Pharmacogenetic Associations of β1-Adrenergic Receptor Polymorphisms With Cardiovascular Outcomes in the SPS3 Trial (Secondary Prevention of Small Subcortical Strokes)

Cardiovascular precision medicine - A pharmacogenomic perspective

Precision medicine envisages the integration of an individual's clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.

Pharmacogenomics of Hypertension in CKD: The CKD-PGX Study

Background

Patients with CKD often have uncontrolled hypertension despite polypharmacy. Pharmacogenomic drug-gene interactions (DGIs) may affect the metabolism or efficacy of antihypertensive agents. We report changes in hypertension control after providing a panel of 11 pharmacogenomic predictors of antihypertensive response.

Methods

A prospective cohort with CKD and hypertension was followed to assess feasibility of pharmacogenomic testing implementation, self-reported provider utilization, and BP control. The analysis population included 382 subjects with hypertension who were genotyped for cross-sectional assessment of DGIs, and 335 subjects followed for 1 year to assess systolic BP (SBP) and diastolic BP (DBP).

Results

Most participants (58%) with uncontrolled hypertension had a DGI reducing the efficacy of one or more antihypertensive agents. Subjects with a DGI had 1.85-fold (95% CI, 1.2- to 2.8-fold) higher odds of uncontrolled hypertension, as compared with those without a DGI, adjusted for race, health system (safety-net hospital versus other locations), and advanced CKD (eGFR <30 ml/min). CYP2C9-reduced metabolism genotypes were associated with losartan response and uncontrolled hypertension (odds ratio [OR], 5.2; 95% CI, 1.9 to 14.7). CYP2D6-intermediate or -poor metabolizers had less frequent uncontrolled hypertension compared with normal metabolizers taking metoprolol or carvedilol (OR, 0.55; 95% CI, 0.3 to 0.95). In 335 subjects completing 1-year follow-up, SBP (-4.0 mm Hg; 95% CI, 1.6 to 6.5 mm Hg) and DBP (-3.3 mm Hg; 95% CI, 2.0 to 4.6 mm Hg) were improved. No significant difference in SBP or DBP change were found between individuals with and without a DGI.

Conclusions

There is a potential role for the addition of pharmacogenomic testing to optimize antihypertensive regimens in patients with CKD.

Genetic Polymorphism of beta1-adrenergic Receptors and the Effect on the Clinical Efficacy of beta-adrenoblockers

Beta-adrenergic blockers are a valuable class of cardiovascular drugs and are widely used in the treatment of arterial hypertension (AH), coronary heart disease, chronic heart failure (CHF), cardiac arrhythmias, significantly improving the prognosis of patients. However, the clinical efficacy of betablockers is largely dependent on the genetic polymorphism of beta1-adrenergic receptors (ADRB1). The aim of the review was a systematic analysis of scientific data from pharmacogenetic studies on the role of beta1-adrenergic receptor polymorphism in the clinical efficacy of beta-blockers in the treatment of hypertension, chronic heart failure, and atrial fibrillation. The results of clinical trials and meta-analyzes were used. Of greatest importance is the genetic polymorphism of beta1-adrenergic receptors of two loci – Arg389Gly and Ser49Gly; the frequency of occurrence of variant and less functionally active alleles Gly389 and Gly49 in Europeans reaches 27% and 15%. The variant Gly389 allele has reduced functional activity and carriers have a weak response to the use of beta-blockers. In carriers of variant alleles Gly389 and Gly49 a reduced hypotensive effect on the use of beta-blockers was observed, and in studies of long-term efficacy, carriage of variant alleles was accompanied by an increase in the frequency and risk of unfavorable outcomes of hypertension. In pharmacogenetic studies, a reduced effect of the effect on myocardial remodeling in patients with CHF for beta-blockers in carriers of the variant Gly389 allele were confirmed. According to two meta-analyzes of trials on use of beta-blockers in patients with CHF, the frequency of increased left ventricle ejection fraction was significantly higher in carriers of the wild Arg389Arg gene type (risk ratio=1.83, p=0,001). In contrast, in atrial fibrillation, the frequency of rhythm control with beta-blockers was achieved better in the presence of the variant allele Gly389 with “loss of function”. Another polymorphic Gly49 allele plays a role in desensitization and down-regulation of beta1-receptor activity, although clinically this effect has been less obvious and contradictory. However, in studies, a more pronounced clinical effect of beta-blockers was observed in carriers of the wild genotype Ser49Ser, as well as in carriers of the haplotype Ser49Ser/Arg389Arg. Thus, genetic polymorphism ADRB1 may be another important predictor of the effectiveness of beta-blockers in clinical practice, which must be taken into account in the treatment of cardiovascular diseases.

