Evaluation of the influence of sex and CYP2C19 and CYP2D6 polymorphisms in the disposition of citalopram

Combined effect of CYP2C19 and CYP2D6 genotypes on escitalopram serum concentration and its metabolic ratio in a European patient population

AIMS

The aim of the present study was to investigate the impact of CYP2D6 genotype on exposure and metabolism of escitalopram in patients stratified by CYP2C19 genotype in a large real-world population.

METHODS

Patients were included from a therapeutic drug monitoring service if they had measured serum concentration of escitalopram and the metabolite, N-desmethyl escitalopram, and performed CYP2C19 and CYP2D6 genotyping. Patients were divided into 16 combined genotype-predicted phenotype subgroups (poor [PM], intermediate [IM], normal [NM] and ultrarapid metabolizers [UM]) of CYP2C19/CYP2D6. The concentration-to-dose (CD) ratio and metabolite-to-parent ratio (metabolic ratio) of escitalopram were compared across subgroups using the Kruskal-Wallis test followed by Dunn's test with CYP2D6 NMs as the reference group.

RESULTS

A total of 5067 patients were included in the study. A stepwise increase in escitalopram CD ratio by decreasing CYP2D6 activity was observed in all CYP2C19 subgroups, except for in CYP2C19 UMs. The percentage differences in escitalopram CD ratio between CYP2D6 PMs and NMs were 24% in CYP2C19 NMs (P < .001), 28% in CYP2C19 IMs (P < .001) and 31% in CYP2C19 PMs (P = .04). As for the CD ratio, CYP2D6 genotype effect on metabolic ratio increased stepwise by decreasing CYP2C19 metabolism.

CONCLUSIONS

CYP2D6 genotype is of significant importance for the individual variation in escitalopram pharmacokinetics. The most relevant increase in escitalopram concentration is seen in individuals with decreased and/or absent CYP2C19 activity. By combining CYP2C19 and CYP2D6 genotypes, the optimal dose for patients may be predicted with greater precision than for CYP2C19 genotype alone.

Influence of CYP2C19, CYP2D6, and ABCB1 Gene Variants and Serum Levels of Escitalopram and Aripiprazole on Treatment-Emergent Sexual Dysfunction: A Canadian Biomarker Integration Network in Depression 1 (CAN-BIND 1) Study

OBJECTIVES

Treatment-emergent sexual dysfunction is frequently reported by individuals with major depressive disorder (MDD) on antidepressants, which negatively impacts treatment adherence and efficacy. We investigated the association of polymorphisms in pharmacokinetic genes encoding cytochrome-P450 drug-metabolizing enzymes, CYP2C19 and CYP2D6, and the transmembrane efflux pump, P-glycoprotein (i.e., ABCB1), on treatment-emergent changes in sexual function (SF) and sexual satisfaction (SS) in the Canadian Biomarker Integration Network in Depression 1 (CAN-BIND-1) sample.

METHODS

A total of 178 adults with MDD received treatment with escitalopram (ESC) from weeks 0-8 (Phase I). At week 8, nonresponders were augmented with aripiprazole (ARI) (i.e., ESC + ARI, n = 91), while responders continued ESC (i.e., ESC-Only, n = 80) from weeks 8-16 (Phase II). SF and SS were evaluated using the sex effects (SexFX) scale at weeks 0, 8, and 16. We assessed the primary outcomes, SF and SS change for weeks 0-8 and 8-16, using repeated measures mixed-effects models.

RESULTS

In ESC-Only, CYP2C19 intermediate metabolizer (IM) + poor metabolizers (PMs) showed treatment-related improvements in sexual arousal, a subdomain of SF, from weeks 8-16, relative to CYP2C19 normal metabolizers (NMs) who showed a decline, F(2,54) = 8.00, p < 0.001, q = 0.048. Specifically, CYP2C19 IM + PMs reported less difficulty with having and sustaining vaginal lubrication in females and erection in males, compared to NMs. Furthermore, ESC-Only females with higher concentrations of ESC metabolite, S-desmethylcitalopram (S-DCT), and S-DCT/ESC ratio in serum demonstrated more decline in SF (r = -0.42, p = 0.004, q = 0.034) and SS (r = -0.43, p = 0.003, q = 0.034), respectively, which was not observed in males. ESC-Only females also demonstrated a trend for a correlation between S-DCT and sexual arousal change in the same direction (r = -0.39, p = 0.009, q = 0.052).

