Multi-Scale Genetic and Transcriptomic Analyses Identify Druggable Targets for Epilepsy

Abstract

Background

Epilepsy 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.

Methods

We 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.

Results

Seven 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.

Conclusions

Multi-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.

Keywords

Epilepsy / Expression Quantitative Trait Loci (eQTL) / Genome-wide association study (GWAS) / Single-cell RNA sequencing (scRNA-seq) / FGFR3 / HAGH

References

[1] Fang Y, Si X, Wang J, et al. . Alzheimer disease and epilepsy: a Mendelian randomization study. Neurology., 2023, 101(4): e399-e409

[2] Luo Y, Wu PF, Zhou J, et al. . Aggravation of seizure-like events by hydrogen sulfide: involvement of multiple targets that control neuronal excitability. CNS Neurosci Ther., 2014, 20(5): 411-419

[3] Leu C, Avbersek A, Stevelink R, et al. . Genome-wide association meta-analyses of drug-resistant epilepsy. eBioMedicine., 2025, 115: 105675

[4] Organization WH. Epilepsy: A public health imperative, 2023, Geneva. World Health Organization

[5] International League Against Epilepsy Consortium on Complex Epilepsies. GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture. Nat Genet., 2023, 55(9): 1471-1482

[6] Jehi L. Advances in therapy for refractory epilepsy. Annu Rev Med., 2025, 76(1): 389-402

[7] Thijs RD, Surges R, O’Brien TJ, et al. . Epilepsy in adults. Lancet., 2019, 393(10172): 689-701

[8] Manzoni C, Kia DA, Ferrari R, et al. . Genome-wide analyses reveal a potential role for the MAPT, MOBP, and APOE loci in sporadic frontotemporal dementia. Am J Hum Genet., 2024, 111(7): 1316-1329

[9] Chia R, Ray A, Shah Z, et al. . Genome sequence analyses identify novel risk loci for multiple system atrophy. Neuron., 2024, 112(13): 2142-2156.e5

[10] Mu J, Cao C, Gong Y, et al. . Relationship between inflammation/immunity and epilepsy: a multi-omics Mendelian randomization study integrating GWAS, eQTL, and mQTL data. Epilepsy Behav., 2024, 161 110112

[11] Ge YJ, Ou YN, Deng YT, et al. . Prioritization of drug targets for neurodegenerative diseases by integrating genetic and proteomic data from brain and blood. Biol Psychiatry., 2023, 93(9): 770-779

[12] Bryois J, Calini D, MacNair W, et al. . Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nat Neurosci., 2022, 25(8): 1104-1112

[13] Fujita M, Gao Z, Zeng L, et al. . Cell subtype-specific effects of genetic variation in the Alzheimer’s disease brain. Nat Genet., 2024, 56(4): 605-614

[14] Qi T, Wu Y, Fang H, et al. . Genetic control of RNA splicing and its distinct role in complex trait variation. Nat Genet., 2022, 54(9): 1355-1363

[15] François L, Romagnolo A, Luinenburg MJ, et al. . Identification of gene regulatory networks affected across drug-resistant epilepsies. Nat Commun., 2024, 15(1): 2180

[16] Chen ZP, Wang S, Zhao X, et al. . Lipid-accumulated reactive astrocytes promote disease progression in epilepsy. Nat Neurosci., 2023, 26(4): 542-554

[17] Zhu Z, Zhang F, Hu H, et al. . Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet., 2016, 48(5): 481-487

[18] Giambartolomei C, Vukcevic D, Schadt EE, et al. . Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet., 2014, 10(5): e1004383

[19] Yarmolinsky J, Robinson JW, Mariosa D, et al. . Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis. eBioMedicine., 2024, 100: 104991

[20] Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol., 2014, 15(12): 550

[21] Yu G, Wang LG, Han Y, et al. . clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS., 2012, 16(5): 284-287

[22] Robin X, Turck N, Hainard A, et al. . pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics., 2011, 12: 77

[23] Satija R, Farrell JA, Gennert D, et al. . Spatial reconstruction of single-cell gene expression data. Nat Biotechnol., 2015, 33(5): 495-502

[24] Chen ZP, Zhao X, Wang S, et al. . GABA-dependent microglial elimination of inhibitory synapses underlies neuronal hyperexcitability in epilepsy. Nat Neurosci., 2025, 28(7): 1404-1417

