Data_Sheet_2_Alterations in Glycerolipid and Fatty Acid Metabolic Pathways in Alzheimer's Disease Identified by Urinary Metabolic Profiling: A Pilot Study.pdf

An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) is needed. Evidence suggests that metabolic dysfunction underlies the pathophysiology of AD. While urine is a non-invasively collectable biofluid and a good source for metabolomics analysis, it is not yet widely used for this purpose. This small-scale pilot study aimed to examine whether the metabolic profile of urine from AD patients reflects the metabolic dysfunction reported to underlie AD pathology, and to identify metabolites that could distinguish AD patients from cognitively healthy controls. Spot urine of 18 AD patients (AD group) and 18 age- and sex-matched, cognitively normal controls (control group) were analyzed by mass spectrometry (MS). Capillary electrophoresis time-of-flight MS and liquid chromatography–Fourier transform MS were used to cover a larger range of molecules with ionic as well as lipid characteristics. A total of 304 ionic molecules and 81 lipid compounds of 12 lipid classes were identified. Of these, 26 molecules showed significantly different relative concentrations between the AD and control groups (Wilcoxon's rank-sum test). Moreover, orthogonal partial least-squares discriminant analysis revealed significant discrimination between the two groups. Pathway searches using the KEGG database, and pathway enrichment and topology analysis using Metaboanalyst software, suggested alterations in molecules relevant to pathways of glycerolipid and glycerophospholipid metabolism, thermogenesis, and caffeine metabolism in AD patients. Further studies of urinary metabolites will contribute to the early detection of AD and understanding of its pathogenesis.

目前亟需一种易于获取且无创的生物标志物，用于阿尔茨海默病（Alzheimer's disease, AD）的早期检测。已有研究证据表明，代谢功能障碍是阿尔茨海默病病理生理学的核心机制。尿液作为一种可无创采集的生物体液，是代谢组学分析的优质样本来源，但其在该领域的应用尚未得到广泛推广。本项小规模预实验旨在探究阿尔茨海默病患者尿液的代谢谱是否能够反映此前报道的、与AD病理相关的代谢功能障碍，并筛选出可用于区分AD患者与认知健康对照者的代谢物。本研究共纳入18名AD患者（AD组）与18名年龄、性别匹配的认知正常对照者（对照组），采用质谱（mass spectrometry, MS）技术对两组受试者的随机尿样本进行分析；分别采用毛细管电泳-飞行时间质谱（capillary electrophoresis time-of-flight MS）与液相色谱-傅里叶变换质谱（liquid chromatography–Fourier transform MS），以覆盖兼具离子特性与脂质特性的更多种类的分子。最终共鉴定出304种离子类分子，以及涵盖12个脂质类别的81种脂质化合物。其中26种分子在AD组与对照组间的相对浓度存在显著差异（Wilcoxon秩和检验，Wilcoxon's rank-sum test）。此外，正交偏最小二乘判别分析（orthogonal partial least-squares discriminant analysis）结果显示，两组样本可实现显著区分。通过KEGG数据库进行通路检索，并借助Metaboanalyst软件开展通路富集与拓扑分析，结果提示AD患者体内与甘油脂代谢、甘油磷脂代谢、产热以及咖啡因代谢相关通路的分子存在异常改变。后续针对尿液代谢物的深入研究，将有助于推动阿尔茨海默病的早期检测，并加深对其发病机制的理解。