A novel multi-marker discovery approach identifies new serum biomarkers for Parkinson's disease in older people: an EXosomes in PArkiNson Disease (EXPAND) ancillary study
A novel multi-marker discovery approach identifies new serum biomarkers for Parkinson's disease in older people: an EXosomes in PArkiNson Disease (EXPAND) ancillary study
复制标题
DOI：
10.1007/s11357-020-00192-2
复制
发表时间：
2020-05-26
期刊：
影响因子：
5.6
通讯作者：
Marzetti, Emanuele
中科院分区：
文献类型：
--
作者：
Calvani, Riccardo;Picca, Anna;Marzetti, Emanuele
多巴胺能黑质纹状体去神经和广泛的细胞内 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，被认为会导致神经退行性变。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。 50 名 70 岁以上的老年人、20 名帕金森病患者和 30 名年龄匹配的对照者被纳入帕金森病外泌体 (EXPAND) 研究的一部分。对一组 68 种炎症、神经发生和神经可塑性以及氨基酸代谢的循环介质进行了分析。生物标志物选择是通过顺序和正交协方差选择（SO-CovSel）来完成的，SO-CovSel是一种多平台回归方法，旨在处理多块数据集中组织的高度相关变量。使用最少数量的变量具有最佳预测能力的 SO-CovSel 模型是用七个生物分子构建的。该模型允许对 94.2 +/- 3.1% 的 PD 参与者和 100% 对照参与者进行正确分类。患有 PD 的老年人的生物标志物特征是白细胞介素 (IL) 8、巨噬细胞炎症蛋白 (MIP)-1 β、磷酸乙醇胺和脯氨酸的循环水平较高，而瓜氨酸、IL9 和 MIP-1 α 的浓度较低。我们的创新方法可以识别和评估一组老年人帕金森病潜在生物标志物的分类性能。未来的研究有必要确定这些生物分子是否可以作为帕金森病的生物标志物，并揭示新的干预目标。
Dopaminergic nigrostriatal denervation and widespread intracellular alpha-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)-1 beta, phosphoethanolamine, and proline, and by lower concentrations of citrulline, IL9, and MIP-1 alpha. 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.