CONCLUSIONS

CYP2C19 metabolizer phenotypes may be influencing changes in sexual arousal related to ESC monotherapy. Thus, preemptive genotyping of CYP2C19 may help to guide selection of treatment that circumvents selective serotonin reuptake inhibitor-related sexual dysfunction thereby improving outcomes for patients. Additionally, further research is warranted to clarify the role of S-DCT in the mechanisms underlying ESC-related changes in SF and SS. This CAN-BIND-1 study was registered on clinicaltrials.gov (Identifier: NCT01655706) on 27 July 2012.

Escitalopram Personalized Dosing: A Population Pharmacokinetics Repository Method

Escitalopram (SCIT) represents a first-line antidepressant and antianxiety medication. Pharmacokinetic studies of SCIT have demonstrated considerable interindividual variability, emphasizing the need for personalized dosing. Accordingly, we aimed to create a repository of parametric population pharmacokinetic (PPK) models of SCIT to facilitate model-informed precision dosing. In November 2022, we searched PubMed, Embase, and Web of Science for published PPK models and identified eight models. All the structural models reported in the literature were either one- or two-compartment models. In order to investigate the variances in model performance, the parameters of all PPK models were derived from the literature published. A representative virtual population, characterized by an age of 30, a body weight of 70 kg, and a BMI of 23 kg/m2, was generated for the purpose of replicating these models. To accomplish this, the rxode2 package in the R programming language was employed. Subsequently, we compared simulated concentration-time profiles and evaluated the impact of covariates on clearance. The most significant covariates were CYP2C19 phenotype, weight, and age, indicating that dosing regimens should be tailored accordingly. Additionally, among Chinese psychiatric patients, SCIT showed nearly double the exposure compared to other populations, specifically when considering the same CYP2C19 population restriction, which is a knowledge gap that needs further investigation. Furthermore, this repository of parametric PPK models for SCIT has a wide range of potential applications, like design miss or delay dose remedy strategies and external PPK model validation.

Pharmacogenetic Dose Modeling Based on CYP2C19 Allelic Phenotypes

Pharmacogenetic variability in drug metabolism leads to patient vulnerability to side effects and to therapeutic failure. Our purpose was to introduce a systematic statistical methodology to estimate quantitative dose adjustments based on pharmacokinetic differences in pharmacogenetic subgroups, addressing the concerns of sparse data, incomplete information on phenotypic groups, and heterogeneity of study design. Data on psychotropic drugs metabolized by the cytochrome P450 enzyme CYP2C19 were used as a case study. CYP2C19 activity scores were estimated, while statistically assessing the influence of methodological differences between studies, and used to estimate dose adjustments in genotypic groups. Modeling effects of activity scores in each substance as a population led to prudential predictions of adjustments when few data were available ('shrinkage'). The best results were obtained with the regularized horseshoe, an innovative Bayesian approach to estimate coefficients viewed as a sample from two populations. This approach was compared to modeling the population of substance as normally distributed, to a more traditional "fixed effects" approach, and to dose adjustments based on weighted means, as in current practice. Modeling strategies were able to assess the influence of study parameters and deliver adjustment levels when necessary, extrapolated to all phenotype groups, as well as their level of uncertainty. In addition, the horseshoe reacted sensitively to small study sizes, and provided conservative estimates of required adjustments.

Pharmacogenetics and Pain Treatment with a Focus on Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) and Antidepressants: A Systematic Review

Background: This systematic review summarizes the impact of pharmacogenetics on the effect and safety of non-steroidal anti-inflammatory drugs (NSAIDs) and antidepressants when used for pain treatment. Methods: A systematic literature search was performed according to the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines regarding the human in vivo efficacy and safety of NSAIDs and antidepressants in pain treatment that take pharmacogenetic parameters into consideration. Studies were collected from PubMed, Scopus, and Web of Science up to the cutoff date 18 October 2021. Results: Twenty-five articles out of the 6547 initially detected publications were identified. Relevant medication–gene interactions were noted for drug safety. Interactions important for pain management were detected for (1) ibuprofen/CYP2C9; (2) celecoxib/CYP2C9; (3) piroxicam/CYP2C8, CYP2C9; (4) diclofenac/CYP2C9, UGT2B7, CYP2C8, ABCC2; (5) meloxicam/CYP2C9; (6) aspirin/CYP2C9, SLCO1B1, and CHST2; (7) amitriptyline/CYP2D6 and CYP2C19; (8) imipramine/CYP2C19; (9) nortriptyline/CYP2C19, CYP2D6, ABCB1; and (10) escitalopram/HTR2C, CYP2C19, and CYP1A2. Conclusions: Overall, a lack of well powered human in vivo studies assessing the pharmacogenetics in pain patients treated with NSAIDs or antidepressants is noted. Studies indicate a higher risk for partly severe side effects for the CYP2C9 poor metabolizers and NSAIDs. Further in vivo studies are needed to consolidate the relevant polymorphisms in NSAID safety as well as in the efficacy of NSAIDs and antidepressants in pain management.

