Jaekyu Shin

Accuracy of the Pharmacogenetic Dosing Table in the Warfarin Label in Predicting Initial Therapeutic Warfarin Doses in a Large, Racially Diverse Cohort

Study Objectives. To compare the accuracy of the pharmacogenetic dosing table included in the warfarin label with two empiric dosing strategies in predicting initial therapeutic warfarin doses, and to identify factors that influence the accuracy of the table.

Pharmacogenetics of β-Blockers

β‐Blockers are an important cardiovascular drug class, recommended as first‐line treatment of numerous diseases such as heart failure, hypertension, and angina, as well as treatment after myocardial infarction. However, responses to a β‐blocker are variable among patients. Results of numerous studies now suggest that genetic polymorphisms may contribute to variability in responses to β‐blockers. This review summarizes the pharmacogenetic data for β‐blockers in patients with various diseases and discusses the potential implications of β‐blocker pharmacogenetics in clinical practice.β-Blockers are an important cardiovascular drug class, recommended as first-line treatment of numerous diseases such as heart failure, hypertension, and angina, as well as treatment after myocardial infarction. However, responses to a β-blocker are variable among patients. Results of numerous studies now suggest that genetic polymorphisms may contribute to variability in responses to β-blockers. This review summarizes the pharmacogenetic data for β-blockers in patients with various diseases and discusses the potential implications of β-blocker pharmacogenetics in clinical practice.

Addressing The Challenges Of The Clinical Application Of Pharmacogenetic Testing

Pharmacogenomics aims to use molecular genetic markers to predict treatment outcome. Indeed, within the past decade there has been a rapid emergence of pharmacogenetic tests to aid clinicians in predicting efficacy or toxicity for some drugs. Despite this major advance in therapeutic drug management, there remain challenges to the appropriate use of pharmacogenetic tests. We discuss UGT1A1 pharmacogenetic testing to illustrate the knowledge gaps impeding widespread use of pharmacogenetic tests in the clinical setting.

Pharmacogenetics: from discovery to patient care

PURPOSE The basic concepts of pharmacogenetics, pharmacogenetic study approaches, factors to consider when applying pharmacogenetic discoveries to patient care, and potential roles for pharmacists in pharmacogenetics are discussed. SUMMARY The Food and Drug Administration (FDA) has recognized pharmacogenomics as an opportunity to identify new biomarkers that may expedite the drug development process. Currently, there are over 50 drugs with pharmacogenetic discoveries on their labeling. Sequence variations in drug disposition genes can alter the pharmacokinetics of a drug, while sequence variations in drug target genes can change the pharmacodynamics of the drug. The two most common strategies to test a pharmacogenetic question are the candidate-gene approach and genomewide association study. Given the complex interplay among the many factors that influence a drug dose, determination of an appropriate dose of a particular drug for a given patient will eventually require knowledge about both genetic and nongenetic factors that affect drug disposition and pharmacodynamics. Many factors can influence the application of pharmacogenetic discoveries to patient care. Before these discoveries find widespread application in clinical practice, additional work is needed, including randomized clinical trials to evaluate the clinical utility of a pharmacogenetic test, the development of guidelines for the clinical use of various pharmacogenetic tests, and provider education on pharmacogenetics. CONCLUSION Pharmacogenetics has made significant progress in the past decade, and many pharmacogenetic discoveries have now been included on FDA-approved drug labeling. Pharmacogenetic discoveries may further promote safe and effective use of medications by more accurately predicting an individuals drug response.

Very important pharmacogene summary ADRB2.

