To implement new informatics tools for the clinical and genetic investigation of generalized epilepsies i.e. childhood absence epilepsy (CAE) and juvenile myoclonic epilepsy (JME).

Research with genetic epilepsy cohorts includes the management of large amounts of data. Since 1992, the Genetic Epilepsy StudieS Consortium (GENESS) has collected phenotype and genotype data on CAE and JME families from Los Angeles, CA (USA), Mexico, Honduras, El Salvador, Guatemala, Peru, Brazil, Spain, France, and Japan. This requires the use of informatics tools for storage, management and analysis to reach the goal of 1000 cases.

We created a platform using a microservices architecture with the open source server environment called NodeJS, a document-oriented database model using a MongoDB, ReactJS with Redux to build the client application, data encryption, and other security restrictions. We added artificial intelligence modules to enhance analysis capability. Then we entered data of 500 probands with JME, which were reanalyzed using the RapidMiner tool. Variables studied were age, gender, seizure types, age at onset of each type, trigger factors, EEG findings, family history, response to treatment and gene mutations. We used the pediatric age groups suggested by the National Institutes of Child Health and Human Development.

The system implemented can provide information management capacity and artificial intelligence modules for complex statistics. The system still needs to be more user-friendly and allow room for descriptive text. Implementation of a cloud service needs more cybersecurity for public use of data in the future. Examples of data analysis will be shown.

Our information management/analysis tool is a novel contribution to research in epilepsy genetics. It is a model of a metadata system that could help the public use of genetic data. This will help phenotype-genotype analysis and could speed gene discovery.

Funding: National Institutes of Health (1R01NS055057), VA Merit Review (5I01CX000743), UNITEC-Honduras.