Lipid-lowering effect of fluvastatin in relation to cytochrome P450 2C9 variant alleles frequently distributed in the Czech population

Genetic variation of CYP2C9 gene and its correlation with cardiovascular disease risk factors

BACKGROUND

The major enzyme that is responsible for Sulfonylureas (SUs) metabolism is hepatic cytochrome P-450 2C9 (CYP2C9). It is encoded by the polymorphic gene CYP2C9, which has many allelic variants, among those the CYP2C9*2 and CYP2C9*3 are the most common and clinically significant allelic variations. People with diabetes mellitus type 2 (T2DM) are more likely to develop cardiovascular disease (CVD), and their risk of dying from it is more than two times higher than that of people without the condition. The purpose of this study was to evaluate the association of genetic variations in the CYP2C9 gene with cardiovascular risk factors by investigating CYP2C9*1, *2, *3, *5, *11, and *13 allelic variants.

METHODS AND RESULTS

A total of 226 participants were enrolled in the current case-control study. Allele-specific amplification- PCR (ASA-PCR) was used to determine the allele of different variations and the results were confirmed by sequencing. The findings of this study showed the presence of the CYP2C9*2 allele in the T2DM group does not differ from its percentage in the control group. Also, CYP2C9*3 allele frequencies identified by Hardy-Weinberg equilibrium (HWE) analysis law were not significant, p = 0.6593 and 0.5828 in T2DM and control groups. There is no statistically significant difference between the control and diabetes groups involving the distribution of CYP2C9 alleles and CYP2C9*5, *11, and *13 polymorphisms were absent in the Iraqi population. No carrier for the CYP2C9*3 homozygous state was found in both groups.

CONCLUSIONS

According to these results T2DM patients with the CYP2C9*2 and *3 variants have an increased risk of developing hypertension.

Pharmacogenomics of Cardiovascular Drugs for Atherothrombotic, Thromboembolic and Atherosclerotic Risk

PURPOSE OF REVIEW

Advances in pharmacogenomics have paved the way for personalized medicine. Cardiovascular diseases still represent the leading cause of mortality in the world. The aim of this review is to summarize the background, rationale, and evidence of pharmacogenomics in cardiovascular medicine, in particular, the use of antiplatelet drugs, anticoagulants, and drugs used for the treatment of dyslipidemia.

RECENT FINDINGS

Randomized clinical trials have supported the role of a genotype-guided approach for antiplatelet therapy in patients with coronary heart disease undergoing percutaneous coronary interventions. Numerous studies demonstrate how the risk of ineffectiveness of new oral anticoagulants and vitamin K anticoagulants is linked to various genetic polymorphisms. Furthermore, there is growing evidence to support the association of some genetic variants and poor adherence to statin therapy, for example, due to the appearance of muscular symptoms. There is evidence for resistance to some drugs for the treatment of dyslipidemia, such as anti-PCSK9.

SUMMARY

Pharmacogenomics has the potential to improve patient care by providing the right drug to the right patient and could guide the identification of new drug therapies for cardiovascular disease. This is very important in cardiovascular diseases, which have high morbidity and mortality. The improvement in therapy could be reflected in the reduction of healthcare costs and patient mortality.

Pharmacogenomic variants affecting efficacy and toxicity of statins in a south Asian population from Sri Lanka

Aim: To describe the diversity of pharmacogenetic variants of statins among Sri Lankans. Materials & methods: Variant data of relevant genes were obtained from an anonymized database of 426 Sri Lankans. Minor allele frequencies (MAFs) were compared with published data from other populations. Results: The MAF of SLCO1B1*5 (rs4149056 [T>C]) was 18.19% (95% CI: 14.53-21.85). MAFs of CYP2C9*2 (rs1799853 [C>T]) and CYP2C9*3 (rs1057910 [A>C]) were 2.58% (95% CI: 1.08-4.08) and 10.30% (95% CI: 7.75-13.61), respectively. MAFs of rs2231142 (G>T) (ABCG2), rs7412 (C>T) (APOE) and rs20455 (A>G) (KIF6) variants were 10.68% (95% CI: 7.76-13.60), 3.52% (95% CI: 1.77-5.27) and 50.7% (95% CI: 45.96-55.45), respectively. Compared with western/other Asian populations, rs20455 (A>G), CYP2C9*3 (A>C) and SLCO1B1*5 (T>C) variants were significantly higher in Sri Lankans. Conclusion: Variants that affect efficacy of statins (KIF6 [rs20455], CYP2C9*3) and increase risk of statin-induced myotoxicity (SLCO1B1*5 and CYP2C9*3) were prevalent in higher frequencies among Sri Lankans compared with western populations.