Tools for optimising pharmacotherapy in psychiatry (therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests): focus on antidepressants

Objectives: More than 40 drugs are available to treat affective disorders. Individual selection of the optimal drug and dose is required to attain the highest possible efficacy and acceptable tolerability for every patient.Methods: This review, which includes more than 500 articles selected by 30 experts, combines relevant knowledge on studies investigating the pharmacokinetics, pharmacodynamics and pharmacogenetics of 33 antidepressant drugs and of 4 drugs approved for augmentation in cases of insufficient response to antidepressant monotherapy. Such studies typically measure drug concentrations in blood (i.e. therapeutic drug monitoring) and genotype relevant genetic polymorphisms of enzymes, transporters or receptors involved in drug metabolism or mechanism of action. Imaging studies, primarily positron emission tomography that relates drug concentrations in blood and radioligand binding, are considered to quantify target structure occupancy by the antidepressant drugs in vivo. Results: Evidence is given that in vivo imaging, therapeutic drug monitoring and genotyping and/or phenotyping of drug metabolising enzymes should be an integral part in the development of any new antidepressant drug.Conclusions: To guide antidepressant drug therapy in everyday practice, there are multiple indications such as uncertain adherence, polypharmacy, nonresponse and/or adverse reactions under therapeutically recommended doses, where therapeutic drug monitoring and cytochrome P450 genotyping and/or phenotyping should be applied as valid tools of precision medicine.

Therapy response prediction in major depressive disorder: current and novel genomic markers influencing pharmacokinetics and pharmacodynamics

Major depressive disorder is connected with high rates of functional disability and mortality. About a third of the patients are at risk of therapy failure. Several pharmacogenetic markers especially located in CYP450 genes such as CYP2D6 or CYP2C19 are of relevance for therapy outcome prediction in major depressive disorder but a further optimization of predictive tools is warranted. The article summarizes the current knowledge on pharmacogenetic variants, therapy effects and side effects of important antidepressive therapeutics, and sheds light on new methodological approaches for therapy response estimation based on genetic markers with relevance for pharmacokinetics, pharmacodynamics and disease pathology identified in genome-wide association study analyses, highlighting polygenic risk score analysis as a tool for further optimization of individualized therapy outcome prediction.

Impact of Drug-Gene-Interaction, Drug-Drug-Interaction, and Drug-Drug-Gene-Interaction on (es)Citalopram Therapy: The PharmLines Initiative

We explored the association between CYP2C19/3A4 mediated drug-gene-interaction (DGI), drug-drug-interaction (DDI) and drug-drug-gene-interaction (DDGI) and (es)citalopram dispensing course. A cohort study was conducted among adult Caucasians from the Lifelines cohort (167,729 participants) and linked dispensing data from the IADB.nl database as part of the PharmLines Initiative. Exposure groups were categorized into (es)citalopram starters with DGI, DDI and DDGI. The primary outcome was drug switching and/or dose adjustment, and the secondary was early discontinuation after the start of (es)citalopram. Logistic regression modeling was applied to estimate adjusted odd ratios with their confidence interval. We identified 316 (es)citalopram starters with complete CYP2C19/3A4 genetic information. The CYP2C19 IM/PM and CYP3A4 NM combination increased risks of switching and/or dose reduction (OR: 2.75, 95% CI: 1.03–7.29). The higher effect size was achieved by the CYP2C19 IM/PM and CYP3A4 IM combination (OR: 4.38, 95% CI: 1.22–15.69). CYP2C19/3A4 mediated DDIs and DDGIs showed trends towards increased risks of switching and/or dose reduction. In conclusion, a DGI involving predicted decreased CYP2C19 function increases the need for (es)citalopram switching and/or dose reduction which might be enhanced by co-presence of predicted decreased CYP3A4 function. For DDI and DDGI, no conclusions can be drawn from the results.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

Analytical methodologies for the enantiodetermination of citalopram and its metabolites

Citalopram (CIT) is a highly selective serotonin reuptake inhibitor (SSRI) frequently used in the treatment of major depressive disorders. It has a chiral centre in its structure and is used in therapy both as a racemic mixture (R,S-CIT) and a pure enantiomer (S-CIT). The differences between the pharmacokinetic and pharmacological profiles of the two enantiomers are well established. Consequently, the development of new efficient chiral analysis methods for their enantiomeric separation is a topic of great actuality. CIT metabolism is stereoselective as it is metabolized in chiral active metabolites, which retain considerable SSRI activity and contribute to the pharmacological effect. Chiral analytical methods are employed for the determination of enantiomeric ratio in pharmaceutical preparations and for monitoring the enantiomer levels in biological samples for therapeutic and toxicologic purposes. The current study reviews the published literature for the chiral analysis of CIT and its metabolites based on chromatographic and electrophoretic methods coupled with UV, fluorescence and mass spectrometry detectors.

