Beta‐blockers are widely used medications for a variety of indications, including heart failure, myocardial infarction, cardiac arrhythmias, and hypertension. Genetic variability in pharmacokinetic (e.g., CYP2D6) and pharmacodynamic (e.g., ADRB1, ADRB2, ADRA2C, GRK4, GRK5) genes have been studied in relation to beta‐blocker exposure and response. We searched and summarized the strength of the evidence linking beta‐blocker exposure and response with the six genes listed above. The level of evidence was high for associations between CYP2D6 genetic variation and both metoprolol exposure and heart rate response. Evidence indicates that CYP2D6 poor metabolizers experience clinically significant greater exposure and lower heart rate in response to metoprolol compared with those who are not poor metabolizers. Therefore, we provide therapeutic recommendations regarding genetically predicted CYP2D6 metabolizer status and metoprolol therapy. However, there was insufficient evidence to make therapeutic recommendations for CYP2D6 and other beta‐blockers or for any beta‐blocker and the other five genes evaluated (updates at www.cpicpgx.org).

Statins are a cornerstone of the pharmacologic treatment and prevention of atherosclerotic cardiovascular disease. Atherosclerotic disease is a predominant cause of mortality and morbidity worldwide. Statins are among the most commonly prescribed classes of medications, and their prescribing indications and target patient populations have been significantly expanded in the official guidelines recently published by the American and European expert panels. Adverse effects of statin pharmacotherapy, however, result in significant cost and morbidity and can lead to nonadherence and discontinuation of therapy. Statin-associated muscle symptoms occur in ~10% of patients on statins and constitute the most commonly reported adverse effect associated with statin pharmacotherapy. Substantial clinical and nonclinical research effort has been dedicated to determining whether genetics can provide meaningful insight regarding an individual patient’s risk of statin adverse effects. This contemporary review of the relevant clinical research on polymorphisms in several key genes that affect statin pharmacokinetics (eg, transporters and metabolizing enzymes), statin efficacy (eg, drug targets and pathways), and end-organ toxicity (eg, myopathy pathways) highlights several promising pharmacogenomic candidates. However, SLCO1B1 521C is currently the only clinically relevant pharmacogenetic test regarding statin toxicity, and its relevance is limited to simvastatin myopathy.

A new global pandemic of coronavirus disease 2019 (COVID-19) has resulted in high mortality and morbidity. Currently numerous drugs are under expedited investigations without well-established safety or efficacy data. Pharmacogenomics may allow individualization of these drugs thereby improving efficacy and safety. In this review, we summarized the pharmacogenomic literature available for COVID-19 drug therapies including hydroxychloroquine, chloroquine, azithromycin, remdesivir, favipiravir, ribavirin, lopinavir/ritonavir, darunavir/cobicistat, interferon beta-1b, tocilizumab, ruxolitinib, baricitinib, and corticosteroids. We searched PubMed, reviewed the Pharmacogenomics Knowledgebase (PharmGKB^®) website, Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, the U.S. Food and Drug Administration (FDA) pharmacogenomics information in the product labeling, and the FDA pharmacogenomics association table. We found several drug-gene variant pairs that may alter the pharmacokinetics of hydroxychloroquine/chloroquine (CYP2C8, CYP2D6, SLCO1A2, and SLCO1B1); azithromycin (ABCB1); ribavirin (SLC29A1, SLC28A2, and SLC28A3); and lopinavir/ritonavir (SLCO1B1, ABCC2, CYP3A). We also identified other variants, that are associated with adverse effects, most notable in hydroxychloroquine/chloroquine (G6PD; hemolysis), ribavirin (ITPA; hemolysis), and interferon β -1b (IRF6; liver toxicity). We also describe the complexity of the risk for QT prolongation in this setting because of additive effects of combining more than one QT-prolonging drug (i.e., hydroxychloroquine/chloroquine and azithromycin), increased concentrations of the drugs due to genetic variants, along with the risk of also combining therapy with potent inhibitors. In conclusion, although direct evidence in COVID-19 patients is lacking, we identified potential actionable genetic markers in COVID-19 therapies. Clinical studies in COVID-19 patients are deemed warranted to assess potential roles of these markers.

Simvastatin is primarily metabolized by CYP3A4. A combined CYP3A4/5 genotype classification, combining the decrease-of-function CYP3A4*22 and the loss-of-function CYP3A5*3, has recently been reported. We aim to determine whether CYP3A4*22 and CYP3A5*3 alleles are associated with increased plasma concentrations of simvastatin lactone (SV) and simvastatin acid (SVA). This is the first report evaluating associations between in-vivo simvastatin concentrations and CYP3A4*22, alone or in a combined CYP3A4/5 genotype-defined classification. Genotypes and simvastatin concentrations were determined for 830 participants (555 Whites and 275 African-Americans) in the Cholesterol and Pharmacogenomics clinical trial with 40 mg/day simvastatin for 6 weeks. Concentrations were determined in 12-h postdose samples. Associations between simvastatin concentrations and CYP3A4*22 and CYP3A5*3 alleles were tested separately and in a combined CYP3A4/5 genotype-defined classification system. In Whites, CYP3A4*22 carriers (n=42) had 14% higher SVA (P=0.04) and 20% higher SV (P=0.06) compared with noncarriers (n=513). CYP3A5*3 allele status was not significantly associated with SV or SVA in Whites. In African-Americans, CYP3A4*22 carriers (n=8) had 170% higher SV (P<0.01) than noncarriers (n=267), but no significant difference was detected for SVA. African-American CYP3A5 nonexpressors (n=28) had 33% higher SV (P=0.02) than CYP3A5 expressors (n=247), but no significant difference was detected for SVA. For both races, SV appeared to decrease across the rank-ordered combined CYP3A4/5 genotype-defined groups (poor, intermediate, and extensive metabolizers); however, similar trends were not observed for SVA. Genetic variation in CYP3A4 was associated with plasma simvastatin concentrations in self-reported Whites. Genetic variations in CYP3A4 and CYP3A5 were associated with plasma simvastatin concentrations in self-reported African-Americans.

Antiplatelet therapy is used in the treatment of patients with acute coronary syndromes, stroke, and those undergoing percutaneous coronary intervention. Clopidogrel is the most widely used antiplatelet P2Y12 inhibitor in clinical practice. Genetic variation in CYP2C19 may influence its enzymatic activity, resulting in individuals who are carriers of loss-of-function CYP2C19 alleles and thus have reduced active clopidogrel metabolites, high on-treatment platelet reactivity, and increased ischemic risk. Prospective studies have examined the utility of CYP2C19 genetic testing to guide antiplatelet therapy, and more recently published meta-analyses suggest that pharmacogenetics represents a key treatment strategy to individualize antiplatelet therapy. Rapid genetic tests, including bedside genotyping platforms that are validated and have high reproducibility, are available to guide selection of P2Y12 inhibitors in clinical practice. The aim of this review is to provide an overview of the background and rationale for the role of a guided antiplatelet approach to enhance patient care.