ArticleCurrent medical science2026
Multi-Scale Genetic and Transcriptomic Analyses Identify Druggable Targets for Epilepsy.
Article in Current medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundEpilepsy is a common neurological disorder with high genetic heterogeneity and affects approximately 70 million people worldwide. Although several studies have combined Genome-Wide Association Studies (GWAS) with bulk expression quantitative trait loci (eQTLs) to explore epilepsy risk genes, the cellular context of genetic regulation remains insufficiently defined.
methodsWe integrated epilepsy GWAS data with brain bulk and single-cell eQTLs using summary-data-based Mendelian randomization (SMR) and Bayesian colocalization to identify causal genes. The identified genes were validated in an independent RNA-seq cohort of patients with refractory epilepsy. We then characterized cell-type specificity and intercellular signaling using single-cell RNA sequencing (scRNA-seq) and CellChat. Druggability and drug-repurposing analyses were performed using DSigDB to identify targeted therapeutic compounds for epilepsy.
resultsSeven epilepsy causal genes (FGFR3, PM20D1, ZNF564, HAGH, CAPN15, CCDC117 and DARS1-AS1) were identified, with FGFR3 and HAGH identified as druggable targets. FGFR3 was predominantly expressed in astrocytes and involved in an astrocyte-centered FGF2-FGFR signaling loop, whereas HAGH was enriched in neurons. DSigDB analysis highlighted the FGFR inhibitor, Ro-4396686, as the top candidate compound.
conclusionsMulti-scale integration of eQTL, GWAS and transcriptomic datasets reveals the genetic variants of epilepsy, with FGFR3-driven FGF signaling representing a principal molecular axis. This study reveals the cellular context of this disorder and highlights FGFR3 and HAGH as promising therapeutic targets.
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