Zhao Zhenxiang, Xing Na, Hou Lin
Department of Neurosurgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Department of Endocrinology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Epilepsia Open. 2025 Feb;10(1):233-242. doi: 10.1002/epi4.13101. Epub 2024 Nov 18.
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.
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.
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).
This study highlights CSF metabolites that could serve as valuable biomarkers and may be critical in developing targeted treatments and preventing epilepsy.
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.
虽然在癫痫患者中观察到了代谢失衡,但特定代谢物在该疾病发展中的直接作用仍未得到充分研究。全面分析脑脊液代谢物(CSF)与癫痫之间的因果关系对于发现创新的治疗干预措施和预防方法至关重要。
分别获取脑脊液代谢物和癫痫亚型的全基因组关联研究(GWAS)汇总数据。共研究了338种脑脊液代谢物作为暴露因素,并将11种癫痫表型作为结果进行检验。采用两样本孟德尔随机化(MR)方法来探究这些代谢物对癫痫的因果影响。因果关系主要通过逆方差加权(IVW)分析进行估计,并辅以一系列敏感性分析以确保结果的稳定性。此外,还进行了反向MR分析以探究双向因果关系的可能性。
在敏感性分析的强化下,IVW方法确定了17种脑脊液代谢物对六种癫痫表型具有因果影响。经过错误发现率(FDR)多重检验校正后,发现两种代谢物(甲基丙二酸和γ-谷氨酰-α-赖氨酸)与癫痫存在强烈的因果联系(p < 0.05且FDR < 0.05)。其他15种代谢物显示出因果关联的提示性证据(p < 0.05且FDR > 0.05)。
本研究突出了脑脊液代谢物可作为有价值的生物标志物,并且在开发针对性治疗方法和预防癫痫方面可能至关重要。
本研究探讨了脑脊液中的某些化学物质如何影响癫痫的发展,旨在寻找治疗或预防癫痫的新方法。研究人员利用基因数据研究了338种脑脊液代谢物与11种癫痫类型之间的关系。他们发现其中17种化学物质可能导致六种癫痫类型。其中两种化学物质与癫痫密切相关,表明它们对于制定特定的治疗方法或预防策略可能很重要。