Gautam Priyanka, Yadav Rahul, Vishwakarma Ranjeet Kumar, Shekhar Shashi, Pathak Abhishek, Singh Chandan
Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi 221005, India.
Department of Biochemistry, Institute of Science, Banaras Hindu University, Varanasi 221005, India.
ACS Chem Neurosci. 2025 Jul 16;16(14):2691-2706. doi: 10.1021/acschemneuro.5c00254. Epub 2025 Jun 9.
ALS is a severe neurodegenerative disorder characterized by motor neuron degeneration, gut dysbiosis, immune dysregulation, and metabolic disturbances. In this study, shotgun metagenomics and H nuclear magnetic resonance (NMR)-based metabolomics were employed to investigate the altered gut microbiome and metabolite profiles in individuals with ALS, household controls (HCs), and nonhousehold controls (NHCs). The principal component analysis (PCA) explained 33% of the variance, and the partial least-squares discriminant analysis (PLS-DA) model demonstrate and values of 0.97 and 0.84, respectively, indicating an adequate model fit. The relative bacterial abundance was 99.34% in the ALS group and 98.94% in the HC group. Among the ten identified genera, , , and were more prevalent in ALS individuals, while and were more abundant in the HC group. We identified 70 metabolites, including short-chain fatty acids (SCFAs), branched-chain amino acids (BCAAs), carbohydrates, and aromatic compounds, using NMR. Orthogonal partial least-squares discriminant analysis (O-PLS-DA) explained 15.8% of the variance, with a clear separation between the ALS and HC groups. Univariate receiver operating characteristic (ROC) analysis identified three fecal metabolites with AUC values above 0.70, including butyrate (0.798), propionate (0.727), and citrate (0.719). These metabolites may serve as potential biomarkers for ALS. The statistical model for metabolic pathway analysis revealed interconnected pathways, highlighting the complexity of metabolic dysregulation, as well as potential microbial and metabolic biomarkers in ALS. These results highlight the role of gut microbiome alterations in ALS and suggest potential avenues for therapeutic intervention.
肌萎缩侧索硬化症（ALS）是一种严重的神经退行性疾病，其特征为运动神经元退化、肠道微生物群失调、免疫调节异常和代谢紊乱。在本研究中，采用鸟枪法宏基因组学和基于氢核磁共振（NMR）的代谢组学来研究肌萎缩侧索硬化症患者、家庭对照（HCs）和非家庭对照（NHCs）的肠道微生物群和代谢物谱的变化。主成分分析（PCA）解释了33%的方差，偏最小二乘判别分析（PLS-DA）模型的 和 值分别为0.97和0.84，表明模型拟合良好。ALS组的相对细菌丰度为99.34%，HC组为98.94%。在鉴定出的十个属中， 、 和 在ALS个体中更为普遍，而 和 在HC组中更为丰富。我们使用NMR鉴定了70种代谢物，包括短链脂肪酸（SCFAs）、支链氨基酸（BCAAs）、碳水化合物和芳香族化合物。正交偏最小二乘判别分析（O-PLS-DA）解释了15.8%的方差，ALS组和HC组之间有明显分离。单变量受试者工作特征（ROC）分析确定了三种粪便代谢物，其AUC值高于0.70，包括丁酸盐（0.798）、丙酸盐（0.727）和柠檬酸盐（0.719）。这些代谢物可能作为ALS的潜在生物标志物。代谢途径分析的统计模型揭示了相互关联的途径，突出了代谢失调的复杂性以及ALS中潜在的微生物和代谢生物标志物。这些结果突出了肠道微生物群改变在ALS中的作用，并提出了潜在的治疗干预途径。