Pharmacogenetic polymorphisms affecting bisoprolol response

β-blockers are commonly prescribed to treat multiple cardiovascular (CV) diseases, but, frequently, adverse drug reactions and intolerance limit their use in clinical practice. Interindividual variability in response to β-blockers may be explained by genetic differences. In fact, pharmacogenetic interactions for some of these drugs have been widely studied, such as metoprolol. But studies that explore genetic variants affecting bisoprolol response are inconclusive, limited or confusing because of mixed results with other β-Blockers, different genetic polymorphisms observed, endpoint studied etc. Because of this, we performed a systematic review in order to find relevant genetic variants affecting bisoprolol response. We have found genetic polymorphism in several genes, but most of the studies focused in ADRB variants. The ADRB1 Arg389Gly (rs1801253) was the most studied genetic polymorphism and it seems to influence the response to bisoprolol, although studies are inconclusive. Even, we performed a meta-analysis about its influence on systolic/diastolic blood pressure in patients treated with bisoprolol, but this did not show statistically significant results. In conclusion, many genetic polymorphisms have been assessed about their influence on patients´ response to bisoprolol and the ADRB1 Arg389Gly (rs1801253) seems the most relevant genetic polymorphism in this regard but results have not been confirmed with a meta-analysis. Our results support the need of further studies about the impact of genetic variants on bisoprolol response, considering different genetic polymorphisms and conducting single and multiple SNPs analysis, including other clinical parameters related to bisoprolol response in a multivariate study.

Pharmacogenetics to guide cardiovascular drug therapy

Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.

Ligand-specific pharmacogenetic effects of nonsynonymous mutations

In pharmacogenomics, variable receptor phenotypes, resulting from genetic polymorphisms, are often described as a change in protein function or regulation observed upon exposure to a drug. However, in some instances, phenotypes are defined using a class of medications rather than individual drugs. This paradigm assumes that a variation associated with a drug response phenotype will retain the magnitude and direction of the effect for other drugs with the same mechanism of action. However, nonsynonymous polymorphisms may have ligand-specific effects. The purpose of this study was to investigate the potential for point mutations to asymmetrically affect the binding of different drugs to a common target. Ligand binding data from site-directed mutagenesis studies on five G-protein coupled receptors (beta-1 and -2 adrenergic, dopamine D2, angiotensin II and mu-opioid receptor) were collected and analyzed. Binding data from 81 studies for 253 ligands with 447 mutant proteins, including 10 naturally occurring human variants, were analyzed, yielding 1989 mutation-ligand pairs. Fold change in binding affinity for mutant proteins, relative to the wild-type, for different drugs was examined for ligand-specific effects, with a fold-change difference of one or more orders of magnitude between agents considered significant. Of the mutations examined, 49% were associated with ligand-specific effects. One human variant (T164I, beta-2 adrenergic receptor) showed ligand-specific effects for antiasthmatic agents. These results indicate that ligand-specific changes in binding are a possible consequence of missense mutations. This implies that caution needs to be exercised when grouping drugs together during design or interpretation of genotype-phenotype association studies.

Influence of ADRB1, ADRB2, and COMT Genetic Polymorphisms on Postoperative Outcomes of Patients Undergoing Cardiac Valve Surgery

PURPOSE

The aim of this study is to prospectively investigate the influence of ADRB and COMT gene polymorphisms on postoperative outcomes of patients undergoing cardiac surgery.

