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Enregistrement W168386431

The role of gastrointestinal microbiota in the efficacy of Green-Lipped Mussel (Perna canaliculus) and glucosamine sulphate in treating knee osteoarthritis

2012· article· en· W168386431 sur OpenAlexaboutno aff
Samantha Coulson

Notice bibliographique

RevueQueensland's institutional digital repository (The University of Queensland) · 2012
Typearticle
Langueen
DomaineMedicine
ThématiqueInflammatory mediators and NSAID effects
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOsteoarthritisMedicineWOMACInternal medicineDysbiosisPhysical therapyDiseasePathology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Objective: Nutraceuticals are highly utilised by patients suffering from osteoarthritis (OA), the most common debilitating musculoskeletal disease known. The clinical efficacy and mechanisms of activity for popular nutraceuticals however are inconsistent and thus inconclusive, preventing medical recommendation for their use. We hypothesise that gastrointestinal tract (GIT) microbiota profiles of patients’ with OA differ from normal healthy controls and subsequently may influence the therapeutic efficacy of orally administered dietary supplements due to the extensive metabolic capacity of GIT microbiota. Our aim was initially to investigate the efficacy of New Zealand green-lipped mussel (GLM) extract in participants diagnosed with knee OA and concurrently assess if GIT dysfunction and analgesic/non-steroidal anti-inflammatory drug (NSAID) consumption influenced the efficacy of GLM extract in treating OA symptoms. Further, we investigated faecal microbiota profiles to determine if (a) GIT dysbiosis was demonstrated by OA participants and (b) if bacterial growth was influenced by the oral administration of GLM extract or glucosamine sulphate (GS). Methods: In the initial open label, single group, pilot study we administered 3,000 mg/day of GLM extract over 8 weeks to 21 participants diagnosed with knee OA. Outcome measures were scored using the Western Ontario McMasters Universities Osteoarthritis Index (WOMAC), the Lequesne algofunctional index and the Gastrointestinal Symptom Rating Scale (GSRS) tools. An intention-to-treat analysis was employed and participant data collected at T0, T4 and T8 weeks. This was followed up by a randomised, open-label comparison study that recruited 38 participants diagnosed with knee OA. Participants were randomised to receive either 3,000 mg/day of GLM extract or 3000mg/day of GS, orally administered for 12 weeks. Faecal microbial analyses were carried out after collecting stools at T0 and T12 weeks. Additional pharmacometric measures were obtained from changes in arthritic scores in the WOMAC and the Lequesne algofunctional indices and the GSRS. An intention-to-treat analysis was employed and participant data collected at T0, T6 and T12 weeks. Results: Paired t tests for the initial open-label, single group study showed significant improvement for the Lequesne, WOMAC (p<0.001) and GSRS (p = 0.005) scores. Sub-analysis demonstrated that OA participants taking analgesic and NSAIDs had higher WOMAC, Lequesne and GSRS scores than participants not taking pain relief medications. The percentage change in outcome scores was greater for participants not taking analgesic/NSAID medications suggesting that such medications and GIT symptoms may influence the therapeutic efficacy of GLM extract. The randomised, open-label comparison study showed no statistically significant change in bacterial growth patterns determined by Wilcoxon test. At baseline, both groups did demonstrate GIT dysbiosis as compared to normal healthy control data, with the overgrowth of a number of bacterial species including Clostridium, Staphylococcus, Streptococcus, Enterococcus, Eubacterium, Lactobacillus and Bifidobacterium species. After 12 weeks duration however, both treatment groups demonstrated a notable trend towards a decline in Clostridia and Staphylococcus species and a further increase in Lactobacilli, Streptococcus, Coliforms (Escherichia coli) and Eubacterium species. In the GLM group, Bifidobacteria tended to increase and Enterococcus and yeast species decreased. The GS-treated group demonstrated a trend towards a decrease in Bacteroides and an increase in yeasts and Coliforms (Escherichia coli). Prevotella species were not detected in the GLM-group and were only detected in 2 participants at baseline only in the GS-group. We further confirm significant improvement (p≤0.001) in all OA outcome measures from T0 to T12 weeks for both the GLM and GS groups. The GSRS scores indicating GIT function, significantly improved over the 12 weeks duration for both GLM extract (p=0.02) and GlcN (p=0.044) supplemented groups. Conclusion: GLM extract significantly improved knee OA symptoms and GIT symptoms in OA patients at 3000mg/day. The therapeutic efficacy of the GLM extract in treating knee OA was possibly correlated to its effects on GIT function by improving GSRS scores from baseline. Results from the initial pilot trial highlighted the requisite for further clinical investigations of GIT function in OA patients. The randomised open-label comparison study demonstrated that both GLM extract and GS significantly improved knee OA symptoms with a trend towards rescuing a dysbiotic gut that was demonstrated in this cohort. Growth trends in the microbiota profiles occurred in both treatment groups; the most notable being a reduction in Clostridia and Staphylococcus species. This study proposes that dietary supplements such as GLM extract and GS may regulate some of the metabolic and possibly immunological activities of GIT microflora as demonstrated by improved OA symptoms. GIT dysbiosis has previously been reported in Rheumatoid arthritis (RA) patients. Now for the first time we can report that OA patients also demonstrate GIT dysbiosis that may play a role in the aetiopathogenesis of the disease. The GIT microbiota is vital to understanding the pathogenesis of arthritic conditions and the therapeutic activity of orally administered dietary supplements.

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)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,005
Tête enseignante GPT0,190
Écart entre enseignants0,185 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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