Common nonsynonymous substitutions in SLCO1B1 predispose to statin intolerance in routinely treated individuals with type 2 diabetes: a go-DARTS study

SLCO1B1 Exome Sequencing and Statin Treatment Response in 64,000 UK Biobank Patients

The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10-8; beta*15 = 0.03 mmol/L, p = 3 × 10-4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance

BACKGROUND AND AIMS

The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance.

METHODS AND RESULTS

A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02).

CONCLUSION

We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

Real-world pharmacogenetics of statin intolerance: effects of SLCO1B1, ABCG2 , and CYP2C9 variants

OBJECTIVE

The association of SLCO1B1 c.521T>C with simvastatin-induced muscle toxicity is well characterized. However, different statins are subject to metabolism and transport also by other proteins exhibiting clinically meaningful genetic variation. Our aim was to investigate associations of SLCO1B1 c.521T>C with intolerance to atorvastatin, fluvastatin, pravastatin, rosuvastatin, or simvastatin, those of ABCG2 c.421C>A with intolerance to atorvastatin, fluvastatin, or rosuvastatin, and that of CYP2C9*2 and *3 alleles with intolerance to fluvastatin.

METHODS

We studied the associations of these variants with statin intolerance in 2042 patients initiating statin therapy by combining genetic data from samples from the Helsinki Biobank to clinical chemistry and statin purchase data.

RESULTS

We confirmed the association of SLCO1B1 c.521C/C genotype with simvastatin intolerance both by using phenotype of switching initial statin to another as a marker of statin intolerance [hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.08-3.25, P  = 0.025] and statin switching along with creatine kinase measurement (HR 5.44, 95% CI 1.49-19.9, P  = 0.011). No significant association was observed with atorvastatin and rosuvastatin. The sample sizes for fluvastatin and pravastatin were relatively small, but SLCO1B1 c.521T>C carriers had an increased risk of pravastatin intolerance defined by statin switching when compared to homozygous reference T/T genotype (HR 2.11, 95% CI 1.01-4.39, P  = 0.047).

CONCLUSION

The current results can inform pharmacogenetic statin prescribing guidelines and show feasibility for the methodology to be used in larger future studies.

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Pharmacogenomics of response to statin treatment and susceptibility to statin-induced adverse drug reactions in Asians: a scoping review

Background

Statins are the most widely used lipid-lowering agents for patients with hyperlipidemia. However, interindividual variations in efficacy and risk of adverse drug reactions to statin treatment have been widely reported. Ethnicity is well known to be one of the contributing factors to this variation, particularly among Asians.

Objectives

To identify genetic variants associated with statin treatment responses among Asian populations with a focus on four commonly prescribed statins: atorvastatin, rosuvastatin, simvastatin, and pravastatin.

Methods

A literature search was conducted in Medline and Embase databases. Studies published from 2008 to 2021 were included. The title and abstract of each article were screened by two reviewers and verified by another two reviewers. Data charted include information on authors, year of study, study population, statin studied, gene studied, study findings, and data of significant statistical value.

Results

A total of 35 articles were included from the 1,939 original studies related to treatment efficacy and 5 articles out of the 284 original studies related to adverse effects. Genetic variants in transmembrane transporters, cytochrome P450 isoenzymes, and apolipoproteins are the most extensively studied among Asian populations, with a main focus on ethnic Chinese. However, Asia consists of genetically different populations, and the results of this review indicated that there is a paucity of studies on other ethnic groups within Asia.

Conclusions

Considering the ethnicity of patients could provide a potential value to personalized medicine in statin therapy.

SLCO1B1 gene-based clinical decision support reduces statin-associated muscle symptoms risk with simvastatin

Background: SLCO1B1 variants are known to be a strong predictor of statin-associated muscle symptoms (SAMS) risk with simvastatin. Methods: The authors conducted a retrospective chart review on 20,341 patients who had SLCO1B1 genotyping to quantify the uptake of clinical decision support (CDS) for genetic variants known to impact SAMS risk. Results: A total of 182 patients had 417 CDS alerts generated, and 150 of these patients (82.4%) received pharmacotherapy that did not increase risks for SAMS. Providers were more likely to cancel simvastatin orders in response to CDS alerts if genotyping had been done prior to the first simvastatin prescription than after (94.1% vs 28.5%, respectively; p < 0.001). Conclusion: CDS significantly reduces simvastatin prescribing at doses associated with SAMS.

PharmVar GeneFocus: SLCO1B1

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin-associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self-assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator-submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar-developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin-associated musculoskeletal symptoms.

Correlates of Myopathy in Diabetic Patients Taking Statins

Diabetes is one of the most common chronic ailments; its incidence has reached epidemic proportions in the 21st century. Diabetes significantly increases micro and macrovascular complications, which are effectively managed with statins. Therefore, statins' pharmacokinetics, pharmacodynamics, and pharmacogenetics have been extensively studied. Although statins act as a keystone in preventing cardiovascular complications, at the same time, they pose a threat to the quality of life of diabetics due to the resulting muscular side effects. This article summarizes the prevalence, clinical manifestations, pathophysiology, and risk factors of statin-induced myopathy in diabetic patients. Among the diverse predisposing risk factors, the primary variables identified for causing myopathy in diabetic patients include age, gender, ethnicity, duration and severity of illness, comorbid conditions, level of physical activity, alcohol use, cholecalciferol (vitamin D3) levels, type and dose of statins, and anti-diabetic drugs or other drugs used concomitantly. In addition, cardiovascular risk quotients also potentially impact diabetic patients making them more vulnerable to developing myopathy from statins. Therefore, this study highlights the importance of managing statin-associated myopathic side effects by providing consensus guidelines on diagnostic, monitoring, and treatment strategies. We also discussed statins' prognostic value in reducing cardiovascular events in diabetic individuals.

Predictive Value of SLCO1B1 c.521T>C Polymorphism on Observed Changes in the Treatment of 1136 Statin-Users

Pharmacogenomic testing is a method to prevent adverse drug reactions. Pharmacogenomics could be relevant to optimize statin treatment, by identifying patients at high risk for adverse drug reactions. We aim to investigate the clinical validity and utility of pre-emptive pharmacogenomics screening in primary care, with SLCO1B1 c.521T>C as a risk factor for statin-induced adverse drug reactions. The focus was on changes in therapy as a proxy for adverse drug reactions observed in statin-users in a population-based Dutch cohort. In total, 1136 statin users were retrospectively genotyped for the SLCO1B1 c.521T>C polymorphism (rs4149056) and information on their statin dispensing was evaluated as cross-sectional research. Approximately half of the included participants discontinued or switched their statin treatment within three years. In our analyses, we could not confirm an association between the SLCO1B1 c.521T>C genotype and any change in statin therapy or arriving at a stable dose sooner in primary care. To be able to evaluate the predictive values of SLCO1B1 c.521T>C genotype on adverse drug reactions from statins, prospective data collection of actual adverse drug reactions and reasons to change statin treatment should be facilitated.

