Effects of alendronate and vitamin D on plasma metabolomic profiles in a rat model of osteoporosis
Notice bibliographique
Résumé
BACKGROUND: Osteoporosis is a progressive bone disease and a significant global health issue, which places a serious economic and health burden on families and societies. Nitrogenated bisphosphonate drugs remain the first line therapy for treating osteoporosis, however their impact on bone cell metabolism and bone health after long term usage is difficult to determine for individual patients. As such, this study aimed to identify the metabolites in plasma that may serve as a diagnostic mechanism for measuring the extent of bisphosphonate drug suppression of bone loss in patients following long-term bisphosphonate drug therapy, and after active vitamin D stimulation of bisphosphonate-suppressed bone metabolism. Our approach was to evaluate combinations of alendronate bisphosphonate and active vitamin D treatment on those same plasma metabolites in an established rat model of osteoporosis, secondary to surgical ovariectomy. METHODS: Metabolomic analyses were performed using the commercially available Biocrates p180 metabolomics kit, which was run on a Sciex Qtrap 4000 mass spectrometer equipped with an Agilent HPLC system. Thirty 6-month old ovariectomized (OVX) rats were randomly assigned into three experimental groups, namely, control OVX rats, OVX rats dosed with alendronate, and a final group of OVX rats dosed with a combination of alendronate and active vitamin D. We used in vivo micro-Computed Tomography (μCT) imaging to confirm the developing osteoporosis phenotype in all ovariectomized rats, initially at baseline, and once more at the study endpoint of 8 weeks. Plasma from all rats was also collected at baseline and at 8 weeks and subjected to metabolomics analysis to identify potential osteoporosis biomarkers. We also determined the correlation between bone volume and specific plasma metabolites in an effort to create an osteoporosis screening tool of bisphosphonate drug metabolic suppression for potential use in clinical practice. RESULTS: Our analyses indicated that alendronate regulated several key plasma metabolites, including certain amino acids, lipids, and glucose, which are likely involved in bone resorption and formation. A distinct metabolite "fingerprint" was observed in all treatment groups compared to the control, with notable differences in metabolic changes. There was a correlation between four metabolites (proline, trans-hydroxyproline, histamine, and methionine) and micro-CT measured percent bone volume, indicating significant changes following ovariectomy surgery and with drug treatments. CONCLUSIONS: For our study, metabolomic profiling served as a useful research tool for elucidating the biological activity and toxicity of bisphosphonate drugs on metabolic bone cell activity. The approach could significantly aid in gauging the impact of long-term bisphosphonate drug usage in osteoporosis patients, for the assessment of osteoporosis drug therapy effectiveness, and to potentially avoid bisphosphonate-related adverse events of bone metabolism suppression. Our study outcomes suggest potential avenues for further research, although unexpected adverse events associated with active vitamin D treatment necessitate caution with interpretation. As such, our findings regarding the impact of vitamin D are exploratory in nature and require additional studies to confirm those findings.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».