Abstracts

Rationale: Absence epilepsy (AE) is a form of genetic generalized epilepsy, characterised by absence seizures and EEG evidence of 3Hz spike-wave-discharges on a normal background. The molecular changes underpinning its development are not well understood. Current research has focused on single-omics interrogation of molecules and have yielded promising results. However, they lack the comprehensiveness to identify the numerous interactions underlying AE. In contrast, multi-omics integration can elucidate complex changes that occur during epileptogenesis. The Genetic Absence Epilepsy Rats from Strasbourg (GAERS) are a well-validated model of AE and its epileptic phenotype closely resembles that seen in humans, making it an excellent model to study AE. Here, we utilized a multi-omics approach to identify, integrate, and correlate AE-specific proteomic and metabolomic changes in GAERS compared to their non-epileptic control (NEC) counterparts with seizure expression, depressive and anxiety outcomes to identify any enriched pathways that may play a role in AE development.

Methods: EEG electrodes were implanted in GAERS (n=6) and NEC rats (n=6), and 24 hours of EEG were recorded 10 days after implantation. The total number and duration of seizures were quantified. Behavioural testing for anxiety (open field) and depression (sucrose preference) were then conducted. Rats were euthanized, cortical and thalamic tissues were harvested and subjected to liquid chromatography coupled to tandem-mass spectrometry (LC-MS/MS) for untargeted proteomic and metabolomic analyses. Linear analysis was conducted on the datasets to identify differences in the expression and abundance of proteins and metabolites. The two datasets were scaled and concatenated into a single multi-omic matrix, weighted correlation network analysis (WCGNA) was performed to identify any enriched pathways that were significantly correlated with seizure and behavioural outcomes.

Results: Integration of proteomic and metabolomic data with seizure and behavioural outcomes identified 22 distinct protein-metabolite modules with varying degrees of correlation to the GAERS compared to NEC in each brain region. Functional enrichment analysis of these modules identified numerous enriched pathways that were common between both regions, such as lysine degradation (cortical p=7.88E-05, thalamic p=8.29E-06) and aminoacyl-tRNA biosynthesis (cortical p=1.38-06, thalamic p=8.95E-05). These were significantly correlated with the GAERS epileptic and behavioural phenotype, indicating that there may be common pathways affecting both sites that play a role in the development of AE. Within these pathways, proteins such as L-lysine and L-arginine were also identified in both the cortical and thalamic network.

Conclusions: This study has identified several biological pathways that are potentially involved in the development of AE. Thus, the use of our novel systems biology approach allows for a more accurate identification of causal pathways which could be targeted with precise therapies.

Funding: Please list any funding that was received in support of this abstract.: N/A.