Using Data to Improve the Management of Diabetes: The Tayside Experience

Tayside is a region in the East of Scotland and forms one of nine local government regions in the country. It is home to approximately 416,000 individuals who fall under the National Health Service (NHS) Tayside health board, which provides health care services to the population. In Tayside, Scotland, a comprehensive informatics network for diabetes care and research has been established for over 25 years. This has expanded more recently to a comprehensive Scotland-wide clinical care system, Scottish Care Information - Diabetes (SCI-Diabetes). This has enabled improved diabetes screening and integrated management of diabetic retinopathy, neuropathy, nephropathy, cardiovascular health, and other comorbidities. The regional health informatics network links all of these specialized services with comprehensive laboratory testing, prescribing records, general practitioner records, and hospitalization records. Not only do patients benefit from the seamless interconnectedness of these data, but also the Tayside bioresource has enabled considerable research opportunities and the creation of biobanks. In this article we describe how health informatics has been used to improve care of people with diabetes in Tayside and Scotland and, through anonymized data linkage, our understanding of the phenotypic and genotypic etiology of diabetes and associated complications and comorbidities.

ABCG2 and SLCO1B1 gene polymorphisms in the Croatian population

BACKGROUND

Organic anion-transporting polypeptide 1B1 (OATP1B1) and the ATP-binding cassette subfamily G member 2, ABCG2, are important transporters involved in the transport of endogenous substrates and xenobiotics, including drugs. Genetic polymorphisms of these transporters have effect on transporter activity. There is significant interethnic variability in the frequency of allele variants.

AIM

To determined allele and genotype frequencies of ABCG2 and SLCO1B1 genes in Croatian populations of European descent.

SUBJECTS AND METHODS

A total of 905 subjects (482 women) were included. Genotyping for ABCG2 c.421C > A (rs2231142) and for SLCO1B1 c.521T > C (rs4149056), was performed by real-time polymerase chain reaction (PCR) using TaqMan^® DME Genotyping Assays.

RESULTS

For ABCG2 c.421C > A, the frequency of CC, CA and AA genotypes was 81.4%, 17.8% and 0.8% respectively. The frequency of variant ABCG2 421 A allele was 9.7%. For SLCO1B1 c.521T > C, the frequency of TT, TC and CC genotypes was 61.7%, 34.8% and 3.5% respectively. The frequency of variant SLCO1B1 521 C allele was 20.9%.

CONCLUSION

The frequency of the ABCG2 and SLCO1B1 allelic variants and genotypes in the Croatian population is in accordance with other European populations. Pharmacogenetic analysis can serve to individualise drug therapy and minimise the risk of developing adverse drug reactions.

Pharmacogenomics of lipid-lowering agents: the impact on efficacy and safety

Hyperlipidemia is a significant risk factor for cardiovascular disease morbidity and mortality. The lipid-lowering drugs are considered the cornerstone of primary and secondary prevention of atherosclerotic cardiovascular disease. Unfortunately, the lack of efficacy and associated adverse effects, ranging from mild-to-moderate to potentially life-threatening, lead to therapy discontinuation. Numerous reports support the role of gene polymorphisms in drugs' pharmacokinetic parameters and their associated adverse reactions. Therefore, this study aims to understand the pharmacogenomics of lipid-lowering drugs and the impact of genetic variants of key genes on the drugs' efficacy and toxicity. Indeed, genetically guided lipid-lowering therapy enhances overall safety, improves drug adherence and achieves long-term therapy.

Personalized medicine in cardiovascular disease: review of literature

Purpose

Personalized medicine (PM) is the concept of managing patients based on their characteristics, including genotypes. In the field of cardiology, advantages of PM could be found in the diagnosis and treatment of several conditions such as arrhythmias and cardiomyopathies; moreover, it may be beneficial to prevent adverse drug reactions (ADR) and select the best medication. Genetic background can help us in selecting effective treatments, appropriate dose requirements, and preventive strategies in individuals with particular genotypes.

Method

In this review, we provide examples of personalized medicine based on human genetics for the most used pharmaceutics in cardiology, including warfarin, clopidogrel, and statins. We also review cardiovascular diseases, including coronary artery disease, arrhythmia, and cardiomyopathies.

Conclusion

Genetic factors are as important as environmental factors and they should be tested and evaluated more in the future by improving in genetic testing tools.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-021-00840-0.

Atorvastatin-associated rhabdomyolysis in a patient with a novel variant of the SLCO1B1 gene: A case report

We report the case of an individual with severe hypercholesterolemia who experienced rhabdomyolysis with high dose atorvastatin. Genetic testing was undertaken to evaluate for suspected familial hypercholesterolemia (FH) and for the presence of gene variants associated with susceptibility to statin associated muscle disease. Genetic testing identified the presence of a potentially damaging variant of the hepatic xenobiotic transporter pump SLCO1B1, a single nucleotide variant (SNV) (rs77271279, c.481+1G>T) that disrupts the canonical donor splice motif. Although this variant has not previously been reported as associated with rhabdomyolysis and thus requires validation in population studies, it likely played a role in this patient's susceptibility to rhabdomyolysis based on functional assessment of the effect of this variant on SLCO1B1 protein function and given the known role of this transporter in statin uptake by the liver. The presence of this gene variant reinforced our decision to treat the patient's hypercholesterolemia with non-statin alternatives (PCSK9 inhibitor and ezetimibe). Genetic testing also identified the presence of a second SLCO1B1 gene variant, c.1200C>G (p.Phe400Leu, rs59113707) and homozygosity for an intron variant of the apolipoprotein(a) (LPA) gene (c.2604.138G>A intron variant, rs9457951) associated with increased Lp(a), a risk factor for atherosclerotic cardiovascular disease. Notably, all three variants are rare in persons of European descent but more frequent in African-Americans. These findings underscore the role of disabling mutations of the SLCO1B1 gene in statin myopathy and the need to validate these and other gene variants associated with statin myopathy in a population of patients with statin-associated muscle disease.

Common Statin Intolerance Variants in ABCB1 and LILRB5 Show Synergistic Effects on Statin Response: An Observational Study Using Electronic Health Records

Background: Statin intolerance impacts approximately 10% of statin users, with side effects ranging from mild myalgia to extreme intolerance resulting in myopathy and rhabdomyolysis. Statin intolerance results in poor adherence to therapy and can impact statin efficacy. Many genetic variants are associated with statin intolerance. The effect of these variants on statin efficacy has not been systematically explored.

