The SLCO1B1*5 genetic variant is associated with statin-induced side effects

Effect of SLCO1B1 gene polymorphisms and vitamin D on statin-induced myopathy

Background Statin therapy used to lower cholesterol levels results in a substantial reduction in cardiovascular complications. Previous observations in different ethnic populations showed that rs2306283A>G, p.Asn130Asp and rs4149056T>C, p.Val174Ala in solute carrier organic anion transporter 1B1 (SLCO1B1) gene encoding the organic transporter protein may be responsible for statin uptake, thus explaining the majority of statin-associated symptoms. In addition to the genetic component, vitamin D (vit D) deficiency is common in Saudi Arabia and worldwide and may cause muscle dysfunction and ache. The aim of the present study was first to reveal an effect of vit D, rs2306283A>G, and rs4149056T>C and related haplotypes on statin-associated myopathy (SAM) and then to investigate a possible interaction between low vit D levels and the above-mentioned variants. Methods The genomic DNA obtained from 50 individuals diagnosed with hypercholesterolemia was genotyped using light SNiP hybridization probes. Results Low vit D levels were associated with SAM (OR=3.6, p=0.03); however, CK levels, rs2306283A>G, and rs4149056T>C did not show any association. Interestingly, rs4149056T>C was interacting with vit D to influence SAM (p=0.02). Haplotype analysis showed that SLCO1B1 *1B and *15 were more prevalent in individuals with SAM (p=0.05). When stratified according to vit D levels, rs2306283A allele showed an increase in individuals having SAM along with low vit D (p=0.03). Conclusions Although preliminary, our results show an involvement of vit D and rs4149056T>C of SLCO1B1 in SAM.

Genetic Testing in Clinical Settings

Genetic testing is used for screening, diagnosis, and prognosis of diseases consistent with a genetic cause and to guide drug therapy to improve drug efficacy and avoid adverse effects (pharmacogenomics). This In Practice review aims to inform about DNA-related genetic test availability, interpretation, and recommended clinical actions based on results using evidence from clinical guidelines, when available. We discuss challenges that limit the widespread use of genetic information in the clinical care setting, including a small number of actionable genetic variants with strong evidence of clinical validity and utility, and the need for improving the health literacy of health care providers and the public, including for direct-to-consumer tests. Ethical, legal, and social issues and incidental findings also need to be addressed. Because our understanding of genetic factors associated with disease and drug response is rapidly increasing and new genetic tests are being developed that could be adopted by clinicians in the short term, we also provide extensive resources for information and education on genetic testing.

COQ2 polymorphisms are not associated with increased risk of statin-induced myalgia/myopathy in the Czech population

BACKGROUND

The gene COQ2, encoding 4-hydroxybenzoate-polyprenyltransferase (coenzyme Q2), belongs to the candidates potentially influencing statin treatment tolerability. This enzyme is involved in the biosynthesis of coenzyme Q10 (CoQ10), in which depletion induced by statin treatment is implicated in the development of statin-associated muscle symptoms (SAMS). Thus, polymorphisms in the COQ2 gene might explain susceptibility to SAMS.

METHODS

Adult patients with SAMS (on low doses of atorvastatin and simvastatin)-induced myalgia/myopathy (n=278), patients on statins but without SAMS (n=293) and population (part of the post-MONICA [Multinational MONItoring of trends and determinants in CArdiovascular disease] study) controls (n=561) were genotyped (polymerase chain reaction-restriction fragment length polymorphism [PCR-RFLP] assay) for rs6535454 and rs4693075 polymorphisms within the COQ2 gene loci.

RESULTS

Distribution of rs6535454 in patients with SAMS (GG=51.1%, GA=40.0%, AA=8.9%) did not significantly differ (p=0.33; respectively 0.32 for codominant models of the analysis) from that in the population controls (GG=48.1%, GA=45.0%, AA=6.9%) or the SAMS-unaffected patients (GG=49.8%, GA=40.3%, AA=9.7%). Similarly, neither rs4693075 was associated with SAMS (CC=36.8%, CG=48.2%, GG=15.0% in patients suffering SAMS vs. CC=36.6%, CG=47.5%, GG=15.9 in controls and CC=35.8%, CG=48.2%, GG=15.9% in symptom-free patients, p=0.94 and 0.95 for codominant models of the analysis). Also, the haplotype distributions were not significantly different between the groups analyzed.

CONCLUSIONS

The polymorphisms of the COQ2 gene do not associate with SAMS in the Czech patients treated with low doses of statins. This is another clue that the coenzyme Q10 pathway is not the most important for the development of SAMS.

Simvastatin-related myopathy in shift workers: a report of two cases

Background

Simvastatin is a widely used drug for dyslipidemia treatment, and the best therapeutic effects are achieved at night time. Simvastatin administration has been associated with the development of myopathy. Some polymorphisms in genes that are involved in the metabolism and transport of simvastatin seem to have an important role in the development of simvastatin-associated myopathy. The administration of 40 mg of simvastatin to 19 hyperlipidemic subjects with regular sleep rhythms (RR) and shift workers (SW) with predominant evening rhythms and sleep-wake disturbances, uncovered two SW volunteers who developed myopathy.

Case presentation

We report two SWs who developed simvastatin-dependent myopathy after three weeks of treatment. The SLCO1B1 521T>C major risk allele was observed in one myopathy-affected and one unaffected subjects, the second affected patient shared polymorphisms with the unaffected subjects.

Conclusions

The lack of consonance in the studied genotypes between SWs affected with simvastatin-associated myopathy can be related to circadian misalignment. Hence, other genes with circadian behavior and induced by simvastatin should be evaluated in future studies.

Impact of pharmacogenetics on statin-induced myopathy in South-Indian subjects

OBJECTIVES

Statins are the most commonly prescribed medications for the treatment of atherosclerotic cardiovascular disease. Statin-associated adverse effects occur in ∼10% of patients and are associated with polymorphisms in several key genes coding for transporters and metabolizing enzymes that affect statin pharmacokinetics. In the present study, we examine the association between cytochrome P450 3A5*3 (CYP3A5*3) T>C (rs776746), COQ G>C (rs4693075), and SLCO1B1 T>C (rs4149056) genetic variants with the risk of myopathy in South Indian patients on statin therapy.

