Effect of cytochrome P450 enzyme polymorphisms on pharmacokinetics of venlafaxine

Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data

BACKGROUND

Venlafaxine dose regimens vary considerably between individuals, requiring personalized dosing.

AIM

This study aimed to identify dose-related influencing factors of venlafaxine through real-world data analysis and to construct a personalized dose model using advanced artificial intelligence techniques.

METHOD

We conducted a retrospective study on patients with depression treated with venlafaxine. Significant variables were selected through a univariate analysis. Subsequently, the predictive performance of seven models (XGBoost, LightGBM, CatBoost, GBDT, ANN, TabNet, and DT) was compared. The algorithm that demonstrated optimal performance was chosen to establish the dose prediction model. Model validation used confusion matrices and ROC analysis. Additionally, a dose subgroup analysis was conducted.

RESULTS

A total of 298 patients were included. TabNet was selected to establish the venlafaxine dose prediction model, which exhibited the highest performance with an accuracy of 0.80. The analysis identified seven crucial variables correlated with venlafaxine daily dose, including blood venlafaxine concentration, total protein, lymphocytes, age, globulin, cholinesterase, and blood platelet count. The area under the curve (AUC) for predicting venlafaxine doses of 75 mg, 150 mg, and 225 mg were 0.90, 0.85, and 0.90, respectively.

CONCLUSION

We successfully developed a TabNet model to predict venlafaxine doses using real-world data. This model demonstrated substantial predictive accuracy, offering a personalized dosing regimen for venlafaxine. These findings provide valuable guidance for the clinical use of the drug.

PBPK modeling to predict the pharmacokinetics of venlafaxine and its active metabolite in different CYP2D6 genotypes and drug-drug interactions with clarithromycin and paroxetine

Venlafaxine, a serotonin-norepinephrine reuptake inhibitor (SNRI), is indicated for the treatment of major depressive disorder, social anxiety disorder, generalized anxiety disorder, and panic disorder. Venlafaxine is metabolized to the active metabolite desvenlafaxine mainly by CYP2D6. Genetic polymorphism of CYP2D6 and coadministration with other medications can significantly affect the pharmacokinetics and/or pharmacodynamics of venlafaxine and its active metabolite. This study aimed to establish the PBPK models of venlafaxine and its active metabolite related to CYP2D6 genetic polymorphism and to predict drug-drug interactions (DDIs) with clarithromycin and paroxetine in different CYP2D6 genotypes. Clinical pharmacogenomic data for venlafaxine and desvenlafaxine were collected to build the PBPK model. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) characteristics of respective compounds were obtained from previously reported data, predicted by the PK-Sim® software, or optimized to capture the plasma concentration-time profiles. Model evaluation was performed by comparing the predicted pharmacokinetic parameters and plasma concentration-time profiles to the observed data. Predicted plasma concentration-time profiles of venlafaxine and its active metabolite were visually similar to the observed profiles and all predicted AUC and Cmax values for respective compounds were included in the twofold error range of observed values in non-genotyped populations and different CYP2D6 genotypes. When clarithromycin or clarithromycin plus paroxetine was concomitantly administered, predicted plasma concentration-time profiles of venlafaxine properly captured the observed profiles in two different CYP2D6 genotypes and all predicted DDI ratios for AUC and Cmax were included within the acceptance range. Consequently, the present model successfully captured the pharmacokinetic alterations of venlafaxine and its active metabolite according to CYP2D6 genetic polymorphism as well as the DDIs between venlafaxine and two CYP inhibitors. The present model can be used to predict the pharmacokinetics of venlafaxine and its active metabolite considering different races, ages, coadministered drugs, and CYP2D6 activity of individuals and it can contribute to individualized pharmacotherapy of venlafaxine.

Physiologically Based Pharmacokinetic Modeling to Unravel the Drug-gene Interactions of Venlafaxine: Based on Activity Score-dependent Metabolism by CYP2D6 and CYP2C19 Polymorphisms

BACKGROUND

Venlafaxine (VEN) is a commonly utilized medication for alleviating depression and anxiety disorders. The presence of genetic polymorphisms gives rise to considerable variations in plasma concentrations across different phenotypes. This divergence in phenotypic responses leads to notable differences in both the efficacy and tolerance of the drug.