A population pharmacokinetic analysis of the oral CYP17 lyase and androgen receptor inhibitor seviteronel in patients with advanced/metastatic castration-resistant prostate cancer or breast cancer

PURPOSE

Seviteronel is an orally-administered selective cytochrome P450c17a 17,20-lyase and androgen receptor inhibitor with anti-tumor activity in vitro and in vivo, and clinical activity in men with advanced castration-resistant prostate cancer (CRPC) and men and women with advanced breast cancer. The purpose of this study was to assess the pharmacokinetics (PK) of seviteronel across the aforementioned populations.

METHODS

This report describes the PK of seviteronel (50-750 mg, QD or BID) using noncompartmental and population approaches from 243 patients with advanced breast or prostate cancer pooled across 4 clinical studies. First dose and steady-state PK were examined, as well as covariates including prandial status, sex and concomitant dexamethasone.

RESULTS

Seviteronel PK can be characterized by transit absorption and a bi-phasic first-order elimination while accounting for covariance between random effects. Prandial status did not significantly affect any parameters to a clinically-relevant extent. Both sex and body weight were significant covariates on clearance, explaining 37% of the interindividual variability on that parameter. There were no significant effects from the race or the presence of a corticosteroid (either dexamethasone or prednisone).

CONCLUSIONS

Seviteronel demonstrates linear PK over the dose range of 50-750 mg given either BID or QD in men with advanced CRPC or men and women with breast cancer. The disposition of seviteronel following oral administration is well described by this population PK model and can be used for accurate simulations for future studies with body weight and sex affecting clearance, but not to a clinically-meaningful degree requiring a change in the current dosing scheme.

Pharmacokinetics of CYP2C9, CYP2C19, and CYP2D6 substrates in healthy Chinese and European subjects

PURPOSE

The aim of this analysis is to compare the pharmacokinetics of drug substrates in healthy Chinese and European subjects of aligned CYP2C9, CYP2C19, or CYP2D6 enzyme activity, providing further insight into drivers of interethnic differences in pharmacokinetics.

METHODS

Following identification of appropriate drug substrates, a comprehensive and structured literature search was conducted to identify single-dose pharmacokinetic data in healthy Chinese or European subjects with reported CYP2C9, CYP2C19, or CYP2D6 activity (genotype or phenotype). The ratio of drug AUC in the Chinese and European subjects classified with aligned enzyme activity was calculated (ethnicity ratio (ER)).

RESULTS

For 22/25 drugs identified, the ERs calculated indicated no or only limited interethnic differences in exposure (<twofold) in Chinese and European subjects with aligned polymorphic enzyme activity. The interethnic differences observed can reflect differences across populations in additional determinants of pharmacokinetics, although the notable between study variation and change over time in methods used to assign enzyme activity may also be contributing factors. There was no association between drug substrate fraction metabolized (fm) for CYP2C9, CYP2C19, or CYP2D6 and the ERs calculated.

CONCLUSION

The spectrum of pharmacokinetic determinants for each drug substrate and their differences across ethnic groups must be considered on a case-by-case basis in addition to metabolism by CYP2C9, CYP2C19, or CYP2D6. This analysis has also highlighted the challenges which arise when comparing published datasets if consistent methods to assign polymorphic enzyme activity have not been used.

A population pharmacokinetic model for R- and S-citalopram and desmethylcitalopram in Alzheimer's disease patients with agitation

The citalopram for Alzheimer’s disease trial evaluated citalopram for the management for agitation in Alzheimer’s disease patients. Sparse data was available from this elderly patient population. A nonlinear mixed effects population pharmacokinetic modeling approach was used to describe the pharmacokinetics of R- and S-citalopram and their primary metabolite (desmethylcitalopram). A structural model with 4 compartments (one compartment/compound) with linear oral absorption and elimination described the data adequately. Overall, the model showed that clearance of the R-enantiomer was slower than the clearance of the S-enantiomer. Without accounting for any patient-specific covariates, the population estimate of the metabolic clearance of citalopram was 8.6 (R-citalopram) and 14 L/h (S-citalopram). The population estimate of the clearance of desmethylcitalopram was 23.8 (R-Dcit) and 38.5 L/h (S-Dcit). Several patient-specific covariates were found to have a significant effect on the pharmacokinetics of R,S-citalopram and desmethylcitalopram. A significant difference in the metabolic clearance of R-citalopram between males and females (13 vs 9.05 L/h) was identified in this analysis. Both R- and S-citalopram metabolic clearance decreased with age. Additionally, consistent with literature reports S-citalopram metabolic clearance increased with increasing body weight and was significantly influenced by CYPC19 genotype, with a difference of 5.8 L/h between extensive/rapid and intermediate/poor metabolizers. R,S-desmethylcitalopram clearance increased with increasing body weight. This model may allow for the opportunity to delineate the effect of R- and S-citalopram on pharmacodynamics outcomes related to the management of agitation in Alzheimer’s disease.