METHODS

A total of 202 patients on atorvastatin or rosuvastatin therapy for 12 years were recruited in the study. Genotyping of drug metabolic CYP3A5*3 gene variant and drug transporter genes COQ G>C (rs4693075) and SLCO1B1 T>C (rs4149056) was analyzed by Sanger's sequencing.

RESULTS

In our study subjects, the percentage of patients diagnosed to have statin-induced myopathy was 18%. The majority of the patients were on 10 mg/day dose of either atorvastatin or rosuvastatin. The homozygous nonexpressors genotype CYP3A5*3/3 frequency of the CYP3A5 polymorphism was higher in patients with myopathy. But we could not find association of CYP3A5, COQ, and SLCO1B1 gene polymorphisms with either rosuvastatin or atorvastatin.

CONCLUSION

Our results clearly demonstrate that the frequency of CYP3A5*3 splicing variant is higher in myopathy group than in the tolerant group. We did not find significant association of genetic polymorphisms in CYP3A5, COQ, and SLCO1B1 with atorvastatin- or rosuvastatin-induced myopathy.

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.

Pharmacogenetics in Cardiovascular Medicine

Considerable interindividual variability in response to cardiovascular pharmacotherapy exists with drug responses varying from being efficacious to inadequate to induce severe adverse events. Fueled by advancements and multidisciplinary collaboration across disciplines such as genetics, bioinformatics, and basic research, the vision of personalized medicine, rather than a one-size-fits-all approach, may be within reach. Pharmacogenetics offers the potential to optimize the benefit-risk profile of drugs by tailoring diagnostic and treatment strategies according to the individual patient. To date, a multitude of studies has tried to delineate the effects of gene-drug interactions for drugs commonly used to treat cardiovascular-related disease. The focus of this review is on how genetic variability may modify drug responsiveness and patient outcomes following therapy with commonly used cardiovascular drugs including clopidogrel, warfarin, statins, and β-blockers. Also included are examples of how genetic studies can be used to guide drug discovery and examples of how genetic information may be deployed in clinical decision making.

Impact of SLCO1B1 Genotype on Pediatric Simvastatin Acid Pharmacokinetics

This study investigated the impact of allelic variation in SLCO1B1, a gene encoding for the liver-specific solute carrier organic anion transporter family member 1B1 protein (SLCO1B1), on simvastatin and simvastatin acid (SVA) systemic exposure in children and adolescents. Participants (8-20 years old) with at least 1 variant SLCO1B1 c.521T>C allele (521TC, n = 15; 521CC, n = 2) and 2 wild-type alleles (521TT, n = 15) completed a single oral dose pharmacokinetic study. At equivalent doses, SVA exposure was 6.3- and 2.5-fold greater in 521CC and TC genotypes relative to 521TT (C_max , 2.1 ± 0.2 vs 1.0 ± 0.5 vs 0.4 ± 0.3 ng/mL; P < .0001; and AUC, 12.1 ± 0.3 vs 4.5 ± 2.5 vs 1.9 ± 1.8 ng·h/mL; P < .0001). The impact of the SLCO1B1 c.521 genotype was more pronounced in children, although considerable interindividual variability in SVA exposure was observed within genotype groups. In addition, SVA systemic exposure was negligible in 25% of pediatric participants. Further investigation of the ontogeny and genetic variation of SVA formation and SLCO1B1-mediated hepatic uptake is necessary to better understand the variability in SVA exposure in children and its clinical consequences.

Genetic and Clinical Factors Are Associated With Statin-Related Myotoxicity of Moderate Severity: A Case-Control Study

We evaluated the contribution of patient-specific clinical and genetic factors to statin-related muscle toxicity (SRM) without a significant creatine kinase elevation (125 cases related to simvastatin or atorvastatin and 481 controls). The association between 12 single nucleotide polymorphisms (SNPs) in nine candidate genes and clinical factors with SRM was evaluated. Of the 12 SNPs genotyped, only rs4149056 in SLCO1B1 was associated with SRM in univariate analysis (with any statin, odd ratio (OR) = 1.73, 95% confidence interval (CI) = 1.14-2.62, P = 0.010) and this association was influenced by sex (P = 0.006) and BMI (P = 0.02). In multivariate and binary logistic regression analyses, SLCO1B1 rs4149056 genotype (OR = 1.66, 95% CI: 1.08-2.54, P = 0.014) and sex (OR = 1.72, 95% CI = 1.15-2.59, P = 0.006) were independently associated with muscle toxicity related to statin treatment. Patient-specific genetic and clinical factors associated with increased systemic exposure to statins are implicated in the full spectrum of SRM, including myalgia in addition to severe myopathy.

Pharmacogenetics in Cardiovascular Medicine

PURPOSE OF REVIEW

Pharmacogenetics is an important component of precision medicine. Even within the genomic era, several challenges lie ahead in the road towards clinical implementation of pharmacogenetics in the clinic. This review will summarize the current state of knowledge regarding pharmacogenetics of cardiovascular drugs, focusing on those with the most evidence supporting clinical implementation- clopidogrel, warfarin and simvastatin.

RECENT FINDINGS

There is limited translation of pharmacogenetics into clinical practice primarily due to the absence of outcomes data from prospective, randomized, genotype-directed clinical trials. There are several ongoing randomized controlled trials that will provide some answers as to the clinical utility of genotype-directed strategies. Several academic medical centers have pushed towards clinical implementation where the clinical validity data are strong. Their experiences will inform operational requirements of a clinical pharmacogenetics testing including the timing of testing, incorporation of test results into the electronic health record, reimbursement and ethical issues.