PURPOSE

A physiologically based pharmacokinetic (PBPK) model for VEN and its metabolite O-desmethylvenlafaxine (ODV) to predict the impact of CYP2D6 and CYP2C19 gene polymorphisms on VEN pharmacokinetics (PK).

METHODS

The parent-metabolite PBPK models for VEN and ODV were developed using PK-Sim® and MoBi®. Leveraging prior research, derived and implemented CYP2D6 and CYP2C19 activity score (AS)-dependent metabolism to simulate exposure in the drug-gene interactions (DGIs) scenarios. The model's performance was evaluated by comparing predicted and observed values of plasma concentration-time (PCT) curves and PK parameters values.

RESULTS

In the base models, 91.1%, 94.8%, and 94.6% of the predicted plasma concentrations for VEN, ODV, and VEN + ODV, respectively, fell within a twofold error range of the corresponding observed concentrations. For DGI scenarios, these values were 81.4% and 85% for VEN and ODV, respectively. Comparing CYP2D6 AS = 2 (normal metabolizers, NM) populations to AS = 0 (poor metabolizers, PM), 0.25, 0.5, 0.75, 1.0 (intermediate metabolizers, IM), 1.25, 1.5 (NM), and 3.0 (ultrarapid metabolizers, UM) populations in CYP2C19 AS = 2.0 group, the predicted DGI AUC0-96 h ratios for VEN were 3.65, 3.09, 2.60, 2.18, 1.84, 1.56, 1.34, 0.61, and for ODV, they were 0.17, 0.35, 0.51, 0.64, 0.75, 0.83, 0.90, 1.11, and the results were similar in other CYP2C19 groups. It should be noted that PK differences in CYP2C19 phenotypes were not similar across different CYP2D6 groups.

CONCLUSIONS

In clinical practice, the impact of genotyping on the in vivo disposition process of VEN should be considered to ensure the safety and efficacy of treatment.

Venlafaxine's therapeutic reference range in the treatment of depression revised: a systematic review and meta-analysis

INTRODUCTION

The selective serotonin and norepinephrine reuptake inhibitor venlafaxine is among the most prescribed antidepressant drugs worldwide and, according to guidelines, its dose titration should be guided by drug-level monitoring of its active moiety (AM) which consists of venlafaxine (VEN) plus active metabolite O-desmethylvenlafaxine (ODV). This indication of therapeutic drug monitoring (TDM), however, assumes a clear concentration/effect relationship for a drug, which for VEN has not been systematically explored yet.

OBJECTIVES

We performed a systematic review and meta-analysis to investigate the relationship between blood levels, efficacy, and adverse reactions in order to suggest an optimal target concentration range for VEN oral formulations for the treatment of depression.

METHODS

Four databases (MEDLINE (PubMed), PsycINFO, Web of Science Core Collection, and Cochrane Library) were systematically searched in March 2022 for relevant articles according to a previously published protocol. Reviewers independently screened references and performed data extraction and critical appraisal.

RESULTS

High-quality randomized controlled trials investigating concentration/efficacy relationships and studies using a placebo lead-in phase were not found. Sixty-eight articles, consisting mostly of naturalistic TDM studies or small noncontrolled studies, met the eligibility criteria. Of them, five cohort studies reported a positive correlation between blood levels and antidepressant effects after VEN treatment. Our meta-analyses showed (i) higher AM and (ii) higher ODV concentrations in patients responding to VEN treatment when compared to non-responders (n = 360, k = 5). AM concentration-dependent occurrence of tremor was reported in one study. We found a linear relationship between daily dose and AM concentration within guideline recommended doses (75-225 mg/day). The population-based concentration ranges (25-75% interquartile) among 11 studies (n = 3200) using flexible dosing were (i) 225-450 ng/ml for the AM and (ii) 144-302 ng/ml for ODV. One PET study reported an occupancy of 80% serotonin transporters for ODV serum levels above 85 ng/ml. Based on our findings, we propose a therapeutic reference range for AM of 140-600 ng/ml.

