Csaba Váradi 1,* , Károly Nehéz 2, Olivér Hornyák 2 , Béla Viskolcz 1 and Jonathan Bones 3,4

Abstract:In this study, we present the application of a novel capillary electrophoresis (CE) methodin combination with label-free quantitation and support vector machine-based feature selection(support vector machine-estimated recursive feature elimination or SVM-RFE) to identify potentialglycan alterations in Parkinson’s disease. Specific focus was placed on the use of neutral coatedcapillaries, by a dynamic capillary coating strategy, to ensure stable and repeatable separationswithout 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 byCE-MS/MS in combination with exoglycosidase sequencing. The annotated structures were quantifiedin 15 controls and 15 Parkinson’s disease patients by label-free quantitation. Lower sialylation andincreased fucosylation were found in Parkinson’s disease patients on tri-antennary glycans with 2and 3 terminal sialic acids. The set of potential glycan alterations was narrowed by a recursive featureelimination algorithm resulting in the efficient classification of male patients.