The GPR17 receptor-A promising goal for therapy and a potential marker of the neurodegenerative process in multiple sclerosis
Open accessAbstract
One of the most important goals in the treatment of demyelinating diseases such as multiple sclerosis (MS) is, in addition to immunomodulation, reconstruction of the lost myelin sheath. The modulator of the central nervous system myelination is the metabotropic receptor coupled to the G-protein: GPR17. GPR17 receptors are considered to be sensors of local damage to the myelin sheath, and play a role in the reconstruction and repair of demyelinating plaques caused by ongoing inflammatory processes. GPR17 receptors are present on nerve cells and precursor oligodendrocyte cells. Under physiological conditions, they are responsible for the differentiation and subsequent maturation of oligodendrocytes, while under pathological conditions (during damage to nerve cells), their expression increases to become mediators in the demyelinating processes. Moreover, they are essential not only in both the processes of inducing damage and the death of neurons, but also in the local repair of the damaged myelin sheath. Therefore, GPR17 receptors may be recognized as the potential goal in creating innovative therapies for the treatment of the neurodegenerative process in MS, based on the acceleration of the remyelination processes. This review examines the role of GRP17 in pathomechanisms of MS development.
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The strong activation of immune- and inflammation-related genes, as well as differential expression of remyelination regulators like Gpr17, suggest that the homeostasis of white matter is compromised at old age.
“The strong activation of immune- and inflammation-related genes, as well as differential expression of remyelination regulators like Gpr17 (Dziedzic et al., 2020; Rivera et al., 2021), suggest that the homeostasis of this region is compromised at old age.”
From Atlas of the aging mouse brain reveals white matter as vulnerable foci (2023) · cites this paper as Dziedzic et al., 2020
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- Authors
- Dziedzic, A., Miller, E., Saluk-Bijak, J., & Bijak, M.
- Affiliations
- University of Łódź (PL)
- Department of Neurological Rehabilitation, Medical University of Lodz, Milionowa 14, 93-113 Lodz, Poland
- Department of General Biochemistry, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland
- Biohazard Prevention Centre, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2020-03-08
- Volume
- 21
- Issue
- 5
- Pages
- 1852
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC7084627
- OpenAlex
- W3010042062
- Cited by
- 38
- References
- 120
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 7 · 2023: 5 · 2022: 6 · 2021: 5 · 2020: 2
- FWCI
- 0.69
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- University of Lodz (506/1136)
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- GPR17, multiple sclerosis, demyelination, remyelination, oligodendrocyte differentiation, G protein-coupled receptors, neurodegeneration, demyelinating plaques, neuroinflammation, therapeutic target
- MeSH terms
- Remyelination, Animals, Humans, Multiple Sclerosis, Biomarkers, Neurodegenerative Diseases, Receptors, G-Protein-Coupled
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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