CONCLUSION

VEN TDM within a range of 140 to 600 ng/ml (AM) will increase the probability of response in nonresponders. A titration within the proposed reference range is recommended in case of non-response at lower drug concentrations as a consequence of VEN's dual mechanism of action via combined serotonin and norepinephrine reuptake inhibition. Drug titration towards higher concentrations will, however, increase the risk for ADRs, in particular with supratherapeutic drug concentrations.

Enantiospecific Uptake and Depuration Kinetics of Chiral Metoprolol and Venlafaxine in Marine Medaka (Oryzias melastigma): Tissue Distribution and Metabolite Formation

The increasing use of chiral pharmaceuticals has led to their widespread presence in the environment. However, their toxicokinetics have rarely been reported. Therefore, the tissue-specific uptake and depuration kinetics of two pairs of pharmaceutical enantiomers, S-(-)-metoprolol versus R-(+)-metoprolol and S-(+)-venlafaxine versus R-(-)-venlafaxine, were studied in marine medaka (Oryzias melastigma) during a 28-day exposure and 14-day clearance period. The toxicokinetics of the studied pharmaceuticals, including uptake and depuration rate constants, depuration half-life (t_1/2), and bioconcentration factor (BCF), were reported for the first time. The whole-fish results demonstrated a higher S- than R-venlafaxine bioaccumulation potential, whereas no significant difference was observed between S- and R-metoprolol. O-desmethyl-metoprolol (ODM) and α-hydroxy-metoprolol (AHM) were the main metoprolol metabolites identified by suspect screening, and the ratios of ODM to AHM were 3.08 and 1.35 for S- and R-metoprolol, respectively. N,O-Didesmethyl-venlafaxine (NODDV) and N-desmethyl-venlafaxine (NDV) were the main venlafaxine metabolites, and the ratios of NODDV to NDV were 1.55 and 0.73 for S- and R-venlafaxine, respectively. The highest tissue-specific BCFs of the four enantiomers were all found in the eyes, meriting in-depth investigation.

Pharmacogenetics in the Treatment of Huntington’s Disease: Review and Future Perspectives

Huntington’s disease (HD) is an autosomal dominant progressive brain disorder, caused by a pathological expansion of a CAG repeat that encodes the huntingtin gene. This genetic neurodegenerative rare disease is characterized by cognitive, motor, and neuropsychiatric manifestations. The aim of the treatment is symptomatic and addresses the hyperkinetic disorders (chorea, dystonia, myoclonus, tics, etc.) and the behavioural and cognitive disturbances (depression, anxiety, psychosis, etc.) associated with the disease. HD is still a complex condition in need of innovative and efficient treatment. The long-term goal of pharmacogenetic studies is to use genotype data to predict the effective treatment response to a specific drug and, in turn, prevent potential undesirable effects of its administration. Chorea, depression, and psychotic symptoms have a substantial impact on HD patients’ quality of life and could be better controlled with the help of pharmacogenetic knowledge. We aimed to carry out a review of the available publications and evidence related to the pharmacogenetics of HD, with the objective of compiling all information that may be useful in optimizing drug administration. The impact of pharmacogenetic information on the response to antidepressants and antipsychotics is well documented in psychiatric patients, but this approach has not been investigated in HD patients. Future research should address several issues to ensure that pharmacogenetic clinical use is appropriately supported, feasible, and applicable.

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.

Joint population pharmacokinetic modeling of venlafaxine and O-desmethyl venlafaxine in healthy volunteers and patients to evaluate the impact of morbidity and concomitant medication

Introduction: Venlafaxine (VEN) is a widely used dual selective serotonin/noradrenaline reuptake inhibitor indicated for depression and anxiety. It undergoes first-pass metabolism to its active metabolite, O-desmethyl venlafaxine (ODV). The aim of the present study was to develop a joint population pharmacokinetic (PPK) model to characterize their pharmacokinetic characters simultaneously. Methods: Plasma concentrations with demographic and clinical data were derived from a bioequivalence study in 24 healthy subjects and a naturalistic TDM setting containing 127 psychiatric patients. A parent-metabolite PPK modeling was performed with NONMEM software using a non-linear mixed effect modeling approach. Goodness of fit plots and normalized prediction distribution error method were used for model validation. Results and conclusion: Concentrations of VEN and ODV were well described with a one-compartment model incorporating first-pass metabolism. The first-pass metabolism was modeled as a first-order conversion. The morbid state and concomitant amisulpride were identified as two significant covariates affecting the clearance of VEN and ODV, which may account for some of the variations in exposure. This model may contribute to the precision medication in clinical practice and may inspire other drugs with pre-system metabolism.

