HMG-CoA reductase inhibitor pharmacogenomics: overview and implications for practice

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.

Population pharmacodynamic analysis of LDL-cholesterol lowering effects by statins and co-medications based on electronic medical records

AIMS

HMG-CoA reductase inhibitors are available for use in low density lipoprotein-cholesterol (LDL-C) lowering therapy. The purposes of this study were to develop a population pharmacodynamic (PPD) model to describe the time course for the LDL-C lowering effects of statins and assess the efficacy of combination therapy based on electronic medical records.

METHODS

Patient backgrounds, laboratory tests and prescribed drugs were collected retrospectively from electronic medical records. Patients who received atorvastatin, pitavastatin or rosuvastatin were enrolled. A physiological indirect response model was used to describe the changes observed in LDL-C concentrations. The PPD analysis was performed using nonmem 7.2.0 with the first order conditional estimation method with interaction (FOCE-INTER).

RESULTS

An indirect response Imax model, based on the 2863 LDL-C concentrations of 378 patients, successfully and quantitatively described the time course for the LDL-C lowering effects of three statins. The combination of ezetimibe, a cholesterol absorption inhibitor, decreased the LDL synthesis rate (Kin ) by 10.9%. A simulation indicated that the combined treatment of ezetimibe with rosuvastatin (2.5 mg day(-1) ) led to superior clinical responses than those with high doses of rosuvastatin (5.0 mg day(-1) ) monotherapy, even in patients with higher baseline LDL-C concentrations prior to the treatment.

CONCLUSIONS

A newly constructed PPD model supported previous evidence for the beneficial effects of ezetimibe combined with rosuvastatin. In addition, the established framework is expected to be applicable to other drugs without pharmacokinetic data in clinical practice.

Pharmacogenetics of response to statins

The 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors (statins) are among the most commonly prescribed drugs worldwide. On average, statins improve lipid profiles and have been shown to have ancillary beneficial effects on inflammation, platelet activity, and endothelial function. However, variability in drug response exists regardless of the measured phenotype, and genetic variability may be a contributing factor. Recently, there has been an interesting shift in statin pharmacogenetic studies. Novel study designs have been employed and nontraditional candidate genes have been investigated in relation to both lipid and nonlipid responses to statins. This review outlines earlier pharmacogenetic studies and highlights newly published findings that expand on previous work. Furthermore, a framework is provided in which the necessary next steps in research are described, with the ultimate goal of translating pharmacogenetic findings into clinically meaningful changes in patient care.

Influence of Drug Transporter Polymorphisms on Pravastatin Pharmacokinetics in Humans

The role of drug transporters in pravastatin disposition is underlined by the fact that pravastatin does not undergo significant cytochrome P-450 (CYP)-mediated biotransformation. The organic anion transporting polypeptide 1B1 (OATP1B1), encoded by SLCO1B1, and multidrug resistance-associated protein 2 [MRP2 (ABCC2)], are thought to be the major transporters involved in the pharmacokinetics of pravastatin in humans. Other transporters that may play a role include OATP2B1, organic anion transporter 3 (OAT3), bile salt export pump (BSEP), and the breast cancer resistance protein (BCRP). OATP1B1 and MRP2 mediate the hepatic uptake and biliary excretion of pravastatin, respectively. The SLCO1B1 and ABCC2 polymorphisms probably contribute to the high interindividual variability in pravastatin disposition. Recent small studies have characterized the impact of the SLCO1B1 polymorphism on pravastatin in humans, and especially the c.521T>C single-nucleotide polymorphism (SNP) seems to be an important determinant of pravastatin pharmacokinetics. Pravastatin plasma concentrations may be up to 100% higher in subjects carrying the c.521C variant, as found in the *5, *15, *16, and *17 haplotypes, reflecting diminished OATP1B1-mediated uptake into the major site of pravastatin elimination, the liver. The SLCO1B1 polymorphism seems to have a similar impact on the pharmacokinetics of single- and multiple-dose pravastatin. Overall, 2-5% of individuals in various populations may be expected to show markedly elevated plasma pravastatin concentrations due to the SLCO1B1 polymorphism. Of note, the impact of the SLCO1B1 polymorphism on statins may be dependent on ethnicity. Although individuals with a diminished hepatic uptake of pravastatin might be expected to show reduced cholesterol-lowering efficacy due to lower intracellular pravastatin concentrations, there is preliminary evidence to suggest that the SLCO1B1 polymorphism is not a major determinant of non-response to pravastatin. The possible consequences of drug transporter polymorphisms, especially the SLCO1B1 and ABCC2 polymorphisms, for the lipid-lowering efficacy and tolerability of pravastatin in various ethnic groups warrant further study.