METHODS

This prospective cohort study included 223 patients undergoing elective cardiac valve surgery using cardiopulmonary bypass. Demographic information, intraoperative data, postoperative data, and blood samples were collected. Patients were genotyped for single-nucleotide polymorphisms (SNPs) of ADRB1 rs1801253, ADRB2 rs1042713, and COMT rs4680. Major adverse cardiovascular and cerebrovascular events (MACCEs) were used as the primary outcome to evaluate the postoperative prognosis of patients. Secondary outcomes included the duration of mechanical ventilatory support, intensive care unit stay, postoperative hospital stay, and postoperative need of inotropic or vasoactive agents.

FINDINGS

The overall incidence of MACCEs was 15.2%. Among 3 SNP loci, only different genotyped carriers of ADRB2 rs1042713 had statistically significant differences in the incidence of MACCEs (P = 0.005), especially for acute kidney injury (P = 0.023). The proportions of postoperative norepinephrine demand of patients carrying the AA genotype of ADRB2 rs1042713 (P = 0.016) and the AG genotype of COMT rs4680 (P = 0.018) were low. The duration of mechanical ventilatory support (P = 0.034) and postoperative hospital stay (P = 0.045) of patients carrying the AG genotype of COMT rs4680 was shortest. After multiple logistic regression analysis, we found that the G allele carriers of ADRB2 rs1042713 had a higher risk of MACCEs (AG vs AA genotype: odds ratio [OR] = 4.348; 95% CI, 1.529-12.359, P = 0.006; GG vs AA genotype: OR = 3.722; 95% CI, 1.060-13.071; P = 0.040), in particular with acute kidney injury (AG vs AA genotype: OR = 5.273; 95% CI, 1.093-25.451; P = 0.038; GG vs AA genotype: OR = 7.533; 95% CI, 1.275-44.522; P = 0.026). There was no SNP-SNP interaction found among the 3 SNPs with multifactor dimensionality reduction analysis.

IMPLICATION

The ADRB2 rs1042713 polymorphism might be related to prognosis of patients undergoing cardiac surgery. Patients carrying the G allele of ADRB2 rs1042713 had a higher risk of developing MACCEs, especially acute kidney injury. chictr.org.com identifier: ChiCTR1800015105.

Pharmacogenetic factors affecting β-blocker metabolism and response

INTRODUCTION

β-blockers are among the most widely prescribed of all drugs, used for treatment of a large number of cardiovascular diseases. Herein we evaluate literature pertaining to pharmacogenetics of β-blocker therapy, provide insight into the robustness of the genetic associations, and determine the appropriateness for translating these genetic associations into clinical practice.

AREAS COVERED

A literature search was conducted using PubMed to collate evidence on associations between CYP2D6, ADRB1, ADRB2, and GRK5 genetic variation and drug-response outcomes in the presence of β-blocker exposure. Pharmacokinetic, pharmacodynamic, and clinical outcomes studies were included if genotype data and β-blocker exposure were documented.

EXPERT OPINION

Substantial data suggest that specific ADRB1 and GRK5 genotypes are associated with improved β-blocker efficacy and have potential for use to guide therapy decisions in the clinical setting. While the data do not justify ordering a CYP2D6 pharmacogenetic test, if CYP2D6 genotype is available in the electronic health record, there may be clinical utility for understanding dosing of β-blockers.