Pharmacogenomics in drug-induced cardiotoxicity: Current status and the future

Drug-induced cardiotoxicity (DICT) is an important concern of drug safety in both drug development and clinical application. The clinical manifestations of DICT include cardiomyopathy, arrhythmia, myocardial ischemia, heart failure, and a series of cardiac structural and functional changes. The occurrence of DICT has negative impacts on the life quality of the patients, brings additional social and economic burden. It is important to identify the potential factors and explore the mechanisms of DICT. Traditional cardiovascular risk factors can only partially explain the risk of DICT. Pharmacogenomic studies show accumulated evidence of genetics in DICT and suggest the potential to guide precision therapy to reduce risk of cardiotoxicity. The comprehensive application of technologies such as third-generation sequencing, human induced pluripotent stem (iPS) cells and genome editing has promoted the in-depth understanding of the functional role of susceptible genes in DICT. This paper reviewed drugs that cause DICT, the clinical manifestations and laboratory tests, as well as the related content of genetic variations associated with the risk of DICT, and further discussed the implication of new technologies in pharmacogenomics of DICT.

Identifying the Common Genetic Basis of Antidepressant Response

Background

Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction.

Methods

Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA.

Results

Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response.

Conclusions

This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

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.

Effects of CYP2D6 Genotypes on Venlafaxine Metabolism in Japanese Psychiatric Patients With Depression

BACKGROUND

Venlafaxine (VEN) is primarily metabolized by CYP2D6. Although several studies have reported the significant effects of CYP2D6 on VEN and O-desmethylvenlafaxine (ODV) pharmacokinetics in Whites, limited data are available regarding the effects of the Asian-specific CYP2D6 genotype on VEN metabolism. This study evaluated the effects of the CYP2D6*10 and CYP2D6*5 genotypes on the steady-state plasma concentrations of VEN and ODV in Japanese patients.

METHODS

This study included 75 Japanese patients with depression who were treated with VEN. Steady-state plasma concentrations of VEN and ODV were measured using liquid chromatography. Polymerase chain reaction was used to determine CYP2D6 genotypes. A stepwise multiple regression analysis was performed to analyze the relationship between independent variables (sex, age, smoking habit, and number of mutated alleles, CYP2D6*10 and CYP2D6*5), subject-dependent variables (plasma concentrations of VEN and ODV [all corrected for dose and body weight]), and the ODV/VEN ratio.

RESULTS

Significant correlations were observed between the daily dose of VEN (corrected for body weight) and plasma concentrations of VEN (r = 0.498, P < 0.001) and ODV (r = 0.380, P = 0.001); ODV plasma concentrations were approximately 3.2 times higher than VEN plasma concentrations (VEN versus ODV = 18.60 ng/mL versus 59.10 ng/mL). VEN plasma concentrations (corrected for dose and body weight) did not differ with differing numbers of CYP2D6-mutated alleles. However, the ODV/VEN ratio decreased as the number of mutated CYP2D6 alleles increased (P = 0.001).

CONCLUSIONS

This is the first study to examine the effects of CYP2D6*10 in a clinical setting. Although no effects on the plasma concentrations of VEN or ODV were observed, CYP2D6 polymorphism affects the ODV/VEN ratio. Further studies are needed to confirm the clinical relevance of these findings.

Precision Medicine into Clinical Practice: A Web-Based Tool Enables Real-Time Pharmacogenetic Assessment of Tailored Treatments in Psychiatric Disorders

The management of neuropsychiatric disorders involves different pharmacological treatments. In order to perform efficacious drug treatments, the metabolism of CYP genes can help to foresee potential drug–drug interactions. The NeuroPGx software is an open-source web-based tool for genotype/diplotype/phenotype interpretation for neuropharmacogenomic purposes. The software provides information about: (i) the genotypes of evaluated SNPs (single nucleotide polymorphisms); (ii) the main diplotypes in CYP genes and corresponding metabolization phenotypes; (iii) the list of neuropsychiatric drugs with recommended dosage adjustment (according to CPIC and DPWG guidelines); (iv) the list of possible (rare) diplotypes and corresponding metabolization phenotypes. The combined application of NeuroPGx software to the OpenArray technology results in an easy, quick, and highly automated device ready to be used in routine clinical practice.