SUMMARY

Pharmacogenetics of clopidogrel, warfarin and simvastatin are three examples where pharmacogenetics testing may provide added clinical value. Continued accumulation of evidence surrounding clinical utility of pharmacogenetics markers is imperative as this will inform reimbursement policy and drive adoption of pharamcogenetics into routine care.

More Power to OATP1B1: An Evaluation of Sample Size in Pharmacogenetic Studies Using a Rosuvastatin PBPK Model for Intestinal, Hepatic, and Renal Transporter-Mediated Clearances

Rosuvastatin is a substrate of choice in clinical studies of organic anion-transporting polypeptide (OATP)1B1- and OATP1B3-associated drug interactions; thus, understanding the effect of OATP1B1 polymorphisms on the pharmacokinetics of rosuvastatin is crucial. Here, physiologically based pharmacokinetic (PBPK) modeling was coupled with a power calculation algorithm to evaluate the influence of sample size on the ability to detect an effect (80% power) of OATP1B1 phenotype on pharmacokinetics of rosuvastatin. Intestinal, hepatic, and renal transporters were mechanistically incorporated into a rosuvastatin PBPK model using permeability-limited models for intestine, liver, and kidney, respectively, nested within a full PBPK model. Simulated plasma rosuvastatin concentrations in healthy volunteers were in agreement with previously reported clinical data. Power calculations were used to determine the influence of sample size on study power while accounting for OATP1B1 haplotype frequency and abundance in addition to its correlation with OATP1B3 abundance. It was determined that 10 poor-transporter and 45 intermediate-transporter individuals are required to achieve 80% power to discriminate the AUC0-48h of rosuvastatin from that of the extensive-transporter phenotype. This number was reduced to 7 poor-transporter and 40 intermediate-transporter individuals when the reported correlation between OATP1B1 and 1B3 abundance was taken into account. The current study represents the first example in which PBPK modeling in conjunction with power analysis has been used to investigate sample size in clinical studies of OATP1B1 polymorphisms. This approach highlights the influence of interindividual variability and correlation of transporter abundance on study power and should allow more informed decision making in pharmacogenomic study design.

The beneficial effects of HMG-CoA reductase inhibitors in the processes of neurodegeneration

Statins, cholesterol lowering drugs, have been demonstrated to exert beneficial effects in other conditions such as primary and progressing neurodegenerative diseases beyond their original role. Observation that statins ameliorate the neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), multiple sclerosis (MS) and cerebral ischemic stroke, the neuroprotective effects of these drugs are thought to be linked to their anti-inflammatory, anti-oxidative, and anti-excitotoxic properties. Despite the voluminous literature on the clinical advantages of 3-hydroxy-3-methylglutaryl Co-enzyme A reductase (HMGCR) inhibitors (statins) in cardiovascular system, the neuroprotective effects and the underlying mechanisms are little understood. Hence, the present review tries to provide a critical overview on the statin-induced neuroprotection, which are presumed to be associated with the ability to reduce cholesterol, Amyloid-β and apolipoprotein E (ApoE) levels, decrease reactive oxygen and nitrogen species (ROS and RNS) formation, inhibit excitotoxicity, modulate matrix metalloproteinases (MMPs), stimulate endothelial nitric oxide synthase (eNOS), and increase cerebral blood perfusion. This review is also aimed to illustrate that statins protect neurons against the neuro-inflammatory processes through balancing pro-inflammatory/anti-inflammatory cytokines. Ultimately, the beneficial role of statins in ameliorating the development of PD, AD, MS and cerebral ischemic stroke has been separately reviewed.

En route to precision medicine through the integration of biological sex into pharmacogenomics

Frequently, pharmacomechanisms are not fully elucidated. Therefore, drug use is linked to an elevated interindividual diversity of effects, whether therapeutic or adverse, and the role of biological sex has as yet unrecognized and underestimated consequences. A pharmacogenomic approach could contribute towards the development of an adapted therapy for each male and female patient, considering also other fundamental features, such as age and ethnicity. This would represent a crucial step towards precision medicine and could be translated into clinical routine. In the present review, we consider recent results from pharmacogenomics and the role of sex in studies that are relevant to cardiovascular therapy. We focus on genome-wide analyses, because they have obvious advantages compared with targeted single-candidate gene studies. For instance, genome-wide approaches do not necessarily depend on prior knowledge of precise molecular mechanisms of drug action. Such studies can lead to findings that can be classified into three categories: first, effects occurring in the pharmacokinetic properties of the drug, e.g. through metabolic and transporter differences; second, a pharmacodynamic or drug target-related effect; and last diverse adverse effects. We conclude that the interaction of sex with genetic determinants of drug response has barely been tested in large, unbiased, pharmacogenomic studies. We put forward the theory that, to contribute towards the realization of precision medicine, it will be necessary to incorporate sex into pharmacogenomics.

Personalized medicine: Genetic risk prediction of drug response

Pharmacogenomics (PGx), a substantial component of "personalized medicine", seeks to understand each individual's genetic composition to optimize drug therapy -- maximizing beneficial drug response, while minimizing adverse drug reactions (ADRs). Drug responses are highly variable because innumerable factors contribute to ultimate phenotypic outcomes. Recent genome-wide PGx studies have provided some insight into genetic basis of variability in drug response. These can be grouped into three categories. [a] Monogenic (Mendelian) traits include early examples mostly of inherited disorders, and some severe (idiosyncratic) ADRs typically influenced by single rare coding variants. [b] Predominantly oligogenic traits represent variation largely influenced by a small number of major pharmacokinetic or pharmacodynamic genes. [c] Complex PGx traits resemble most multifactorial quantitative traits -- influenced by numerous small-effect variants, together with epigenetic effects and environmental factors. Prediction of monogenic drug responses is relatively simple, involving detection of underlying mutations; due to rarity of these events and incomplete penetrance, however, prospective tests based on genotype will have high false-positive rates, plus pharmacoeconomics will require justification. Prediction of predominantly oligogenic traits is slowly improving. Although a substantial fraction of variation can be explained by limited numbers of large-effect genetic variants, uncertainty in successful predictions and overall cost-benefit ratios will make such tests elusive for everyday clinical use. Prediction of complex PGx traits is almost impossible in the foreseeable future. Genome-wide association studies of large cohorts will continue to discover relevant genetic variants; however, these small-effect variants, combined, explain only a small fraction of phenotypic variance -- thus having limited predictive power and clinical utility.