The impact of CYP2C19 polymorphisms on citalopram metabolism in patients with major depressive disorder

WHAT IS KNOWN AND OBJECTIVE

Genetic variations in drug-metabolizing enzyme genes change drug pharmacokinetics and response. CYP2C19 is a clinically important enzyme that metabolizes citalopram (CIT). The objective of this study was to determine CYP2C19 genetic polymorphisms and to evaluate the impact of these polymorphisms on the metabolism of citalopram in a sample of the Turkish population. We also assessed *17 polymorphism in healthy subjects in this population.

METHODS

The CYP2C19 genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism method (209 healthy individuals and 50 patients for CIT metabolism), and the plasma concentrations of CIT and demethylcitalopram (DCIT) were quantified by high-performance liquid chromatography.

RESULTS AND DISCUSSION

The CYP2C19*1 and *17 allele frequencies for the patient group and the healthy group were 71·0%, 18·0% and 81·1%, 18·9%, respectively. There was no significant difference between the two groups (P > 0·05). The mean plasma concentrations and the mean dose-corrected (C/D) plasma levels of DCIT were significantly higher in patients with the CYP2C19*1/*1 genotype compared to patients with CYP2C19*1/*2 and CYP2C19*2/*2 genotypes (P < 0·05). Furthermore, the mean metabolic ratio (MR, CIT/DCIT) was also significantly higher in the CYP2C19*1/*2 + CYP2C19*2/*2 genotypes (P < 0·05). On the other hand, plasma CIT, DCIT concentrations and M/R value in the CYP2C19*1/*1 genotypes were no different to those of the CYP2C19*1/*17 genotypes (P > 0·05).

WHAT IS NEW AND CONCLUSION

Our data suggest that CYP2C19*17 polymorphism does not have a significant effect on CIT metabolism. In contrast CYP2C19*2 polymorphism has a prominent role and is likely to contribute to interindividual variability in CIT metabolism in vivo at therapeutic doses.

Pharmacogenetics of major depressive disorder: top genes and pathways toward clinical applications

The pharmacogenetics of antidepressants has been not only a challenging but also frustrating research field since its birth in the 1990s. Indeed, great expectations followed the first evidence of familiar aggregation of antidepressant response. Despite the progress from candidate gene studies to genome-wide association studies (GWAS), results fell out the expectations and they were often inconsistent. Anyway, the cumulative evidence supports the involvement of some genes and molecular pathways in antidepressant efficacy. The best single genes are SLC6A4, HTR2A, BDNF, GNB3, FKBP5, ABCB1, and cytochrome P450 genes (CYP2D6 and CYP2C19). Molecular pathways involved in inflammation and neuroplasticity show the greatest support. The first studies evaluating benefits of genotype-guided antidepressant treatments provided encouraging results and confirmed the relevance of SLC6A4, HTR2A, ABCB1, and cytochrome P450 genes. Further progress in genotyping and data analysis would allow to move forward and complete the understanding of antidepressant pharmacogenetics and its translation into clinical applications.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Selective Serotonin Reuptake Inhibitors

Selective serotonin reuptake inhibitors (SSRIs) are primary treatment options for major depressive and anxiety disorders. CYP2D6 and CYP2C19 polymorphisms can influence the metabolism of SSRIs, thereby affecting drug efficacy and safety. We summarize evidence from the published literature supporting these associations and provide dosing recommendations for fluvoxamine, paroxetine, citalopram, escitalopram, and sertraline based on CYP2D6 and/or CYP2C19 genotype (updates at www.pharmgkb.org).

Effect of Cytochrome P450 polymorphism on the action and metabolism of selective serotonin reuptake inhibitors

INTRODUCTION

The aim of this article is to review the field of clinically relevant pharmacogenetic effects of cytochrome P450 polymorphisms on metabolism, kinetics, and action of selective serotonin reuptake inhibitors (SSRIs).