Methods: Using longitudinal electronic health records and genetic biobank data from Tayside, Scotland, we examined the effect of seven genetic variants with previously reported associations with simvastatin or atorvastatin intolerance on the outcome of statin response. Statin response was measured by the reduction achieved when comparing pre- and post-statin non-high-density lipoprotein-cholesterol (non-HDL-C). Post-treatment statin response was limited to non-HDL-C measured within 6months of therapy initiation. Univariate and multivariable linear regression models were used to assess the main and adjusted effect of the variants on statin efficacy.

Results: Around 9,401 statin users met study inclusion criteria, of whom 8,843 were first prescribed simvastatin or atorvastatin. The average difference in post-treatment compared to pre-treatment non-HDL-cholesterol was 1.45 (±1.04) mmol/L. In adjusted analyses, only two variants, one in the gene ATP-binding cassette transporter B1 (ABCB1; rs1045642), and one in leukocyte immunoglobulin like receptor B5 (LILRB5; rs12975366), were associated with statin efficacy. In ABCB1, homozygous carriers of the C allele at rs1045642 had 0.06mmol/L better absolute reduction in non-HDL-cholesterol than carriers of the T allele (95% CI: 0.01, 0.1). In LILRB5 (rs12975366), carriers of the C allele had 0.04mmol/L better absolute reduction compared to those homozygous for the T allele (95% CI: 0.004, 0.08). When combined into a two-variant risk score, individuals with both the rs1045642-CC genotype and the rs12975366-TC or CC genotype had a 0.11mmol/L greater absolute reduction in non-HDL-cholesterol compared to those with rs1045642-TC or TT genotype and the rs12975366-TT genotype (95% CI: 0.05, 0.16; p<0.001).

Conclusion: We report two genetic variants for statin adverse drug reactions (ADRs) that are associated with statin efficacy. While the ABCB1 variant has been shown to have an association with statin pharmacokinetics, no similar evidence for LILRB5 has been reported. These findings highlight the value of genetic testing to deliver precision therapeutics to statin users.

Utilizing Large Electronic Medical Record Data Sets to Identify Novel Drug-Gene Interactions for Commonly Used Drugs

Real-world prescribing of drugs differs from the experimental systems, physiological-pharmacokinetic models, and clinical trials used in drug development and licensing, with drugs often used in patients with multiple comorbidities with resultant polypharmacy. The increasing availability of large biobanks linked to electronic healthcare records enables the potential to identify novel drug-gene interactions in large populations of patients. In this study we used three Scottish cohorts and UK Biobank to identify drug-gene interactions for the 50 most commonly used drugs and 162 variants in genes involved in drug pharmacokinetics. We defined two phenotypes based upon prescribing behavior-drug-stop or dose-decrease. Using this approach, we replicate 11 known drug-gene interactions including, for example, CYP2C9/CYP2C8 variants and sulfonylurea/thiazolidinedione prescribing and ABCB1/ABCG2 variants and statin prescribing. We identify eight novel associations after Bonferroni correction, three of which are replicated or validated in the UK Biobank or have other supporting results: The C-allele at rs4918758 in CYP2C9 was associated with a 25% (15-44%) lower odds of dose reduction of quinine, P = 1.6 × 10^-5 ; the A-allele at rs9895420 in ABCC3 was associated with a 46% (24-62%) reduction in odds of dose reduction with doxazosin, P = 1.2 × 10^-4 , and altered blood pressure response in the UK Biobank; the CYP2D6*2 variant was associated with a 30% (18-40%) reduction in odds of stopping ramipril treatment, P = 1.01 × 10^-5 , with similar results seen for enalapril and lisinopril and with other CYP2D6 variants. This study highlights the scope of using large population bioresources linked to medical record data to explore drug-gene interactions at scale.

Association between CYP3A5 Polymorphism and Statin-Induced Adverse Events: A Systemic Review and Meta-Analysis

Purpose: Cytochrome P450 (CYP) is involved in the metabolism of statins; CYP3A5 is the main enzyme responsible for lipophilic statin metabolism. However, the evidence of the association between CYP3A5*3 polymorphism and the risk of statin-induced adverse events remains unclear. Therefore, this study aimed to perform a systematic review and meta-analysis to investigate the relationship between the CYP3A5*3 polymorphism and the risk of statin-induced adverse events. Methods: The PubMed, Web of Science, and EMBASE databases were searched for qualified studies published until August 2020. Observational studies that included the association between statin-induced adverse events and the CYP3A5*3 polymorphism were reviewed. The odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated to assess the strength of the relationship. The Mantel-Haenszel method was used to provide the pooled ORs. Heterogeneity was estimated with I² statistics and publication bias was determined by Begg's and Egger's test of the funnel plot. Data analysis was performed using Review Manager (version 5.4) and R Studio (version 3.6). Results: In total, data from 8 studies involving 1614 patients were included in this meta-analysis. The CYP3A5*3 polymorphism was found to be associated with the risk of statin-induced adverse events (*3/*3 vs. *1/*1 + *1/*3: OR = 1.40, 95% CI = 1.08-1.82). For myopathy, the pooled OR was 1.30 (95% CI: 0.96-1.75). The subgroup analysis of statin-induced myopathy revealed a trend, which did not achieve statistical significance. Conclusions: This meta-analysis demonstrated that the CYP3A5*3 polymorphism affected statin-induced adverse event risk. Therefore, CYP3A5 genotyping may be useful to predict statin toxicity.

Robust Performance of Potentially Functional SNPs in Machine Learning Models for the Prediction of Atorvastatin-Induced Myalgia

Statins can cause muscle symptoms resulting in poor adherence to therapy and increased cardiovascular risk. We hypothesize that combinations of potentially functional SNPs (pfSNPs), rather than individual SNPs, better predict myalgia in patients on atorvastatin. This study assesses the value of potentially functional single nucleotide polymorphisms (pfSNPs) and employs six machine learning algorithms to identify the combination of SNPs that best predict myalgia.

Methods: Whole genome sequencing of 183 Chinese, Malay and Indian patients from Singapore was conducted to identify genetic variants associated with atorvastatin induced myalgia. To adjust for confounding factors, demographic and clinical characteristics were also examined for their association with myalgia. The top factor, sex, was then used as a covariate in the whole genome association analyses. Variants that were highly associated with myalgia from this and previous studies were extracted, assessed for potential functionality (pfSNPs) and incorporated into six machine learning models. Predictive performance of a combination of different models and inputs were compared using the average cross validation area under ROC curve (AUC). The minimum combination of SNPs to achieve maximum sensitivity and specificity as determined by AUC, that predict atorvastatin-induced myalgia in most, if not all the six machine learning models was determined.

