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.
Females present a higher risk of adverse drug reactions. Sex‐related differences in drug concentrations may contribute to these observations but they remain understudied given the underrepresentation ...of females in clinical trials. The aim of this study was to investigate whether anthropometric and socioeconomic factors and comorbidities could explain sex‐related differences in concentrations and dosing for metoprolol and oxypurinol, the active metabolite of allopurinol. We conducted an analysis of two cross‐sectional studies. Participants were self‐described “White” adults taking metoprolol or allopurinol selected from the Montreal Heart Institute Hospital Cohort. A total of 1007 participants were included in the metoprolol subpopulation and 459 participants in the allopurinol subpopulation; 73% and 86% of the participants from the metoprolol and allopurinol subpopulations were males, respectively. Females presented higher age‐ and dose‐adjusted concentrations of both metoprolol and oxypurinol (both p < 0.03). Accordingly, females presented higher unadjusted and age‐adjusted concentration:dose ratio of both metoprolol and allopurinol/oxypurinol compared to males (all p < 3.0 × 10−4). Sex remained an independent predictor of metoprolol concentrations (p < 0.01), but not of oxypurinol concentrations, after adjusting for other predictors. In addition to sex, age, daily dose, use of moderate to strong CYP2D6 inhibitors, weight, and CYP2D6 genotype‐inferred phenotype were associated with concentrations of metoprolol (all p < 0.01). Daily dose, weight, estimated glomerular filtration rate (eGFR), and employment status were associated with oxypurinol concentrations (all p < 0.01). Females present higher dose‐adjusted concentrations of metoprolol and oxypurinol than males. This suggests the need for sex‐specific dosing requirements for these drugs, although this hypothesis should be validated in prospective studies.
Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to ...identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented with multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p > 5 × 10sup.−8). Our results are consistent with prior findings regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, as well as allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.
Abstract
Small studies suggest that amiodarone is a weak inhibitor of cytochrome P450 (CYP) 2D6. Inhibition of CYP2D6 leads to increases in concentrations of drugs metabolized by the enzyme, such as ...metoprolol. Considering that both metoprolol and amiodarone have β‐adrenergic blocking properties and that the modest interaction between the two drugs would result in increased metoprolol concentrations, this could lead to a higher risk of bradycardia and atrioventricular block. The primary objective of this study was to evaluate whether metoprolol plasma concentrations collected at random timepoints from patients enrolled in the Montreal Heart Institute Hospital Cohort could be useful in identifying the modest pharmacokinetic interaction between amiodarone and metoprolol. We performed an analysis of a cross‐sectional study, conducted as part of the Montreal Heart Institute Hospital Cohort. All participants were self‐described “White” adults with metoprolol being a part of their daily pharmacotherapy regimen. Of the 999 patients being treated with metoprolol, 36 were also taking amiodarone. Amiodarone use was associated with higher metoprolol concentrations following adjustment for different covariates (
p
= .0132). Consistently, the association between amiodarone use and lower heart rate was apparent and significant after adjustment for all covariates under study (
p
= .0001). Our results highlight that single randomly collected blood samples can be leveraged to detect modest pharmacokinetic interactions.
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.
•Novel sensitive method developed and validated for quantifying (S)-metoprolol and one of its metabolite in human plasma.•Phospholipid removal microelution-solid phase extraction minimizes matrix ...effects and allows good recovery using minimal sample volumes.•Excellent chiral separation using isocyanate derivatization.•Successful application on a clinical cohort of patients taking metoprolol.
A sensitive liquid chromatography-tandem mass spectrometry (LC–MS/MS) assay was developed and validated for the quantification of (S)-metoprolol (MET) and its main metabolite, (S)-α-hydroxymetoprolol (OH-MET). Human plasma samples (50 μL) were spiked with both analytes and their deuterated internal standards (IS) (S)-MET-(d7) and α-OH-MET-(d5). Phospholipid removal microelution-solid phase extraction (PRM-SPE) was performed using a 4-step protocol with Oasis PRiME MCX μElution 96-well cartridges. The eluates were reconstituted in 100 μL of acetonitrile with 50 μg/mL (S)-α-methylbenzyl isocyanate (MBIC) for chiral derivatization. After 60 min at room temperature, the reaction was quenched using 100 μL of water 2 % formic acid. Chromatographic separation of the derivatized analytes was performed on a Kinetex phenyl-hexyl core-shell stationary phase with an elution gradient. Mobile phases were composed of a mixture of water and methanol, with ammonium formate and formic acid as buffers. Total runtime was 15 min. Analyte detection was performed by an AB/SCIEX 4000 QTRAP mass spectrometer with multiple reaction monitoring. Chromatograms showed MBIC successfully reacted with racemic MET, α-OH-MET, and their respective IS. Detection by positive electrospray ionization did not reveal derivatized by-products. Quantification ranges were validated for (S)-MET and (S)-α-OH-MET between 0.5–500 and 1.25−500 ng/mL, respectively, with correlation coefficients (r2) >0.9906. The PRM-SPE assay showed low matrix effects (86.9–104.0 %) and reproducible recoveries (69.4–78.7 %) at low, medium, and high quality control (QC) levels. Precision and accuracy were all comprised between 85–115 % for all three QCs, and between 80–120 % for the lower limit of quantification, for intra- and inter-day values (n = 6, 3 consecutive days). Non-derivatized analytes were stable at room temperature, after 3 freeze-thaw cycles, and stored for 30 days at −80 °C (n = 4). Reinjection reproducibility of a previously validated batch was achieved after 8 days under auto-sampler conditions, indicating the stability of (S)-MET and (S)-α-OH-MET derivatives. Its clinical use was established in a cohort of 50 patients and could be used to further investigate the clinical impact of (S)-MET concentrations.