AREAS COVERED

The relevant literature in humans on the implications of genetic variation on SSRI drug exposure, drug safety, and efficacy was systematically evaluated. There is a large amount of evidence on the influences of CYP polymorphisms on the pharmacokinetics of SSRIs. Regulatory agencies have issued warnings or advice considering dose adjustments in the presence of affected metabolic phenotypes for several SSRIs. Evidence-based dose adjustments for drugs dependent on CYP genotype are available to clinicians. However, few data on the relationship between genetically determined elevated plasma concentrations of SSRIs and specific side effects or therapeutic failure are currently available.

EXPERT OPINION

Genetic polymorphisms in CYP2D6 and CYP2C19 exert large influences on the individual exposure to SSRIs, leading to the aim to achieve similar concentration time courses in different metabolizer phenotypes. The implementation of a stratified approach to medication with SSRIs in different metabolic phenotypes on a rational basis will require new studies assessing the association between clinical outcomes (such as adverse reactions) and genetically determined elevated plasma concentrations.

Prediction of in vivo clearance and associated variability of CYP2C19 substrates by genotypes in populations utilizing a pharmacogenetics-based mechanistic model

It is important to examine the cytochrome P450 2C19 (CYP2C19) genetic contribution to drug disposition and responses of CYP2C19 substrates during drug development. Design of such clinical trials requires projection of genotype-dependent in vivo clearance and associated variabilities of the investigational drug, which is not generally available during early stages of drug development, but is essential for CYP2C19 substrates with multiple clearance pathways. This study evaluated the utility of pharmacogenetics-based mechanistic modeling in predicting such parameters. Hepatic CYP2C19 activity and variability within genotypes were derived from in vitro S-mephenytoin metabolic activity in genotyped human liver microsomes (N = 128). These data were then used in mechanistic models to predict genotype-dependent disposition of CYP2C19 substrates (i.e., S-mephenytoin, citalopram, pantoprazole, and voriconazole) by incorporating in vivo clearance or pharmacokinetics of wild-type subjects and parameters of other clearance pathways. Relative to the wild-type, the CYP2C19 abundance (coefficient of variation percentage) in CYP2C19*17/*17, *1/*17, *1/*1, *17/null, *1/null, and null/null microsomes was estimated as 1.85 (117%), 1.79 (155%), 1.00 (138%), 0.83 (80%), 0.38 (130%), and 0 (0%), respectively. The subsequent modeling and simulations predicted, within 2-fold of the observed, the means and variabilities of urinary S/R-mephenytoin ratio (36 of 37 genetic groups), the oral clearance of citalopram (9 of 9 genetic groups) and pantoprazole (6 of 6 genetic groups), and voriconazole oral clearance (4 of 4 genetic groups). Thus, relative CYP2C19 genotype-dependent hepatic activity and variability were quantified in vitro and used in a mechanistic model to predict pharmacokinetic variability, thus allowing the design of pharmacogenetics and drug-drug interaction trials for CYP2C19 substrates.

Altered brain concentrations of citalopram and escitalopram in P-glycoprotein deficient mice after acute and chronic treatment

According to both in vitro and in vivo data P-glycoprotein (P-gp) may restrict the uptake of several antidepressants into the brain, thus contributing to the poor success rate of current antidepressant therapies. The therapeutic activity of citalopram resides in the S-enantiomer, whereas the R-enantiomer is practically devoid of serotonin reuptake potency. To date, no in vivo data are available that address whether the enantiomers of citalopram and its metabolites are substrates of P-gp. P-gp knockout (abcb1ab (-/-)) and wild-type (abcb1ab (+/+)) mice underwent acute (single-dose) and chronic (two daily doses for 10 days) treatment with citalopram (10mg/kg) or escitalopram (5mg/kg) Serum and brain samples were collected 1-6h after the first or last i.p. injection for subsequent drug analysis by an enantioselective HPLC method. In brain, 3-fold higher concentrations of S- and R-citalopram, and its metabolites, were found in abcb1ab (-/-) mice than in abcb1ab (+/+) mice after both acute and chronic citalopram treatments. After escitalopram treatment, the S-citalopram brain concentration was 3-5 times higher in the knockout mice than in controls. The results provide novel evidence that the enantiomers of citalopram are substrates of P-gp. Possible clinical and toxicological implications of this finding need to be further elucidated.

