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Impact of CYP2C19 genotype on sertraline exposure in 1200 Scandinavian patients.

ABSTRACT: Sertraline is an (SSRI-)antidepressant metabolized by the polymorphic CYP2C19 enzyme. The aim of this study was to investigate the impact of CYP2C19 genotype on the serum concentrations of sertraline in a large patient population. Second, the proportions of patients in the various CYP2C19 genotype-defined subgroups obtaining serum concentrations outside the therapeutic range of sertraline were assessed. A total of 2190 sertraline serum concentration measurements from 1202 patients were included retrospectively from the drug monitoring database at Diakonhjemmet Hospital in Oslo. The patients were divided into CYP2C19 genotype-predicted phenotype subgroups, i.e. normal (NMs), ultra rapid (UMs), intermediate (IMs), and poor metabolisers (PMs). The differences in dose-harmonized serum concentrations of sertraline and N-desmethylsertraline-to-sertraline metabolic ratio were compared between the subgroups, with CYP2C19 NMs set as reference. The patient proportions outside the therapeutic concentration range were also compared between the subgroups with NMs defined as reference. Compared with the CYP2C19 NMs, the sertraline serum concentration was increased 1.38-fold (95% CI 1.26-1.50) and 2.68-fold (95% CI 2.16-3.31) in CYP2C19 IMs and PMs, respectively (p?

SUBMITTER: Braten LS

PROVIDER: S-EPMC6969041 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Impact of CYP2C19 genotype on sertraline exposure in 1200 Scandinavian patients.

Bråten Line S LS Haslemo Tore T Jukic Marin M MM Ingelman-Sundberg Magnus M Molden Espen E Kringen Marianne K MK

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 20191024 3

Sertraline is an (SSRI-)antidepressant metabolized by the polymorphic CYP2C19 enzyme. The aim of this study was to investigate the impact of CYP2C19 genotype on the serum concentrations of sertraline in a large patient population. Second, the proportions of patients in the various CYP2C19 genotype-defined subgroups obtaining serum concentrations outside the therapeutic range of sertraline were assessed. A total of 2190 sertraline serum concentration measurements from 1202 patients were included ...[more]

PMID: 31649299

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Project description:The purpose of this study was to characterize escitalopram population pharmacokinetics (PK) in patients treated for major depression in a cross-national, US-Italian clinical trial. Data from the 2 sites participating in this trial, conducted at Pittsburgh (United States) and Pisa (Italy), were used. Patients received 5, 10, 15, or 20 mg of escitalopram daily for a minimum of 32 weeks. Nonlinear mixed effects modeling was used to model the PK characteristics of escitalopram. One- and 2-compartment models with various random effect implementations were evaluated during model development. Objective function values and goodness-of-fit plots were used as model selection criteria. CYP2C19 genotype, age, weight, body mass index, sex, race, and clinical site were evaluated as possible covariates. In total, 320 plasma concentrations from 105 Pittsburgh patients and 153 plasma concentrations from 67 Pisa patients were available for the PK model development. A 1-compartmental model with linear elimination and proportional error best described the data. Apparent clearance (CL/F) and volume of distribution (V/F) for escitalopram without including any covariates in the patient population were 23.5 L/h and 884 L, respectively. CYP2C19 genotype, weight, and age had a significant effect on CL/F, and patient body mass index affected estimated V/F. Patients from Pisa, Italy, had significantly lower clearances than patients from Pittsburgh that disappeared after controlling for patient CYP2C19 genotype, age, and weight. Postprocessed individual empirical Bayes estimates on clearance for the 172 patients show that patients without allele CYP2C19(*)2 or (*)3 (n = 82) cleared escitalopram 33.7% faster than patients with heterogeneous or homogeneous (*)2 or (*)3 ((*)17/(*)2, (*)17/(*)3, (*)1/(*)2, (*)1/(*)3, (*)2/(*)2, (*)2/(*)3, and (*)3/(*)3, n = 46). CL/F significantly decreased with increasing patient age. Patients younger than 30 years (n = 45) cleared escitalopram 20.7% and 42.7% faster than patients aged 30 to 50 years (n = 84) and older than 50 years of age (n = 43), respectively. CYP2C19 genotype, age, and weight strongly influenced the CL/F of escitalopram. These variables may affect patient tolerance of this antidepressant and may provide important information in the effort to tailor treatments to patients' individual needs.

