Proteomics of Multiple Sclerosis : inherent issues in defining the pathoetiology and identifying (early) biomarkers

Monokesh K. Sen, Mohammed S. M. Almuslehi, Peter J. Shortland, David A. Mahns, Jens R. Coorssen

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Multiple Sclerosis (MS) is a demyelinating disease of the human central nervous system having an unconfirmed pathoetiology. Although animal models are used to mimic the pathology and clinical symptoms, no single model successfully replicates the full complexity of MS from its initial clinical identification through disease progression. Most importantly, a lack of preclinical biomarkers is hampering the earliest possible diagnosis and treatment. Notably, the development of rationally targeted therapeutics enabling pre‐emptive treatment to halt the disease is also delayed without such biomarkers. Using literature mining and bioinformatic analyses, this review assessed the available proteomic studies of MS patients and animal models to discern (1) whether the models effectively mimic MS; and (2) whether reasonable biomarker candidates have been identified. The implication and necessity of assessing proteoforms and the critical importance of this to identifying rational biomarkers are discussed. Moreover, the challenges of using different proteomic analytical approaches and biological samples are also addressed.
Original languageEnglish
Article number7377
Number of pages48
JournalInternational Journal of Molecular Sciences
Volume22
Issue number14
Publication statusPublished - 2021

Open Access - Access Right Statement

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Fingerprint

Dive into the research topics of 'Proteomics of Multiple Sclerosis : inherent issues in defining the pathoetiology and identifying (early) biomarkers'. Together they form a unique fingerprint.

Cite this