Klatt Stephan, Doecke James D, Roberts Anne, Boughton Berin A, Masters Colin L, Horne Malcolm, Roberts Blaine R
The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia.
Cooperative Research Centre for Mental Health, Parkville, VIC, 3052, Australia.
NPJ Parkinsons Dis. 2021 Oct 14;7(1):94. doi: 10.1038/s41531-021-00239-x.
Characterisation and diagnosis of idiopathic Parkinson's disease (iPD) is a current challenge that hampers both clinical assessment and clinical trial development with the potential inclusion of non-PD cases. Here, we used a targeted mass spectrometry approach to quantify 38 metabolites extracted from the serum of 231 individuals. This cohort is currently one of the largest metabolomic studies including iPD patients, drug-naïve iPD, healthy controls and patients with Alzheimer's disease as a disease-specific control group. We identified six metabolites (3-hydroxykynurenine, aspartate, beta-alanine, homoserine, ornithine (Orn) and tyrosine) that are significantly altered between iPD patients and control participants. A multivariate model to predict iPD from controls had an area under the curve (AUC) of 0.905, with an accuracy of 86.2%. This panel of metabolites may serve as a potential prognostic or diagnostic assay for clinical trial prescreening, or for aiding in diagnosing pathological disease in the clinic.
特发性帕金森病（iPD）的特征描述和诊断是当前一项挑战，它阻碍了临床评估和临床试验的开展，因为可能纳入了非帕金森病病例。在此，我们采用靶向质谱分析法对从231名个体血清中提取的38种代谢物进行定量。该队列目前是最大的代谢组学研究之一，纳入了iPD患者、未接受过药物治疗的iPD患者、健康对照以及作为疾病特异性对照组的阿尔茨海默病患者。我们鉴定出6种代谢物（3-羟基犬尿氨酸、天冬氨酸、β-丙氨酸、高丝氨酸、鸟氨酸（Orn）和酪氨酸）在iPD患者与对照参与者之间存在显著变化。一个用于从对照中预测iPD的多变量模型的曲线下面积（AUC）为0.905，准确率为86.2%。这组代谢物可作为一种潜在的预后或诊断检测方法，用于临床试验预筛选，或辅助临床诊断病理性疾病。
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