Few genome-wide association studies (GWASs) have been conducted to identify predictors of drug concentrations. The authors therefore sought to discover the pharmacogenomic markers involved in ...metoprolol pharmacokinetics.
The authors performed a GWAS of a cross-sectional study of 993 patients from the Montreal Heart Institute Biobank taking metoprolol.
A total of 391 and 444 SNPs reached the significance threshold of 5 × 10
for metoprolol and α-OH-metoprolol concentrations, respectively. All were located on chromosome 22 at or near the
gene, encoding CYP450 2D6, metoprolol's main metabolizing enzyme.
The results reinforce previous findings of the importance of the
locus for metoprolol concentrations and confirm that large biobanks can be used to identify genetic determinants of drug pharmacokinetics at a GWAS significance level.
Using large biobanks with randomly collected patient samples, a genome-wide association study confirms
as the principal genomic determinant of metoprolol concentrations while identifying new potential markers.
To evaluate the current opinion, experience and educational preferences of pharmacists in Quebec concerning pharmacogenomics.
A web-based survey containing 25 questions was sent to all Quebec ...pharmacists.
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.
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.
La pharmacogénomique (PGx) étudie le concept selon lequel les déterminants génétiques peuvent aider à prédire la réponse clinique d’un patient aux médicaments. Les concentrations plasmatiques de ces ...derniers sont essentielles pour déterminer l’exposition, les profils pharmacocinétiques (PK), les effets cliniques et éventuellement les doses des médicaments, dont la plupart sont métabolisés par des enzymes hépatiques, les cytochromes P450 (CYPs). Néanmoins, la plupart des découvertes en matière de PGx concernant la prédiction des profils de concentrations des médicaments ont généralement recours à des plans d’études PK traditionnels avec une approche fonctionnelle. Bien qu’utile, cette méthodologie comporte des limites pour les études PGx, notamment le nombre restreint de sujets inclus, qui réduit la puissance statistique des associations PGx et limite l’identification de nouveaux variants génétiques moins fréquents. À l’inverse, les grandes cohortes observationnelles sont largement utilisées pour identifier des marqueurs génétiques physiopathologiques. Cette thèse de doctorat visait donc à 1) synthétiser les données publiées concernant les effets cliniques des polymorphismes génétiques de l’enzyme CYP2D6 sur le traitement au métoprolol, un agent β-bloquant. Les concentrations plasmatiques de métoprolol ont montré à plusieurs reprises qu’elles étaient fortement influencées par la PGx du CYP2D6; 2) développer une nouvelle méthode bioanalytique capable de quantifier les concentrations chirales de métoprolol des patients dans un contexte clinique; 3) mener une étude clinique en utilisant une grande cohorte observationnelle, ou biobanque, comme preuve de concept pour recréer l’association précédemment établie entre les phénotypes inférés des génotypes du CYP2D6 et les concentrations plasmatiques de métoprolol. Ces projets sont présentés en tant que chapitres de thèse et sous forme de manuscrits publiés. Le premier projet consistait en une revue systématique qui a permis d’extraire toutes les études relatives à la PGx du métoprolol-CYP2D6. La synthèse qualitative a suggéré que les métaboliseurs lents du CYP2D6, dépourvus de capacité enzymatique, avaient des valeurs plus élevées concernant les réductions de la fréquence cardiaque et de tension artérielle, ainsi que la survenue d’épisodes bradycardiques relativement aux autres phénotypes. Une méta-analyse ultérieure a confirmé la significativité de ces associations. Le deuxième projet a combiné des techniques bioanalytiques telles que la dérivation, l’extraction en phase solide et la chromatographie liquide avec spectrométrie de masse en tandem. Une méthode permettant de surmonter les limites analytiques antérieures a été validée avec succès pour mesurer les concentrations plasmatiques de (S)-métoprolol, l’énantiomère pharmacologiquement actif, et de son métabolite spécifique au CYP2D6. L’applicabilité d’une telle méthode a ensuite été démontrée grâce aux échantillons d’un groupe de patients issus de la Cohorte Hospitalière de l’Institut de Cardiologie de Montréal (ICM). Puis, le troisième projet présente la réalisation de l’étude LEVEL-PGx (LEVEraging Large observational cohort studies to identify pharmacogenetic determinants of drug dosing : A proof-of-concept study in the Montreal Heart Institute Hospital Cohort). L’étude portait sur un échantillon de >1000 patients sélectionnés dans la cohorte hospitalière de l’ICM, incluant leur génotypage pour CYP2D6 et la quantification du métoprolol racémique et de son métabolite spécifique au CYP2D6 dans des échantillons provenant de la Biobanque de l’ICM. Un seul échantillon unique et aléatoire par patient a été utilisé. Le recours à des modèles multivariables a validé le concept selon lequel de grandes cohortes transversales recueillant des échantillons biologiques pouvaient être utilisées afin d’identifier des associations PGx de concentrations de médicaments et ce, à des valeurs satisfaisant les seuils de significativité d’essais pangénomiques. D’autres analyses de cette cohorte