Pharmacogenetics of antidepressant drugs: an update after almost 20 years of research

Major depressive disorder (MDD) is an emergent cause of personal and socio-economic burden, both for the high prevalence of the disorder and the unsatisfying response rate of the available antidepressant treatments. No reliable predictor of treatment efficacy and tolerance in the single patient is available, thus drug choice is based on a trial and error principle with poor clinical efficiency. Among modulators of treatment outcome, genetic polymorphisms are thought to explain a significant share of the inter-individual variability. The present review collected the main pharmacogenetic findings primarily about antidepressant response and secondly about antidepressant induced side effects, and discussed the main strengths and limits of both candidate and genome-wide association studies and the most promising methodological opportunities and challenges of the field. Despite clinical applications of antidepressant pharmacogenetics are not available yet, previous findings suggest that genotyping may be applied in the clinical practice. In order to reach this objective, further rigorous pharmacogenetic studies (adequate sample size, study of better defined clinical subtypes of MDD, adequate covering of the genetic variability), their combination with the results obtained through complementary methodologies (e.g., pathway analysis, epigenetics, transcriptomics, and proteomics), and finally cost-effectiveness trials are required.

Genetic variability of drug-metabolizing enzymes: the dual impact on psychiatric therapy and regulation of brain function

Polymorphic drug-metabolizing enzymes (DMEs) are responsible for the metabolism of the majority of psychotropic drugs. By explaining a large portion of variability in individual drug metabolism, pharmacogenetics offers a diagnostic tool in the burgeoning era of personalized medicine. This review updates existing evidence on the influence of pharmacogenetic variants on drug exposure and discusses the rationale for genetic testing in the clinical context. Dose adjustments based on pharmacogenetic knowledge are the first step to translate pharmacogenetics into clinical practice. However, also clinical factors, such as the consequences on toxicity and therapeutic failure, must be considered to provide clinical recommendations and assess the cost-effectiveness of pharmacogenetic treatment strategies. DME polymorphisms are relevant not only for clinical pharmacology and practice but also for research in psychiatry and neuroscience. Several DMEs, above all the cytochrome P (CYP) enzymes, are expressed in the brain, where they may contribute to the local biochemical homeostasis. Of particular interest is the possibility of DMEs playing a physiological role through their action on endogenous substrates, which may underlie the reported associations between genetic polymorphisms and cognitive function, personality and vulnerability to mental disorders. Neuroimaging studies have recently presented evidence of an effect of the CYP2D6 polymorphism on basic brain function. This review summarizes evidence on the effect of DME polymorphisms on brain function that adds to the well-known effects of DME polymorphisms on pharmacokinetics in explaining the range of phenotypes that are relevant to psychiatric practice.

In vivo quantitative prediction of the effect of gene polymorphisms and drug interactions on drug exposure for CYP2C19 substrates

We present a unified quantitative approach to predict the in vivo alteration in drug exposure caused by either cytochrome P450 (CYP) gene polymorphisms or CYP-mediated drug-drug interactions (DDI). An application to drugs metabolized by CYP2C19 is presented. The metrics used is the ratio of altered drug area under the curve (AUC) to the AUC in extensive metabolizers with no mutation or no interaction. Data from 42 pharmacokinetic studies performed in CYP2C19 genetic subgroups and 18 DDI studies were used to estimate model parameters and predicted AUC ratios by using Bayesian approach. Pharmacogenetic information was used to estimate a parameter of the model which was then used to predict DDI. The method adequately predicted the AUC ratios published in the literature, with mean errors of -0.15 and -0.62 and mean absolute errors of 0.62 and 1.05 for genotype and DDI data, respectively. The approach provides quantitative prediction of the effect of five genotype variants and 10 inhibitors on the exposure to 25 CYP2C19 substrates, including a number of unobserved cases. A quantitative approach for predicting the effect of gene polymorphisms and drug interactions on drug exposure has been successfully applied for CYP2C19 substrates. This study shows that pharmacogenetic information can be used to predict DDI. This may have important implications for the development of personalized medicine and drug development.

Distribution of CYP2C19*2 and CYP2C19*3 polymorphisms in Venezuelan populations with different admixture

BACKGROUND

The conquest and colonization of Venezuela generated very heterogeneous populations as a product of admixture; for this reason, the distribution of polymorphisms of the CYP2C19 gene was studied in various Venezuelan populations.

METHODS

Two hundred and eighty-one individuals, from three Venezuelan populations with different admixtures, were genotyped for CYP2C19*2 and CYP2C19*3 polymorphisms. Differences between groups were analysed using a chi-square test of heterogeneity and association of allele frequencies with the level of genetic admixture was performed using a principal component analysis (PCA). No significant differences in distribution of alleles, genotypes and phenotypes were found between the populations studied.

RESULTS

In Venezuela, high frequencies of the alleles CYP2C19*2 and CYP2C19*3 were found compared with Europeans, Africans and Latin Americans, similar to those reported in Asia. PCA analysis suggested that the presence of alleles CYP2C19*2 and CYP2C19*3 is associated with the indigenous component in the Venezuelan populations studied.