Associations between SLCO1B1, APOE and CYP2C9 and lipid-lowering efficacy and pharmacokinetics of fluvastatin: a meta-analysis

Objective: This meta-analysis was designed to investigate the associations between SLCO1B1, APOE and CYP2C9 and the lipid-lowering effects and pharmacokinetics of fluvastatin. Methods: Studies were searched from inception to March 2023, including three SNPs related to fluvastatin, SLCO1B1, CYP2C9 and APOE. Weighted mean differences and corresponding 95% CIs were analyzed to evaluate the associations between SNPs and outcomes. Results: SLCO1B1 521T>C was associated with lower total cholesterol and low-density lipoprotein reduction. Patients carrying 521CC or total cholesterol had a significantly higher area under the curve than those carrying 521TT, but no significant difference existed. Conclusion: CYP2C9 and SLCO1B1 may be associated with the efficacy and pharmacokinetics of fluvastatin.

Precision Nephrology in Patients with Diabetes and Chronic Kidney Disease

Diabetes is the leading cause of kidney failure and specifically, diabetic kidney disease (DKD) occurs in up to 30% of all diabetic patients. Kidney disease attributed to diabetes is a major contributor to the global burden of the disease in terms of clinical and socio-economic impact, not only because of the risk of progression to End-Stage Kidney Disease (ESKD), but also because of the associated increase in cardiovascular (CV) risk. Despite the introduction of novel treatments that allow us to reduce the risk of future outcomes, a striking residual cardiorenal risk has been reported. This risk is explained by both the heterogeneity of DKD and the individual variability in response to nephroprotective treatments. Strategies that have been proposed to improve DKD patient care are to develop novel biomarkers that classify with greater accuracy patients with respect to their future risk (prognostic) and biomarkers that are able to predict the response to nephroprotective treatment (predictive). In this review, we summarize the principal prognostic biomarkers of type 1 and type 2 diabetes and the novel markers that help clinicians to individualize treatments and the basis of the characteristics that predict an optimal response.

Combining familial hypercholesterolemia and statin genetic studies as a strategy for the implementation of pharmacogenomics. A multidisciplinary approach

The diagnostic process of familial hypercholesterolemia frequently involves the use of genetic studies. Patients are treated with lipid-lowering drugs, frequently statins. Although pharmacogenomic clinical practice guidelines focusing on genotype-based statin prescription have been published, their use in routine clinical practice remains very modest.We have implemented a new NGS strategy that combines a panel of genes related to familial hypercholesterolemia with genomic regions related to the pharmacogenomics of lipid-lowering drugs described in clinical practice guidelines and in EMA and FDA drug labels. A multidisciplinary team of doctors, biologists, and pharmacists creates a clinical report that provides diagnostic and therapeutic findings using a knowledge management and clinical decision support system, as well as an algorithm for treatment selection.For 12 months, a total of 483 genetic diagnostic studies for familial hypercholesterolemia were carried out, of which 221 (45.8%) requested a complementary pharmacogenomic test. Of these 221 patients, 66.5% were carriers of actionable variants in any of the studied pharmacogenomic pathways: 46.6% of patients in one pathway, 19.0% in two pathways, and 0.9% in three pathways. 45.7% of patients could have a response to atorvastatin different from that of the reference population, 45.7% for simvastatin and lovastatin, 29.0% for fluvastatin, and 6.7% patients for pitavastatin.This implementation approach facilitates the incorporation of pharmacogenomic studies in clinical care practice, it does not add complexity nor additional steps to laboratory processes, and improves the pharmacotherapeutic process of patients.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Relationship between genetic polymorphism of drug transporters and the efficacy of Rosuvastatin, atorvastatin and simvastatin in patients with hyperlipidemia

Background

To determine the effect of genetic polymorphism of drug transporters on the efficacy of treatment with Rosuvastatin, Atorvastatin and Simvastatin in patients with hyperlipidemia.

