Epilepsy is the most common chronic neurological disorder, affecting ~70 million individuals worldwide. However, approximately one-third of the patients are refractory to epilepsy medication. Of note, 100% of patients with genetic epilepsy who are resistant to the traditional drug, valproic acid (VPA), are also refractory to the other anti-epileptic drugs. The aim of the present study was to compare the transcriptomes in VPA responders and non-responders, to explore the mechanism of action of VPA and identify possible biomarkers to predict VPA resistance. Thus, RNA-seq was employed for transcriptomic analysis, differentially expressed genes (DEGs) were analyzed using Cuffdiff software and the DAVID database was used to infer the functions of the DEGs. A protein-protein interaction network was obtained using STRING and visualized with Cytoscape. A total of 389 DEGs between VPA-responsive and non-responsive pediatric patients were identified. Of these genes, 227 were upregulated and 162 were downregulated. The upregulated DEGs were largely associated with cytokines, chemokines and chemokine receptor-binding factors, whereas the downregulated DEGs were associated with cation channels, iron ion binding proteins, and immunoglobulin E receptors. In the pathway analysis, the toll-like receptor signaling pathway, pathways in cancer, and cytokine-cytokine receptor interaction were mostly enriched by the DEGs. Furthermore, three modules were identified by protein-protein interaction analysis, and the potential hub genes, chemokine (C-C motif) ligand 3 and 4, chemokine (C-X-C motif) ligand 9, tumor necrosis factor-α and interleukin-1β, which are known to be closely associated with epilepsy, were identified. These specific chemokines may participate in processes associated with VPA resistance and may be potential biomarkers for monitoring the efficacy of VPA.
Keywords: RNA-seq; biomarkers; efficacy; valproic acid.