Precision Cardiovascular Medicine: State of Genetic Testing

In the 15 years following the release of the first complete human genome sequences, our understanding of rare and common genetic variation as determinants of cardiovascular disease susceptibility, prognosis, and therapeutic response has grown exponentially. As such, the use of genomics to enhance the care of patients with cardiovascular diseases has garnered increased attention from clinicians, researchers, and regulatory agencies eager to realize the promise of precision genomic medicine. However, owing to a large burden of "complex" common diseases, emphasis on evidence-based practice, and a degree of unfamiliarity/discomfort with the language of genomic medicine, the development and implementation of genomics-guided approaches designed to further individualize the clinical management of a variety of cardiovascular disorders remains a challenge. In this review, we detail a practical approach to genetic testing initiation and interpretation as well as review the current state of cardiovascular genetic and pharmacogenomic testing in the context of relevant society and regulatory agency recommendations/guidelines.

Interindividual and interethnic variability in drug disposition: polymorphisms in organic anion transporting polypeptide 1B1 (OATP1B1; SLCO1B1)

OATP1B1 (SLCO1B1) is predominantly expressed at the basolateral membrane of hepatocytes and is critically important for the hepatic uptake and clearance of numerous drug substrates and endogenous compounds. In general, the organic anion transporting polypeptides (OATP; SLCO) represent a superfamily of uptake transporters that mediate the sodium-independent transport of a diverse range of amphipathic organic compounds including bile salts, steroid conjugates, thyroid hormones, anionic peptides, numerous drugs and other xenobiotic substances. OATP1B1 is highly polymorphic and a number of relevant and ethnically dependent polymorphisms have been identified and functionally characterized. In particular, the SLCO1B1 521T>C and 388A>G polymorphisms are commonly occurring variants in ethnically diverse populations and numerous in vitro and clinical studies have evaluated the consequences of these variants to interindividual differences in drug disposition and response. OATP1B1 is particularly important for the disposition of HMG-CoA reductase inhibitors, or statins, as it is known to efficiently transport most statins to their site of action within hepatocytes. Many studies have focused on the consequences of OATP1B1 variants to statin disposition in vitro and in vivo and would suggest that genetic variability in SLCO1B1 has important implications for statin pharmacokinetics, risk for statin-induced myopathy, and modulation of statin treatment response. This review describes what is currently known regarding SLCO1B1 genotype, OATP1B1 protein expression and interindividual and interethnic consequences to drug disposition, with particular focus on statin pharmacokinetics and implications for drug response and toxicity.

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.

Use of Pharmacogenetic Information in the Treatment of Cardiovascular Disease

BACKGROUND

In 1964, Robert A. O'Reilly's research group identified members of a family who required remarkably high warfarin doses (up to 145 mg/day, 20 times the average dose) to achieve appropriate anticoagulation. Since this time, pharmacogenetics has become a mainstay of cardiovascular science, and genetic variants have been implicated in several fundamental classes of medications used in cardiovascular medicine.

CONTENT

In this review, we discuss genetic variants that affect drug response to 3 classes of cardiovascular drugs: statins, platelet P2Y12 inhibitors, and anticoagulants. These genetic variations have pharmacodynamic and pharmacokinetic effects and have been shown to explain differences in drug response such as lipid lowering, prevention of cardiovascular disease, and prevention of stroke, as well as incidence of adverse events such as musculoskeletal side effects and bleeding. Several groups have begun to implement pharmacogenetics testing as part of routine clinical care with the goal of improving health outcomes. Such strategies identify both patients at increased risk of adverse outcomes and alternative strategies to mitigate this risk as well as patients with “normal” genotypes, who, armed with this information, may have increased confidence and adherence to prescribed medications. While much is known about the genetic variants that underlie these effects, translation of this knowledge into clinical practice has been hampered by difficulty in implementing cost-effective, point-of-care tools to improve physician decision-making as well as a lack of data, as of yet, demonstrating the efficacy of using genetic information to improve health.

SUMMARY

Many genetic variants that affect individual responses to drugs used in cardiovascular disease prevention and treatment have been described. Further study of these variants is needed before successful implementation into clinical practice.

Racial Differences in the Cholesterol-Lowering Effect of Statin

Statin treatment to reduce low-density lipoprotein cholesterol (LDL-C) is associated with the prevention of cardiovascular events in Western patients. Similar results have been reported in studies conducted in Japan. However, the dose of statins and the degree of LDL-C reduction achieved with statins are different between Asian and Western patients. In addition, there are limited data regarding racial differences in response to statins. In this review, racial differences between Asians and Westerners in response to statins are described.

Impact of New Genomic Technologies on Understanding Adverse Drug Reactions

It is well established that variations in genes can alter the pharmacokinetic and pharmacodynamic profile of a drug and immunological responses to it. Early advances in pharmacogenetics were made with traditional genetic techniques such as functional cloning of genes using knowledge gained from purified proteins, and candidate gene analysis. Over the past decade, techniques for analysing the human genome have accelerated greatly as knowledge and technological capabilities have grown. These techniques were initially focussed on understanding genetic factors of disease, but increasingly they are helping to clarify the genetic basis of variable drug responses and adverse drug reactions (ADRs). We examine genetic methods that have been applied to the understanding of ADRs, review the current state of knowledge of genetic factors that influence ADR development, and discuss how the application of genome-wide association studies and next-generation sequencing approaches is supporting and extending existing knowledge of pharmacogenetic processes leading to ADRs. Such approaches have identified single genes that are major contributing genetic risk factors for an ADR, (such as flucloxacillin and drug-induced liver disease), making pre-treatment testing a possibility. They have contributed to the identification of multiple genetic determinants of a single ADR, some involving both pharmacologic and immunological processes (such as phenytoin and severe cutaneous adverse reactions). They have indicated that rare genetic variants, often not previously reported, are likely to have more influence on the phenotype than common variants that have been traditionally tested for. The problem of genotype/phenotype discordance affecting the interpretation of pharmacogenetic screening and the future of genome-based testing applied to ADRs are also discussed.