Methods

The study consists of 180 patients, aged 40–75 years, with hyperlipidemia. All patients were divided into two equal groups: patients with different SLCO1B1 (521CC, 521CT and 521TT) and MDR1 (3435CC, 3435TC and 3435TT) genotypes. Each group was divided into rosuvastatin-treated, atorvastatin-treated and simvastatin-treated subgroups. The lipid-lowering effect of statins was assessed by tracing changes in total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels.

Results

The use of statins over a 4-month period led to substantial reductions in TC and LDL-C levels. The hypolipidemic effect of studied agents was seen in both groups. However, it was less pronounced in patients with 521CC genotype. No statistically significantly differences were found between carriers of 3435TT, 3435CT and 3435CC genotypes.

Conclusions

The lipid-lowering efficacy of rosuvastatin was higher compared to other two statins. Patients with SLCO1B1 521CC genotype are more likely to encounter a decrease in the hypolipidemic effect of statins. Such a risk should be considered when treating this category of patients. MDR1 polymorphism had no significant effect on statin efficacy.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

The influence of genetic polymorphisms in drug metabolism enzymes and transporters on the pharmacokinetics of different fluvastatin formulations

The purpose of the present study was to investigate the impact of genetic polymorphism on fluvastatin pharmacokinetics. In addition, we compared the fluvastatin pharmacokinetics differences between extended-release (ER) 80 mg tablet and immediate-release (IR) 40 mg capsule in terms of drug metabolism enzyme and transporter genetic polymorphisms. In this open-label, randomized, two-period, two-treatment, crossover study (n = 24), effects of ABCG2, SLCO1B1, ABCB1, CYP2C9 and CYP3A5 polymorphisms on the pharmacokinetics of fluvastatin were analyzed. The administration dosage for IR 40 mg and ER 80 mg were twice and once daily, respectively, for total 7 d. Blood samples for pharmacokinetic evaluation were taken on the 1st and 7th d. The lower exposure following ER was observed. For ER tablets, SLCO1B1 T521C genotype correlated with AUC_0-24 of repeat doses (P = 0.010). SLCO1B1 T521C genotype had no statistically significant effect on AUC_0-24 of IR capsule of fluvastatin after single or repeated doses. In vitro study demonstrated that when the concentration of fluvastatin was low (< 1 µmol/l), the uptake of fluvastatin in the HEK293-OATP1B1 with SLCO1B1 521TT (K_m =0.18 µmol/l) was faster than that with SLCO1B1 521CC (K_m =0.49 µmol/l), On the other hand, when concentration reached to higher level (> 1 µmol/l), transport velocity of fluvastatin by HEK293-OATP1B1 with SLCO1B1 521TT (K_m  = 11.4 µmol/l) and with SLCO1B1 521TCC (K_m =15.1 µmol/l) tend to be the same. It suggests that the increased effect of SLCO1B1 T521C genotype on ER formulation of fluvastatin was mainly caused by lower blood concentrations. We recommend that formulation should be incorporated into future pharmacogenomics studies.

Pharmacogenetics of statins treatment: Efficacy and safety

WHAT IS KNOWN AND OBJECTIVE

Statins are widely used worldwide in the prevention and treatment of coronary atherosclerotic heart disease and ischaemic stroke. However, in clinical application, statins have shown great individual differences in terms of the efficacy and safety, some of which are related to genetic factors. The purpose of this article was to summarize the recent advances about the correlation between gene polymorphisms and the efficacy/safety of statins.

