Genetic relationship between epilepsy and mental disorders: A comprehensive GWAS analysis

Rena Abudusalamu; Aierpati Maimaiti; Wenjuan Han; Xixian Wang; Tengfei Jiao; Dengfeng Han; Lei Jiang

doi:10.1016/j.yebeh.2025.110500

Genetic relationship between epilepsy and mental disorders: A comprehensive GWAS analysis

Epilepsy Behav. 2025 Jun 2:171:110500. doi: 10.1016/j.yebeh.2025.110500. Online ahead of print.

Authors

Rena Abudusalamu¹, Aierpati Maimaiti², Wenjuan Han², Xixian Wang², Tengfei Jiao³, Dengfeng Han⁴, Lei Jiang⁵

Affiliations

¹ First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Xinshi District, Urumqi, Xinjiang 830054, China.
² Department of Neurosurgery Centre, First Affiliated Hospital of Xinjiang Medical University No. 137 Liyushan South Road, Xinshi District, Urumqi, Xinjiang 830054, China.
³ Karamay Central Hospital of Xinjiang, No. 67 Zhungeer Road, Karamay District, Karamay City, Xinjiang Uygur Autonomous Region 834000, China.
⁴ Department of Neurology, First Affiliated Hospital of Xinjiang Medical University, China. Electronic address: DengfengHan_12@163.com.
⁵ Department of Neurosurgery Centre, First Affiliated Hospital of Xinjiang Medical University, China. Electronic address: jiangleidr@126.com.

PMID: 40460570
DOI: 10.1016/j.yebeh.2025.110500

Abstract

Objective: Epilepsy (Epi) frequently co-occurs with various mental disorders; however, the genetic correlation and potential shared genetic mechanisms between them remain unclear. This study aims to systematically analyze the genetic correlation between Epi and various mental disorders by integrating genome-wide association study (GWAS) data, and to explore potential shared genetic mechanisms.

Methods: We employed Meta-Analysis Helper (METAL) to integrate GWAS data from multiple studies, thereby enhancing statistical power. Various genetic statistical methods were used, including global genetic correlation analysis Genetic Novelty Analysis (GNOVA) and high-definition likelihood (HDL), novel local genetic correlation analysis (LAVA), GWAS polygenic analysis (MTAG), and Summary-based Mendelian Randomization (SMR), to assess the genetic correlation between Epi and mental disorders and to identify relevant genetic loci. Functional enrichment analysis was used to explore the biological pathways associated with these shared genetic variants.

Results: Our analysis revealed significant global genetic correlations between Epi and several mental disorders, including Anxiety Disorder (ANX), Bipolar Disorder (BD), Major Depressive Disorder (MDD), and Schizophrenia (SCZ). Through LAVA analysis, we identified several genetic loci with significant shared genetic effects, such as 13q32.1, 2p16.1, and others. Additionally, MTAG and SMR analyses revealed multiple key genes with pleiotropic effects, which may play crucial roles in the onset of these disorders. Functional enrichment analysis indicated that the associated genes are primarily involved in pathways related to neurodevelopment, synaptic function, and immune regulation.

Significance: This study reveals the shared genetic background between Epi and mental disorders, providing new insights into the genetic mechanisms underlying such comorbidities. Future research may further validate these findings and explore their potential applications in personalized medicine and precision therapy.

Keywords: Epilepsy (Epi); Genome-wide association study (GWAS); Mental disorders; Novel local genetic correlation analysis (LAVA); Shared genetic inheritance.