The role of organic anion transporting polypeptides in drug absorption, distribution, excretion and drug-drug interactions

INTRODUCTION

The in vivo fate and effectiveness of a drug depends highly on its absorption, distribution, metabolism, excretion and toxicity (ADME-Tox). Organic anion transporting polypeptides (OATPs) are membrane proteins involved in the cellular uptake of various organic compounds, including clinically used drugs. Since OATPs are significant players in drug absorption and distribution, modulation of OATP function via pharmacotherapy with OATP substrates/inhibitors, or modulation of their expression, affects drug pharmacokinetics. Given their cancer-specific expression, OATPs may also be considered anticancer drug targets. Areas covered: We describe the human OATP family, discussing clinically relevant consequences of altered OATP function. We offer a critical analysis of published data on the role of OATPs in ADME and in drug-drug interactions, especially focusing on OATP1A2, 1B1, 1B3 and 2B1. Expert opinion: Four members of the OATP family, 1A2, 1B1, 1B3 and 2B1, have been characterized in detail. As biochemical and pharmacological knowledge on the other OATPs is lacking, it seems timely to direct research efforts towards developing the experimental framework needed to investigate the transport mechanism and substrate specificity of the poorly described OATPs. In addition, elucidating the role of OATPs in tumor development and therapy response are critical avenues for further research.

Ontogeny of Hepatic Drug Transporters as Quantified by LC-MS/MS Proteomics

Protein expression of major hepatic uptake and efflux drug transporters in human pediatric (n = 69) and adult (n = 41) livers was quantified by liquid chromatography / tandem mass spectroscopy (LC-MS/MS). Transporter protein expression of OCT1, OATP1B3, P-gp, and MRP3 was age-dependent. Particularly, significant differences were observed in transporter expression (P < 0.05) between the following age groups: neonates vs. adults (OCT1, OATP1B3, P-gp), neonates or infants vs. adolescents and/or adults (OCT1, OATP1B3, and P-gp), infants vs. children (OATP1B3 and P-gp), and adolescents vs. adults (MRP3). OCT1 showed the largest increase, of almost 5-fold, in protein expression with age. Ontogenic expression of OATP1B1 was confounded by genotype and was revealed only in livers harboring SLCO1B1*1A/*1A. In livers >1 year, tissues harboring SLCO1B1*14/*1A showed 2.5-fold higher (P < 0.05) protein expression than SLCO1B1*15/*1A. Integration of these ontogeny data in physiologically based pharmacokinetic (PBPK) models will be a crucial step in predicting hepatic drug disposition in children.

Statin-associated muscle symptoms and SLCO1B1 rs4149056 genotype in patients with familial hypercholesterolemia

Patients with familial hypercholesterolemia (FH) may be at increased risk for statin-associated muscle symptoms because they require long-term treatment with high-intensity statin therapy. We sought to determine (1) whether other predisposing factors, including the well-known genetic variant associated with statin-associated muscle symptoms-solute carrier organic anion transporter family, member 1B1 (SLCO1B1) rs4149056-also increase the risk of statin-associated muscle symptoms in FH patients, and (2) the natural history and management for FH patients with statin-associated muscle symptoms.

METHODS

We queried electronic records (2004-2014) of 278 genetically screened FH patients (113 men, 165 women; mean [SD] pretreatment low-density lipoprotein cholesterol [LDL-C] 259 [72] mg/dL) recruited from lipid clinics in the Dallas, TX, area from 2004 to 2014. Statin-associated muscle symptoms were defined as muscle symptoms arising while taking a statin and interrupting therapy.

RESULTS

The risk of muscle symptoms was associated with age (odds ratio 1.6 [95% CI 1.2-2.2]), body mass index in non-African Americans (0.90 [0.83-0.97]), and hypertension (0.4 [0.2-0.9]). Simvastatin was the most commonly used statin, and it was the statin most associated with muscle symptoms. Among FH patients with muscle symptoms, 41% (n = 40) reestablished statin therapy ("eventually tolerant") and 29% (n = 28) never reestablished statin therapy ("never tolerant"). Rosuvastatin (43%) and pravastatin (30%) were the most common eventually tolerated statins, and eventually tolerant patients achieved lower treated LDL-C levels (eventually tolerant 127 vs never tolerant 192 mg/dL, P < .001). Never tolerant patients also developed muscle symptoms on nonstatins (16% vs 50%, P = .003). SLCO1B1 rs4149056 genotyping revealed 224 wild-type patients (TT) and 49 heterozygotes (TC). SLCO1B1 genotype was not associated with the risk of statin-associated muscle symptoms (odds ratio 1.40 [95% CI 0.74-2.64]).

CONCLUSION

Age, not SLCO1B1 rs4149056 genotype, was the strongest risk factor for statin-associated muscle symptoms in FH patients. After developing muscle symptoms, many patients reestablished statin therapy and achieved significant LDL-C reductions. Overall, 10% of all FH patients had statin-associated muscle symptoms and never reestablished statin therapy. Such patients developed muscle symptoms even on nonstatin lipid-lowering drugs and continued to have elevations in LDL-C. Further insight is needed into the relationship between FH and statin-associated muscle symptoms so all FH patients can be adequately treated.

Pediatric Statin Administration: Navigating a Frontier with Limited Data

Increasingly, children and adolescents with dyslipidemia qualify for pharmacologic intervention. As they are for adults, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors (statins) are the mainstay of pediatric dyslipidemia treatment when lifestyle modifications have failed. Despite the overall success of these drugs, the magnitude of variability in dose-exposure-response profiles contributes to adverse events and treatment failure. In children, the cause of treatment failures remains unclear. This review describes the updated guidelines for screening and management of pediatric dyslipidemia and statin disposition pathway to assist the provider in recognizing scenarios where alterations in dosage may be warranted to meet patients' specific needs.

