Creatine kinase elevation caused by a combination of fluvastatin and telmisartan in a patient heterozygous for the CYP2C9*3 and ABCC2 -24C > T variants: a case report

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Drug-induced liver injury after switching from tamoxifen to anastrozole in a patient with a history of breast cancer being treated for hypertension and diabetes

Anastrozole is a selective non-steroidal aromatase inhibitor that blocks the conversion of androgens to estrogens in peripheral tissues. It is used as adjuvant therapy for early-stage hormone-sensitive breast cancer in postmenopausal women. Significant side effects of anastrozole include osteoporosis and increased levels of cholesterol. To date, seven case reports on anastrozole hepatotoxicity have been published. We report the case of an 81-year-old woman with a history of breast cancer, arterial hypertension, type 2 diabetes mellitus, hyperlipidemia, and chronic renal insufficiency. Four days after switching hormone therapy from tamoxifen to anastrozole, icterus developed along with a significant increase in liver enzymes (measured in the blood). The patient was admitted to hospital, where a differential diagnosis of jaundice was made and anastrozole was withdrawn. Subsequently, hepatic functions quickly normalized. The observed liver injury was attributed to anastrozole since other possible causes of jaundice were excluded. However, concomitant pharmacotherapy could have contributed to the development of jaundice and hepatotoxicity, after switching from tamoxifen to anastrozole since several the patient’s medications were capable of inhibiting hepatobiliary transport of bilirubin, bile acids, and metabolized drugs through inhibition of ATP-binding cassette proteins. Telmisartan, tamoxifen, and metformin all block bile salt efflux pumps. The efflux function of multidrug resistance protein 2 is known to be reduced by telmisartan and tamoxifen and breast cancer resistance protein is known to be inhibited by telmisartan and amlodipine. Moreover, the activity of P-glycoprotein transporters are known to be decreased by telmisartan, amlodipine, gliquidone, as well as the previously administered tamoxifen. Finally, the role of genetic polymorphisms of cytochrome P450 enzymes and/or drug transporters cannot be ruled out since the patient was not tested for polymorphisms.

Drug-drug-gene interactions and adverse drug reactions

The economic and health burden caused by adverse drug reactions has increased dramatically in the last few years. This is likely to be mediated by increasing polypharmacy, which increases the likelihood for drug–drug interactions. Tools utilized by healthcare practitioners to flag potential adverse drug reactions secondary to drug–drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To date there have been limited published studies on impact of genetic variation on drug–drug interactions. In this review, we establish a detailed classification for pharmacokinetic drug–drug–gene interactions, and give examples from the literature that support this approach. The increasing availability of real-world drug outcome data linked to genetic bioresources is likely to enable the discovery of previously unrecognized, clinically important drug–drug–gene interactions.

Complex Drug-Drug-Gene-Disease Interactions Involving Cytochromes P450: Systematic Review of Published Case Reports and Clinical Perspectives

Drug pharmacokinetics (PK) is influenced by multiple intrinsic and extrinsic factors, among which concomitant medications are responsible for drug-drug interactions (DDIs) that may have a clinical relevance, resulting in adverse drug reactions or reduced efficacy. The addition of intrinsic factors affecting cytochromes P450 (CYPs) activity and/or expression, such as genetic polymorphisms and diseases, may potentiate the impact and clinical relevance of DDIs. In addition, greater variability in drug levels and exposures has been observed when such intrinsic factors are present in addition to concomitant medications perpetrating DDIs. This variability results in poor predictability of DDIs and potentially dramatic clinical consequences. The present review illustrates the issue of complex DDIs using systematically searched published case reports of DDIs involving genetic polymorphisms, renal impairment, cirrhosis, and/or inflammation. Current knowledge on the impact of each of these factors on drug exposure and DDIs is summarized and future perspectives for the management of such complex DDIs in clinical practice are discussed, including the use of advanced Computerized Physician Order Entry (CPOE) systems, the development of model-based dose optimization strategies, and the education of healthcare professionals with respect to personalized medicine.

An update on efflux and uptake transporters as determinants of statin response

INTRODUCTION

Statins are used in the treatment of dyslipidemia promoting primary and secondary prevention against detrimental cardiovascular events. ATP-binding cassette (ABC) and solute carrier (SLC) membrane transporters transport statins across the cell membrane. Differences in drug transporter tissue expression and activity contribute to variability in statin pharmacokinetics (PK) and response. Areas covered: The purpose of this review is to discuss factors impacting transporter expression and the effect this has on statin efficacy and safety. Previous studies have demonstrated that genetic polymorphisms, drug-drug interactions (DDI), nuclear receptors, and microRNAs affect statin PK and pharmacodynamics. Expert opinion: Genetic variants of ABCG2 and SLCO1B1 transporters affect statin PK and, as a result, the intended lipid-lowering response. However, the effect size is small, limiting its applicability in clinical practice. Furthermore, genetic variants do not totally explain the observed intervariability in statin response. Thus, it is likely that transcriptional and post-transcriptional regulation of drug transporters are also highly involved. Further studies are required to understand the contribution of each of these new factors in statin disposition and toxicity.