The beta2-adrenergic receptor (beta2-AR) is a member of the G-protein-coupled adrenergic receptor family with seven transmembrane segments. Similar to other members of this receptor family, beta2-AR specifically binds and is activated by the endogenous class of ligands known as catecholamines, and epinephrine in particular. The gene encoding this receptor, ADRB2, was cloned by Kobilka et al. in 1987 and is localized to chromosome 5q31–q32, a region that has been linked with asthma and asthma related phenotypes [1,2]. ADRB2 consists of a single exon of 2015 nucleotides, which encodes a 413 amino acid protein. This review highlights the genetic polymorphisms in ADRB2 and the pivotal role of beta2- AR in the regulation of the cardiac, pulmonary, vascular, endocrine, and central nervous systems. ADRB2 is abundantly expressed in bronchial smooth muscle cells and activation of the resulting receptor leads to bronchodilation. In addition, this gene is expressed in cardiac myocytes and vascular smooth muscle cells. Activation of beta2-AR in these cells causes an increase in the rate and force of heart contractions. Intracellular signaling upon beta2-AR activation is largely affected through a trimer of G proteins coupled to adenylate cyclase, to produce cyclic adenosine monophosphate. This, in turn, activates protein kinase A, leading to the phosphorylation and down-regulation of proteins including beta2-AR itself (please refer to PharmGKB β-agonist and β-blocker Pathway for further details: https://www.pharmgkb.org/do/serve?objId=PA2024&objCls=Pathway#). Beta2-AR is the target of clinically important drugs for asthma and cardiovascular conditions including hypertension and congestive heart failure (CHF). Beta-receptor agonists (e.g. albuterol, salmeterol) and antagonists (e.g. carvedilol and propranolol) are among the most commonly prescribed medications in the treatment of asthma and cardiovascular disease, respectively. Although some beta-blockers are ‘selective’ for the beta1-AR (e.g. metoprolol and atenolol), these also antagonize the beta2-AR at higher concentrations. A number of genetic polymorphisms in the ADRB2 gene have been described which affect gene expression, the function of the resulting receptor, and response to beta2-agonists.

Comparison of warfarin pharmacogenetic dosing algorithms in a racially diverse large cohort

AIMS Multiple warfarin pharmacogenetic dosing algorithms have been reported to date. However, there is only limited information available on the performance of the algorithms that can be used with the results of a US FDA-cleared warfarin pharmacogenetic test. We compared the performance of warfarin pharmacogenetic dosing algorithms in a large racially diverse cohort. MATERIALS & METHODS Warfarin pharmacogenetic dosing algorithms were identified using the PubMed database. Patient information from the International Warfarin Pharmacogenetics Consortium database was used to predict therapeutic warfarin doses according to each algorithm. By using bootstrapping analysis, the performance of algorithms was tested by comparing the mean absolute error and mean percentage of patients whose predicted dose fell within 20% of actual dose (percentage within 20%) in the entire cohort, and by race and therapeutic dose range. RESULTS A total of 13 algorithms and 1940 patients were included in the study. Overall, all the algorithms had similar performances (mean absolute error: 10.3 mg/week and mean percentage within 20%-41.4%). However, algorithms derived from racially mixed populations tended to perform better than those derived from single race populations. Mixed population algorithms had the lowest mean absolute error and the highest percentage within 20% across the racial groups. Most algorithms performed better in the intermediate-dose range (between 21 and 49 mg/week) than in the low (≤21 mg/week) or high-(≥49 mg/week) range. CONCLUSION Published warfarin pharmacogenetic algorithms performed similarly, although mixed population algorithms tended to perform better than race-specific algorithms.

Promoter Polymorphisms in ACE (Angiotensin I–Converting Enzyme) Associated With Clinical Outcomes in Hypertension

Genetic variants of ACE are suspected risk factors in cardiovascular disease, but the alleles responsible for the variations remain unidentified. To search for regulatory polymorphisms, allelic angiotensin I–converting enzyme (ACE) mRNA expression was measured in 65 heart tissues, followed by genotype scanning of the ACE locus. Marked allelic expression imbalance (AEI) detected in five African‐American subjects was associated with single‐nucleotide polymorphisms (SNPs) (rs7213516, rs7214530, and rs4290) residing in conserved regions 2–3 kb upstream of ACE. Moreover, each of the SNPs affected transcription in reporter gene assays. SNPs rs4290 and rs7213516 were tested for associations with adverse cardiovascular outcomes in hypertensive patients with coronary disease (International Verapamil SR Trandolapril Study Genetic Substudy (INVEST‐GENES), n = 1,032). Both SNPs were associated with adverse cardiovascular outcomes, largely attributable to nonfatal myocardial infarction in African Americans, showing an odds ratio of 6.16 (2.43–15.60) (P < 0.0001) for rs7213516. The high allele frequency in African Americans (16%) compared to Hispanics (4%) and Caucasians (<1%) suggests that these alleles contribute to variation between populations in cardiovascular risk and treatment outcomes.

