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Title: | Integrating Rehabilomics into the Multi-Omics Approach in the Management of Multiple Sclerosis: The Way for Precision Medicine? | Authors: | BONNECHERE, Bruno | Issue Date: | 2022 | Publisher: | MDPI | Source: | Genes, 14 (1) (Art N° 63) | Abstract: | Over recent years, significant improvements have been made in the understanding of (epi)genetics and neuropathophysiological mechanisms driving the different forms of multiple sclerosis (MS). For example, the role and importance of the bidirectional communications between the brain and the gut—also referred to as the gut-brain axis—in the pathogenesis of MS is receiving increasing interest in recent years and is probably one of the most promising areas of research for the management of people with MS. However, despite these important advances, it must be noted that these data are not—yet—used in rehabilitation. Neurorehabilitation is a cornerstone of MS patient management, and there are many techniques available to clinicians and patients, including technology-supported rehabilitation. In this paper, we will discuss how new findings on the gut microbiome could help us to better understand how rehabilitation can improve motor and cognitive functions. We will also see how the data gathered during the rehabilitation can help to get a better diagnosis of the patients. Finally, we will discuss how these new techniques can better guide rehabilitation to lead to precision rehabilitation and ultimately increase the quality of patient care. | Keywords: | rehabilomics;precision medicine;genes;gut microbiome;rehabilitation;technology- supported rehabilitation | Document URI: | http://hdl.handle.net/1942/39244 | ISSN: | 2073-4425 | e-ISSN: | 2073-4425 | DOI: | 10.3390/genes14010063 | ISI #: | 000915129500001 | Rights: | 2022 by the author. 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 (https://creativecommons.org/licenses/by/4.0/). | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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genes-14-00063-v3.pdf | Published version | 6.19 MB | Adobe PDF | View/Open |
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