Project description:Introduction: Pharmacogenetics-informed drug prescribing is increasingly applied in clinical practice. Typically, drug metabolizing phenotypes are determined based on genetic test results, whereupon dosage or drugs are adjusted. Drug-drug-interactions (DDIs) caused by concomitant medication can however cause mismatches between predicted and observed phenotypes (phenoconversion). Here we investigated the impact of CYP2C19 genotype on the outcome of CYP2C19-dependent DDIs in human liver microsomes. Methods: Liver samples from 40 patients were included, and genotyped for CYP2C19*2, *3 and *17 variants. S-mephenytoin metabolism in microsomal fractions was used as proxy for CYP2C19 activity, and concordance between genotype-predicted and observed CYP2C19 phenotype was examined. Individual microsomes were subsequently co-exposed to fluvoxamine, voriconazole, omeprazole or pantoprazole to simulate DDIs. Results: Maximal CYP2C19 activity (Vmax) in genotype-predicted intermediate metabolizers (IMs; *1/*2 or *2/*17), rapid metabolizers (RMs; *1/*17) and ultrarapid metabolizers (UMs; *17/*17) was not different from Vmax of predicted normal metabolizers (NMs; *1/*1). Conversely, CYP2C19*2/*2 genotyped-donors exhibited Vmax rates ∼9% of NMs, confirming the genotype-predicted poor metabolizer (PM) phenotype. Categorizing CYP2C19 activity, we found a 40% concordance between genetically-predicted CYP2C19 phenotypes and measured phenotypes, indicating substantial phenoconversion. Eight patients (20%) exhibited CYP2C19 IM/PM phenotypes that were not predicted by their CYP2C19 genotype, of which six could be linked to the presence of diabetes or liver disease. In subsequent DDI experiments, CYP2C19 activity was inhibited by omeprazole (-37% ± 8%), voriconazole (-59% ± 4%) and fluvoxamine (-85% ± 2%), but not by pantoprazole (-2 ± 4%). The strength of CYP2C19 inhibitors remained unaffected by CYP2C19 genotype, as similar percental declines in CYP2C19 activity and comparable metabolism-dependent inhibitory constants (Kinact/KI) of omeprazole were observed between CYP2C19 genotypes. However, the consequences of CYP2C19 inhibitor-mediated phenoconversion were different between CYP2C19 genotypes. In example, voriconazole converted 50% of *1/*1 donors to a IM/PM phenotype, but only 14% of *1/*17 donors. Fluvoxamine converted all donors to phenotypic IMs/PMs, but *1/*17 (14%) were less likely to become PMs than *1/*1 (50%) or *1/*2 and *2/*17 (57%). Conclusion: This study suggests that the differential outcome of CYP2C19-mediated DDIs between genotypes are primarily dictated by basal CYP2C19 activity, that may in part be predicted by CYP2C19 genotype but likely also depends on disease-related factors.

Project description:Genotyping for CYP2C19 no function alleles to guide antiplatelet therapy after percutaneous coronary intervention (PCI) improves clinical outcomes. Although results for the increased function CYP2C19*17 allele are also reported, its clinical relevance in this setting remains unclear. A collaboration across nine sites examined antiplatelet therapy prescribing and clinical outcomes in 3,342 patients after implementation of CYP2C19-guided antiplatelet therapy. Risk of major atherothrombotic and bleeding events over 12 months after PCI were compared across cytochrome P450 2C19 isozyme (CYP2C19) metabolizer phenotype and antiplatelet therapy groups by proportional hazards regression. Clopidogrel was prescribed to a similar proportion of CYP2C19 normal (84.5%), rapid (82.9%), and ultrarapid metabolizers (80.6%) (P = 0.360). Clopidogrel-treated normal metabolizers (20.4 events/100 patient-years; adjusted hazard ratio (HR) 1.00, 95% confidence interval (CI), 0.75-1.33, P = 0.993) and clopidogrel-treated rapid or ultrarapid metabolizers (19.1 events/100 patient-years; adjusted HR 0.95, 95% CI, 0.69-1.30, P = 0.734) exhibited no difference in major atherothrombotic events compared with patients treated with prasugrel or ticagrelor (17.6 events/100 patient-years). In contrast, clopidogrel-treated intermediate and poor metabolizers exhibited significantly higher atherothrombotic event risk compared with prasugrel/ticagrelor-treated patients (adjusted HR 1.56, 95% CI, 1.12-2.16, P = 0.008). When comparing clopidogrel-treated rapid or ultrarapid metabolizers to normal metabolizers, no difference in atherothrombotic (adjusted HR 0.97, 95% CI, 0.73-1.29, P = 0.808) or bleeding events (adjusted HR 1.34, 95% CI, 0.83-2.17, P = 0.224) were observed. In a real-world setting of genotype-guided antiplatelet therapy, the CYP2C19*17 allele did not significantly impact post-PCI prescribing decisions or clinical outcomes. These results suggest the CYP2C19 *1/*17 and *17/*17 genotypes have limited clinical utility to guide antiplatelet therapy after PCI.

Dataset Information

Impact of CYP2C19 genotype on sertraline exposure in 1200 Scandinavian patients.

Publications

Impact of CYP2C19 genotype on sertraline exposure in 1200 Scandinavian patients.

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