Pharmacogenomics of Hypertension Treatment

Hypertension is one of the strongest modifiable cardiovascular risk factors, affecting an increasing number of people worldwide. Apart from poor medication adherence, the low efficacy of some therapies could also be related to inter-individual genetic variability. Genetic studies of families revealed that heritability accounts for 30% to 50% of inter-individual variation in blood pressure (BP). Genetic factors not only affect blood pressure (BP) elevation but also contribute to inter-individual variability in response to antihypertensive treatment. This article reviews the recent pharmacogenomics literature concerning the key classes of antihypertensive drugs currently in use (i.e., diuretics, β-blockers, ACE inhibitors, ARB, and CCB). Due to the numerous studies on this topic and the sometimes-contradictory results within them, the presented data are limited to several selected SNPs that alter drug response. Genetic polymorphisms can influence drug responses through genes engaged in the pathogenesis of hypertension that are able to modify the effects of drugs, modifications in drug–gene mechanistic interactions, polymorphisms within drug-metabolizing enzymes, genes related to drug transporters, and genes participating in complex cascades and metabolic reactions. The results of numerous studies confirm that genotype-based antihypertension therapies are the most effective and may help to avoid the occurrence of major adverse events, as well as decrease the costs of treatment. However, the genetic heritability of drug response phenotypes seems to remain hidden in multigenic and multifactorial complex traits. Therefore, further studies are required to analyze all associations and formulate final genome-based treatment recommendations.

Pharmacogenomics of Cognitive Dysfunction and Neuropsychiatric Disorders in Dementia

Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6-10 drugs/day with the consequent risk for drug-drug interactions and adverse drug reactions (ADRs >80%) which accelerate cognitive decline. The pharmacoepigenetic machinery is integrated by pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes redundantly and promiscuously regulated by epigenetic mechanisms. CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 geno-phenotypes are involved in the metabolism of over 90% of drugs currently used in patients with dementia, and only 20% of the population is an extensive metabolizer for this tetragenic cluster. ADRs associated with anti-dementia drugs, antipsychotics, antidepressants, anxiolytics, hypnotics, sedatives, and antiepileptic drugs can be minimized by means of pharmacogenetic screening prior to treatment. These drugs are substrates, inhibitors, or inducers of 58, 37, and 42 enzyme/protein gene products, respectively, and are transported by 40 different protein transporters. APOE is the reference gene in most pharmacogenetic studies. APOE-3 carriers are the best responders and APOE-4 carriers are the worst responders; likewise, CYP2D6-normal metabolizers are the best responders and CYP2D6-poor metabolizers are the worst responders. The incorporation of pharmacogenomic strategies for a personalized treatment in dementia is an effective option to optimize limited therapeutic resources and to reduce unwanted side-effects.

Relationship between a Weighted Multi-Gene Algorithm and Blood Pressure Control in Hypertension

Hypertension (HTN) is a complex disease with interactions among multiple organ systems, including the heart, vasculature, and kidney with a strong heritable component. Despite the multifactorial nature of HTN, no clinical guidelines utilize a multi-gene approach to guide blood pressure (BP) therapy. Non-smokers with a family history of HTN were included in the analysis (n = 384; age = 61.0 ± 0.9, 11% non-white). A total of 17 functional genotypes were weighted according to the previous effect size in the literature and entered into an algorithm. Pharmacotherapy was ranked from 1–4 as most to least likely to respond based on the algorithmic assessment of individual patient’s genotypes. Three-years of data were assessed at six-month intervals for BP and medication history. There was no difference in BP at diagnosis between groups matching the top drug recommendation using the multi-gene weighted algorithm (n = 92) vs. those who did not match (n = 292). However, from diagnosis to nadir, patients who matched the primary recommendation had a significantly greater drop in BP when compared to patients who did not. Further, the difference between diagnosis to current 1-year average BP was lower in the group that matched the top recommendation. These data suggest an association between a weighted multi-gene algorithm on the BP response to pharmacotherapy.

Roles of Host Immunity in Viral Myocarditis and Dilated Cardiomyopathy

The pathogenesis of viral myocarditis includes both the direct damage mediated by viral infection and the indirect lesion resulted from host immune responses. Myocarditis can progress into dilated cardiomyopathy that is also associated with immunopathogenesis. T cell-mediated autoimmunity, antibody-mediated autoimmunity (autoantibodies), and innate immunity, working together, contribute to the development of myocarditis and dilated cardiomyopathy.

