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Record 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 on OpenAlexaboutno aff
Samantha Coulson

Bibliographic record

VenueQueensland's institutional digital repository (The University of Queensland) · 2012
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisMedicineWOMACInternal medicineDysbiosisPhysical therapyDiseasePathology
DOInot available

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.190
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes1
Has abstractyes

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