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Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics

Journal article
Authors N. K. Magdalinou
A. J. Noyce
R. Pinto
E. Lindström
Jessica Holmén Larsson
Mikko Hölttä
Kaj Blennow
H. R. Morris
Tobias Skillbäck
T. T. Warner
A. J. Lees
I. Pike
M. Ward
Henrik Zetterberg
Johan Gobom
Published in Parkinsonism & Related Disorders
Volume 37
Pages 65-71
ISSN 1353-8020
Publication year 2017
Published at Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry
Pages 65-71
Language en
Links dx.doi.org/10.1016/j.parkreldis.201...
Keywords Parkinsonian disorders, Parkinson's disease, Progressive supranuclear palsy, Multiple system atrophy, PROGRESSIVE SUPRANUCLEAR PALSY, MULTIPLE SYSTEM ATROPHY, DISEASE, GENE, DISCOVERY, ALZHEIMER, DIAGNOSIS, CRITERIA
Subject categories Neurochemistry

Abstract

Introduction: Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than a-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. Objectives: To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. Methods: CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. Results: 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Conclusion: Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as candidate biomarkers in parkinsonism. (C) 2017 Published by Elsevier Ltd.

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