Blood biomarkers with Parkinson's disease clusters and prognosis: The oxford discovery cohort

帕金森病患者的血液生物标志物与预后:牛津发现队列

阅读:1

Abstract

BACKGROUND: Predicting prognosis in Parkinson's disease (PD) has important implications for individual prognostication and clinical trials design and targeting novel treatments. Blood biomarkers could help in this endeavor. METHODS: We identified 4 blood biomarkers that might predict prognosis: apolipoprotein A1, C-reactive protein, uric acid and vitamin D. These biomarkers were measured in baseline serum from 624 Parkinson's disease subjects (median disease duration, 1.0 years; interquartile range, 0.5-2.0) from the Oxford Discovery prospective cohort. We compared these biomarkers against PD subtypes derived from clinical features in the baseline cohort using data-driven approaches. We used multilevel models with MDS-UPDRS parts I, II, and III and Montreal Cognitive Assessment as outcomes to test whether the biomarkers predicted subsequent progression in motor and nonmotor domains. We compared the biomarkers against age of PD onset and age at diagnosis. The q value, a false-discovery rate alternative to P values, was calculated as an adjustment for multiple comparisons. RESULTS: Apolipoprotein A1 and C-reactive protein levels differed across our PD subtypes, with severe motor disease phenotype, poor psychological well-being, and poor sleep subtype having reduced apolipoprotein A1 and higher C-reactive protein levels. Reduced apolipoprotein A1, higher C-reactive protein, and reduced vitamin D were associated with worse baseline activities of daily living (MDS-UPDRS II). CONCLUSION: Baseline clinical subtyping identified a pro-inflammatory biomarker profile significantly associated with a severe motor/nonmotor disease phenotype, lending biological validity to subtyping approaches. No blood biomarker predicted motor or nonmotor prognosis. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。