Epilepsy is a disorder that affects around 1% of the population. Approximately one third of patients do not respond to anti-convulsant drugs treatment. To understand the underlying biological processes involved in drug resistant epilepsy (DRE), a combination of proteomics strategies was used to compare molecular differences and enzymatic activities in tissue implicated in seizure onset to tissue with no abnormal activity within patients. Label free quantitation identified 17 proteins with altered abundance in the seizure onset zone as compared to tissue with normal activity. Assessment of oxidative protein damage by protein carbonylation identified additional 11 proteins with potentially altered function in the seizure onset zone. Pathway analysis revealed that most of the affected proteins are involved in energy metabolism and redox balance. Further, enzymatic assays showed significantly decreased activity of transketolase indicating a disruption of the Pentose Phosphate Pathway and diversion of intermediates into purine metabolic pathway, resulting in the generation of the potentially pro-convulsant metabolites. Altogether, these findings suggest that imbalance in energy metabolism and redox balance, pathways critical to proper neuronal function, play important roles in neuronal network hyperexcitability and can be used as a primary target for potential therapeutic strategies to combat DRE. Significance: Epileptic seizures are some of the most difficult to treat neurological disorders. Up to 40% of patients with epilepsy are resistant to first- and second-line anticonvulsant therapy, a condition that has been classified as refractory epilepsy. One potential therapy for this patient population is the ketogenic diet (KD), which has been proven effective against multiple refractory seizure types However, compliance with the KD is extremely difficult, and carries severe risks, including ketoacidosis, renal failure, and dangerous electrolyte imbalances. Therefore, identification of pathways disruptions or shortages can potentially uncover cellular targets for anticonvulsants, leading to a personalized treatment approach depending on a patient's individual metabolic signature.
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