Role of Pharmacogenomics in the Management of Traditional and Novel Oral Anticoagulants

Warfarin is the most commonly prescribed oral anticoagulant. However, it remains a difficult drug to manage mostly because of its narrow therapeutic index and wide interpatient variability in anticoagulant effects. Over the past decade, there has been substantial progress in our understanding of genetic contributions to variable warfarin response, particularly with regard to warfarin dose requirements. The genes encoding for cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) are the major genetic determinants of warfarin pharmacokinetics and pharmacodynamics, respectively. Numerous studies have demonstrated significant contributions of these genes to warfarin dose requirements. The CYP2C9 gene has also been associated with bleeding risk with warfarin. The CYP4F2 gene influences vitamin K availability and makes minor contributions to warfarin dose requirements. Less is known about genes influencing warfarin response in African‐American patients compared with other racial groups, but this is the focus of ongoing research. Several warfarin pharmacogenetic dosing algorithms and United States Food and Drug Administration—cleared genotyping tests are available for clinical use. Clinical trials are ongoing to determine the clinical utility and cost‐effectiveness of genotype‐guided warfarin dosing. Results from these trials will likely influence clinical uptake and third party payer reimbursement for genotype‐guided warfarin therapy. There is still a lack of pharmacogenetic data for the newly approved oral anticoagulants, dabigatran and rivaroxaban, and with other oral anticoagulants in the research and development pipeline. These data, once known, could be of great importance as routine monitoring parameters for these agents are not available.

Factors influencing doctors’ selection of dabigatran in non‐valvular atrial fibrillation

Rationale, aims and objectives This study was designed to examine the factors that influence doctors’ decision in initiating or switching from warfarin to dabigratran. Method A survey questionnaire was sent to 181 doctors who were most likely to prescribe dabigatran (e.g. cardiologists and general internists) at the University of California, San Francisco Medical Center between November 2011 and February 2012. Survey participants were asked to complete an electronic or a paper version of the questionnaire, which consisted of 17 multiple-choice questions. Fishers exact test and Cochran–Mantel–Haenszel test were used to compare survey responses between cardiologists and general internists. Results A total of 65 survey responses were received (35.9% response rate). There were 13 cardiologists and 51 general internists who participated in the study. Cost (25%), renal function (21%) and CHADS 2 score (18%) were the three factors doctors considered most often to determine a patients eligibility for dabigatran in warfarin-naive patients. On the other hand, histories of unstable international normalized ratio (37%) and missed appointments (17%) along with cost (19%) were most often considered in patients on warfarin. Cardiologists had prescribed dabigatran more often and had a significantly higher level of comfort with prescribing the drug than general internists (P = 0.003; 77% vs. 27%). Conclusions Cost was the most important factor influencing doctors’ decision to prescribe dabigatran. Safety and effectiveness of dabigatran as well as patient preference were additional factors influencing their decision. General internists were less comfortable with prescribing dabigatran than cardiologists.

Simplified method for determination of clarithromycin in human plasma using protein precipitation in a 96-well format and liquid chromatography–tandem mass spectrometry

A simplified method to determine clarithromycin concentrations in human plasma using protein precipitation in a 96-well plate and liquid chromatography-tandem mass spectrometry was developed and validated. Plasma proteins were precipitated with acetonitrile and roxithromycin was used as the internal standard. After vortex mixing and centrifugation, the supernatants were directly injected onto a Phenomenex Luna Phenyl-Hexyl column (50 mm x 2.0 mm ID, 3 microm). The mobile phase consisted of water and methanol (30:70, v/v) containing 0.1% formic acid and 5mM ammonium acetate. The flow rate was 0.22 mL/min and the total run time (injection to injection) was less than 3 min. Detection of the analytes was achieved using positive ion electrospray tandem mass spectrometry in selected reaction monitoring (SRM) mode. The linear standard curve ranged from 100 to 5000 ng/mL and the precision and accuracy (inter- and intra-run) were within 7.9% and 4.9%, respectively. The method was successfully used to determine clarithromycin concentrations in human plasma samples obtained from healthy subjects who were given clarithromycin 500 mg for 3 days. The method is rapid, simple, precise and directly applicable to clarithromycin pharmacokinetic studies.