Serum N-Glycosylation in Parkinson's Disease: A Novel Approach for Potential Alterations.
Csaba VáradiKároly NehézOlivér HornyákBéla ViskolczJonathan BonesPublished in: Molecules (Basel, Switzerland) (2019)
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.
Keyphrases
- mass spectrometry
- ms ms
- end stage renal disease
- deep learning
- machine learning
- capillary electrophoresis
- label free
- ejection fraction
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- liquid chromatography
- healthcare
- liquid chromatography tandem mass spectrometry
- multiple sclerosis
- single cell
- high performance liquid chromatography
- ionic liquid
- gas chromatography