Flores-Torres Mario H, Peng Xiaojing, Jeanfavre Sarah, Clish Clary, Wang Ying, McCullough Marjorie L, Healy Brian, Schwarzschild Michael A, Bjornevik Kjetil, Ascherio Alberto
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Metabolomics Platform, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA.
Mov Disord. 2025 Aug 13. doi: 10.1002/mds.30308.
The long prodromal phase of Parkinson's disease (PD) and the link the disease has with metabolic factors suggest that metabolomics could help identify affected individuals at early stages.
The goal was to examine whether plasma metabolomic profiles could identify individuals in the prodromal and clinical phase of PD.
We quantified and compared the plasma metabolomic profiles of 922 individuals with PD who provided blood samples at a median of 11 years before (n = 809) or 2 years after (n = 113) disease diagnosis to that of matched controls, all selected from three established cohort studies (Nurses' Health Study, Health Professionals Follow-up Study, and Cancer Prevention Study II). We used conditional logistic regression models and machine learning techniques to identify metabolites predicting prodromal and clinically manifest PD.
Several metabolites, especially amino acids, acyl-carnitines, and other lipids were nominally associated with PD since the years leading to disease diagnosis. Metabolites proposed as biomarkers of foods or care products tended to be associated with a higher PD risk closer to disease diagnosis. Metabolites reflecting higher intake of coffee, smoking, and acetaminophen tended to be associated with a lower PD risk over the course of the disease. Metabolomic profiles in prodromal samples were unable to accurately predict future clinical PD.
Metabolic pathways related to the metabolism of amino acids and lipids may be involved in PD progression. Metabolomic differences may also result from behavioral changes and medical management, emphasizing the need to consider prodromal and clinical data in future studies. © 2025 International Parkinson and Movement Disorder Society.
帕金森病（PD）的前驱期较长，且该疾病与代谢因素存在关联，这表明代谢组学有助于在早期阶段识别患病个体。
旨在研究血浆代谢组学特征是否能够识别处于PD前驱期和临床期的个体。
我们对922名PD患者的血浆代谢组学特征进行了定量和比较，这些患者在疾病诊断前中位数11年（n = 809）或诊断后2年（n = 113）提供了血样，与匹配的对照组进行比较，所有样本均选自三项已建立的队列研究（护士健康研究、卫生专业人员随访研究和癌症预防研究II）。我们使用条件逻辑回归模型和机器学习技术来识别预测前驱期和临床期PD的代谢物。
自疾病诊断前数年起，几种代谢物，尤其是氨基酸、酰基肉碱和其他脂质与PD存在名义上的关联。被提议作为食物或护理产品生物标志物的代谢物在疾病诊断越近时往往与较高的PD风险相关。反映咖啡、吸烟和对乙酰氨基酚摄入量较高的代谢物在疾病过程中往往与较低的PD风险相关。前驱期样本的代谢组学特征无法准确预测未来的临床PD。
与氨基酸和脂质代谢相关的代谢途径可能参与PD的进展。代谢组学差异也可能由行为变化和医疗管理导致，这强调了在未来研究中需要考虑前驱期和临床数据。© 2025国际帕金森和运动障碍协会。