Pharmacogenetics of chronic cardiovascular drugs: applications and implications

Cardiovascular disease continues to be a tremendous worldwide problem, and drug therapy is a major modality to attenuate its burden. At present, conditions such as hypertension, dyslipidaemia and heart failure are pharmacologically managed with an empirical trial-and-error approach. However, it has been suggested that this approach fails to adequately address the therapeutic needs of many patients, and pharmacogenetics has been offered as a tool to enhance patient-specific drug therapy. This review outlines pharmacogenetic studies of common cardiovascular drugs, such as diuretics, beta-blockers, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, statins and warfarin, ultimately highlighting considerations for future research and practice.

Statin response and pharmacokinetics variants

Despite statin therapy being effective in the primary and secondary prevention of coronary heart disease, the benefit of treatment varies between individuals. Interindividual variations in pharmacokinetics play a central role in the cause of variability of drug disposition, and, in turn, the drug's clinical efficacy. Exploring genetic variations that influence pharmacokinetics may lead clinicians to apply the most efficient and safe drug therapy. So far, variants in eight candidate genes related to pharmacokinetics of statins have been investigated as the potential determinant of drug responsiveness or adverse event risk. All reported data remains inconclusive, but it has been suggested that combined analysis of more than two different polymorphisms, or a combination of genetic association and studies using in vitro recombinant expression techniques, may be more informative in predicting the specific phenotype of a genetic variant. Future studies using these approaches could provide more striking evidence, which may be sufficient to justify genetic analysis regarding pharmacokinetic variants in the clinical practice of statin therapy.

Statin pharmacogenomics: what have we learned, and what remains unanswered?

PURPOSE OF REVIEW

Statins are widely prescribed and are established as first-line therapy for the primary and secondary prevention of coronary heart disease. Response to treatment varies considerably from person to person; however, inherited traits (genetic variability) may play a central role in this inter-individual variation. The purpose of this review is to summarize recent progress in the research for exploring genetic determinants of clinical efficacy and safety of statin therapy.

RECENT FINDINGS

In addition to 41 previous studies of 19 genes, the results of 17 pharmacogenomic studies investigating the relationship between common genetic variants and response to statin therapy in terms of lipid responses, clinical outcomes, and adverse events have been reported since January 2004 - 15 candidate genes related to pharmacodynamics and three to pharmacokinetics of statins. These reported data suggest that genetic variations influencing intestinal cholesterol absorption, cholesterol production, and lipoprotein catabolism may all play a role in modulating responsiveness, as well as genes involved in drug metabolism of statins. They also suggest that combined analysis of multiple variants in several genes, all of which have possible functional relations, is more likely to give significant results, especially when being performed with a larger number of participants.

SUMMARY

Pharmacogenomic studies of statin therapy will provide a better picture as to who is most likely and least likely to benefit from treatment, which results in more individualized management of coronary artery disease.

Pharmacogenomics of statin responsiveness

Statins are widely prescribed and are established as first-line therapy for the primary and secondary prevention of coronary artery disease. However, the benefit of treatment varies between patients. Genetic variation can contribute to interindividual variations in clinical efficacy of drug therapy, and significant progress has been made in identifying common genetic polymorphisms that influence responsiveness to statin therapy. To date, >30 candidate genes related to pharmacokinetics and pharmacodynamics of statins have been investigated as potential determinants of drug responsiveness in terms of low-density lipoprotein cholesterol lowering. Genetic variation at gene loci that affect intestinal cholesterol absorption include apolipoprotein (apo) E; adenosine triphosphate-binding cassette transporter G5 and G8; cholesterol production, such as 3-hydroxy-3-methylglutaryl coenzyme A reductase; and lipoprotein catabolism, such as apoB and the low-density lipoprotein receptor, all may play a role in modulating responsivesness as well genes involved in metabolism of statins such as cytochrome P450. However, there is considerable variation in results reported, and the data suggest that combined analysis of multiple genetic variants in several genes, all of which have possible functional significance, is more likely to give significant results than single gene studies in small sample populations. In the future, pharmacogenomic studies with a greater number of participants (>2,000 participants) should provide a better picture as to who is most likely and who is least likely to benefit from statin therapy.