ont indiqué que cette méthodologie parvenait à identifier des associations PGx qui influençaient la fréquence cardiaque au repos et la posologie du métoprolol à-travers les phénotypes du CYP2D6 et pour les déterminants génétiques uniques, même en présence de co-médications. Cependant, ces associations PGx avec les paramètres cliniques n’ont pas atteint une significativité applicable aux seuils pangénomiques. En résumé, par la reproduction d’une association PGx préalablement démontrée, l’ensemble des travaux présentés dans cette thèse suggère que l’identification et la découverte de nouveaux déterminants génétiques prédictifs des concentrations et des doses des médicaments pourrait s’effectuer par le biais de grandes cohortes observationnelles à l’échelle du génome. Ces approches permettraient de développer des modèles prédictifs plus précis de l’exposition et de la réponse aux médicaments, ce qui pourrait favoriser les découvertes PGx et, dans certains cas, éventuellement développer le potentiel translationnel d’une approche thérapeutique personnalisée selon le profil génétique des patients.
Pharmacogenomics (PGx) studies the concept that genetic determinants can help predict a patient’s clinical response to therapies. Drug concentrations are an essential component to determining the exposure, pharmacokinetic (PK) profiles, clinical effects, and potentially drug doses, most of which are metabolized through the cytochrome P450 (CYPs) liver enzymes. Nevertheless, most PGx discoveries regarding the prediction of drug concentration profiles have generally resorted to traditional PK study designs with a functional approach. Though useful, this methodology contains limitations for gene-drug interaction studies, most notably the restricted number of subjects included, which reduces the statistical power for PGx associations and limits the identification of new, less frequent genetic variants. On the opposite, large observational cohorts have long been utilized for identifying genetic markers of disease. This doctoral thesis therefore aimed to 1) synthesize published data regarding the clinical effects of CYP2D6 genetic polymorphism on metoprolol therapy. A β-blocker, metoprolol plasma concentrations have shown repeatedly to be heavily influenced by the PGx of the CYP2D6 enzyme; 2) develop a new bioanalytical method able to quantify patients’ chiral concentrations of metoprolol in a clinical setting; 3) conduct a clinical study using a large observational cohort, or biobank, as a proof of concept to recreate the previously established association between CYP2D6 genotype-inferred phenotypes and metoprolol plasma concentrations. Those projects are presented as thesis chapters in the form of published manuscripts. The first project was a systematic review that allowed us to find all studies pertaining to the PGx of metoprolol. The qualitative synthesis suggested that CYP2D6 poor metabolizers (PMs), without enzymatic capacity, had greater values regarding reductions in heart rate, blood pressures, and occurrences in bradycardia relative to non-PMs. A subsequent meta-analysis confirmed the significance of those associations. The second project combined bioanalytical techniques such as derivatization, solid phase extraction, and liquid chromatography-tandem mass spectrometry. A method overcoming previous analytical shortcomings was successfully validated to measure (S)-metoprolol plasma concentrations and its CYP2D6-specific metabolite. Its application was later demonstrated in a group of patients from the Montreal Heart Institute (MHI) Hospital Cohort. Then, the third project presents the conduct of the LEVEL-PGx study (LEVEraging Large observational cohort studies to identify pharmacogenetic determinants of drug dosing: A proof-of-concept study in the Montreal Heart Institute Hospital Cohort). The study implicated a sample of >1000 selected patients selected from the MHI Hospital Cohort, along with the genotyping of CYP2D6, and the quantification of racemic metoprolol and its CYP2D6-specific metabolite in samples from the MHI Biobank. A single, random sample per patient was used. Multivariable modeling validated the concept that large observational cohorts collecting biospecimens could be utilized to identify PGx associations of drug concentrations with genome-wide significance. Further analyses in our cohort indicated that the tested PGx associations influenced resting heart rate and metoprolol daily drug dosage across CYP2D6 phenotypes and for single genetic determinants, regardless of interfering comedications. However, such PGx associations with clinical parameters could not achieve genome-wide significance. In summary, the body of work presented in this thesis suggested that, using a previously validated PGx association, the identification of novel genetic determinants predictive of drug concentrations and dosage could be discovered and identified at the genome-wide level with large observational cohorts. These approaches would help develop more accurate predictive models of drug exposure and response, which could favor PGx discoveries and the translational potential of a personalized approach to treatments according to a patient’s genetic profile.
Epilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the ...detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.
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