Pharmacogenomic studies of hypertension: paving the way for personalized antihypertensive treatment

Introduction

Increasing clinical evidence supports the implementation of genotyping for anti-hypertensive drug dosing and selection. Despite robust evidence gleaned from clinical trials, the translation of genotype guided therapy into clinical practice faces significant challenges. Challenges to implementation include the small effect size of individual variants and the polygenetic nature of antihypertensive drug response, a lack of expert consensus on dosing guidelines even without genetic information, and proper definition of major antihypertensive drug toxicities. Balancing clinical benefit with cost, while overcoming these challenges, remains crucial.

Areas covered

This review presents the most impactful clinical trials and cohorts which continue to inform and guide future investigation. Variants were selected from among those identified in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR), the Genetic Epidemiology of Responses to Antihypertensives study (GERA), the Genetics of Drug Responsiveness in Essential Hypertension (GENRES) study, the SOPHIA study, the Milan Hypertension Pharmacogenomics of hydro-chlorothiazide (MIHYPHCTZ), the Campania Salute Network, the International Verapamil SR Trandolapril Study (INVEST), the Nordic Diltiazem (NORDIL) Study, GenHAT, and others.

Expert Commentary

The polygenic nature of antihypertensive drug response is a major barrier to clinical implementation. Further studies examining clinical effectiveness are required to support broad-based implementation of genotype-based prescribing in medical practice.

The rs2108622 polymorphism is related to the early risk of ischemic stroke in non-valvular atrial fibrillation subjects under oral anticoagulation

Oral anticoagulant treatments, such as vitamin K antagonists (VKAs), are the main treatments administered to atrial fibrillation (AF) patients in order to prevent ischemic stroke (IS). However, the genes involved in the VKA metabolism can undergo variations in a single nucleotide (SNP). These SNPs may then affect the VKA target enzyme (VKORC1), VKA degradation enzyme (CYP2C9), and vitamin K bioavailability enzyme (CYP4F2). We genotyped these SNPs in a cohort of patients with non-valvular AF who were under VKA treatment after suffering an IS. Clinical variables, CHADS2-VASC score and data about the international normalized ratio (INR) within the therapeutic range were all recorded. DNA was extracted from blood and genotyping was carried out by DNA sequencing. The main endpoint was the time from VKA onset to IS. Of a total of 356 consecutive IS patients monitored, 33 were included in the study. The median time to the event was 2248.0 days (interquartile range [IQR] 896.3-3545.3). The median CHADS2-VASC score was 4.0 (IQR 3.0-6.0). When we considered the risk of IS within 2 years under VKA treatment, we found that only the rs2108622 AA genotype was significantly associated with this endpoint (early IS) (hazard ratio 6.81, 95% CI 1.37-33.92, p = 0.019). Kaplan-Meier curve analysis also showed a significant relationship between early IS and rs2108622 AA genotype (Log rank p = 0.022). The CYP4F2 gene rs2108622 polymorphism was associated with a risk of early IS in NV-AF patients under VKA treatment.

Recent developments and future directions for the use of pharmacogenomics in cardiovascular disease treatments

INTRODUCTION

Cardiovascular disease is still the leading cause of death worldwide. There are many environmental and genetic factors that play a role in the development of cardiovascular disease. The treatment of cardiovascular disease is beginning to move in the direction of personalized medicine by using biomarkers from the patient's genome to design more effective treatment plans. Pharmacogenomics have already uncovered many links between genetic variation and response of many different drugs. Areas covered: This article will focus on the main polymorphisms that impact the risk of adverse effects and response efficacy of statins, clopidogrel, aspirin, β-blockers, warfarin dalcetrapib and vitamin E. The genes discussed include SLCO1B1, ABCB1, CYP3A4, CYP3A5, CYP2C19, PTGS1, PTGS2, ADRB1, ADCY9, CYP2C19, PON1, CES1, PEAR1, GPIIIa, CYP2D6, CKORC1, CYP2C9 and Hp. Expert opinion: Although there are some convincing results that have already been incorporated in the labelling treatment guidelines, most gene-drug relationships have been inconsistent. A better understanding of the relationships between genetic factors and drug response will provide more opportunities for personalized diagnosis and treatment of cardiovascular disease.