IDAE: Integrative Data Analysis in Epilepsy

by A. Skupin, J. Klein and M. Esposito

Epilepsy is the fourth most common neurological disorder characterised by recurrent seizures and a rather heterogeneous clinical appearance with 30% of patients not responding to available drug treatments.

In the IDAE project, we address this challenge by an interdisciplinary and translational approach combining biomedical expertise and deep phenotyping in zebrafish models for epilepsy with advanced data analysis methods and mechanistic metabolic modelling. In particular, we will use interpretable machine-learning methods to integrate available heterogeneous data sets of brain dynamics, brain composition and metabolic profiles of diverse genetic zebrafish models to reveal underlying disease mechanisms which will identify a mechanistic genotype-phenotype relation and pave the way for improved patient stratification. For this purpose, we will re-analyse local field recordings of zebrafish models and microscopy time course data and integrate these seizure characteristics with brain composition deciphered from single-cell RNA sequencing data. The brain dynamics will be subsequently linked to specific metabolic activity identified by metabolomics and characterised by metabolic networks, which will then be used to perform mechanistic metabolic modelling to identify potential biomarker signatures. Based on the deep phenotyping in zebrafish, we will eventually apply the developed stratification strategy to human EEG data and provide metabolic profile biomarker candidates to be validated in future translational approaches.

Overall, the project will develop new approaches for mechanistic data integration in biomedicine and apply them to heterogeneous data sets on epilepsy to facilitate improved patient stratification.

Prof. Dr. Alexander SKUPIN	Prof. Dr. Jacques KLEIN	Prof. Dr. Massimiliano ESPOSITO