Enantioselectivity in Drug Pharmacokinetics and Toxicity: Pharmacological Relevance and Analytical Methods

Enzymes, receptors, and other binding molecules in biological processes can recognize enantiomers as different molecular entities, due to their different dissociation constants, leading to diverse responses in biological processes. Enantioselectivity can be observed in drugs pharmacodynamics and in pharmacokinetic (absorption, distribution, metabolism, and excretion), especially in metabolic profile and in toxicity mechanisms. The stereoisomers of a drug can undergo to different metabolic pathways due to different enzyme systems, resulting in different types and/or number of metabolites. The configuration of enantiomers can cause unexpected effects, related to changes as unidirectional or bidirectional inversion that can occur during pharmacokinetic processes. The choice of models for pharmacokinetic studies as well as the subsequent data interpretation must also be aware of genetic factors (such as polymorphic metabolic enzymes), sex, patient age, hepatic diseases, and drug interactions. Therefore, the pharmacokinetics and toxicity of a racemate or an enantiomerically pure drug are not equal and need to be studied. Enantioselective analytical methods are crucial to monitor pharmacokinetic events and for acquisition of accurate data to better understand the role of the stereochemistry in pharmacokinetics and toxicity. The complexity of merging the best enantioseparation conditions with the selected sample matrix and the intended goal of the analysis is a challenge task. The data gathered in this review intend to reinforce the importance of the enantioselectivity in pharmacokinetic processes and reunite innovative enantioselective analytical methods applied in pharmacokinetic studies. An assorted variety of methods are herein briefly discussed.

[Therapeutic drug monitoring of antidepressants: Why venlafaxine is the most monitored drug? A review of literature]

Venlafaxine is the third most frequently prescribed antidepressant in France the last decade, with about 400,000 daily doses. Therapeutic drug monitoring (TDM) of this medication, by measuring the active moiety venlafaxine (V) and O-desmethylvenlafaxine (ODV), is recommended (level of recommendation 2). However, this antidepressant seems to be the one for which clinicians most often use TDM, much more frequently than escitalopram, which is more prescribed and for which TDM is also recommended. The main goal of this review is to provide an update on the TDM of venlafaxine: its therapeutic interval, its level of recommendation and the origin of its "success". From the literature does not enable to define a therapeutic interval for the active moiety V+ODV, that is to say a steady-state trough concentration allowing a clinical response without toxicity. Nevertheless, a target concentration from 100 to 400μg/L is certainly relevant for the majority of patients without any pharmacodynamic resistance ; though a greater concentration could result in an earlier response or could be required for a clinical response in a minority of patients. A patient with no clinical response despite a concentration greater than 1000μg/L should be proposed another antidepressant. Measurement of the ODV/V ratio is also a useful tool, values below 0.3 usually reflecting a slow metabolizer phenotype for cytochrome P-450 2D6, which is more at risk of adverse effects. Research for this phenotype probably explains many prescriptions for TDM.

Pharmacogenetic/Pharmacogenomic Tests for Treatment Prediction in Depression

Genetic factors play a significant but complex role in antidepressant (AD) response and tolerability. During recent years, there is growing enthusiasm in the promise of pharmacogenetic/pharmacogenomic (PGx) tools for optimizing and personalizing treatment outcomes for patients with major depressive disorder (MDD). The influence of pharmacokinetic and pharmacodynamic genes on response and tolerability has been investigated, including those encoding the cytochrome P450 superfamily, P-glycoprotein, monoaminergic transporters and receptors, intracellular signal transduction pathways, and the stress hormone system. Genome-wide association studies are also identifying new genetic variants associated with AD response phenotypes, which, combined with methods such as polygenic risk scores (PRS), is opening up new avenues for novel personalized treatment approaches for MDD. This chapter describes the basic concepts in PGx of AD response, reviews the major pharmacokinetic and pharmacodynamic genes involved in AD outcome, discusses PRS as a promising approach for predicting AD efficacy and tolerability, and addresses key challenges to the development and application of PGx tests.

