecting with URGs, 57 DE-URGs were obtained. Enrichment analysis showed significant enrichment of these genes in protein ubiquitination modification, immune inflammatory signaling pathways, and pathways related to neurodegenerative diseases. The LASSO regression identified 15 ubiquitination-related genes with diagnostic potential, and the combined diagnostic model based on these genes achieved an AUC of 0.965 in the training set. In the brain tissue samples, the combined index model achieved an AUC of 0.929 in the validation set, demonstrating good cross-tissue generalizability. A total of 125 transcription factors were predicted to potentially interact with the DE-URGs. ConclusionAbnormal expression of ubiquitination-related genes is observed in the peripheral blood of patients with epilepsy. The imbalance of ubiquitination function may play a key role in the pathogenesis of epilepsy. The combined index model based on 15 ubiquitination-related genes exhibits high diagnostic efficacy and cross-tissue stability, which provides new candidate molecules for the screening of potential biomarkers and the early diagnosis of epilepsy