Serum N-Glycosylation in Parkinson's Disease: A Novel Approach for Potential Alterations

In this study, we present the application of a novel capillary electrophoresis (CE) method in combination with label-free quantitation and support vector machine-based feature selection (support vector machine-estimated recursive feature elimination or SVM-RFE) to identify potential glycan alteratio...

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Bibliographic Details
Published in:Molecules (Basel, Switzerland) Switzerland), 2019-06, Vol.24 (12), p.2220
Main Authors: Váradi, Csaba, Nehéz, Károly, Hornyák, Olivér, Viskolcz, Béla, Bones, Jonathan
Format: Article
Language:English
Subjects:
Algorithms
Capillaries
capillary electrophoresis
Classification
Conditioning
Digestion
Disease
Electrolytes
Electroosmosis
Electrophoresis, Capillary
Flow stability
Glycosylation
Humans
Identification
label-free quantitation
Males
Parkinson Disease - metabolism
Parkinson's disease
Polyethylene
Polyethylene oxide
Silica
Support Vector Machine
Support vector machines
Tandem Mass Spectrometry
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Summary:In this study, we present the application of a novel capillary electrophoresis (CE) method in combination with label-free quantitation and support vector machine-based feature selection (support vector machine-estimated recursive feature elimination or SVM-RFE) to identify potential glycan alterations in Parkinson's disease. Specific focus was placed on the use of neutral coated capillaries, by a dynamic capillary coating strategy, to ensure stable and repeatable separations without the need of non-mass spectrometry (MS) friendly additives within the separation electrolyte. The developed online dynamic coating strategy was applied to identify serum N-glycosylation by CE-MS/MS in combination with exoglycosidase sequencing. The annotated structures were quantified in 15 controls and 15 Parkinson's disease patients by label-free quantitation. Lower sialylation and increased fucosylation were found in Parkinson's disease patients on tri-antennary glycans with 2 and 3 terminal sialic acids. The set of potential glycan alterations was narrowed by a recursive feature elimination algorithm resulting in the efficient classification of male patients.
ISSN:1420-3049
1420-3049
DOI:10.3390/molecules24122220