Clinical Relevance of Pharmacogenetics in Serotonin Syndrome

Serotonin syndrome is a predictable life-threatening condition that is caused by serotonergic stimulation of the central and peripheral nervous systems. A patient's genetic profile can amplify exposure risk as many serotonergic drugs are metabolized by CYP450 enzymes, and these enzymes may be altered in functionality. We report a case of an elderly man who presented with serotonin syndrome after a dose change in valproic acid 5 weeks prior. His medication list consisted of low-dose serotonergic agents, which is unusual as most cases of serotonin syndrome involve higher doses. A review of his pharmacogenetic profile is presented to retrospectively evaluate the additive risk for serotonin syndrome and implications on resuming serotonergic agents.

Influence of combinations of drugs that act on the CYP2D6 metabolic pathway in the treatment of major depressive disorder: A population-based study

Objective

To describe the frequency of drug combinations (substrate-substrate or substrate-inhibitor) with the potential to interfere with the CYP2D6 metabolic pathway in patients receiving antidepressant medication for major depressive disorder.

Methods

We carried out an observational study using outpatient medical records. We included adult subjects who initiated antidepressant medication during 2008–2010. Patients were assigned to three study groups: no combination, substrate-substrate, and substrate-inhibitor. Follow-up period was 12 months. Main measures: demographics, comorbidity and medication persistence. Statistical analysis included a logistic regression model, P < 0.05.

Results

Five thousand six hundred and thirty patients were recruited (61.9 years, 76.9% female), 24.4% (CI: 23.8 – 26.0%) received some kind of drug combination (substrate-substrate: 15.4%, substrate-inhibitor: 9.0%). Variables significantly associated with drugs combinations that may act on the CYP2D6 metabolic pathway were: dementia (OR = 4.2), neuropathy (OR = 4.2) and stroke (OR = 1.9), P < 0.001. Medication persistence at 12 months was longer in patients with no combination (55.3%) than in patients receiving substrate-substrate (50.5%) or substrate-inhibitor (45.0%) combinations, P < 0.001.

Conclusions

Twenty-five percent of major depressive disorder patients received a combination of drugs with the potential to interfere with CYP2D6 metabolic pathway. These combinations increased with comorbidity and resulted in shorter medication persistence of antidepressant treatment.

Cytochrome P450-mediated inhibition of venlafaxine metabolism by trimipramine

OBJECTIVE

The aim of this study was to ensure patients' safety and to enhance treatment efficacy, knowledge about pharmacokinetic interactions even in complex clinical situations of polypharmacy is invaluable. This study is to uncover the potential of pharmacokinetic interactions between venlafaxine and trimipramine in a naturalistic sample.

METHODS

Out of a therapeutic drug monitoring database with plasma concentrations of venlafaxine (VEN) and O-desmethylvenlafaxine (ODV), we considered two groups of patients receiving venlafaxine without known cytochrome P450 confounding medications, taking solely venlafaxine: V0 (n = 905), and a group of patients co-medicated with trimipramine, VTRIM (n = 33). For VEN, ODV and active moiety (sum of VEN + ODV) plasma concentrations and dose-adjusted concentrations as well as ODV/VEN ratios were compared between groups using the Mann-Whitney U test with a significance level of 0.05.

RESULTS

Patients co-medicated with trimipramine had higher plasma concentrations of VEN (183.0 vs. 72.0, +154%, P = 0.002) and AM (324.0 vs. 267.5, +21%, P = 0.005) and higher dose adjusted plasma concentrations than patients in the control group (P = 0.001 and P = 0.003). No differences were found for ODV and C/D ODV (P < 0.05 for both comparisons). The metabolite to parent ratio, ODV/VEN, was significantly lower in the VTRIM group (1.15 vs. 2.37, P = 0.012).

CONCLUSION

Findings suggest inhibitory effects of trimipramine on venlafaxine pharmacokinetics most likely via an inhibition of CYP 2D6 or by saturated enzyme capacity. The lack of in vitro data hampers the understanding of the exact mechanisms. Clinicians should be aware of drug-drug interactions when combining these agents. Therapeutic drug monitoring helps to ensure treatment efficacy and patients' safety.