Impact of CYP2D6, CYP3A5, CYP2C19, CYP2A6, SLCO1B1, ABCB1, and ABCG2 gene polymorphisms on the pharmacokinetics of simvastatin and simvastatin acid

OBJECTIVE

The effects of various polymorphisms in cytochrome P450 (CYP) enzyme and transporter genes on the pharmacokinetics (PK) of simvastatin were evaluated in healthy Korean men.

METHODS

Plasma concentration data for simvastatin and simvastatin acid were pooled from four phase I studies comprising 133 participants. The polymorphisms CYP2D6*4, CYP2D6*5, CYP2D6*14, CYP2D6*41, CYP3A5*3, CYP2C19*2, CYP2C19*3, CYP2A6*7, and CYP2A6*9; SLCO1B1 rs4149056, rs2306283, and rs4149015; ABCB1 rs1128503, rs2032582, and rs1045642; and ABCG2 rs2231142 were evaluated in each participant. Noncompartmental PK results were compared by genotype.

RESULTS

CYP2D6*5 and CYP2D6*14 were found to be associated with a higher area under the curve (AUC) for simvastatin, whereas the AUC of simvastatin acid was significantly increased in patients with the SLCO1B1 rs4149056, ABCG2 rs2231142, and CYP2D6*41 allele variants. Patients with the CYP2D6*41 variant showed a higher peak serum concentration (Cmax) of both simvastatin and simvastatin acid. The SLCO1B1 rs4149056 and rs4149015 polymorphisms were associated with an increased AUC ratio (i.e. ratio of simvastatin acid to simvastatin), whereas the SLCO1B1 rs4149056 and CYP2D6*5 variants were related to a higher Cmax ratio.

CONCLUSION

The CYP2D6*5, CYP2D6*14, CYP2D6*41, CYP3A5*3, SLCO1B1 rs4149056 and rs4149015, and ABCG2 rs2231142 genetic polymorphisms are associated with the PK of both simvastatin and simvastatin acid. This could potentially be used as a basis for individualized simvastatin therapy by predicting the clinical outcomes of this treatment.

Association between SLCO1B1 -521T>C and -388A>G polymorphisms and risk of statin-induced adverse drug reactions: A meta-analysis

An increasing number of studies have investigated the association between SLCO1B1 -521T>C and -388A>G polymorphisms and the risk of statin-induced adverse drug reactions (ADRs), but the results have been inconsistent. This meta-analysis was performed to gain more insight into the relationship. PubMed, Embase, Cochrane Library and Web of Science were searched for relevant articles published before March 5th, 2015. The quality of included studies was evaluated by the Newcastle-Ottawa Quality scale. Pooled effect estimates (odds ratios [ORs] or hazard ratios [HRs) and corresponding 95 % confidence intervals (CIs) were calculated to assess the association in overall and subgroup analyses for various genetic models. Begg's rank correlation test and Egger's linear regression test were used to examine the publication bias. A total of nine cohort and four case-control studies involving 11, 246 statin users, of whom 2, 355 developing ADRs were included in the analysis. Combined analysis revealed a significant association between the SLCO1B1-521T>C polymorphism and increased risk for ADRs caused by various statins, but the synthesis heterogeneity was generally large (dominant model: pooled effect estimate = 1.85, 95 % CI 1.20-2.85, P = 0.005; I (2) = 80.70 %, Pheterogeneity < 0.001). Subgroup analysis by statin type showed that the ADRs risk was significantly elevated among simvastatin users (dominant model: pooled effect estimate = 3.43, 95 % CI 1.80-6.52, P = 0.001; I (2) = 59.60 %, Pheterogeneity = 0.060), but not among atorvastatin users. No significant relationship was found between the -388A>G polymorphism and ADRs caused by various statins (dominant model: pooled effect estimate = 0.94, 95 % CI 0.79-1.13, P = 0.526; I (2) = 40.10 %, Pheterogeneity = 0.196). The meta-analysis suggests that SLCO1B1 -521T>C polymorphism may be a risk factor for statin-induced ADRs, especially in simvastatin therapy. Conversely, there may be no significant association for -388A>G polymorphism.

Laboratory Medicine in the Clinical Decision Support for Treatment of Hypercholesterolemia: Pharmacogenetics of Statins

Statin responsiveness is an area of great research interest given the success of the drug class in the treatment of hypercholesterolemia and in primary and secondary prevention of cardiovascular disease. Interrogation of the patient's genome for gene variants will eventually guide anti-hyperlipidemic intervention. In this review, we discuss methodological approaches to discover genetic markers predictive of class-wide and drug-specific statin efficacy and safety. Notable pharmacogenetic findings are summarized from hypothesis-free genome wide and hypothesis-led candidate gene association studies. Physiogenomic models and clinical decision support systems will be required for DNA-guided statin therapy to reach practical use in medicine.

Molecular mechanisms of statin intolerance

Statins reduce cardiovascular morbidity and mortality in primary and secondary prevention. Despite their efficacy, many persons are unable to tolerate statins due to adverse events such as hepatotoxicity and myalgia/myopathy. In the case of most patients, it seems that mild-to-moderate abnormalities in liver and muscle enzymes are not serious adverse effects and do not outweigh the benefits of coronary heart disease risk reduction. The risk for mortality or permanent organ damage ascribed to statin use is very small and limited to cases of myopathy and rhabdomyolysis. Statin-induced muscle-related adverse events comprise a highly heterogeneous clinical disorder with numerous, complex etiologies and a variety of genetic backgrounds. Every patient who presents with statin-related side effects cannot undergo the type of exhaustive molecular characterization that would include all of these mechanisms. Frequently the only solution is to either discontinue statin therapy/reduce the dose or attempt intermittent dosing strategies at a low dose.