Effect modification by region in the associations of LEP G2548A and LEPR Q223R polymorphisms with statin-induced CK elevation

We investigated the associations of LEP G2548A and LEPR Q223R polymorphisms with statin-induced creatine kinase (CK) elevation among Chinese patients with hyperlipidemia. A total of587 enrolled individuals were treated with 20 mg/d oral simvastatin for 8 consecutive weeks. Genotyping of LEP G2548A and LEPR Q223R were conducted using PCR-RFLP. Multiple regression analyses showed that, in the Dongzhi region only, patients carrying the LEP AA genotype had a significantly greater increase in CK levels compared to those carrying the AG+GG genotypes after four weeks (P = 0.004) and eight weeks (P < 0.001) consecutive simvastatin treatment. Patients were further divided into three groups based on the tertiles of the CK distribution. Compared to subjects in the lowest tertile of CK elevation, the adjusted relative odds of having the AG+GG genotypes among subjects in the highest tertile was 0.5 (95% CI, 0.3 to 0.7) and 0.4 (95% CI, 0.2 to 0.6) after the fourth and eighth weeks, respectively. The interaction terms between the Beijing or Dongzhi region and the LEP GA+AA genotypes were marginally significant for CK elevation at the fourth week (P = 0.057) and significant for CK elevation at the eighth week (P = 0.002). The adverse effect of the LEP G2548A polymorphism on increasing CK levels may be dependent on the environmental milieu. It suggests that lifestyle interventions might offset the side effects of simvastatin therapy among those with genetic susceptibility. Further research is needed to identify specific individual-level factors for clinical practice that modify the effect of genotype.

Identification and characterization of fluvastatin metabolites in rats by UHPLC/Q-TOF/MS/MS and in silico toxicological screening of the metabolites

The present study reports the in vivo and in vitro identification and characterization of metabolites of fluvastatin, the 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitor, using liquid chromatography-mass spectrometry (LC-MS). In vitro studies were conducted by incubating the drug with human liver microsomes and rat liver microsomes. In vivo studies were carried out by administration of the drug in the form of suspension to the Sprague-Dawley rats followed by collection of urine, faeces and blood at different time points up to 24 h. Further, samples were prepared by optimized sample preparation method, which includes freeze liquid extraction, protein precipitation and solid phase extraction. The extracted and concentrated samples were analysed using ultrahigh-performance liquid chromatography-quadruple time-of-flight tandem mass spectrometry. A total of 15 metabolites were observed in urine, which includes hydroxyl, sulphated, desisopropyl, dehydrogenated, dehydroxylated and glucuronide metabolites. A few of the metabolites were also present in faeces and plasma samples. In in vitro studies, a few metabolites were observed that were also present in in vivo samples. All the metabolites were characterized using ultrahigh-performance liquid chromatography-quadruple time-of-flight tandem mass spectrometry in combination with accurate mass measurement. Finally, in silico toxicity studies indicated that some of the metabolites show or possess carcinogenicity and skin sensitization. Several metabolites that were identified in rats are proposed to have toxicological significance on the basis of in silico evaluation. However, these metabolites are of no human relevance. Copyright © 2017 John Wiley & Sons, Ltd.

Current and Emerging Uses of Statins in Clinical Therapeutics: A Review

Statins, a class of cholesterol-lowering medications that inhibit 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase, are commonly administered to treat atherosclerotic cardiovascular disease. Statin use may expand considerably given its potential for treating an array of cholesterol-independent diseases. However, the lack of conclusive evidence supporting these emerging therapeutic uses of statins brings to the fore a number of unanswered questions including uncertainties regarding patient-to-patient variability in response to statins, the most appropriate statin to be used for the desired effect, and the efficacy of statins in treating cholesterol-independent diseases. In this review, the adverse effects, costs, and drug–drug and drug–food interactions associated with statin use are presented. Furthermore, we discuss the pleiotropic effects associated with statins with regard to the onset and progression of autoimmune and inflammatory diseases, cancer, neurodegenerative disorders, strokes, bacterial infections, and human immunodeficiency virus. Understanding these issues will improve the prognosis of patients who are administered statins and potentially expand our ability to treat a wide variety of diseases.