Understanding variation in metoprolol response: CYP2D6, drug interactions, and phenoconversion

Metoprolol, a β1-selective blocker, is widely used for treating cardiovascular and non-cardiovascular conditions. Its pharmacokinetics (PK) and pharmacodynamics (PD) vary significantly between individuals, in part due to CYP2D6 genetic polymorphisms. Co-administration of CYP2D6 inhibitors can lead to phenotype-genotype discordance, known as phenoconversion, resulting in clinically significant changes in metoprolol exposure and response. This review examines studies of the combined impact of CYP2D6 genotype and inhibitor use on metoprolol PK and PD. A literature search of PubMed, Embase, and Scopus identified 17 relevant clinical studies. Strong inhibitors such as paroxetine and fluoxetine increased metoprolol exposure by up to 8-fold and induced phenoconversion in extensive metabolizers. Moderate inhibitors, including mirabegron and amiodarone, increased metoprolol exposure by 2- to 3-fold, particularly in those with high baseline CYP2D6 activity. These inhibitors also reduced heart rate and blood pressure, mimicking the response seen in poor metabolizers. Weak inhibitors caused minimal PK changes without notable PD effects. Severe adverse drug reactions, including bradycardia and hypotension, occurred with strong inhibitors, especially in patients with cardiovascular disease and reduced CYP2D6 function. CYP2D6 phenoconversion is a clinically important but often overlooked contributor to metoprolol response variability. Incorporating phenoconversion into clinical practice can lead to more effective pharmacotherapy with metoprolol.

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Publication Details

Journal
Pharmacogenomics
Published
2025-11-02
DOI
https://doi.org/10.1080/14622416.2025.2597182
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
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article

Understanding variation in metoprolol response: CYP2D6, drug interactions, and phenoconversion

David E. Lanfear, Jasmine A. Luzum, Bayan Azizi
Pharmacogenomics
Pharmacogenetics and Drug Metabolism
article

Understanding variation in metoprolol response: CYP2D6, drug interactions, and phenoconversion

David E. Lanfear, Jasmine A. Luzum, Bayan Azizi
article en

Abstract

Metoprolol, a β1-selective blocker, is widely used for treating cardiovascular and non-cardiovascular conditions. Its pharmacokinetics (PK) and pharmacodynamics (PD) vary significantly between individuals, in part due to CYP2D6 genetic polymorphisms. Co-administration of CYP2D6 inhibitors can lead to phenotype-genotype discordance, known as phenoconversion, resulting in clinically significant changes in metoprolol exposure and response. This review examines studies of the combined impact of CYP2D6 genotype and inhibitor use on metoprolol PK and PD. A literature search of PubMed, Embase, and Scopus identified 17 relevant clinical studies. Strong inhibitors such as paroxetine and fluoxetine increased metoprolol exposure by up to 8-fold and induced phenoconversion in extensive metabolizers. Moderate inhibitors, including mirabegron and amiodarone, increased metoprolol exposure by 2- to 3-fold, particularly in those with high baseline CYP2D6 activity. These inhibitors also reduced heart rate and blood pressure, mimicking the response seen in poor metabolizers. Weak inhibitors caused minimal PK changes without notable PD effects. Severe adverse drug reactions, including bradycardia and hypotension, occurred with strong inhibitors, especially in patients with cardiovascular disease and reduced CYP2D6 function. CYP2D6 phenoconversion is a clinically important but often overlooked contributor to metoprolol response variability. Incorporating phenoconversion into clinical practice can lead to more effective pharmacotherapy with metoprolol.

PharmacogenomicsVol. 26(15-16)
Henry Ford Health System (US), University of Michigan (US), Henry Ford Health + Michigan State University Health Sciences (US), Michigan State University (US)
Openalex Percentile: Top 52%
Pharmacogenetics and Drug Metabolism
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Understanding variation in metoprolol response: CYP2D6, drug interactions, and phenoconversion — David E. Lanfear, Jasmine A. Luzum, et al. · Pharmacogenomics (2025) | TGRS Research Map | TGRS