Plasma biomarkers differentiate Parkinson's disease from atypical parkinsonism syndromes

Chin Hsien Lin, Shieh Yueh Yang, Herng Er Horng, Che Chuan Yang, Jen Jie Chieh, Hsin Hsien Chen, Bing Hsien Liu, Ming Jang Chiu*

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

48 引文 斯高帕斯(Scopus)

摘要

Objective: Parkinson's disease (PD) has significant clinical overlaps with atypical parkinsonism syndromes (APS), which have a poorer treatment response and a more aggressive course than PD. We aimed to identify plasma biomarkers to differentiate PD from APS. Methods: Plasma samples (n = 204) were obtained from healthy controls and from patients with PD, dementia with Lewy bodies (DLB), multiple system atrophy, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), or frontotemporal dementia (FTD) with parkinsonism (FTD-P) or without parkinsonism. We measured plasma levels of α-synuclein, total tau, p-Tau181, and amyloid beta 42 (Aβ42) by immunomagnetic reduction-based immunoassay. Results: Plasma α-synuclein level was significantly increased in patients with PD and APS when compared with controls and FTD without parkinsonism (p < 0.01). Total tau and p-Tau181 were significantly increased in all disease groups compared to controls, especially in patients with FTD (p < 0.01). A multivariate and receiver operating characteristic curve analysis revealed that a cut-offvalue for Aβ42 multiplied by p-Tau181 for discriminating patients with FTD from patients with PD and APS was 92.66 (pg/ml)2, with an area under the curve (AUC) of 0.932. An α-synuclein cut-offof 0.1977 pg/ml could separate FTD-P from FTD without parkinsonism (AUC 0.947). In patients with predominant parkinsonism, an α-synuclein cut-offof 1.388 pg/ml differentiated patients with PD from those with APS (AUC 0.87). Conclusion: Our results suggest that integrated plasma biomarkers improve the differential diagnosis of PD from APS (PSP, CBD, DLB, and FTD-P).

原文英語
文章編號123
期刊Frontiers in Aging Neuroscience
10
發行號APR
DOIs
出版狀態已發佈 - 2018 4月 27

ASJC Scopus subject areas

  • 老化
  • 認知神經科學

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