Identification of serum miR-378 and miR-575 as diagnostic indicators and predicting surgical prognosis in human epilepsy
Abstract
Objectives: Epilepsy (EP) was a common neurological disorder characterized by excessive abnormal synchronization of neuronal discharges in the brain due to chronic recurrent seizures of multiple etiologies. Recently, a variety of miRNAs were found to be dysregulated, participating in the occurrence and development of various diseases, including EP. This study mainly determines the abnormal expression of miR-378 and miR-575 in EP patients to validate their potential in distinguishing EP from healthy controls.
Methods: Clinical parameters in all participants were recorded. qRT-PCR analysis was applied to determine the expressions of miR-378 and miR-575 in EP patients and healthy volunteers. The student’s t-test and chi-square test was applied to analyze clinical indicators between EP patients and controls. According to the surgical outcome, EP patients were further divided into Engel I~IV EP. The potentials of miR-378 and miR-575 in discriminating EP from healthy participants and predicting surgical prognosis were calculated by receiver operating characteristic (ROC) analysis.
Results: There were no significant differences in age, gender, smoking history, and BMI index between EP patients and healthy controls. miR-378 and miR-575 were significantly declined in Engel I~II and III~IV EP patients in comparison to healthy participants. Moreover, miR-378 and miR-575 displayed high sensitivity, specificity, and accuracy in discriminating EP patients from healthy controls and predicting surgical outcome. Moreover, after surgical treatment, miR-378 and miR-575 levels were increased compared with those at admission, suggesting their potentials in treatment response.
Conclusion: miR-378 and miR-575 could be utilized as novel and non-invasive serum biomarkers in discriminating EP from healthy controls and predicting surgical outcome, shedding new insights on epileptogenesis and EP treatment.
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Copyright (c) 2021 XiuXiu Li, ZhiQing Gao, Mei Ling Ma, Li Li, ShiFeng Guo

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