Cerebrospinal fluid metabolites as potential biomarkers for epilepsy: Insights from genome-wide association studies.

Abstract

Objectives: While metabolic imbalances have been observed in individuals with epilepsy, the direct involvement of specific metabolites in the development of the condition remains underexplored. A comprehensive analysis of the causality between cerebrospinal fluid metabolites (CSF) and epilepsy is pivotal in discovering innovative therapeutic interventions and prophylactic approaches.

Methods: Summary data from genome-wide association studies (GWAS) of CSF metabolites and epilepsy subtypes were obtained separately. A total of 338 CSF metabolites were investigated as exposures, and 11 epilepsy phenotypes were examined as the outcomes. A two sample Mendelian randomization (MR) approach was utilized to explore the causal influence of these metabolites on epilepsy. Causality was primarily estimated through inverse variance weighted (IVW) analysis, complemented by a range of sensitivity analyses to ensure result stability. Additionally, reverse MR analysis was performed to explore the possibility of bidirectional causality.

Results: The IVW method, reinforced by sensitivity analyses, pinpointed 17 CSF metabolites with causal implications for six epilepsy phenotypes. After False Discovery Rate (FDR) multiple testing correction, two metabolites (Methylmalonate and Gamma-glutamyl-alpha-lysine) were found to have robust causal links to epilepsy (p < 0.05 and FDR<0.05). The other 15 metabolites exhibited suggestive evidence of a causal association (p < 0.05 and FDR>0.05).

Significance: This study highlights CSF metabolites that could serve as valuable biomarkers and may be critical in developing targeted treatments and preventing epilepsy.

Plain language summary: This study explores how certain chemicals in the brain fluid might influence the development of epilepsy, aiming to find new ways to treat or prevent it. Researchers looked at the relationship between 338 cerebrospinal fluid metabolites and 11 types of epilepsy using genetic data. They found that 17 of these chemicals could potentially cause six types of epilepsy. Two of these chemicals were strongly linked to epilepsy, suggesting they could be important for creating specific treatments or prevention strategies.