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MS-based glycomics: An analytical tool to assess nervous system diseases

Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe’s aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality...

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Autores principales: Peng, Wenjing, Kobeissy, Firas, Mondello, Stefania, Barsa, Chloe, Mechref, Yehia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9671362/
https://www.ncbi.nlm.nih.gov/pubmed/36408389
http://dx.doi.org/10.3389/fnins.2022.1000179
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author Peng, Wenjing
Kobeissy, Firas
Mondello, Stefania
Barsa, Chloe
Mechref, Yehia
author_facet Peng, Wenjing
Kobeissy, Firas
Mondello, Stefania
Barsa, Chloe
Mechref, Yehia
author_sort Peng, Wenjing
collection PubMed
description Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe’s aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed.
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spelling pubmed-96713622022-11-18 MS-based glycomics: An analytical tool to assess nervous system diseases Peng, Wenjing Kobeissy, Firas Mondello, Stefania Barsa, Chloe Mechref, Yehia Front Neurosci Neuroscience Neurological diseases affect millions of peopleochemistryorldwide and are continuously increasing due to the globe’s aging population. Such diseases affect the nervous system and are characterized by a progressive decline in brain function and progressive cognitive impairment, decreasing the quality of life for those with the disease as well as for their families and loved ones. The increased burden of nervous system diseases demands a deeper insight into the biomolecular mechanisms at work during disease development in order to improve clinical diagnosis and drug design. Recently, evidence has related glycosylation to nervous system diseases. Glycosylation is a vital post-translational modification that mediates many biological functions, and aberrant glycosylation has been associated with a variety of diseases. Thus, the investigation of glycosylation in neurological diseases could provide novel biomarkers and information for disease pathology. During the last decades, many techniques have been developed for facilitation of reliable and efficient glycomic analysis. Among these, mass spectrometry (MS) is considered the most powerful tool for glycan analysis due to its high resolution, high sensitivity, and the ability to acquire adequate structural information for glycan identification. Along with MS, a variety of approaches and strategies are employed to enhance the MS-based identification and quantitation of glycans in neurological samples. Here, we review the advanced glycomic tools used in nervous system disease studies, including separation techniques prior to MS, fragmentation techniques in MS, and corresponding strategies. The glycan markers in common clinical nervous system diseases discovered by utilizing such MS-based glycomic tools are also summarized and discussed. Frontiers Media S.A. 2022-11-03 /pmc/articles/PMC9671362/ /pubmed/36408389 http://dx.doi.org/10.3389/fnins.2022.1000179 Text en Copyright © 2022 Peng, Kobeissy, Mondello, Barsa and Mechref. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Peng, Wenjing
Kobeissy, Firas
Mondello, Stefania
Barsa, Chloe
Mechref, Yehia
MS-based glycomics: An analytical tool to assess nervous system diseases
title MS-based glycomics: An analytical tool to assess nervous system diseases
title_full MS-based glycomics: An analytical tool to assess nervous system diseases
title_fullStr MS-based glycomics: An analytical tool to assess nervous system diseases
title_full_unstemmed MS-based glycomics: An analytical tool to assess nervous system diseases
title_short MS-based glycomics: An analytical tool to assess nervous system diseases
title_sort ms-based glycomics: an analytical tool to assess nervous system diseases
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9671362/
https://www.ncbi.nlm.nih.gov/pubmed/36408389
http://dx.doi.org/10.3389/fnins.2022.1000179
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