METHODS

We searched the databases including PharmGKB and PubMed (published before June 2019) using the keywords such as 'statin', 'gene polymorphism' and 'SNP' and obtained more than 100 articles. In this review, we described the clinical studies of genetic variants associated with both the efficacy and adverse reactions of statins. We also clarified the importance of taking pharmacogenetic variation into account to improve the clinical application of statins.

RESULTS AND DISCUSSION

The available data were collected and analysed to present the polymorphisms of candidate genes encoding the most promising proteins including SLCO1B1 (encoding uptake transporters); ABCB1, ABCC2, ABCG2 (encoding effluent transporter); APOE, APOA5 (encoding apolipoprotein); genes encoding cytochrome P450 enzyme system; KIF6, HMGCR, LDLR, LPA, PCSK9, COQ2, CETP, etc These genes were proved to be related to the pharmacodynamics and pharmacokinetics of statins, thus affecting the efficacy and safety.

WHAT IS NEW AND CONCLUSION

In this paper, the correlation between gene polymorphisms and the efficacy/safety of statins was summarized. The authors reached a consensus that the variants of the genes encoding uptake and effluent transporters have the most effect on the efficacy/safety of statins. It pointed out that it is desirable to do genetic testing of these transporter genes to reduce the incidence of myopathy or to achieve better outcomes before patients use statins, especially in the regions with high frequency of risk allele.

Enantiospecific Pharmacogenomics of Fluvastatin

The aim of this study was to investigate how variability in multiple genes related to pharmacokinetics affects fluvastatin exposure. We determined fluvastatin enantiomer pharmacokinetics and sequenced 379 pharmacokinetic genes in 200 healthy volunteers. CYP2C9*3 associated with significantly increased area under the plasma concentration-time curve (AUC) of both 3R,5S-fluvastatin and 3S,5R-fluvastatin (by 67% and 94% per variant allele copy, P = 3.77 × 10^-9 and P = 3.19 × 10^-12 ). In contrast, SLCO1B1 c.521T>C associated with increased AUC of active 3R,5S-fluvastatin only (by 34% per variant allele copy; P = 8.15 × 10^-8 ). A candidate gene analysis suggested that CYP2C9*2 also affects the AUC of both fluvastatin enantiomers and that SLCO2B1 single-nucleotide variations may affect the AUC of 3S,5R-fluvastatin. Thus, SLCO transporters have enantiospecific effects on fluvastatin pharmacokinetics in humans. Genotyping of both CYP2C9 and SLCO1B1 may be useful in predicting fluvastatin efficacy and myotoxicity.

Targeting the Mevalonate Pathway Suppresses VHL-Deficient CC-RCC through an HIF-Dependent Mechanism

Clear cell renal cell carcinoma (CC-RCC) is a devastating disease with limited therapeutic options available for advanced stages. The objective of this study was to investigate HMG-CoA reductase inhibitors, also known as statins, as potential therapeutics for CC-RCC. Importantly, treatment with statins was found to be synthetically lethal with the loss of the von Hippel-Lindau (VHL) tumor suppressor gene, which occurs in 90% of CC-RCC driving the disease. This effect has been confirmed in three different CC-RCC cell lines with three different lipophilic statins. Inhibition of mevalonate synthesis by statins causes a profound cytostatic effect at nanomolar concentrations and becomes cytotoxic at low micromolar concentrations in VHL-deficient CC-RCC. The synthetic lethal effect can be fully rescued by both mevalonate and geranylgeranylpyrophosphate, but not by squalene, indicating that the effect is due to disruption of small GTPase isoprenylation and not the inhibition of cholesterol synthesis. Inhibition of Rho and Rho kinase (ROCK) signaling contributes to the synthetic lethality effect, and overactivation of hypoxia-inducible factor signaling resulting from VHL loss is required. Finally, statin treatment is able to inhibit both tumor initiation and progression of subcutaneous 786-OT1-based CC-RCC tumors in mice. Thus, statins represent potential therapeutics for the treatment of VHL-deficient CC-RCC. Mol Cancer Ther; 17(8); 1781-92. ©2018 AACR.