Venlafaxine pharmacogenetics: a comprehensive review

Antidepressant response could be from 42 to 50% genetically determined. Venlafaxine (VEN) was the sixth most-prescribed antidepressant in the USA in 2017. Therefore, we reviewed studies which focused on the pharmacogenetics of VEN and found that there is a lack of guidelines for pharmacogenetic testing for VEN. Within investigated genetic polymorphisms, few of them can be indicated as potential predictors of VEN efficacy and tolerance. However, additional pharmacogenetic studies of VEN should be performed to reproduce already obtained results or explain contradictory ones. The individualization of pharmacotherapy is a key issue in providing patients with the highest possible quality of treatment, therefore pharmacogenetic studies should be one of the components of therapy optimization.

Effects of CYP2D6 activity on the efficacy and safety of mirtazapine in patients with depressive disorders and comorbid alcohol use disorder

The objective of the study was to investigate the effects of CYP2D6 activity on the efficacy and safety of mirtazapine in patients with depressive disorders and comorbid alcohol use disorder who received mirtazapine. The study included 109 Russian patients who received mirtazapine at a dose of 30.0 [15.0; 45.0] mg per day. Genotyping of CYP2D6*4 (1846G > A, rs3892097) was performed using real-time polymerase chain reaction with allele-specific hybridization. The activity of CYP2D6 was evaluated by determining the concentration of endogenous substrate of the enzyme and its urinary metabolite - pinoline to 6-hydroxy-1,2,3,4-tetrahydro-beta-carboline ratio, using high-performance liquid chromatography - mass spectrometry. The statistically significant differences between the scores on the Hamilton Depression Rating Scale (HAMD) in patients with different genotypes were revealed by day 16: (GG) 5.0 [3.0; 6.0], (GA) 1.5 [1.0; 3.2] (p < 0.001), and for the The UKU Side Effects Rating Scale (UKU): (GG) 6.0 [6.0; 7.0], (GA) 8.5 [8.0; 10.0] (p < 0.001). The calculation of correlation coefficients between the differences in scale scores and metabolic rate showed the presence of statistically significant weak inverse correlation with the efficacy indicator evaluated by HAMD (r = -0.278, p < 0.05), but not by UKU (r = 0.274, p > 0.05). This study demonstrated that an increased CYP2D6 activity reduces the efficacy of treatment with mirtazapine.

Reduced clearance of venlafaxine in a combined treatment with quetiapine

Venlafaxine and the atypical antipsychotic quetiapine are often administered concomitantly. Both drugs share several metabolic hepatic pathways. However, pharmacokinetic interactions between venlafaxine and quetiapine have not been studied yet. A therapeutic drug monitoring database containing serum concentrations of venlafaxine (VEN) and its active metabolite O-desmethylvenlafaxine (ODVEN) was analyzed. Two groups of patients were compared: venlafaxine monotherapy V₀ (n = 153) and co-medication with quetiapine, V_QUE (n = 71). Serum concentrations of VEN, ODVEN, and active moiety, AM (VEN + ODVEN), metabolite to parent compound ratio (ODVEN/VEN) and dose adjusted serum concentrations were compared using non-parametrical tests without information on CYP2D6 genotype. The two groups did not differ in terms of the daily dosage of venlafaxine, age, or sex. Median serum concentrations in the quetiapine group showed significantly, 15.8% and 29.3% higher values for AM and ODVEN (p = 0.002, Cohen's d = 0,41; p = 0.003, d = 0,44), respectively. Dose adjusted serum concentrations of active moiety and ODVEN revealed comparable differences (p = 0.038, d = 0,32; p = 0.015, d = 0,28) with significantly higher values in the co-medicated group. Significantly higher values for ODVEN and AM suggest a reduced clearance of ODVEN and active moiety when quetiapine is co-administered. This may be a consequence of a reduced metabolism of venlafaxine to the inactive metabolite N-desmethylvenlafaxine via CYP3A4, the main metabolizing enzyme for quetiapine, and a shift towards a higher proportion of the active metabolite ODVEN. Therapeutic drug monitoring is recommended in the case of co-medication to ensure clinical efficacy and patient safety. Although the increase of AM is moderate, we consider it relevant for clinicians given the prevalence of concomitant medication of quetiapine and venlafaxine.

