Large, observational genetic studies are commonly used to identify genetic factors associated with diseases and disease‐related traits. Such cohorts have not been commonly used to identify genetic predictors of drug dosing or concentrations, perhaps because of the heterogeneity in drug dosing and formulation, and the random timing of blood sampling. We hypothesized that large sample sizes relative to traditional pharmacokinetic studies would compensate for this variability and enable the identification of pharmacogenetic predictors of drug concentrations. We performed a cross‐sectional, proof‐of‐concept association study to replicate the well‐established association between metoprolol concentrations and CYP2D6 genotype‐inferred metabolizer phenotypes in participants from the Montreal Heart Institute Hospital Cohort undergoing metoprolol therapy. Plasma concentrations of metoprolol and α‐hydroxymetoprolol (α‐OH‐metoprolol) were measured in samples collected randomly regarding the previous metoprolol dose. A total of 999 individuals were included. The metoprolol daily dose ranged from 6.25 to 400 mg (mean 84.3 ± 57.1 mg). CYP2D6‐inferred phenotype was significantly associated with both metoprolol and α‐OH‐metoprolol in unadjusted and adjusted models (all p < 10 −14 ). Models for metoprolol daily dose showed consistent results. Our study suggests that randomly drawn blood samples from biobanks can serve as a new approach to discover genetic associations related to drug concentrations and dosing, with potentially broader implications for genomewide association studies on the pharmacogenomics of drug metabolism.

Aims: CYP2D6 genetic polymorphisms are associated with metoprolol pharmacokinetics. Whether the clinical response to metoprolol is also affected remains uncertain. Methods:We conducted a systematic review on the effects of CYP2D6 polymorphism on the clinical response to metoprolol. Searches were conducted using MEDLINE. Meta-analyses were performed on the impact of CYP2D6-inferred phenotypes on heart rate (HR) reduction, diastolic (DBP) and systolic (SBP) blood pressure reduction, average daily doses, all-type adverse events and bradycardia.Results: Our qualitative assessment indicated inconsistent results in individual studies and endpoints, but CYP2D6 poor metabolizers (PM) generally presented a greater reduction in HR. The meta-analysis of 15 studies, including a total of 1146 individuals, found a reduction in HR of 3 beats/min (P = .017), and of SBP and DBP by 3 mmHg (P = .0048) for PM compared to non-PM individuals using similar metoprolol doses. Bradycardia appeared more frequent by 4-fold for PM, although significant heterogeneity was observed regarding bradycardia, which limits the scope of this finding.Conclusion: Patients without any CYP2D6 metabolic capacities appear to have increased reduction in DBP, HR and SBP during metoprolol treatment and may be at a higher risk of bradycardia compared to patients with active CYP2D6 phenotypes.Further prospective data are required to determine whether CYP2D6 is associated with clinical events in patients treated with metoprolol, as well as to demonstrate the clinical utility of an individualized approach of prescribing metoprolol using CYP2D6-inferred phenotypes. K E Y W O R D S cytochrome P450 enzymes, genetic polymorphism, meta-analysis, pharmacogenomics, systematic review

Aim: To evaluate the current opinion, experience and educational preferences of pharmacists in Quebec concerning pharmacogenomics. Method: A web-based survey containing 25 questions was sent to all Quebec pharmacists. Results: Most pharmacists were willing to advise patients (81%) and physicians (84%) on treatment choices based on pharmacogenomic test results after proper training. Only 31% had been previously exposed to pharmacogenomic test results, and 91% were favorable to pharmacogenomics training, with e-learning through interactive video sessions (69%). The preferred training session length was between 1 and 3 h (59%). Hospital pharmacists were more often exposed to pharmacogenomic tests (p < 0.0001) and more frequently advised patients on treatment choices (p < 0.001) than community pharmacists. Conclusion: Pharmacists remain favorable toward pharmacogenomics, but its use in clinical practice stays limited. Identifying the educational preferences of pharmacists may help in the development of educational programs to help them integrate pharmacogenomics in their clinical practice.