CONCLUSIONS

Future studies are needed to confirm this association. High frequencies of intermediate metabolizers (20-38%) and of poor metabolizers (2-7%) were observed, similar to values reported for Asians and higher than those reported for South Americans. This is the first study evaluating CYP2C19 polymorphisms in the Venezuelan general population.

Impact of genetic polymorphisms in CYP2C9 and CYP2C19 on the pharmacokinetics of clinically used drugs

Human cytochrome P450 (CYP) is a superfamily of hemoproteins which oxidize a number of endogenous compounds and xenobiotics. The human CYP2C subfamily consists of four members: CYP2C8, CYP2C9, CYP2C18 and CYP2C19. CYP2C9 and CYP2C19 are important drug-metabolizing enzymes and together metabolize approximately 20% of therapeutically used drugs. Forty-two allelic variants for CYP2C9 and 34 for CYP2C19 have been reported. The frequencies of these variants show marked inter-ethnic variation. The functional consequences of genetic polymorphisms have been examined, and many studies have shown the clinical importance of these polymorphisms. Current evidence suggests that taking the genetically determined metabolic capacity of CYP2C9 and CYP2C19 into account has the potential to improve individual risk/benefit relationships. However, more prospective studies with clinical endpoints are needed before the paradigm of "personalized medicine" based on the variants can be established. This review summarizes the currently available important information on this topic.

Psychotropic drug-drug interactions involving P-glycoprotein

Multidrug resistance P-glycoprotein (P-gp; also known as MDR1 and ABCB1) is expressed in the luminal membrane of the small intestine and blood-brain barrier, and the apical membranes of excretory cells such as hepatocytes and kidney proximal tubule epithelia. P-gp regulates the absorption and elimination of a wide range of compounds, such as digoxin, paclitaxel, HIV protease inhibitors and psychotropic drugs. Its substrate specificity is as broad as that of cytochrome P450 (CYP) 3A4, which encompasses up to 50 % of the currently marketed drugs. There has been considerable interest in variations in the ABCB1 gene as predictors of the pharmacokinetics and/or treatment outcomes of several drug classes, including antidepressants and antipsychotics. Moreover, P-gp-mediated transport activity is saturable, and is subject to modulation by inhibition and induction, which can affect the pharmacokinetics, efficacy or safety of P-gp substrates. In addition, many of the P-gp substrates overlap with CYP3A4 substrates, and several psychotropic drugs that are P-gp substrates are also CYP3A4 substrates. Therefore, psychotropic drugs that are P-gp substrates may cause a drug interaction when P-gp inhibitors and inducers are coadministered, or when psychotropic drugs or other medicines that are P-gp substrates are added to a prescription. Hence, it is clinically important to accumulate data about drug interactions through studies on P-gp, in addition to CYP3A4, to assist in the selection of appropriate psychotropic medications and in avoiding inappropriate combinations of therapeutic agents. There is currently insufficient information available on the psychotropic drug interactions related to P-gp, and therefore we summarize the recent clinical data in this review.

Genetic polymorphisms of cytochrome P450 enzymes and antidepressant metabolism

INTRODUCTION

The cytochrome P450 (CYP) enzymes are the major enzymes responsible for Phase I reactions in the metabolism of several substances, including antidepressant medications. Thus, it has been hypothesized that variants in the CYP network may influence antidepressant efficacy and safety. Nonetheless, data on this field are still contradictory. The authors aim to give an overview of the published studies analyzing the influence of CYP highly polymorphic loci on antidepressant treatment in order to translate the acquired knowledge to a clinical level.

AREAS COVERED

The authors collected and compared experimental works and reviews published from the 1980s to the present and included in the Medline database. The included studies pertain to the effects of CYP gene polymorphisms on antidepressant pharmacokinetic parameters and clinical outcomes (response and drug-related adverse effects), with a focus on applications in clinical practice. The authors focused mainly on in vivo studies in humans (patients or healthy volunteers).

EXPERT OPINION

Great variability in antidepressant metabolism among individuals has been demonstrated. Thus, with the current interest in individualized medicine, several genetic tests to detect CYP variants have been produced. They provide a potentially useful way to anticipate some clinical outcomes of antidepressant treatment, although they will only be extensively used in clinical practice if precise and specific treatment options and guidelines based on genetic tests can be provided.

Sex differences in drug disposition

Physiological, hormonal, and genetic differences between males and females affect the prevalence, incidence, and severity of diseases and responses to therapy. Understanding these differences is important for designing safe and effective treatments. This paper summarizes sex differences that impact drug disposition and includes a general comparison of clinical pharmacology as it applies to men and women.