Pharmacogenetics of chronic cardiovascular drugs: applications and implications

Evidence for Clinical Implementation of Pharmacogenomics in Cardiac Drugs

OBJECTIVE

To comprehensively assess the pharmacogenomic evidence of routinely used drugs for clinical utility.

METHODS

Between January 2, 2011, and May 31, 2013, we assessed 71 drugs by identifying all drug/genetic variant combinations with published clinical pharmacogenomic evidence. Literature supporting each drug/variant pair was assessed for study design and methods, outcomes, statistical significance, and clinical relevance. Proposed clinical summaries were formally scored using a modified AGREE (Appraisal of Guidelines for Research and Evaluation) II instrument, including recommendation for or against guideline implementation.

RESULTS

Positive pharmacogenomic findings were identified for 51 of 71 cardiovascular drugs (71.8%), representing 884 unique drug/variant pairs from 597 publications. After analysis for quality and clinical relevance, 92 drug/variant pairs were proposed for translation into clinical summaries, encompassing 23 drugs (32.4% of drugs reviewed). All were recommended for clinical implementation using AGREE II, with mean ± SD overall quality scores of 5.18±0.91 (of 7.0; range, 3.67-7.0). Drug guidelines had highest mean ± SD scores in AGREE II domain 1 (Scope) (91.9±6.1 of 100) and moderate but still robust mean ± SD scores in domain 3 (Rigor) (73.1±11.1), domain 4 (Clarity) (67.8±12.5), and domain 5 (Applicability) (65.8±10.0). Clopidogrel (CYP2C19), metoprolol (CYP2D6), simvastatin (rs4149056), dabigatran (rs2244613), hydralazine (rs1799983, rs1799998), and warfarin (CYP2C9/VKORC1) were distinguished by the highest scores. Seven of the 9 most commonly prescribed drugs warranted translation guidelines summarizing clinical pharmacogenomic information.

CONCLUSION

Considerable clinically actionable pharmacogenomic information for cardiovascular drugs exists, supporting the idea that consideration of such information when prescribing is warranted.

Radionuclide imaging of neurohormonal system of the heart

Heart failure is one of the growing causes of death especially in developed countries due to longer life expectancy. Although many pharmacological and instrumental therapeutic approaches have been introduced for prevention and treatment of heart failure, there are still limitations and challenges. Nuclear cardiology has experienced rapid growth in the last few decades, in particular the application of single photon emission computed tomography (SPECT) and positron emission tomography (PET), which allow non-invasive functional assessment of cardiac condition including neurohormonal systems involved in heart failure; its application has dramatically improved the capacity for fundamental research and clinical diagnosis. In this article, we review the current status of applying radionuclide technology in non-invasive imaging of neurohormonal system in the heart, especially focusing on the tracers that are currently available. A short discussion about disadvantages and perspectives is also included.

Personal genomes, quantitative dynamic omics and personalized medicine

The rapid technological developments following the Human Genome Project have made possible the availability of personalized genomes. As the focus now shifts from characterizing genomes to making personalized disease associations, in combination with the availability of other omics technologies, the next big push will be not only to obtain a personalized genome, but to quantitatively follow other omics. This will include transcriptomes, proteomes, metabolomes, antibodyomes, and new emerging technologies, enabling the profiling of thousands of molecular components in individuals. Furthermore, omics profiling performed longitudinally can probe the temporal patterns associated with both molecular changes and associated physiological health and disease states. Such data necessitates the development of computational methodology to not only handle and descriptively assess such data, but also construct quantitative biological models. Here we describe the availability of personal genomes and developing omics technologies that can be brought together for personalized implementations and how these novel integrated approaches may effectively provide a precise personalized medicine that focuses on not only characterization and treatment but ultimately the prevention of disease.

Novel CYP3A4 intron 6 single nucleotide polymorphism is associated with simvastatin-mediated cholesterol reduction in the Rotterdam Study

OBJECTIVES

CYP3A4 is involved in the oxidative metabolism of many drugs and xenobiotics including the HMG-CoA reductase inhibitor simvastatin. The objective of this study was to investigate whether a new CYP3A4 functional single nucleotide polymorphism (SNP) in intron 6 (CYP3A4*22) modifies the effect of simvastatin on total cholesterol (TOTc) or LDL cholesterol (LDLc) reduction in a population-based cohort study.

METHODS

In a total of 80 incident simvastatin users, the association between the CYP3A4 intron 6 C>T SNP (rs35599367) and reduction in cholesterol levels was analyzed using linear regression analysis and adjusting for potential confounding factors.

RESULTS

The CYP3A4*22 allele was associated with a trend towards a stronger simvastatin lipid-lowering response, as reflected by the greater reduction in both TOTc and LDLc levels when compared with homozygous wild type. We observed that the CYP3A4*22 allele carriers had an increased reduction in TOTc and LDLc: -0.25 mmol/l (95% confidence interval [CI(95%)]=[-0.52; 0.01], P=0.058) and -0.29 mmol/l (CI(95%)=[-0.58; 0.01], P=0.054) when compared with homozygous CC. When we adjusted the model for potential confounding factors, the corresponding reduction in TOTc was -0.31 mmol/l (CI(95%)=[-0.59;-0.04], P=0.028) and for LDLc -0.34 mmol/l (CI(95%)=[-0.66; -0.02], P=0.034) greater for CYP3A4*22 allele carriers when compared with homozygotes wild type.

