Omics-based Precision Medicine of Epilepsy

Epilepsy is a major disease of the nervous system (WHO, 2015), as well as the second most common neural disease. It has been recorded that there have been 65 million epilepsy patients all over the world, more than 10 million in China, resulted in high morbidity, high mortality, heavy social and social psychological burden. Due to complex etiology, which genetic playing a large part for 70%-80%, easy to recurrent, as well as various seizure types, a great heterogeneity in clinical manifestation, epilepsy is difficult to treat in general, at least 33% patients. At present, It's still a big challenge in early warning, choice of treatment, efficacy and severe adverse reaction rate, prognosis assessment. Lack of precise diagnosis based genetic and molecular bio-markers for treatment are the main key points. Recently, clinical phenotype classifications of epilepsy have been refined, the exist researches had made a progress in gene mutation mechanism and targeted therapy, which pushed epilepsy being another disease could be precise treated after tumor. It's sure to provide a breakthrough for another neural diseases if epilepsy precise treatment project are successful.

Research projects: Part 1: Based on already existed large samples of epilepsy clinical cases, choose 2,0000 non-acquired epilepsy patients for clinical general phenotype and middle phenotype(EEG and MRI) data collection to further multi-dimensional standardization measure and evaluate. Through metabolic detection to define micro-phenotype. Establish a standardized clinical and biological samples database. Part 2: By NGS technology to sequence for all cases, including family members, then require genotype. To test brain tissue DNA somatic mutation, which MRI negative and had an operation. To verify the newly discovered pathogenic candidate genes and carry on functional studies. Finally, to draw epileptic genetic mutations mapping in Chinese people. Part 3: Integrated clinical and genetic epilepsy phenotypic data, combined with neural EEG and image bitmap data points for bio-markers analysis, included early warning, classification of diagnosis, curative effect prediction and epilepsy con-morbidity disease.