Impact of CYP2D6 and ADRB1 polymorphisms on heart rate of post-PCI patients treated with metoprolol

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.

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.

Impact of genotype-predicted CYP2D6 metabolism on clinical effects and tolerability of metoprolol in patients after myocardial infarction - a prospective observational study

PURPOSE

The β-1 adrenergic receptor blocker metoprolol is primarily metabolized by the polymorphic enzyme cytochrome P 450 2D6 (CYP2D6), an enzyme with substantial genetic heterogeneity. Our purpose was to investigate the impact of CYP2D6 metabolism on clinical effects and tolerability of metoprolol in patients after myocardial infarction (MI).

METHODS

We included 136 patients with MI discharged on treatment with metoprolol with a recommendation to the general practitioner (GP) to increase the metoprolol dose up to 200 mg/day within 2 months if possible. At follow-up, metoprolol dosage after up-titration, metoprolol steady-state trough plasma concentrations, hemodynamic parameters, potential metoprolol-induced adverse drug reactions and number of visits to the GP were measured. CYP2D6 genotyping including the reduced-function variant alleles CYP2D6*9, CYP2D6*10 and CYP2D6*41 was performed after end of follow-up.

RESULTS

According to the genotype-defined CYP2D6 phenotypes, 30% of the patients were metoprolol extensive metabolizers (EMs), 55% intermediate metabolizers (IMs) and 13% poor metabolizers (PMs; carriers of non-coding and reduced-function variant included). Dose-adjusted metoprolol trough concentrations were significantly higher in IM (2-fold) and PM (6.2-fold) groups vs. the EM group (p < 0.001). Only 35% of patients in the PM group achieved the primary end point, i.e. reaching at least 85% of the expected maximum heart rate (HR) during exercise, compared with 78% in the EM group (p < 0.01), and maximum observed HR at exercise was significantly lower in the PM group vs. the EM group (129 ± 5 vs. 142 ± 2 bpm, p < 0.007). In contrast, metoprolol maintenance dose, blood pressure, exercise capacity, number of visits at the GP and frequency and severity of self-reported potential metoprolol-related adverse drug reactions were not significantly different between the groups.

CONCLUSION

Using a comprehensive CYP2D6 genotyping panel, the present study demonstrates a > 6-fold increase of dose-adjusted plasma metoprolol trough concentration in CYP2D6 PMs vs. EMs with a parallel lower increase in achieved maximum HR during exercise but without association between genotype and frequency or severity of self-reported adverse drug effects. This may indicate that CYP2D6 PMs potentially could benefit of the increased plasma concentration per dose in a naturalistic setting.

Genomics Testing and Personalized Medicine in the Preoperative Setting

Pharmacogenomics (PGx) is the study of how individuals' personal genotypes may affect their responses to various pharmacologic agents. The application of PGx principles in perioperative medicine is fairly novel. Challenges in executing PGx programs into health care systems include physician buy-in and integration into usual clinical workflow, including the electronic health record. This article discusses the current evidence highlighting the potential of PGx with various drug categories (including opioids, nonopioid analgesics, sedatives, β-blockers, antiemetics, and anticoagulants) used in the perioperative process and the challenges of integrating PGx into a health care system and relevant workflows.