CONCLUSION

The CYP3A4*22 intron 6 SNP T-variant allele was associated with reduced CYP3A4 activity, resulting in a better lipid lowering response to simvastatin, when data were adjusted for confounding factors. This observation is a step towards the clarification of the reasons of interindividual variability in statins response and may potentially lead to improved tailoring of simvastatin therapy.

Pharmacogenomics in the assessment of therapeutic risks versus benefits: inside the United States Food and Drug Administration

Pharmacogenomics is the study of how genetic variations influence responses to drugs, diagnostics, or biologic agents. The field of pharmacogenomics has significant potential to enhance drug development and aid in making regulatory decisions. The United States Food and Drug Administration (FDA) has supported pharmacogenomics for nearly a decade by providing regulatory advice and reviewing applications, with the intent of discovering and applying genetic determinants of treatment effects. The FDA will continue to develop policies and processes centered on genomics and individualized therapeutics to guide rational drug development. It will also continue to inform the public of clinically relevant pharmacogenomic issues through various mechanisms of communication, such as drug labeling. In this review, we provide a perspective on several pharmacogenomic activities at the FDA. In addition, we attempt to clarify what we believe are several misperceptions regarding the FDA's pharmacogenomic initiatives. We hope this perspective provides a window into some ways in which the FDA is enabling individualized therapeutics through its mission-critical activities.

Using genetic information to select treatment for patients with heart failure: has the time come?

Personalized medicine is the concept of patient care becoming individualized based on distinctive characteristics. Pharmacogenetics is an application of personalized medicine, which may allow us to predict response to treatment based on an individual's genetic makeup. While several therapeutic areas have made significant advances in using pharmacogenetics to tailor therapies, it is not yet widely used in the treatment of heart failure. In this review, we summarize some of the emerging data on the use of pharmacogenetics in heart failure therapies.

Comprehensive whole-genome and candidate gene analysis for response to statin therapy in the Treating to New Targets (TNT) cohort

BACKGROUND

Statins are effective at lowering low-density lipoprotein cholesterol and reducing risk of cardiovascular disease, but variability in response is not well understood. To address this, 5745 individuals from the Treating to New Targets (TNT) trial were genotyped in a combination of a whole-genome and candidate gene approach to identify associations with response to atorvastatin treatment.

METHODS AND RESULTS

A total of 291 988 single-nucleotide polymorphisms (SNPs) from 1984 individuals were analyzed for association with statin response, followed by genotyping top hits in 3761 additional individuals. None was significant at the whole-genome level in either the initial or follow-up test sets for association with low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglyceride response. In addition to the whole-genome platform, 23 candidate genes previously associated with statin response were analyzed in these 5745 individuals. Three SNPs in apoE were most highly associated with low-density lipoprotein cholesterol response, followed by 1 in PCSK9 with a similar effect size. At the candidate gene level, SNPs in HMGCR were also significant though the effect was less than with those in apoE and PCSK9. rs7412/apoE had the most significant association (P=6x10(-30)), and its high significance in the whole-genome study (P=4x10(-9)) confirmed the suitability of this population for detecting effects. Age and gender were found to influence low-density lipoprotein cholesterol response to a similar extent as the most pronounced genetic effects.

CONCLUSIONS

Among SNPs tested with an allele frequency of at least 5%, only SNPs in apoE are found to influence statin response significantly. Less frequent variants in PCSK9 and smaller effect sizes in SNPs in HMGCR were also revealed.

Renin-angiotensin-aldosterone system (RAAS) pharmacogenomics: implications in heart failure management

Blockade of the renin-angiotensin-aldosterone system (RAAS) with ACE inhibitors has been a cornerstone of heart failure therapy for over 15 years. More recently, further blockade of RAAS with aldosterone antagonists and angiotensin receptor blockers (ARBs) has been studied. While these therapies have certainly improved outcomes in the treatment of heart failure, morbidity and mortality remain extremely high. Furthermore, polypharmacy and complex regimens of seven medications on average is the norm for management of heart failure. This results in increased costs, patient burden, and uncertainty as to the best course of therapy. The ability to personalize patients' therapeutic regimens using pharmacogenomics has the potential of providing more effective and efficient use of RAAS-modulating medications. This review highlights the implications of major RAAS pharmacogenetic studies, while outlining future directions for translation to practice.

Pharmacogenetics of response to statins

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

Beta blocker specificity: a building block toward personalized medicine

Drugs known as beta blockers, which antagonize the beta-adrenergic receptor (beta-AR), are an important component of the treatment regimen for chronic heart failure (HF). However, a significant body of evidence indicates that genetic heterogeneity at the level of the beta(1)-AR may be a factor in explaining the variable responses of HF patients to beta blockade. In this issue of the JCI, Rochais et al. describe how a single amino acid change in beta(1)-AR alters its structural conformation and improves its functional response to carvedilol, a beta blocker currently used in the treatment of HF (see the related article beginning on page 229). This may explain why some HF patients have better responses not only to carvedilol but to certain other beta blockers as well. The data greatly enhance our mechanistic understanding of myocardial adrenergic signaling and support the development of "tailored" or "personalized" medicine, in which specific therapies could be prescribed based on a patient's genotype.