Body mass index (BMI) is a crucial health indicator for obesity. With the progression of socio-economic status and alterations in lifestyle, an increasing number of global populations are at risk of obesity. Given the complexity and severity of neurological diseases, early identification of risk factors is vital for the diagnosis and prognosis of such diseases. In this study, we employed Mendelian randomization (MR) analysis utilizing the most comprehensive genome-wide association study (GWAS) data to date. We selected single nucleotide polymorphisms (SNPs) that are unaffected by confounding factors and reverse causality as instrumental variables. These variables were used to evaluate the genetic and causal relationships between Body Mass Index (BMI) and various neurological diseases, including Parkinson’s Disease (PD), Alzheimer's Disease (AD), Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Ischemic Stroke (IS), and Epilepsy (EP). The Inverse Variance Weighted (IVW) analysis indicated that there was no significant causal relationship between Body Mass Index (BMI) indicators and PD (P-value = 0.511), AD (P-value = 0.076), ALS (P-value = 0.641), EP (P-value = 0.380). However, a causal relationship was found between BMI indicators and MS (P-value = 0.035), and IS (P-value = 0.000), with the BMI index positively correlated with the risk of both diseases. The Cochran’s Q test for MR-IVW showed no heterogeneity in the MR analysis results between the BMI index and the neurological diseases (P > 0.05). The Egger intercept test for pleiotropy revealed no horizontal pleiotropy detected in any of the neurological diseases studied (P > 0.05). It was found that there was no causal relationship between BMI and PD, AD, ALS, EP, and a genetic causal association with MS, and IS. Meanwhile, the increase in BMI can lead to a higher risk of MS and IS, which reveals the critical role of obesity as a risk factor for specific neurological diseases in the pathogenesis of the diseases.

体重指数（BMI）是肥胖的重要健康指标。随着社会经济地位的进步和生活方式的改变，全球越来越多的人口面临肥胖的风险。鉴于神经系统疾病的复杂性和严重性，早期识别危险因素对于此类疾病的诊断和预后至关重要。在这项研究中，我们采用孟德尔随机化 (MR) 分析，利用迄今为止最全面的全基因组关联研究 (GWAS) 数据。我们选择不受混杂因素和反向因果关系影响的单核苷酸多态性（SNP）作为工具变量。这些变量用于评估体重指数 (BMI) 与各种神经系统疾病之间的遗传和因果关系，包括帕金森病 (PD)、阿尔茨海默病 (AD)、肌萎缩侧索硬化症 (ALS)、多发性硬化症 (MS)、缺血性脑病中风 (IS) 和癫痫 (EP)。逆方差加权（IVW）分析表明，体重指数（BMI）指标与PD（P值=0.511）、AD（P值=0.076）、ALS（P值=0.641）之间不存在显着因果关系。 ），EP（P值 = 0.380）。然而，BMI指标与MS（ P值=0.035）和IS（P值=0.000）之间存在因果关系，BMI指数与两种疾病的风险呈正相关。 MR-IVW Cochran's Q 检验显示 BMI 指数与神经系统疾病之间的 MR 分析结果无异质性（P  > 0.05）。多效性的 Egger 截距检验显示，在所研究的任何神经系统疾病中均未检测到水平多效性（P  > 0.05）。结果发现，BMI 与 PD、AD、ALS、EP 之间不存在因果关系，与 MS 和 IS 之间存在遗传因果关系。同时，BMI的增加会导致MS和IS的风险增加，这揭示了肥胖作为特定神经系统疾病的危险因素在疾病发病机制中的关键作用。