Results: Through whole genome association analyses using sex as a covariate, a larger proportion of pfSNPs compared to non-pf SNPs were found to be highly associated with myalgia. Although none of the individual SNPs achieved genome wide significance in univariate analyses, machine learning models identified a combination of 15 SNPs that predict myalgia with good predictive performance (AUC >0.9). SNPs within genes identified in this study significantly outperformed SNPs within genes previously reported to be associated with myalgia. pfSNPs were found to be more robust in predicting myalgia, outperforming non-pf SNPs in the majority of machine learning models tested.

Conclusion: Combinations of pfSNPs that were consistently identified by different machine learning models to have high predictive performance have good potential to be clinically useful for predicting atorvastatin-induced myalgia once validated against an independent cohort of patients.

Statin-Induced Myopathy: Translational Studies from Preclinical to Clinical Evidence

Statins are the most prescribed and effective drugs to treat cardiovascular diseases (CVD). Nevertheless, these drugs can be responsible for skeletal muscle toxicity which leads to reduced compliance. The discontinuation of therapy increases the incidence of CVD. Thus, it is essential to assess the risk. In fact, many studies have been performed at preclinical and clinical level to investigate pathophysiological mechanisms and clinical implications of statin myotoxicity. Consequently, new toxicological aspects and new biomarkers have arisen. Indeed, these drugs may affect gene transcription and ion transport and contribute to muscle function impairment. Identifying a marker of toxicity is important to prevent or to cure statin induced myopathy while assuring the right therapy for hypercholesterolemia and counteracting CVD. In this review we focused on the mechanisms of muscle damage discovered in preclinical and clinical studies and highlighted the pathological situations in which statin therapy should be avoided. In this context, preventive or substitutive therapies should also be evaluated.

A systematic review and meta-analysis of genotype-based and individualized data analysis of SLCO1B1 gene and statin-induced myopathy

This meta-analysis was conducted to determine the genotypic effects of rs4149056 and rs2306283 polymorphism in SLCO1B1 gene on myopathy in patients with statin. Studies were searched using multiple databases and selected following inclusion criteria. Two reviewers independently performed data extraction and assessments for risk of bias. Fixed-or-random-effect was applied to pool allele frequency/effects. Mixed-effect logit model was used to pool genotypic effects using individual patient data. Heterogeneity and publication bias were explored. Fourteen studies were pooled for rs4149056; the minor C allele frequency were 15% in Caucasians and 14% in Asians. Six studies were pooled for rs2306283; the minor G allele frequency was 34% in Caucasian and 75% in Asians. Genotypic effects of rs4149056 polymorphism in Caucasians indicated that statin users who carried CC and TC genotypes had a significantly higher risk of myopathy than those who carried TT genotype, with a pooled odds ratio (OR) of 2.9 (95% confidence interval, 1.59, 5.34) and 1.6 (1.20, 2.16), respectively. For subgroup analysis, CC and TC genotypes also suggested a higher risk of myopathy in simvastatin users [OR = 2.8 (1.17, 6.77) and OR = 1.8 (1.15, 2.77), respectively] and in atorvastatin users [OR = 4.0 (1.23, 12.63) and OR = 2.0 (1.11, 3.52), respectively] than those who carried TT genotype. There was no significant association between rs2306283 polymorphism and myopathy in Caucasians and Asians. There was no evidence of publication bias for both polymorphisms.

Effect of Pharmacogenetic Testing for Statin Myopathy Risk vs Usual Care on Blood Cholesterol: A Randomized Clinical Trial

IMPORTANCE

Nonadherence to statin guidelines is common. The solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotype is associated with simvastatin myopathy risk and is proposed for clinical implementation. The unintended harms of using pharmacogenetic information to guide pharmacotherapy remain a concern for some stakeholders.

OBJECTIVE

To determine the impact of delivering SLCO1B1 pharmacogenetic results to physicians on the effectiveness of atherosclerotic cardiovascular disease (ASCVD) prevention (measured by low-density lipoprotein cholesterol [LDL-C] levels) and concordance with prescribing guidelines for statin safety and effectiveness.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial was performed from December 2015 to July 2019 at 8 primary care practices in the Veterans Affairs Boston Healthcare System. Participants included statin-naive patients with elevated ASCVD risk. Data analysis was performed from October 2019 to September 2020.

INTERVENTIONS

SLCO1B1 genotyping and results reporting to primary care physicians at baseline (intervention group) vs after 1 year (control group).

MAIN OUTCOMES AND MEASURES

The primary outcome was the 1-year change in LDL-C level. The secondary outcomes were 1-year concordance with American College of Cardiology-American Heart Association and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statin therapy and statin-associated muscle symptoms (SAMS).

RESULTS

Among 408 patients (mean [SD] age, 64.1 [7.8] years; 25 women [6.1%]), 193 were randomized to the intervention group and 215 were randomized to the control group. Overall, 120 participants (29%) had a SLCO1B1 genotype indicating increased simvastatin myopathy risk. Physicians offered statin therapy to 65 participants (33.7%) in the intervention group and 69 participants (32.1%) in the control group. Compared with patients whose physicians did not know their SLCO1B1 results at baseline, patients whose physicians received the results had noninferior reductions in LDL-C at 12 months (mean [SE] change in LDL-C, -1.1 [1.2] mg/dL in the intervention group and -2.2 [1.3] mg/dL in the control group; difference, -1.1 mg/dL; 90% CI, -4.1 to 1.8 mg/dL; P < .001 for noninferiority margin of 10 mg/dL). The proportion of patients with American College of Cardiology-American Heart Association guideline-concordant statin prescriptions in the intervention group was noninferior to that in the control group (12 patients [6.2%] vs 14 patients [6.5%]; difference, -0.003; 90% CI, -0.038 to 0.032; P < .001 for noninferiority margin of 15%). All patients in both groups were concordant with CPIC guidelines for safe statin prescribing. Physicians documented 2 and 3 cases of SAMS in the intervention and control groups, respectively, none of which was associated with a CPIC guideline-discordant prescription. Among patients with a decreased or poor SLCO1B1 transporter function genotype, simvastatin was prescribed to 1 patient in the control group but none in the intervention group.

CONCLUSIONS AND RELEVANCE

Clinical testing and reporting of SLCO1B1 results for statin myopathy risk did not result in poorer ASCVD prevention in a routine primary care setting and may have been associated with physicians avoiding simvastatin prescriptions for patients at genetic risk for SAMS. Such an absence of harm should reassure stakeholders contemplating the clinical use of available pharmacogenetic results.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02871934.

