Metabolomics Department, Beaumont Research Institute, Beaumont Health, Royal Oak, MI 48073, USA.
Oakland University-William Beaumont School of Medicine, Rochester, MI 48309, USA.
Cells. 2020 Oct 31;9(11):2394. doi: 10.3390/cells9112394.
CSF from unique groups of Parkinson's disease (PD) patients was biochemically profiled to identify previously unreported metabolic pathways linked to PD pathogenesis, and novel biochemical biomarkers of the disease were characterized. Utilizing both H NMR and DI-LC-MS/MS we quantitatively profiled CSF from patients with sporadic PD ( = 20) and those who are genetically predisposed (LRRK2) to the disease ( = 20), and compared those results with age and gender-matched controls ( = 20). Further, we systematically evaluated the utility of several machine learning techniques for the diagnosis of PD. H NMR and mass spectrometry-based metabolomics, in combination with bioinformatic analyses, provided useful information highlighting previously unreported biochemical pathways and CSF-based biomarkers associated with both sporadic PD (sPD) and LRRK2 PD. Results of this metabolomics study further support our group's previous findings identifying bile acid metabolism as one of the major aberrant biochemical pathways in PD patients. This study demonstrates that a combination of two complimentary techniques can provide a much more holistic view of the CSF metabolome, and by association, the brain metabolome. Future studies for the prediction of those at risk of developing PD should investigate the clinical utility of these CSF-based biomarkers in more accessible biomatrices. Further, it is essential that we determine whether the biochemical pathways highlighted here are recapitulated in the brains of PD patients with the aim of identifying potential therapeutic targets.
从帕金森病(PD)患者的独特群体中提取脑脊液,对其进行生化分析,以确定与 PD 发病机制相关的以前未报道的代谢途径,并对该疾病的新型生化生物标志物进行了特征描述。利用 H NMR 和 DI-LC-MS/MS,我们定量分析了散发性 PD(n=20)和遗传易患 PD(LRRK2)患者(n=20)的脑脊液,并将这些结果与年龄和性别匹配的对照组(n=20)进行了比较。此外,我们还系统地评估了几种机器学习技术在 PD 诊断中的应用。基于 H NMR 和质谱的代谢组学,结合生物信息学分析,提供了有用的信息,突出了以前未报道的与散发性 PD(sPD)和 LRRK2 PD 相关的生化途径和脑脊液生物标志物。这项代谢组学研究的结果进一步支持了我们小组之前的研究结果,即鉴定胆汁酸代谢为 PD 患者主要异常生化途径之一。这项研究表明,两种互补技术的结合可以更全面地了解脑脊液代谢组,进而了解大脑代谢组。未来对易患 PD 的高危人群的预测研究应调查这些基于脑脊液的生物标志物在更易获取的生物基质中的临床实用性。此外,至关重要的是,我们必须确定这里强调的生化途径是否在 PD 患者的大脑中得到重现,目的是确定潜在的治疗靶点。