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Enregistrement W2886612265 · doi:10.4103/1673-5374.235242

Drug repurposing for neuroregeneration in multiple sclerosis

2018· article· en· W2886612265 sur OpenAlexaff
Peter Göttle, Patrick Küry, David Kremer

Notice bibliographique

RevueNeural Regeneration Research · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Sclerosis Research Studies
Établissements canadiensSt. Peter's Hospital
Organismes subventionnairesnon disponible
Mots-clésNeuroregenerationMultiple sclerosisMyelinRemyelinationMedicineNeuroscienceNeurodegenerationDemyelinating diseaseNeuroinflammationStem-cell therapyStem cellCentral nervous systemPathologyDiseaseImmunologyBiologyMesenchymal stem cellCell biology

Résumé

récupéré en direct d'OpenAlex

Multiple sclerosis (MS) is a chronic, inflammatory and neurodegenerative disease of the central nervous system (CNS) affecting at least 2.5 million people worldwide. While the relapsing subtypes of MS are well treatable, the disease per se remains incurable and results in progressive disability. Its etiology is complex and far from being understood. However, it is well-established that its central histopathological hallmark is demyelination - the autoimmune destruction of myelin sheaths. These elaborate structures wrap around axons electrically isolating them and provide accelerated electrical transmission as well as physical and trophic support in the brain and spinal cord (Lassmann, 2018). Demyelination impairs axonal integrity which leads to permanent disability (Lassmann, 2018). Whereas relapsing MS (RMS) which is most common at disease onset is characterized by episodes of autoimmune attacks (relapse) followed by spontaneous partial functional recovery (remission), most patients eventually develop a progressive disease course. Progressive MS stages, however, are mainly characterized by reduced or absent immune cell infiltration but ongoing neurodegeneration. Neuroregeneration in MS, on the other hand, basically refers to myelin repair - a process that can repair some of the existing lesions via recruitment of resident oligodendroglial precursor cells (OPCs) and neural stem cells (NSCs) which can differentiate and produce new axonal myelin sheaths restoring axonal integrity (Franklin and Ffrench-Constant, 2017). However, the repair capacity of precursor- and stem cells declines with age and disease progression. Moreover, differences in the extent of myelin regeneration can be observed between lesions and patients, potentially indicating heterogeneous underlying mechanisms which interfere with myelin restoration (Franklin and Ffrench-Constant, 2017). In this regard, several oligodendroglial differentiation inhibitors have been identified which are supposed to prevent successful cell maturation in an inflammatory environment (Kremer et al., 2011). Of note, whereas a number of RMS treatments exist that successfully reduce relapse rate, none of the currently available disease-modifying therapies (DMT) has been shown to effectively enhance lesion repair. Hence, there is an unmet clinical need to develop new disability-reversing therapies aiming at the preservation of both axons and oligodendroglial cells. Different strategies for enhancing remyelination are conceivable including cell-based therapies relying on exogenous cell supply (Scolding et al., 2017), the neutralization of differentiation inhibitors (Kremer et al., 2011) or direct stimulatory approaches for improved adult oligodendrogenesis (Kremer et al., 2016). As cell-based therapies are restricted in their practical feasibility, stimulation and promotion of endogenous cell-based repair represents a more promising avenue. To this end, the development of new drugs, acting on inhibitory or stimulatory glial pathways, and the repurposing of existing drugs represent possible approaches. The strategy of drug repurposing offers the advantage of identifying new targets for known drugs already clinically approved for other indications minimizing risks and costs. Hence, high-throughput drug-screenings (Mei et al., 2014) as well as computational drug-repurposing approaches (Azim et al., 2017) are being used. In this context, recent screenings identified the ability of the histamine H1 receptor blocker clemastine, the muscarinic receptor antagonist benztropine and the atypical neuroleptic quetiapine, to promote myelin repair (Mei et al., 2014). On the other hand, ocrelizumab, a monoclonal antibody directed against CD20 on B cells and initially designed for treatment of rheumatoid arthritis (RA), demonstrated efficacy on disability progression in primary progressive MS patients (Montalban et al., 2017; Kremer et al., 2018). Moreover, the phosphodiesterase inhibitor ibudilast, an approved asthma treatment, was found to reduce brain atrophy in progressive MS patients (Kremer et al., 2018). Investigating its effects in secondary progressive MS, a clinical study found that siponimod, a novel sphingosine-1-phosphate (S1P)-receptor modulator, reduced confirmed disability progression by 21% over three months of treatment (Kappos et al., 2018). Finally, in our recent own contribution to the field, we closer investigated the effect of teriflunomide, currently used as an immunomodulatory DMT for RMS. In our preclinical study we focused on oligodendroglial cells, their differentiation capacity and their ability to differentiate and wrap around central nervous system (CNS) axons. We could demonstrate that teriflunomide - beyond its role as an immune modulator acting via inhibition of pyrimidine biosynthesis in activated lymphocytes - can also significantly promote OPC differentiation and internode formation (Figure 1), particularly when applied early and in pulses (Göttle et al., 2018). Future in vivo studies will reveal to what degree teriflunomide also holds promise for remyelination in hostile in vivo settings and whether such repair processes could explain the reduced disability progression as observed in the teriflunomide multiple sclerosis trials (TEMSO, ClinicalTrials.gov number NCT00134563; TOWER, ClinicalTrials.gov number NCT00751881) (Freedman et al., 2018). At the current time-point it can therefore be concluded that, given the heterogeneity of clinical MS subtypes and the dynamics of lesion development in time and space, it will be challenging to find the appropriate window of opportunity for therapy – no matter if using newly designed drugs or repurposed ones.Figure 1: Teriflunomide's mode of action.It has been well accepted that teriflunomide reduces the number of activated peripheral T and B lymphocytes, which could potentially infiltrate the central nervous system (CNS). Our new study provides evidence that local parenchymal teriflunomide concentrations could also positively affect oligodendroglial precursor cells by means of promoting cell differentiation, maturation and subsequent generation of myelin sheaths around previously demyelinated axons.Cited research work in the laboratory of the authors was supported by the Jürgen Manchot Foundation Düsseldorf, by the research commission of the medical faculty of Heinrich-Heine-University of Düsseldorf and by a grant of Sanofi Genzyme. The MS Center at the Department of Neurology is supported in part by the Walter and Ilse Rose Foundation and the James and Elisabeth Cloppenburg, Peek & Cloppenburg Düsseldorf Stiftung. Additional file: Open peer review reports 1, 2.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,027

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0080,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,348
Tête enseignante GPT0,430
Écart entre enseignants0,082 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2018
Routes d'admission1
Résumé présentoui

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