Fluvastatin for lowering lipids

BACKGROUND

Fluvastatin is thought to be the least potent statin on the market, however, the dose-related magnitude of effect of fluvastatin on blood lipids is not known.

OBJECTIVES

Primary objectiveTo quantify the effects of various doses of fluvastatin on blood total cholesterol, low-density lipoprotein (LDL cholesterol), high-density lipoprotein (HDL cholesterol), and triglycerides in participants with and without evidence of cardiovascular disease.Secondary objectivesTo quantify the variability of the effect of various doses of fluvastatin.To quantify withdrawals due to adverse effects (WDAEs) in randomised placebo-controlled trials.

SEARCH METHODS

The Cochrane Hypertension Information Specialist searched the following databases for randomised controlled trials up to February 2017: the Cochrane Central Register of Controlled Trials (CENTRAL) (2017, Issue 1), MEDLINE (1946 to February Week 2 2017), MEDLINE In-Process, MEDLINE Epub Ahead of Print, Embase (1974 to February Week 2 2017), the World Health Organization International Clinical Trials Registry Platform, CDSR, DARE, Epistemonikos and ClinicalTrials.gov. We also contacted authors of relevant papers regarding further published and unpublished work. No language restrictions were applied.

SELECTION CRITERIA

Randomised placebo-controlled and uncontrolled before and after trials evaluating the dose response of different fixed doses of fluvastatin on blood lipids over a duration of three to 12 weeks in participants of any age with and without evidence of cardiovascular disease.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed eligibility criteria for studies to be included, and extracted data. We entered data from placebo-controlled and uncontrolled before and after trials into Review Manager 5 as continuous and generic inverse variance data, respectively. WDAEs information was collected from the placebo-controlled trials. We assessed all trials using the 'Risk of bias' tool under the categories of sequence generation, allocation concealment, blinding, incomplete outcome data, selective reporting, and other potential biases.

MAIN RESULTS

One-hundred and forty-five trials (36 placebo controlled and 109 before and after) evaluated the dose-related efficacy of fluvastatin in 18,846 participants. The participants were of any age with and without evidence of cardiovascular disease, and fluvastatin effects were studied within a treatment period of three to 12 weeks. Log dose-response data over doses of 2.5 mg to 80 mg revealed strong linear dose-related effects on blood total cholesterol and LDL cholesterol and a weak linear dose-related effect on blood triglycerides. There was no dose-related effect of fluvastatin on blood HDL cholesterol. Fluvastatin 10 mg/day to 80 mg/day reduced LDL cholesterol by 15% to 33%, total cholesterol by 11% to 25% and triglycerides by 3% to 17.5%. For every two-fold dose increase there was a 6.0% (95% CI 5.4 to 6.6) decrease in blood LDL cholesterol, a 4.2% (95% CI 3.7 to 4.8) decrease in blood total cholesterol and a 4.2% (95% CI 2.0 to 6.3) decrease in blood triglycerides. The quality of evidence for these effects was judged to be high. When compared to atorvastatin and rosuvastatin, fluvastatin was about 12-fold less potent than atorvastatin and 46-fold less potent than rosuvastatin at reducing LDL cholesterol. Very low quality of evidence showed no difference in WDAEs between fluvastatin and placebo in 16 of 36 of these short-term trials (risk ratio 1.52 (95% CI 0.94 to 2.45).

AUTHORS' CONCLUSIONS

Fluvastatin lowers blood total cholesterol, LDL cholesterol and triglyceride in a dose-dependent linear fashion. Based on the effect on LDL cholesterol, fluvastatin is 12-fold less potent than atorvastatin and 46-fold less potent than rosuvastatin. This review did not provide a good estimate of the incidence of harms associated with fluvastatin because of the short duration of the trials and the lack of reporting of adverse effects in 56% of the placebo-controlled trials.

