Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome, Italy.
Department of Chemistry, Sapienza Università di Roma, Rome, Italy.
Geroscience. 2020 Oct;42(5):1323-1334. doi: 10.1007/s11357-020-00192-2. Epub 2020 May 26.
Dopaminergic nigrostriatal denervation and widespread intracellular α-synuclein accumulation are neuropathologic hallmarks of Parkinson's disease (PD). A constellation of peripheral processes, including metabolic and inflammatory changes, are thought to contribute to neurodegeneration. In the present study, we sought to obtain insight into the multifaceted pathophysiology of PD through the application of a multi-marker discovery approach. Fifty older adults aged 70+, 20 with PD and 30 age-matched controls were enrolled as part of the EXosomes in PArkiNson Disease (EXPAND) study. A panel of 68 circulating mediators of inflammation, neurogenesis and neural plasticity, and amino acid metabolism was assayed. Biomarker selection was accomplished through sequential and orthogonalized covariance selection (SO-CovSel), a multi-platform regression method developed to handle highly correlated variables organized in multi-block datasets. The SO-CovSel model with the best prediction ability using the smallest number of variables was built with seven biomolecules. The model allowed correct classification of 94.2 ± 3.1% participants with PD and 100% controls. The biomarker profile of older adults with PD was defined by higher circulating levels of interleukin (IL) 8, macrophage inflammatory protein (MIP)-1β, phosphoethanolamine, and proline, and by lower concentrations of citrulline, IL9, and MIP-1α. Our innovative approach allowed identifying and evaluating the classification performance of a set of potential biomarkers for PD in older adults. Future studies are warranted to establish whether these biomolecules could serve as biomarkers for PD as well as unveil new targets for interventions.
多巴胺能黑质纹状体神经纤维丧失和广泛的细胞内 α-突触核蛋白积累是帕金森病(PD)的神经病理学标志。一系列外周过程,包括代谢和炎症变化,被认为有助于神经退行性变。在本研究中,我们试图通过应用多标志物发现方法来深入了解 PD 的多方面病理生理学。作为 EXosomes in PArkiNson Disease(EXPAND)研究的一部分,招募了 50 名年龄在 70 岁以上的老年人,其中 20 名患有 PD,30 名年龄匹配的对照组。测定了一组 68 种循环炎症、神经发生和神经可塑性以及氨基酸代谢介质。通过顺序和正交协方差选择(SO-CovSel)进行生物标志物选择,这是一种多平台回归方法,用于处理以多块数据集组织的高度相关变量。使用最少数量的变量构建了具有最佳预测能力的 SO-CovSel 模型,其中包含 7 种生物分子。该模型能够正确分类 94.2±3.1%的 PD 患者和 100%的对照组。PD 老年患者的生物标志物特征表现为循环白细胞介素(IL)8、巨噬细胞炎性蛋白(MIP)-1β、磷酸乙醇胺和脯氨酸水平升高,瓜氨酸、IL9 和 MIP-1α浓度降低。我们的创新方法允许识别和评估一组潜在的 PD 老年患者生物标志物的分类性能。未来的研究需要建立这些生物分子是否可以作为 PD 的生物标志物,并揭示干预的新靶点。