Abstract DP249: Integrative Bioinformatics Analysis to Identify Molecular Mechanisms and Biomarkers of Post-Stroke Epilepsy

Introduction: Post-stroke epilepsy (PSE) is an important complication of stroke. We aimed to identify genomic associations and build a protein-protein interaction (PPI) network linking stroke- and epilepsy-related genes, using open-source databases for potential clinical insights. Methods: We searched and retrieved genomic data from the National Human Genome Research Institute-European Bioinformatics Institute Catalog, Ensembl Variant Effect Predictor, ClinVar, and Open Targets databases. We conducted PPI network analysis of proteins commonly identified between stroke and epilepsy using STRING 12 and Cytoscape 3.10.0. Network hub proteins were identified through four topological analyses using CytoHubba and functional clusters were determined using Molecular Complex Detection (MCODE). Functional enrichment analysis was performed with the Ingenuity Pathway Analysis tool. Enriched pathways were identified with a false discovery rate (FDR)-corrected p-value < 0.05, and pathways were ranked according to their FDR-corrected p-values. We used GEO RNA-seq expression datasets to validate the findings from GWAS and other databases. Results: The database search identified 3618 unique gene associations (930 for stroke, 2688 for epilepsy, and 115 common between stroke and epilepsy). The resulting PPI network of 115 common proteins contained 108 nodes (proteins) and 145 edges (interactions). The overlapping hub proteins in the PPI network included TK2, MT-ND1, MT-ND2, MT-ND4, MT-ND5, MT-ND6, MT-CO1, MT-CO2, MT-CYB, and POLG. We identified 5 functional clusters in our PPI network (Figure 1), mainly associated with neuroinflammation, oxidative phosphorylation, blood vessel development, mitochondrial matrix, and neuronal migration. Common proteins were enriched in pathways including brain development, neuroinflammation, mitochondrial complex, and oxidative phosphorylation. Of 115 common proteins, we validated 20 common proteins in RNA-seq expression datasets of patients with stroke and epilepsy. We validated 20 proteins associated with cerebrovascular dysfunction in patients with stroke and epilepsy (Figure 2) , and will report protein pathways associated with PSE. Conclusions: This comprehensive analysis identifies key hub proteins and indicates neuroinflammation’s role at the intersection of stroke and epilepsy. Our findings highlight potential biomarkers or therapeutic targets of PSE that warrant further investigation.