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.

Correlation between single-nucleotide polymorphisms and statin-induced myopathy: a mixed-effects model meta-analysis

PURPOSE

A meta-analysis was performed to evaluate the correlation between single-nucleotide polymorphisms (SNPs) and risk of statin-induced myopathy (SIM).

METHODS

We retrieved the studies published on SIM until April 2019 from the PubMed, Embase, and Cochrane Library databases. We collected data from 32 studies that analyzed 10 SNPs in five genes and included 21,692 individuals and nine statins.

RESULTS

The analysis of the heterozygous (p = 0.017), homozygous (p = 0.002), dominant (p = 0.005), and recessive models (p = 0.009) of SLCO1B1 rs4149056 showed that this SNP increases the risk of SIM. Conversely, heterozygous (p = 0.048) and dominant models (p = 0.030) of SLCO1B1 rs4363657 demonstrated that this SNP is associated with a reduced risk of SIM. Moreover, an increased risk of SIM was predicted for carriers of the rs4149056 C allele among simvastatin-treated patients, whereas carriers of the GATM rs9806699 A allele among rosuvastatin-treated patients had a lower risk of SIM.

CONCLUSION

The meta-analysis revealed that the rs4149056 and rs4363657 SNPs in SLCO1B1 and the rs9806699 SNP in GATM are correlated with the risk of SIM.

Pharmacogenetics of Statin-Induced Myotoxicity

Statins, a class of lipid-lowering medications, have been a keystone treatment in cardiovascular health. However, adverse effects associated with statin use impact patient adherence, leading to statin discontinuation. Statin-induced myotoxicity (SIM) is one of the most common adverse effects, prevalent across all ages, genders, and ethnicities. Although certain demographic cohorts carry a higher risk, the impaired quality of life attributed to SIM is significant. The pathogenesis of SIM remains to be fully elucidated, but it is clear that SIM is multifactorial. These factors include drug-drug interactions, renal or liver dysfunction, and genetics. Genetic-inferred risk for SIM was first reported by a landmark genome-wide association study, which reported a higher risk of SIM with a polymorphism in the SLCO1B1 gene. Since then, research associating genetic factors with SIM has expanded widely and has become one of the foci in the field of pharmacogenomics. This review provides an update on the genetic risk factors associated with SIM.

A Genome-wide Association Study of Circulating Levels of Atorvastatin and Its Major Metabolites

Atorvastatin (ATV) is frequently prescribed and generally well  tolerated, but can lead to myotoxicity, especially at higher doses. A genome-wide association study of circulating levels of ATV, 2-hydroxy (2-OH) ATV, ATV lactone (ATV L), and 2-OH ATV L was performed in 590 patients who had been hospitalized with a non-ST elevation acute coronary syndrome 1 month earlier and were on high-dose ATV (80 mg or 40 mg daily). The UGT1A locus (lead single nucleotide polymorphism, rs887829) was strongly associated with both increased 2-OH ATV/ATV (P = 7.25 × 10^-16 ) and 2-OH ATV L/ATV L (P = 3.95 × 10^-15 ) metabolic ratios. Moreover, rs45446698, which tags CYP3A7*1C, was nominally associated with increased 2-OH ATV/ATV (P = 6.18 × 10^-7 ), and SLCO1B1 rs4149056 with increased ATV (P = 2.21 × 10^-6 ) and 2-OH ATV (P = 1.09 × 10^-6 ) levels. In a subset of these patients whose levels of ATV and metabolites had also been measured at 12 months after hospitalization (n = 149), all of these associations remained, except for 2-OH ATV and rs4149056 (P = 0.057). Clinically, rs4149056 was associated with increased muscular symptoms (odds ratio (OR) 3.97; 95% confidence interval (CI) 1.29-12.27; P = 0.016) and ATV intolerance (OR 1.55; 95% CI 1.09-2.19; P = 0.014) in patients (n = 870) primarily discharged on high-dose ATV. In summary, both novel and recognized genetic associations have been identified with circulating levels of ATV and its major metabolites. Further study is warranted to determine the clinical utility of genotyping rs4149056 in patients on high-dose ATV.

The impact of statins on physical activity and exercise capacity: an overview of the evidence, mechanisms, and recommendations

PURPOSE

Statins are among the most widely prescribed medications worldwide. Considered the 'gold-standard' treatment for cardiovascular disease (CVD), statins inhibit HMG-CoA reductase to ultimately reduce serum LDL-cholesterol levels. Unfortunately, the main adverse event of statin use is the development of muscle-associated problems, referred to as SAMS (statin-associated muscle symptoms). While regular moderate physical activity also decreases CVD risk, there is apprehension that physical activity may induce and/or exacerbate SAMS. While much work has gone into identifying the epidemiology of SAMS, only recent research has focused on the extent to which these muscle symptoms are accompanied by functional declines. The purpose of this review is to provide an overview of possible mechanisms underlying SAMS and summarize current evidence regarding the relationship between statin treatment, physical activity, exercise capacity, and SAMS development.

METHODS

PubMed and Google Scholar databases were used to search the most relevant and up-to-date peer-reviewed research on the topic.

RESULTS

The mechanism(s) behind SAMS, including altered mitochondrial metabolism, reduced coenzyme Q10 levels, reduced vitamin D levels, impaired calcium homeostasis, elevated extracellular glutamate, and genetic polymorphisms, still lack consensus and remain up for debate. Our summation of the evidence leads us to suggest that the etiology of SAMS development is likely multifactorial. Our review also demonstrates that there is limited evidence for statins impairing exercise adaptations or reducing exercise capacity for the majority of the investigated populations.

CONCLUSION

The available evidence indicates that the benefits of engaging in physical activity while on statin medication largely outweigh the risks.

Association between rs4149056 variant in SLCO1B1 and early discontinuation of statin after acute myocardial infarction

Data from two French surveys were used to analyze the association between in-hospital statin discontinuation and SLCO1B1 polymorphism (rs4149056) in patients with acute myocardial infarction. Using TaqMan allelic discrimination assay, 1674 and 1708 patients were genotyped for SLCO1B1 in 2005 and 2010, respectively. The association with in-hospital statin discontinuation was assessed after adjusting for confounding factors. In 2005, homozygosity for the reduced-function allele was associated with an increased risk of in-hospital statin discontinuation (OR: 3.68; p = 0.004) compared with the wild-type allele but this association disappeared in 2010. However, statin type and intensity-dose differed significantly between the surveys. SLCO1B1 polymorphism (rs4149056) does not seem to be a major determinant of early ‘in-hospital’ statin discontinuation after acute myocardial infarction.

