Restless legs syndrome (RLS), also known as Willis-Ekbom disease, is a sleep and neurological sensorimotor disorder. The prevalence of RLS is at â5-15% in the general population. RLS could severely impact the daytime work productivity and the life quality of patients. However, the current diagnostic methods fail to provide an accurate and timely diagnosis, and the pathophysiology of RLS is not fully understood. Glycomics can help to unravel the underlying biochemical mechanisms of RLS, to identify specific glycome changes, and to develop powerful biomarkers for early detection and guiding interventions. Herein, we undertook a shotgun glycomics approach to determine and characterize the potential glycan biomarker candidates in the blood serum of RLS patients. Glycan profiles and isomeric quantitations were assessed by liquid chromatography-mass spectrometry analysis and compared with healthy controls. 24 N-glycan biomarker candidates show substantial differences between RLS patients and controls after the Benjamini-Hochberg multiple testing correction. Among those structures, glycans with the composition of HexNAc6Hex8Fuc1NeuAc2, HexNAc6Hex6Fuc1NeuAc3, and HexNAc5Hex6Fuc1NeuAc2 show the most significant alteration in the expression profile (p < 0.001). Furthermore, 23 isomeric structures in the RLS cohorts show significant differences after the Benjamini-Hochberg multiple testing correction. HexNAc4Hex5Fuc1NeuAc2 (4512-3) and HexNAc6Hex7NeuAc3 (6703-1) (p < 0.001) were downexpressed in the RLS cohort. HexNAc6Hex7NeuAc3 (6703-2) and HexNAc5Hex6NeuAc3 (5603-5) (p < 0.001) were expressed higher in the RLS cases. These results demonstrate that it is possible to detect specific glycome traits in individuals with RLS. The discovery of the N-glycan expression alterations might be useful in understanding the molecular mechanism of RLS, developing more refined and objective diagnostic methods, and discovering novel targeted therapeutic interventions.

Serum Glycomics Profiling of Patients with Primary Restless Legs Syndrome Using LC-MS/MS

Mondello S.
Co-primo
Formal Analysis
;
2020-01-01

Abstract

Restless legs syndrome (RLS), also known as Willis-Ekbom disease, is a sleep and neurological sensorimotor disorder. The prevalence of RLS is at â5-15% in the general population. RLS could severely impact the daytime work productivity and the life quality of patients. However, the current diagnostic methods fail to provide an accurate and timely diagnosis, and the pathophysiology of RLS is not fully understood. Glycomics can help to unravel the underlying biochemical mechanisms of RLS, to identify specific glycome changes, and to develop powerful biomarkers for early detection and guiding interventions. Herein, we undertook a shotgun glycomics approach to determine and characterize the potential glycan biomarker candidates in the blood serum of RLS patients. Glycan profiles and isomeric quantitations were assessed by liquid chromatography-mass spectrometry analysis and compared with healthy controls. 24 N-glycan biomarker candidates show substantial differences between RLS patients and controls after the Benjamini-Hochberg multiple testing correction. Among those structures, glycans with the composition of HexNAc6Hex8Fuc1NeuAc2, HexNAc6Hex6Fuc1NeuAc3, and HexNAc5Hex6Fuc1NeuAc2 show the most significant alteration in the expression profile (p < 0.001). Furthermore, 23 isomeric structures in the RLS cohorts show significant differences after the Benjamini-Hochberg multiple testing correction. HexNAc4Hex5Fuc1NeuAc2 (4512-3) and HexNAc6Hex7NeuAc3 (6703-1) (p < 0.001) were downexpressed in the RLS cohort. HexNAc6Hex7NeuAc3 (6703-2) and HexNAc5Hex6NeuAc3 (5603-5) (p < 0.001) were expressed higher in the RLS cases. These results demonstrate that it is possible to detect specific glycome traits in individuals with RLS. The discovery of the N-glycan expression alterations might be useful in understanding the molecular mechanism of RLS, developing more refined and objective diagnostic methods, and discovering novel targeted therapeutic interventions.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3190472
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