Interference of Echinacea Purpurea and St. John's Wort with Anti-inflammatory and Anti-hypertensive Medication via Inhibition of Cytochrome P450 3A4
Notice bibliographique
Résumé
Medicinal plants, such as Echinacea and St. John's wort (Hypericum perforatum), represent an essential component of the healthcare system of developing countries, but the popularity of medicinal plant products is steadily increasing in developed countries as well. It is reported that up to 30% of North Americans incorporate nutraceuticals into their diets. These supplements may lead to therapeutic benefits for patients, but they also possess the ability to cause interactions with other medications by altering the activity of several drug metabolizing enzymes. One such group is the cytochrome P450 (CYP450) family of enzymes, which are responsible for the majority of phase I metabolism of xenobiotics such as herbal supplements and pharmaceuticals. Within the cytochrome P450 family of enzymes, the isoform CYP3A4 is responsible for the metabolism of over 50% of clinically relevant drugs and represents 30% of the entire CYP450 content of the liver. These factors make CYP3A4's function central to the efficacious treatment of patients. Another important aspect of effective drug treatment includes a complete knowledge of the medications and/or supplements a patient is taking, unfortunately some patients consume herbal products without notifying their doctors. Patients who consume drugs that are metabolized through the same pathways as phytopharmaceuticals are at an increased risk for potentially negative drug phytopharmaceutical interactions to occur. On this basis, my hypothesis is that Echinacea and St. John's wort extracts interfere with the metabolism of anti-inflammatory and anti-hypertensive medications, which is most likely due to their inhibition of CYP3A4. The objectives are to examine the potential interference of three separate Echinacea preparations and one St. John's wort preparation on the metabolism of anti inflammatory and anti-hypertensive agents. The hypothesis is to be tested using cultured hepatocytes (HepG2) in a high-throughput method. Interference of Echinacea or St. John's wort with the pharmaceutical preparations was assessed using Promega's P450-Glo™ assay, which utilizes luminescent reagents to quantitate CYP3A4 activity. HPLC and LC-MS were used to verify the contents of Echinacea products prior to conducting the assay. The experiments suggest that both Echinacea and St. John's wort products have an ability to inhibit CYP3A4, but to varying degrees. Echinacea commercial preparations inhibited CYP3A4 by up to 60% at the concentrations examined (0.01-1 0mg/mL), while St. John's wort reached a similar inhibition plateau at a tenth of the concentration (0.001-lmg/mL). Clonidine's metabolic profile was altered by approximately 50%, with dexamethasone, metolazone, and propranolol being affected in a similar manner. Enalapril's profile appeared to be affected by the Echinacea preparations the most, exhibiting an alteration of over 60%. In contrast, nifedipine was the least changed of the medications examined with a maximum alteration of slightly over 40%, but, interestingly, this occurred at the second highest concentrations tested (I mg/mL). There appeared to be a greater level of variation between the alterations seen between different drug profiles with St. John's wort compared to Echinacea. Dexamethasone and clonidine's metabolic profiles were changed the most of the drugs tested, displaying alterations of 80 and 60%, respectively. Propranolol displayed slightly less alteration in its profile at 50%, followed by nifedipine and enalapril at 30% and rounded out by metolazone at 20% alteration. Both herbal supplements appear to have the potential to cause harmful herb drug interactions, but further studies need to be conducted to determine the relevance of the data by extending these studies to an in vivo model. This information can be used to increase awareness about the potential for drug phytopharmaceutical interactions for both patients and doctors.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, pas un consensus.
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