Statin-Related Myotoxicity: A Comprehensive Review of Pharmacokinetic, Pharmacogenomic and Muscle Components

Statins are a cornerstone in the pharmacological prevention of cardiovascular disease. Although generally well tolerated, a small subset of patients experience statin-related myotoxicity (SRM). SRM is heterogeneous in presentation; phenotypes include the relatively more common myalgias, infrequent myopathies, and rare rhabdomyolysis. Very rarely, statins induce an anti-HMGCR positive immune-mediated necrotizing myopathy. Diagnosing SRM in clinical practice can be challenging, particularly for mild SRM that is frequently due to alternative aetiologies and the nocebo effect. Nevertheless, SRM can directly harm patients and lead to statin discontinuation/non-adherence, which increases the risk of cardiovascular events. Several factors increase systemic statin exposure and predispose to SRM, including advanced age, concomitant medications, and the nonsynonymous variant, rs4149056, in SLCO1B1, which encodes the hepatic sinusoidal transporter, OATP1B1. Increased exposure of skeletal muscle to statins increases the risk of mitochondrial dysfunction, calcium signalling disruption, reduced prenylation, atrogin-1 mediated atrophy and pro-apoptotic signalling. Rare variants in several metabolic myopathy genes including CACNA1S, CPT2, LPIN1, PYGM and RYR1 increase myopathy/rhabdomyolysis risk following statin exposure. The immune system is implicated in both conventional statin intolerance/myotoxicity via LILRB5 rs12975366, and a strong association exists between HLA-DRB1*11:01 and anti-HMGCR positive myopathy. Epigenetic factors (miR-499-5p, miR-145) have also been implicated in statin myotoxicity. SRM remains a challenge to the safe and effective use of statins, although consensus strategies to manage SRM have been proposed. Further research is required, including stringent phenotyping of mild SRM through N-of-1 trials coupled to systems pharmacology omics- approaches to identify novel risk factors and provide mechanistic insight.

Drug-drug-gene interactions and adverse drug reactions

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

Muscle Toxicity of Drugs: When Drugs Turn Physiology into Pathophysiology

Drugs are prescribed to manage or prevent symptoms and diseases, but may sometimes cause unexpected toxicity to muscles. The symptomatology and clinical manifestations of the myotoxic reaction can vary significantly between drugs and between patients on the same drug. This poses a challenge on how to recognize and prevent the occurrence of drug-induced muscle toxicity. The key to appropriate management of myotoxicity is prompt recognition that symptoms of patients may be drug related and to be aware that inter-individual differences in susceptibility to drug-induced toxicity exist. The most prevalent and well-documented drug class with unintended myotoxicity are the statins, but even today new classes of drugs with unintended myotoxicity are being discovered. This review will start off by explaining the principles of drug-induced myotoxicity and the different terminologies used to distinguish between grades of toxicity. The main part of the review will focus on the most important pathogenic mechanisms by which drugs can cause muscle toxicity, which will be exemplified by drugs with high risk of muscle toxicity. This will be done by providing information on key clinical and laboratory aspects, muscle electromyography patterns and biopsy results, and pathological mechanism and management for a specific drug from each pathogenic classification. In addition, rather new classes of drugs with unintended myotoxicity will be highlighted. Furthermore, we will explain why it is so difficult to diagnose drug-induced myotoxicity, and which tests can be used as a diagnostic aid. Lastly, a brief description will be given of how to manage and treat drug-induced myotoxicity.

Evidence to Support Inclusion of Pharmacogenetic Biomarkers in Randomised Controlled Trials

Pharmacogenetics and biomarkers are becoming normalised as important technologies to improve drug efficacy rates, reduce the incidence of adverse drug reactions, and make informed choices for targeted therapies. However, their wider clinical implementation has been limited by a lack of robust evidence. Suitable evidence is required before a biomarker's clinical use, and also before its use in a clinical trial. We have undertaken a review of five pharmacogenetic biomarker-guided randomised controlled trials (RCTs) and evaluated the evidence used by these trials to justify biomarker inclusion. We assessed and quantified the evidence cited in published rationale papers, or where these were not available, obtained protocols from trial authors. Very different levels of evidence were provided by the trials. We used these observations to write recommendations for future justifications of biomarker use in RCTs and encourage regulatory authorities to write clear guidelines.

Role of genetics in the prediction of statin-associated muscle symptoms and optimization of statin use and adherence

Statin therapy reduces cardiovascular events in patients with, or at risk of, atherosclerotic cardiovascular disease. However, statins are underutilized in patients for whom they are indicated and are frequently discontinued. Discontinuation may be the result of statin-associated muscle symptoms (SAMS), which encompass a broad spectrum of clinical phenotypes from myalgia to severe myopathy. As with many adverse drug reactions (ADRs), inter-individual variability in susceptibility to SAMS is due, at least in part, to differences in host genetics. The genetic basis for SAMS has been investigated in candidate gene studies, genome-wide association studies, and, more recently, studies of multi-omic networks, including at the transcriptome level. In this article, we provide a systematic review of the pharmacogenetic basis of SAMS, focusing on how an understanding of the genetic and molecular determinants of SAMS can be considered in a personalized approach to reduce the incidence of this ADR, optimize statin adherence, and reduce the risk for cardiovascular events.

Genomewide Association Study of Statin-Induced Myopathy in Patients Recruited Using the UK Clinical Practice Research Datalink

Statins can be associated with myopathy. We have undertaken a genomewide association study (GWAS) to discover and validate genetic risk factors for statin‐induced myopathy in a “real‐world” setting. One hundred thirty‐five patients with statin myopathy recruited via the UK Clinical Practice Research Datalink were genotyped using the Illumina OmniExpress Exome version 1.0 Bead Chip and compared with the Wellcome Trust Case‐Control Consortium (n = 2,501). Nominally statistically significant single nucleotide polymorphism (SNP) signals in the GWAS (P < 5 × 10⁻⁵) were further evaluated in several independent cohorts (comprising 332 cases and 449 drug‐tolerant controls). Only one (rs4149056/c.521C>T in the SLCO1B1 gene) SNP was genomewide significant in the severe myopathy (creatine kinase > 10 × upper limit of normal or rhabdomyolysis) group (P = 2.55 × 10⁻⁹; odds ratio 5.15; 95% confidence interval 3.13–8.45). The association with SLCO1B1 was present for several statins and replicated in the independent validation cohorts. The data highlight the role of SLCO1B1 c.521C>T SNP as a replicable genetic risk factor for statin myopathy. No other novel genetic risk factors with a similar effect size were identified.

