Gut microbiome-targeted therapies and bone health across the lifespan: a scoping review
Bibliographic record
Abstract
Emerging evidence suggests that bone turnover is influenced by the gut microbiome through critical bone signaling pathways. The purpose of this scoping review is to examine prebiotic, probiotic, and synbiotic interventions on bone outcomes in humans across the lifespan. PubMed, Scopus, and EBSCOhost were searched until January 2023 to identify clinical trials examining bone mineral density (BMD) or bone mineral content (BMC) with gut microbiome interventions. Of three prebiotic interventions, one reported higher areal BMD (aBMD) in adolescents. In two studies in postmenopausal women, no changes in aBMD were observed despite decreased biomarkers of bone resorption. Probiotic interventions in perimenopausal or postmenopausal women demonstrated increased aBMD or attenuated bone loss in various bone regions. All studies observed attenuated bone loss (n = 4) or increased aBMD (n = 1). One study assessed a synbiotic intervention on aBMD and observed decreased biomarkers of bone resorption but no changes in aBMD. Results suggest potential for microbiome-targeted therapies (prebiotics, probiotics and synbiotics) to attenuate bone loss. However, changes in biomarkers of bone turnover were not always accompanied by changes in bone mineralization. Future studies should utilize longer duration interventions to investigate the influence of prebiotic, probiotic, and synbiotic interventions across diverse age, sex, and ethnic cohorts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".