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Wiener Medizinische Wochenschrift

Erschienen in:

07.03.2022 | main topic

Experimental laboratory biomarkers in multiple sclerosis

verfasst von: Borros Arneth, Jörg Kraus

Erschienen in: Wiener Medizinische Wochenschrift | Ausgabe 15-16/2022

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Summary

Background

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system; the cause of this condition remains unknown. Researchers have analyzed different biomarkers related to MS. Here, experimental laboratory biomarkers for MS are identified and analyzed.

Methods

The current study examined articles investigating biomarkers for MS. Records were obtained from the PubMed, LILACS, and EBSCO databases using an identical search strategy and terms that included “multiple sclerosis,” “MS,” and “biomarkers.” In the current review, we also focus on lesser known biomarkers that have not yet been established for use in clinical practice.

Results

Previous studies have explored molecular substances that may help diagnose MS and manage its adverse effects. Commonly studied factors include neurofilaments, sCD163, CXCL13, NEO, NF‑L, OPN, B cells, T cells, and integrin-binding proteins.

Conclusions

Interactions between environmental and genetic factors have been implicated in the development of MS. Previous investigations have identified a wide range of biomarkers that can be used for diagnosis and disease management. These molecules and their associated studies provide vital insight and data to help primary physicians improve clinical and health outcomes for MS patients.

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Nächster Artikel An overview of pivotal trials and real-world evidence for CD20-depleting therapy in multiple sclerosis

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Titel: Experimental laboratory biomarkers in multiple sclerosis
verfasst von: Borros Arneth
Jörg Kraus
Publikationsdatum: 07.03.2022
Verlag: Springer Vienna
Erschienen in: Wiener Medizinische Wochenschrift / Ausgabe 15-16/2022
Print ISSN: 0043-5341
Elektronische ISSN: 1563-258X
DOI: https://doi.org/10.1007/s10354-022-00920-7

Springer Medizin Österreich

Summary

Background

Methods

Results

Conclusions

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