Fevipiprant has a low risk of influencing co-medication pharmacokinetics: Impact on simvastatin and rosuvastatin in different SLCO1B1 genotypes

Fevipiprant, a prostaglandin D₂ receptor 2 antagonist, is in clinical development as a treatment for asthma. The goal of this study was to assess the potential of fevipiprant to cause drug-drug interactions (DDI) as a perpetrator, that is, by altering the pharmacokinetics (PK) of co-medications. In vitro drug interaction studies of clinically relevant drug metabolizing enzymes and transporters were conducted for fevipiprant and its acyl glucuronide (AG) metabolite. Comparison of K_i values with unbound systemic or portal vein steady-state plasma exposure of fevipiprant and its AG metabolite revealed the potential for inhibition of organic anion transporting polypeptide 1B1 (OATP1B1) transporters (R-value of 5.99), while other targets including cytochrome P450 enzymes were not, or only marginally, inhibited. Consequently, an open-label, two-part, two-period, single-sequence clinical study assessed the effect of fevipiprant 450 mg QD on the pharmacokinetics of simvastatin 20 mg and rosuvastatin 20 mg, two statins with different dependency in OATP1B1-mediated hepatic uptake, in healthy adult volunteers. The study also assessed the pharmacogenetics of the SLCO1B1 gene, which encodes OATP1B1. Clinically, fevipiprant 450 mg QD showed a low potential for interaction and increased the peak concentrations of simvastatin acid and rosuvastatin by 2.23- and 1.87-fold, respectively, with little or no impact on total exposure. Genotype analysis confirmed that SLCO1B1 genotype influences statin pharmacokinetics to a similar extent either with or without fevipiprant co-administration. In summary, fevipiprant at 450 mg QD has only minor liabilities as a perpetrator for DDI.

Precision Medicine and Personalized Management of Lipoprotein and Lipid Disorders in Chronic and End-Stage Kidney Disease

Precision medicine is an emerging field that calls for individualization of treatment strategies based on characteristics unique to each patient. In lipid management, current guidelines are driven mainly by clinical trial results that presently indicate that patients with non-dialysis-dependent chronic kidney disease (CKD) should be treated with a β-hydroxy β-methylglutaryl-CoA reductase inhibitor, also known as statin therapy. For patients with end-stage kidney disease (ESKD) being treated with hemodialysis, statin therapy has not been shown to successfully reduce poor outcomes in trials and therefore is not recommended. The two major guidelines dissent on whether statin therapy should be of moderate or high intensity in non-dialysis-dependent CKD patients, but often leave the prescribing clinician to make that decision. These decisions often are complicated by the increased concerns for adverse events such as myopathies in patients with advanced kidney disease and ESKD. In the future, there may be an opportunity to further identify CKD and ESKD patients who are more likely to benefit from lipid-modifying therapy as opposed to those who likely will suffer from its side effects using precision medicine tools. For now, data from genetics studies and subgroup analyses may provide insight for future research directions in this field and we review some of the work that has been published in this regard.

The Role of Next-Generation Sequencing in Pharmacogenetics and Pharmacogenomics

Inherited genetic variations in pharmacogenetic loci are widely acknowledged as important determinants of phenotypic differences in drug response, and may be actionable in the clinic. However, recent studies suggest that a considerable number of novel rare variants in pharmacogenes likely contribute to a still unexplained fraction of the observed interindividual variability. Next-generation sequencing (NGS) represents a rapid, relatively inexpensive, large-scale DNA sequencing technology with potential relevance as a comprehensive pharmacogenetic genotyping platform to identify genetic variation related to drug therapy. However, many obstacles remain before the clinical use of NGS-based test results, including technical challenges, functional interpretation, and strict requirements for diagnostic tests. Advanced computational analyses, high-throughput screening methodologies, and generation of shared resources with cell-based and clinical information will facilitate the integration of NGS data into candidate genotyping approaches, likely enhancing future drug phenotype predictions in patients.

The Integrating Pharmacogenetics in Clinical Care (I-PICC) Study: Protocol for a point-of-care randomized controlled trial of statin pharmacogenetics in primary care

BACKGROUND

The association between the SLCO1B1 rs4149056 variant and statin-associated muscle symptoms (SAMS) is well validated, but the clinical utility of its implementation in patient care is unknown.

DESIGN

The Integrating Pharmacogenetics in Clinical Care (I-PICC) Study is a pseudo-cluster randomized controlled trial of SLCO1B1 genotyping among statin-naïve primary care and women's health patients across the Veteran Affairs Boston Healthcare System. Eligible patients of enrolled primary care providers are aged 40-75 and have elevated risk of cardiovascular disease by American College of Cardiology/American Heart Association (ACC/AHA) guidelines. Patients give consent by telephone in advance of an upcoming appointment, but they are enrolled only if and when their provider co-signs an order for SLCO1B1 testing, performed on a blood sample already collected in clinical care. Enrolled patients are randomly allocated to have their providers receive results through the electronic health record at baseline (PGx + arm) versus after 12 months (PGx- arm). The primary outcome is the change in low-density lipoprotein cholesterol (LDL-C) after one year. Secondary outcomes are concordance with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for simvastatin prescribing, concordance with ACC/AHA guidelines for statin use, and incidence of SAMS. With 408 patients, the study has >80% power to exclude a between-group LDL-C difference of 10 mg/dL (non-inferiority design) and to detect between-group differences of 15% in CPIC guideline concordance (superiority design).

CONCLUSION

The outcomes of the I-PICC Study will inform the clinical utility of preemptive SLCO1B1 testing in the routine practice of medicine, including its proposed benefits and unforeseen risks.

Impact of SLCO1B1 Pharmacogenetic Testing on Patient and Healthcare Outcomes: A Systematic Review

Demonstrated improvements in patient outcomes will facilitate the clinical implementation of pharmacogenetic testing. Using the association between solute carrier organic anion transporter family member 1B1 (SLCO1B1) and statin-associated muscle symptoms (SAMSs) as a model, we conducted a systematic review of patient outcomes after delivery of SLCO1B1 results. Using PubMed and Embase searches through December 19, 2017, we identified 37 eligible records reporting preliminary or final outcomes, including six studies delivering only SLCO1B1 results and five large healthcare system-based implementation projects of multipharmacogene panels. Two small trials have demonstrated at least short-term improvements in low-density lipoprotein cholesterol after SLCO1B1 testing among previously statin intolerant patients. Evidence from large implementation projects suggests that SLCO1B1 results may change prescribing patterns for some high-risk patients. No study has reported improvements in SAMSs or cardiovascular events or tracked the economic outcomes of SLCO1B1 testing. Ongoing studies should collect and report outcomes relevant to pharmacogenetics stakeholders.

