Abstract
OBJECTIVE: Observational studies have shown an association between COVID-19 and epilepsy. However, causality remains unproven. This study aimed to investigate the causative effect of genetically predicted COVID-19 phenotypes on epilepsy risk using a two-sample Mendelian randomization (MR) analysis. METHODS: We retrieved summary-level datasets for three COVID-19 phenotypes (COVID-19 susceptibility, COVID-19 hospitalization, and COVID-19 severity) and epilepsy from the genome-wide association studies conducted by the COVID-19 Host Genetics Initiative (COVID-19 HGI) and International League Against Epilepsy (ILAE) consortium, respectively. To analyze the final results, nine MR analytic methods were utilized. The inverse-variance weighted (IVW) method was chosen as the primary approach for data analysis to evaluate the potential causal effect. Other MR analytic methods (MR-Egger regression, weighted median estimator, mode based-estimator, and MR-PRESSO) were used as a supplement to IVW to ensure the robustness of the results. RESULTS: The IVW approach demonstrated no causal association between any genetically predicted COVID-19 phenotype and the risk of epilepsy [COVID-19 susceptibility: odds ratio (OR) = 0.99, 95% confidence interval (CI) = 0.86-1.14, p = 0.92; COVID-19 hospitalization: OR = 1.00, 95% CI = 0.96-1.04, p = 0.95; COVID-19 severity: OR = 0.99, 95% CI = 0.96-1.01, p = 0.25]. Other MR complementary methods revealed consistent results. Additionally, no evidence for heterogeneity and horizontal pleiotropy was found. SIGNIFICANCE: This MR study revealed no genetically predicted causal relationship between COVID-19 phenotypes and epilepsy.