Pharmacogenetic Foundations of Therapeutic Efficacy and Adverse Events of Statins

Background: In the era of precision medicine, more attention is paid to the search for predictive markers of treatment efficacy and tolerability. Statins are one of the classes of drugs that could benefit from this approach because of their wide use and their incidence of adverse events. Methods: Literature from PubMed databases and bibliography from retrieved publications have been analyzed according to terms such as statins, pharmacogenetics, epigenetics, toxicity and drug–drug interaction, among others. The search was performed until 1 October 2016 for articles published in English language. Results: Several technical and methodological approaches have been adopted, including candidate gene and next generation sequencing (NGS) analyses, the latter being more robust and reliable. Among genes identified as possible predictive factors associated with statins toxicity, cytochrome P450 isoforms, transmembrane transporters and mitochondrial enzymes are the best characterized. Finally, the solute carrier organic anion transporter family member 1B1 (SLCO1B1) transporter seems to be the best target for future studies. Moreover, drug–drug interactions need to be considered for the best approach to personalized treatment. Conclusions: Pharmacogenetics of statins includes several possible genes and their polymorphisms, but muscular toxicities seem better related to SLCO1B1 variant alleles. Their analysis in the general population of patients taking statins could improve treatment adherence and efficacy; however, the cost–efficacy ratio should be carefully evaluated.

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.

Seventeen years of statin pharmacogenetics: a systematic review

AIM

We evaluated the evidence of pharmacogenetic associations with statins in a systematic review.

METHODS

Two separate outcomes were considered of interest: modification of low-density lipoprotein cholesterol (LDL-C) response and modification of risk for cardiovascular events.

RESULTS

In candidate gene studies, 141 loci were claimed to be associated with LDL-C response. Only 5% of these associations were positively replicated. In addition, six genome-wide association studies of LDL-C response identified common SNPs in APOE, LPA, SLCO1B1, SORT1 and ABCG2 at genome-wide significance. None of the investigated SNPs consistently affected the risk reduction for cardiovascular events.

CONCLUSION

Only five genetic loci were consistently associated with LDL-C response. However, as effect sizes are modest, there is no evidence for the value of genetic testing in clinical practice.

Drug-drug interactions that interfere with statin metabolism

INTRODUCTION

Lipid-lowering drugs, especially hydroxymethylglutaryl-CoA reductase inhibitors (statins), are widely used in the treatment and prevention of atherosclerotic diseases. The benefits of statins are well documented. However, myotoxic side effects, which can sometimes be severe, including myopathy or rhabdomyolysis, have been associated with the use of statins. In some cases, this toxicity is associated with pharmacokinetic alterations. Potent inhibitors of CYP 3A4 significantly increase plasma concentrations of the active forms of simvastatin, lovastatin and atorvastatin. Fluvastatin is metabolized by CYP2C9, while pravastatin, rosuvastatin and pitavastatin are not susceptible to inhibition by any CYP.

AREAS COVERED

This review discusses the pharmacokinetic aspects of the drug-drug interaction with statins and genetic polymorphisms in CYPs, which are involved in the metabolism of statins, and highlights the importance of establishing a system utilizing electronic medical information practically to avoid adverse drug reactions.

EXPERT OPINION

An understanding of the mechanisms underlying statin interactions will help to minimize drug interactions and develop statins that are less prone to adverse interactions. Quantitatively analyzed information for the low-density lipoprotein cholesterol lowering effects of statin based on electronic medical records may be useful for avoiding the adverse effect of statins.

The pharmacogenomics of statins

The statin class of cholesterol-lowering drugs have been used for decades to successfully lower plasma cholesterol concentrations and cardiovascular risk. Adverse effects of statins are generally considered mild, but increase with age of patients and polypharmacy. One aspect of statin therapy that is still difficult for prescribers to predict is the individual's response to statin therapy. Recent advances in the field of pharmacogenomics have indicated variants of candidate genes that affect statin efficacy and safety. In this review, a number of candidates that affect statin pharmacokinetics and pharmacodynamics are discussed. Some of these candidates, in particular those involved in import and efflux of statins, have now been linked to increased risk of side effects. Furthermore, pharmacogenomic studies continue to reveal new players that are involved in the fine-tuning of the complex regulation of cholesterol homeostasis and response to statins.