The frequency of SLCO1B1*5 polymorphism genotypes among Russian and Sakha (Yakutia) patients with hypercholesterolemia

Introduction

Statins are the most commonly prescribed medicines for treatment of hypercholesterolemia. At the same time, up to 25% of patients cannot tolerate or have to discontinue the statin therapy due to statin-induced myopathy. In a majority of cases, statin-induced myopathy is attributed to SLCO1B1 gene polymorphism. The strongest association between statin-induced myopathy and SLCO1B1 gene polymorphism was described for simvastatin. Our research was focused on the frequency of SLCO1B1*5 genetic variant in the Russian population and in the native population of Sakha (Yakutia).

Materials and methods

A total of 1,071 hyperlipidemic Russian and 76 hyperlipidemic Sakha (Yakutian) patients were included in the study. Genotypes of SLCO1B1*5 (c.521T>C, rs4149056) were determined with polymerase chain reaction amplification. The results of our study were compared with data about hyperlipidemic patients in available publications.

Results

In the Russian population 665 (62%) patients had TT genotype of SLCO1B1*5, 346 (32%) patients had TC genotype, and in 60 patients (6%) CC variant was found (Hardy–Weinberg’s chi-square test was 3.1 P=0.21). In comparison with Brazil, France, the People’s Republic of China, Japan, and the native population of Sakha (Yakutia), C-allele, which causes an increased risk of statin-induced myopathy, was found significantly more often in the Russian population. In the native population of Sakha (Yakutia) SLCO1B1 polymorphism was TT – 62 (82%), TC – 11 (14%), CC – 3 (4%) (Hardy–Weinberg’s chi-square test was 5.13 P=0.077). In comparison with data from Brazil, France, the People’s Republic of China, and Japan, C-allele frequency in the Sakha (Yakutian) population was not significantly different.

Conclusion

Thus, we have studied the incidence of pathologic SLCO1B1 c.521C-allele in Russian and Sakha hyperlipidemic patients. The presence of SLCO1B1 C-allele in patients with hyperlipidemia forces us to be more careful in hypolipidemic drug prescription, especially statins, according to a higher risk of statin-induced myopathy development. The fact that SLCO1B1 C-allele is rarer among Sakha patients, could be interesting from the point of studying adverse drug effects frequency and statins’ effectiveness.

Assessment of pharmacogenetic tests: presenting measures of clinical validity and potential population impact in association studies

The progressing discovery of genetic variants associated with drug-related adverse events has raised expectations for pharmacogenetic tests to improve drug efficacy and safety. To further the use of pharmacogenetics in health care, tests with sufficient potential to improve efficacy and safety, as reflected by good clinical validity and population impact, need to be identified. The potential benefit of pharmacogenetic tests is often concluded from the strength of the association between the variant and the adverse event; measures of clinical validity are generally not reported. This paper describes measures of clinical validity and potential population health impact that can be calculated from association studies. We explain how these measures are influenced by the strength of the association and by the frequencies of the variant and the adverse event. The measures are illustrated using examples of testing for HLA-B*5701 associated with abacavir-induced hypersensitivity and SLCO1B1 c.521T>C (*5) associated with simvastatin-induced adverse events.

ToxEvaluator: an integrated computational platform to aid the interpretation of toxicology study-related findings

Attempts are frequently made to investigate adverse findings from preclinical toxicology studies in order to better understand underlying toxicity mechanisms. These efforts often begin with limited information, including a description of the adverse finding, knowledge of the structure of the chemical associated with its cause and the intended pharmacological target. ToxEvaluator was developed jointly by Pfizer and the Comparative Toxicogenomics Database (http://ctdbase.org) team at North Carolina State University as an in silico platform to facilitate interpretation of toxicity findings in light of prior knowledge. Through the integration of a diverse set of in silico tools that leverage a number of public and proprietary databases, ToxEvaluator streamlines the process of aggregating and interrogating diverse sources of information. The user enters compound and target identifiers, and selects adverse event descriptors from a safety lexicon and mapped MeSH disease terms. ToxEvaluator provides a summary report with multiple distinct areas organized according to what target or structural aspects have been linked to the adverse finding, including primary pharmacology, structurally similar proprietary compounds, structurally similar public domain compounds, predicted secondary (i.e. off-target) pharmacology and known secondary pharmacology. Similar proprietary compounds and their associated in vivo toxicity findings are reported, along with a link to relevant supporting documents. For similar public domain compounds and interacting targets, ToxEvaluator integrates relationships curated in Comparative Toxicogenomics Database, returning all direct and inferred linkages between them. As an example of its utility, we demonstrate how ToxEvaluator rapidly identified direct (primary pharmacology) and indirect (secondary pharmacology) linkages between cerivastatin and myopathy.

Individual and Combined Associations of Genetic Variants in CYP3A4, CYP3A5, and SLCO1B1 With Simvastatin and Simvastatin Acid Plasma Concentrations

Our objective was to evaluate the associations of genetic variants affecting simvastatin (SV) and simvastatin acid (SVA) metabolism [the gene encoding cytochrome P450, family 3, subfamily A, polypeptide 4 (CYP3A4)*22 and the gene encoding cytochrome P450, family 3, subfamily A, polypeptide 5 (CYP3A5)*3] and transport [the gene encoding solute carrier organic anion transporter family member 1B1 (SLCO1B1) T521C] with 12-hour plasma SV and SVA concentrations. The variants were genotyped, and the concentrations were quantified by high performance liquid chromatography-tandem mass spectrometry in 646 participants of the Cholesterol and Pharmacogenetics clinical trial of 40 mg/d SV for 6 weeks. The genetic variants were tested for association with 12-hour plasma SV, SVA, or the SVA/SV ratio using general linear models. CYP3A5*3 was not significantly associated with 12-hour plasma SV or SVA concentration. CYP3A4*1/*22 participants had 58% higher 12-hour plasma SV concentration compared with CYP3A4*1/*1 participants (P = 0.006). SLCO1B1 521T/C and 521C/C participants had 71% (P < 0.001) and 248% (P < 0.001) higher 12-hour plasma SVA compared with SLCO1B1 521T/T participants, respectively. CYP3A4 and SLCO1B1 genotypes combined categorized participants into low (<1), intermediate (≈1), and high (>1) SVA/SV ratio groups (P = 0.001). In conclusion, CYP3A4*22 and SLCO1B1 521C were significantly associated with increased 12-hour plasma SV and SVA concentrations, respectively. CYP3A5*3 was not significantly associated with 12-hour plasma SV or SVA concentrations. The combination of CYP3A4*22 and SLCO1B1 521C was significantly associated with SVA/SV ratio, which may translate into different clinical SV risk/benefit profiles.

