Rifampin, a cytochrome P450 3A inducer, decreases plasma concentrations of antipsychotic risperidone in healthy volunteers

Mahatthanatrakul, Werawath; Nontaput, Tharinee; Ridtitid, Wibool; Wongnawa, Malinee; Sunbhanich, Methi

doi:10.1111/j.1365-2710.2007.00811.x

Cited by 46 publications

(27 citation statements)

References 28 publications

(34 reference statements)

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“…In particular, the function pathways coincided with previously reported rifampin-induced biological functions. For example, rifampin affected the hepatic drug disposition and metabolism [28, 29] and it was a potent inducer of drug-metabolizing enzymes [6, 29–31]. Rifampin is also an inhibitor which rapidly downregulates angiogenesis and mitogenesis-related genes to target cancer cells [12, 32, 33].…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies have demonstrated that the drug-metabolizing enzymes [6], transporters, and microRNAs (miRNAs) are regulated by rifampin [11, 12], and the mechanisms of the regulation of some of these genes are well-studied; however, little has been done to put the global gene expression effects of rifampin into biological pathways and interactive networks. Protein interaction network can depict and integrate information pertaining to domain architecture, post-translational modification, interaction networks and disease association for each protein in the human proteome [13].…”

Section: Introductionmentioning

confidence: 99%

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Identification of rifampin-regulated functional modules and related microRNAs in human hepatocytes based on the protein interaction network

Wang

et al. 2016

BMC Genomics

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BackgroundIn combination with gene expression profiles, the protein interaction network (PIN) constructs a dynamic network that includes multiple functional modules. Previous studies have demonstrated that rifampin can influence drug metabolism by regulating drug-metabolizing enzymes, transporters, and microRNAs (miRNAs). Rifampin induces gene expression, at least in part, by activating the pregnane X receptor (PXR), which induces gene expression; however, the impact of rifampin on global gene regulation has not been examined under the molecular network frameworks.MethodsIn this study, we extracted rifampin-induced significant differentially expressed genes (SDG) based on the gene expression profile. By integrating the SDG and human protein interaction network (HPIN), we constructed the rifampin-regulated protein interaction network (RrPIN). Based on gene expression measurements, we extracted a subnetwork that showed enriched changes in molecular activity. Using the Kyoto Encyclopedia of Genes and Genomes (KEGG), we identified the crucial rifampin-regulated biological pathways and associated genes. In addition, genes targeted by miRNAs that were significantly differentially expressed in the miRNA expression profile were extracted based on the miRNA-gene prediction tools. The miRNA-regulated PIN was further constructed using associated genes and miRNAs. For each miRNA, we further evaluated the potential impact by the gene interaction network using pathway analysis.Results and DisccussionWe extracted the functional modules, which included 84 genes and 89 interactions, from the RrPIN, and identified 19 key rifampin-response genes that are associated with seven function pathways that include drug response and metabolism, and cancer pathways; many of the pathways were supported by previous studies. In addition, we identified that a set of 6 genes (CAV1, CREBBP, SMAD3, TRAF2, KBKG, and THBS1) functioning as gene hubs in the subnetworks that are regulated by rifampin. It is also suggested that 12 differentially expressed miRNAs were associated with 6 biological pathways.ConclusionsOur results suggest that rifampin contributes to changes in the expression of genes by regulating key molecules in the protein interaction networks. This study offers valuable insights into rifampin-induced biological mechanisms at the level of miRNAs, genes and proteins.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2909-6) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of rifampin-regulated functional modules and related microRNAs in human hepatocytes based on the protein interaction network

Wang

et al. 2016

BMC Genomics

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“…CYP3A4 is abundant in human liver microsomes and plays an important role in the metabolism of many drugs, including anticancer drugs. Furthermore, CYP3A4 shows about five-to tenfold inter-patient variability [25][26][27] in the disposition of these drugs metabolic efficiency, and intra-patient variability is widely recognized for several major inducers [28,29] or inhibitors [30,31].…”

Section: Discussionmentioning

confidence: 99%

Phase I dose-finding and pharmacokinetic study of docetaxel and gefitinib in patients with advanced or metastatic non-small-cell lung cancer: evaluation of drug–drug interaction

Motonaga

Yamamoto²,

Makino

et al. 2015

Cancer Chemother Pharmacol

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“…Inhibition of CYP3A4 by ketoconazole has been shown to result in increased plasma concentrations or decreased clearance of several atypical antipsychotics, including clozapine, quetiapine, ziprasidone, and risperidone [19][20][21]. Studies in healthy volunteers have shown that rifampin decreases plasma concentrations and increases clearance of risperidone [22,23], and there is evidence implicating rifampin in a clinically significant interaction with clozapine [24]. Such interactions may also be anticipated with quetiapine [20].…”

Section: Discussionmentioning

confidence: 99%

Lurasidone drug-drug interaction studies: a comprehensive review

Chiu

Ereshefsky

Preskorn

et al. 2014

Drug Metabolism and Drug Interactions

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Background: To evaluate potential drug-drug interactions with the atypical antipsychotic lurasidone. Methods: Seven phase I studies were conducted to investigate the effects of repeated dosing of ketoconazole, diltiazem, rifampin, or lithium on the pharmacokinetics (PK) of single oral doses of lurasidone, or the effects of repeated dosing of lurasidone on the PK of digoxin, midazolam, or the oral contraceptive norgestimate/ethinyl estradiol. Two 6-week, phase III studies included evaluation of the potential for interaction between lurasidone and lithium or valproate. Maximum serum or plasma concentration (C max ) and area under the concentration-time curve (AUC) were calculated. Results: Concomitant ketoconazole administration resulted in a 6.8-fold increase in lurasidone C max and a 9.3-fold increase in lurasidone AUC; concomitant diltiazem administration resulted in 2.1-and 2.2-fold increases, respectively. Rifampin decreased lurasidone C max and AUC (one-seventh and onefifth of lurasidone alone, respectively). Steady-state dosing with lurasidone increased C max and AUC 0-24 (AUC from time 0 to 24 h postdose) of digoxin by 9% and 13%, respectively, and of midazolam by 21% and 44%, respectively. There were no significant interactions between lurasidone and lithium, valproate, ethinyl estradiol, or norelgestromin (the major active metabolite of norgestimate). Conclusions: Lurasidone PK is altered by strong cytochrome P450 (CYP) 3A4 inhibitors or inducers, and coadministration is contraindicated; whereas moderate CYP3A4 inhibitors have less effect, and lurasidone dosage restrictions are recommended. No dose adjustment

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Rifampin, a cytochrome P450 3A inducer, decreases plasma concentrations of antipsychotic risperidone in healthy volunteers

Cited by 46 publications

References 28 publications

Identification of rifampin-regulated functional modules and related microRNAs in human hepatocytes based on the protein interaction network

Identification of rifampin-regulated functional modules and related microRNAs in human hepatocytes based on the protein interaction network

Phase I dose-finding and pharmacokinetic study of docetaxel and gefitinib in patients with advanced or metastatic non-small-cell lung cancer: evaluation of drug–drug interaction

Lurasidone drug-drug interaction studies: a comprehensive review

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