[25] Jin S, Guerrero-Juarez CF, Zhang L, et al. . Inference and analysis of cell-cell communication using Cell Chat. Nat Commun., 2021, 12(1): 1088

[26] Franz M, Rodriguez H, Lopes C, et al. . GeneMANIA update 2018. Nucleic Acids Res., 2018, 46(W1): W60-W64

[27] Freshour SL, Kiwala S, Cotto KC, et al. . Integration of the Drug-Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts. Nucleic Acids Res., 2021, 49(D1): D1144-D1151

[28] Finan C, Gaulton A, Kruger FA, et al. . The druggable genome and support for target identification and validation in drug development. Sci Transl Med., 2017, 9(383): eaag1166

[29] Mirza N, Appleton R, Burn S, et al. . Genetic regulation of gene expression in the epileptic human hippocampus. Hum Mol Genet., 2017, 26(9): 1759-1769

[30] Shimada T, Yoshida T, Yamagata K. Neuritin mediates activity-dependent axonal branch formation in part via FGF signaling. J Neurosci., 2016, 36(16): 4534-4548

[31] Bernardo P, Budetta M, Aliberti F, et al. . Temporal lobe malformations, focal epilepsy, and FGFR3 mutations: a non-causal association?. Neurol Sci., 2021, 42(5): 2063-2067

[32] Huse JT, Snuderl M, Jones DT, et al. . Polymorphous low-grade neuroepithelial tumor of the young (PLNTY): an epileptogenic neoplasm with oligodendroglioma-like components, aberrant CD34 expression, and genetic alterations involving the MAP kinase pathway. Acta Neuropathol., 2017, 133(3): 417-429

[33] Bangel FN, Yamada K, Arai M, et al. . Genetic analysis of the glyoxalase system in schizophrenia. Prog Neuro Psychopharmacol Biol Psychiatry., 2015, 59: 105-110

[34] Mohandas N, Loke YJ, Hopkins S, et al. . Evidence for type-specific DNA methylation patterns in epilepsy: a discordant monozygotic twin approach. Epigenomics., 2019, 11(8): 951-968

[35] Song N, Fang Y, Zhu H, et al. . Kir6.2 is essential to maintain neurite features by modulating PM20D1-reduced mitochondrial ATP generation. Redox Biol., 2021, 47: 102168

[36] Wang R, Wang Q. Identification and external validation of a transcription factor-related prognostic signature in pediatric neuroblastoma. J Oncol., 2021, 2021: 1370451

[37] Peng J, Yang S, Zhou C, et al. . Identification of common biomarkers in diabetic kidney disease and cognitive dysfunction using machine learning algorithms. Sci Rep., 2024, 14(1): 22057

[38] Zheng C, Wei Y, Zhang Q, et al. . Multiomics analyses reveal DARS1-AS1/YBX1–controlled posttranscriptional circuits promoting glioblastoma tumorigenesis/radioresistance. Sci Adv., 2023, 9(31): eadf3984

[39] Zha C, Farah CA, Holt RJ, et al. . Biallelic variants in the small optic lobe calpain CAPN15 are associated with congenital eye anomalies, deafness and other neurodevelopmental deficits. Hum Mol Genet., 2020, 29(18): 3054-3063

[40] Mor-Shaked H, Salah S, Yanovsky-Dagan S, et al. . Biallelic deletion in a minimal CAPN15 intron in siblings with a recognizable syndrome of congenital malformations and developmental delay. Clin Genet., 2021, 99(4): 577-582

[41] Wang Y, Zhou T, Wan J, et al. . Comparative transcriptome analysis reveals a regulatory network of microRNA-29b during mouse early embryonic development. Oncotarget., 2016, 7(33): 53772-53782

[42] McDermott LA, Higgins B, Simcox M, et al. . Biological evaluation of a multi-targeted small molecule inhibitor of tumor-induced angiogenesis. Bioorg Med Chem Lett., 2006, 16(7): 1950-1953

Funding

Natural Science Foundation of Hubei Province(2023AFB040)

Hubei Provincial Forensic Science Research Project(202406)

Shanghai Key Lab of Forensic Medicine(KF202311)

Hubei Key Laboratory of the Forensic Science(KFKT2023003)

the Key R&D projects in Hubei Province(2023BCB133)

RIGHTS & PERMISSIONS

The Author(s), under exclusive licence to the Huazhong University of Science and Technology