Cardiovascular Pharmacogenomics--Implications for Patients With CKD

CKD is an independent risk factor for cardiovascular disease (CVD). Thus, patients with CKD often require treatment with cardiovascular drugs, such as antiplatelet, antihypertensive, anticoagulant, and lipid-lowering agents. There is significant interpatient variability in response to cardiovascular therapies, which contributes to risk for treatment failure or adverse drug effects. Pharmacogenomics offers the potential to optimize cardiovascular pharmacotherapy and improve outcomes in patients with CVD, although data in patients with concomitant CKD are limited. The drugs with the most pharmacogenomic evidence are warfarin, clopidogrel, and statins. There are also accumulating data for genetic contributions to β-blocker response. Guidelines are now available to assist with applying pharmacogenetic test results to optimize warfarin dosing, selection of antiplatelet therapy after percutaneous coronary intervention, and prediction of risk for statin-induced myopathy. Clinical data, such as age, body size, and kidney function have long been used to optimize drug prescribing. An increasing number of institutions are also implementing genetic testing to be considered in the context of important clinical factors to further personalize drug therapy for patients with CVD.

Adverse drug reactions and organ damage: The liver

Drug-induced liver injury (DILI) is among the most challenging acute or chronic liver conditions to be handled by physicians. Despite its low incidence in the general population, DILI is a frequent cause of acute liver failure. As such, the possibility of DILI should be considered in all patients who present with acute liver damage, independent of any known pre-existing liver disease. DILI can be classified as intrinsic/dose-dependent (e.g., acetaminophen toxicity) or idiosyncratic/dose-independent, with the latter form being relatively uncommon. Amoxicillin-clavulanate is the antimicrobial that is most frequently associated with idiosyncratic DILI. Large, ongoing, prospective studies in western countries have reported other drugs associated with DILI, including nonsteroidal anti-inflammatory drugs, statins, and herbal and dietary supplements. An important safety issue, DILI is one of the most frequently cited reasons for cessation of drug development during or after preclinical studies and for withdrawal of a drug from the market. This review summarizes the epidemiology, risk factors, commonly implicated drugs, clinical features, and diagnosis of DILI, with the aim of aiding physicians in the management of this debated problem. Old and new biomarkers for DILI and pharmacogenetic studies are also described.

Clinical association between pharmacogenomics and adverse drug reactions

Adverse drug reactions (ADRs) are a major public health concern and cause significant patient morbidity and mortality. Pharmacogenomics is the study of how genetic polymorphisms affect an individual's response to pharmacotherapy at the level of a whole genome. This article updates our knowledge on how genetic polymorphisms of important genes alter the risk of ADR occurrence after an extensive literature search. To date, at least 244 pharmacogenes identified have been associated with ADRs of 176 clinically used drugs based on PharmGKB. At least 28 genes associated with the risk of ADRs have been listed by the Food and Drug Administration as pharmacogenomic biomarkers. With the availability of affordable and reliable testing tools, pharmacogenomics looks promising to predict, reduce, and minimize ADRs in selected populations.

Statin-associated myopathy: from genetic predisposition to clinical management

Statin-associated myopathy (SAM) represents a broad spectrum of disorders from insignificant myalgia to fatal rhabdomyolysis. Its frequency ranges from 1-5 % in clinical trials to 15-20 % in everyday clinical practice. To a large extent, these variations can be explained by the definition used. Thus, we propose a scoring system to classify statin-induced myopathy according to clinical and biochemical criteria as 1) possible, 2) probable or 3) definite. The etiology of this disorder remains poorly understood. Most probably, an underlying genetic cause is necessary for overt SAM to develop. Variants in a few gene groups that encode proteins involved in: i) statin metabolism and distribution (e.g. membrane transporters and enzymes; OATP1B1, ABCA1, MRP, CYP3A4), ii) coenzyme Q10 production (e.g. COQ10A and B), iii) energy metabolism of muscle tissue (e.g. PYGM, GAA, CPT2) and several others have been proposed as candidates which can predispose to SAM. Pharmacological properties of individual statin molecules (e.g. lipophilicity, excretion pathways) and patients´ characteristics influence the likelihood of SAM development. This review summarizes current data as well as our own results.

SLCO1B1 genetic variants, long-term low-density lipoprotein cholesterol levels and clinical events in patients following cardiac catheterization

AIM

SLCO1B1 variants are associated with intermediate outcomes that may increase risk of death/myocardial infarction (MI) in statin-treated patients.

PATIENTS & METHODS

In high-risk Caucasians undergoing cardiac catheterization, we tested the association between rs4149056/625T>C and rs2306283/492A>G with low-density lipoprotein cholesterol (LDL-c) over 3 years (n = 1402) and death/MI over 6 years (n = 2994), accounting for statin use or type during follow-up.

RESULTS

Carriers of the rs4149056 C allele had 6.2 ± 1.7 mg/dl higher LDL-c per C allele (p < 0.001) but were not at higher risk for death/MI (p = 0.9). We found no associations between rs2306283 and LDL-c or death/MI (p > 0.6).

CONCLUSION

Functional SLCO1B1 variants are not associated with death/MI in patients commonly treated with statins, despite higher LDL-c in carriers of the rs4149056 C allele.