Plasma proteomics in epilepsy: Network-based identification of proteins associated with seizures.

Purpose: Identification of potential biomarkers of seizures.

Methods: In this exploratory study, we quantified plasma protein intensities in 15 patients with recent seizures compared to 15 patients with long-standing seizure freedom. Using TMT-based proteomics we found fifty-one differentially expressed proteins.

Results: Network analyses including co-expression networks and protein-protein interaction networks, using the STRING database, followed by network centrality and modularity analyses revealed 22 protein modules, with one module showing a significant association with seizures. The protein-protein interaction network centered around this module identified a subnetwork of 125 proteins, grouped into four clusters. Notably, one cluster (mainly enriching inflammatory pathways and Gene Ontology terms) demonstrated the highest enrichment of known epilepsy-related genes.

Conclusion: Overall, our network-based approach identified a protein module linked with seizures. The module contained known markers of epilepsy and inflammation. The results also demonstrate the potential of network analysis in discovering new biomarkers for improved epilepsy management.