Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China.
Department of Neurosurgery, Jinan University Affiliated 999 Brain Hospital, Guangzhou, China.
Brain Behav. 2024 Jun;14(6):e3602. doi: 10.1002/brb3.3602.
The causes and triggering factors of epilepsy are still unknown. The results of genome-wide association studies can be utilized for a phenome-wide association study using Mendelian randomization (MR) to identify potential risk factors for epilepsy.
This study utilizes two-sample MR analysis to investigate whether 316 phenotypes, including lifestyle, environmental factors, blood biomarker, and more, are causally associated with the occurrence of epilepsy. The primary analysis employed the inverse variance weighted (IVW) model, while complementary MR analysis methods (MR Egger, Wald ratio) were also employed. Sensitivity analyses were also conducted to evaluate heterogeneity and pleiotropy.
There was no evidence of a statistically significant causal association between the examined phenotypes and epilepsy following Bonferroni correction (p < 1.58 × 10) or false discovery rate correction. The results of the MR analysis indicate that the frequency of tiredness or lethargy in the last 2 weeks (p = 0.042), blood uridine (p = 0.003), blood propionylcarnitine (p = 0.041), and free cholesterol (p = 0.044) are suggestive causal risks for epilepsy. Lifestyle choices, such as sleep duration and alcohol consumption, as well as biomarkers including steroid hormone levels, hippocampal volume, and amygdala volume were not identified as causal factors for developing epilepsy (p > 0.05).
Our study provides additional insights into the underlying causes of epilepsy, which will serve as evidence for the prevention and control of epilepsy. The associations observed in epidemiological studies may be partially attributed to shared biological factors or lifestyle confounders.
癫痫的病因和触发因素仍不清楚。全基因组关联研究的结果可用于使用孟德尔随机化(MR)进行表型全基因组关联研究,以确定癫痫的潜在危险因素。
本研究采用两样本 MR 分析,探讨 316 种表型(包括生活方式、环境因素、血液生物标志物等)是否与癫痫的发生存在因果关系。主要分析采用逆方差加权(IVW)模型,同时还采用了补充性 MR 分析方法(MR Egger、Wald 比)。还进行了敏感性分析以评估异质性和多效性。
在 Bonferroni 校正(p < 1.58×10)或错误发现率校正后,没有证据表明所检查的表型与癫痫之间存在统计学上显著的因果关联。MR 分析的结果表明,过去 2 周内疲劳或嗜睡的频率(p = 0.042)、血液尿苷(p = 0.003)、血液丙酰肉碱(p = 0.041)和游离胆固醇(p = 0.044)与癫痫的发生呈因果关系。生活方式选择,如睡眠时间和饮酒,以及生物标志物,如类固醇激素水平、海马体积和杏仁核体积,未被确定为癫痫发病的因果因素(p > 0.05)。
本研究为癫痫的潜在病因提供了新的认识,为癫痫的预防和控制提供了依据。在流行病学研究中观察到的关联可能部分归因于共同的生物学因素或生活方式混杂因素。