Analysis of SLCO1B1 and APOE genetic polymorphisms in a large ethnic Hakka population in southern China

OBJECTIVE

Statins are the most widely used lipid-lowering drugs, which have a significant effect on the inhibition of cardiovascular disease. The efficacy and side effects of statins are associated with the polymorphisms of SLCO1B1 and APOE genes. The purpose of this study was to analyze the SLCO1B1 and APOE gene polymorphisms in the Hakka population of southern China.

METHODS

A total of 3249 subjects including 2019 males and 1230 females participated in this study. Polymerase chain reaction (PCR)-fluorescence probe technique for polymorphisms analysis and analyzed the genotypes frequencies of SLCO1B1 and APOE genes.

RESULTS

The frequencies of SLCO1B1 521T>C between men and women were statistically significant (SLCO1B1 521TT, χ2  = 8.431, P = .004; SLCO1B1 521TC, χ2  = 7.436, P = .007). The frequencies of haplotypes *1b/*1b (40.07%) and *1a/*1b (32.56%) of SLCO1B1 gene accounted for 72.63%, followed by *1b/*15(14.40%), *1a/*1a (5.82%), *1a/*15 (5.57%), *15/*15 (1.45%), and *1a/*5 (0.12%). The frequencies of haplotypes *1a/*15 and *1b/*1b of SLCO1B1 gene between men and women were statistically significant (*1a/*15, χ2  = 6.789, P = .009; *1b/*1b, χ2  = 3.998, P = .004). In this study, genotype ɛ3/ɛ3 accounted for 69.04%, followed by ɛ3/ɛ4 (16.19%), ɛ2/ɛ3 (11.60%), ɛ2/ɛ4 (1.35%), ɛ4/ɛ4 (1.08%), and ɛ2/ɛ2 (0.74%) in all subjects, in which ɛ3 had the greatest allele frequency (82.93%), followed by ɛ4 (9.85%) and ɛ2 (7.22%). We found that 47 subjects carrying the SLCO1B1 521 (CC) polymorphism who had not any myopathy caused by statins.

CONCLUSIONS

We analyzed the SLCO1B1 and APOE gene polymorphisms in the Hakka population of southern China. This study provides a reference for the individualized meditation for Hakka population in this area.

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.

Influence of 6 genetic variants on the efficacy of statins in patients with dyslipidemia

BACKGROUND

Patients with dyslipidemia are often treated with statins to reduce lipids and hence cardiovascular risk, but treatment response is variable, partly due to genetic factors.

METHODS

We studied the influence of 6 gene variants (APOE c.526C > T (APOE2), APOE c.388T > C (APOE4), SLCO1B1 c.521T > C, CYP3A4 c.-392G > A, HMGCR c.1564-106A > G, and LPA c.3947 + 467T > C) on statin efficacy assessing 2 indicators: the percent reduction in total cholesterol (TC) and non-HDL cholesterol (non-HDL), as well as the achievement of therapeutic goals. The study was performed in a group of patients (n = 100) without previous pharmacological treatment. Multiple regression models were used to calculate the percentage of explanation in response variability added by every variant to a basal model constructed with significant nongenetic control variables.

RESULTS

The most influential variant was HMGCR c.1564-106A > G (rs3846662), and carriers showed a significantly lower reduction in TC and non-HDL. This variant is related to an alternative splicing involving exon 13, which is also regulated by lipid concentrations in patients without the variant. Concerning therapeutic goals, HMGCR c.1564-106A > G hindered the achievement of TC targets on patients.

CONCLUSIONS

The HMGCR c.1564-106A > G variant was associated with less statin efficacy to decrease cholesterol.

Investigating Real-World Clopidogrel Pharmacogenetics in Stroke Using a Bioresource Linked to Electronic Medical Records

Clopidogrel efficacy is influenced by genetic variation of cytochrome P450 (CYP)2C19, however, few studies have considered patients who have a stroke. We used electronic medical records (EMRs) linked to a bioresource to examine real-world implications of clopidogrel pharmacogenetics in stroke. Patients hospitalized for any arterial thrombo-occlusive (ATO) event who subsequently redeemed clopidogrel prescriptions in the community were entered into the study (n = 651). During 24-month follow-up, the primary endpoint of recurrent ATO or death occurred in 299 patients (46%). CYP2C19*2 loss-of-function allele carriers had an increased risk (hazard ratio (HR) = 1.29; 95% confidence interval (CI) = 1.04-1.59; P = 0.019). In the ischemic stroke subgroup (n = 94), the estimate of risk was greater (HR = 2.23; 95% CI = 1.17-4.24; P = 0.015), which was further supported by a meta-analysis of available studies. In conclusion, we have demonstrated the clinical impact of CYP2C19*2 on clopidogrel efficacy using a purely EMR approach. This suggests that the risk in the ischemic stroke population may be particularly high.

A common missense variant of LILRB5 is associated with statin intolerance and myalgia

Aims

A genetic variant in LILRB5 (leukocyte immunoglobulin-like receptor subfamily-B) (rs12975366: T > C: Asp247Gly) has been reported to be associated with lower creatine phosphokinase (CK) and lactate dehydrogenase (LDH) levels. Both biomarkers are released from injured muscle tissue, making this variant a potential candidate for susceptibility to muscle-related symptoms. We examined the association of this variant with statin intolerance ascertained from electronic medical records in the GoDARTS study.

Methods and results

In the GoDARTS cohort, the LILRB5 Asp247 variant was associated with statin intolerance (SI) phenotypes; one defined as having raised CK and being non-adherent to therapy [odds ratio (OR) 1.81; 95% confidence interval (CI): 1.34-2.45] and the other as being intolerant to the lowest approved dose of a statin before being switched to two or more other statins (OR 1.36; 95% CI: 1.07-1.73). Those homozygous for Asp247 had increased odds of developing both definitions of intolerance. Importantly the second definition did not rely on CK elevations. These results were replicated in adjudicated cases of statin-induced myopathy in the PREDICTION-ADR consortium (OR1.48; 95% CI: 1.05-2.10) and for the development of myalgia in the JUPITER randomized clinical trial of rosuvastatin (OR1.35, 95% CI: 1.10-1.68). A meta-analysis across the studies showed a consistent association between Asp247Gly and outcomes associated with SI (OR1.34; 95% CI: 1.16-1.54).

Conclusion

This study presents a novel immunogenetic factor associated with statin intolerance, an important risk factor for cardiovascular outcomes. The results suggest that true statin-induced myalgia and non-specific myalgia are distinct, with a potential role for the immune system in their development. We identify a genetic group that is more likely to be intolerant to their statins.