Effects of CYP2D6 genetic polymorphisms on the efficacy and safety of fluvoxamine in patients with depressive disorder and comorbid alcohol use disorder

Background

Fluvoxamine therapy is used for treatment of patients with depressive disorder, but it is often ineffective, and some patients suffer from dose-dependent undesirable side effects such as vertigo, headache, indigestion, xerostomia, increased anxiety, etc. CYP2D6 is involved in the biotransformation of fluvoxamine. Meanwhile, the genes encoding these isoenzymes have a high level of polymorphism, which may affect the protein synthesis.

Objective

The primary objective of our study was to investigate the effects of CYP2D6 genetic polymorphisms on the efficacy and safety of fluvoxamine in patients with depressive disorder and comorbid alcohol use disorder, in order to develop the algorithms of optimization of fluvoxamine therapy for reducing the risk of dose-dependent undesirable side effects and pharmacoresistance.

Methods

The study involved 45 male patients (average age: 36.44±9.96 years) with depressive disorder and comorbid alcohol use disorder. A series of psychometric scales was used in the research. Genotyping of CYP2D6 (1846G>A) was performed using real-time polymerase chain reaction.

Results

According to results of Mann–Whitney U-test, statistically significant differences between the efficacy and safety of fluvoxamine were obtained on 9th and 16th days of therapy in patients with GG and GA genotypes (The Hamilton Rating Scale for Depression: 10.0 [10.0; 23.0] vs 25.0 [24.0; 16.0] (P<0.001) on the 9th day and 4.0 [2.0; 5.0] vs 6.0 [6.0; 7.0] on the 16th day; The UKU Side Effect Rating Scale: 6.0 [4.0; 6.0] vs 9.0 [9.0; 10.0] (P<0.001) on the 9th day and 5.0 [1.0; 9.0] vs 19.0 [18.0; 22.0] on the 16th day).

Conclusion

This study demonstrated the lower efficacy and safety of fluvoxamine in patients with depressive disorder and comorbid alcohol use disorders with GA genotype in CYP2D6 1846G>A polymorphic marker.

Pharmacogenetic landscape of Metabolic Syndrome components drug response in Tunisia and comparison with worldwide populations

Genetic variation is an important determinant affecting either drug response or susceptibility to adverse drug reactions. Several studies have highlighted the importance of ethnicity in influencing drug response variability that should be considered during drug development. Our objective is to characterize the genetic variability of some pharmacogenes involved in the response to drugs used for the treatment of Metabolic Syndrome (MetS) in Tunisia and to compare our results to the worldwide populations. A set of 135 Tunisians was genotyped using the Affymetrix Chip 6.0 genotyping array. Variants located in 24 Very Important Pharmacogenes (VIP) involved in MetS drug response were extracted from the genotyping data. Analysis of variant distribution in Tunisian population compared to 20 worldwide populations publicly available was performed using R software packages. Common variants between Tunisians and the 20 investigated populations were extracted from genotyping data. Multidimensional screening showed that Tunisian population is clustered with North African and European populations. The greatest divergence was observed with the African and Asian population. In addition, we performed Inter-ethnic comparison based on the genotype frequencies of five VIP biomarkers. The genotype frequencies of the biomarkers rs3846662, rs1045642, rs7294 and rs12255372 located respectively in HMGCR, ABCB1, VKORC1 and TCF7L2 are similar between Tunisian, Tuscan (TSI) and European (CEU). The genotype frequency of the variant rs776746 located in CYP3A5 gene is similar between Tunisian and African populations and different from CEU and TSI. The present study shows that the genetic make up of the Tunisian population is relatively complex in regard to pharmacogenes and reflects previous historical events. It is important to consider this ethnic difference in drug prescription in order to optimize drug response to avoid serious adverse drug reactions. Taking into account similarities with other neighboring populations, our study has an impact not only on the Tunisian population but also on North African population which are underrepresented in pharmacogenomic studies.

Seizure Induced by a Therapeutic Dose of Venlafaxine ER: A Case Report

Venlafaxine is a selective serotonin and norepinephrine reuptake inhibitor commonly used for the treatment of depression. Although listed as an adverse reaction, seizure activity associated with a therapeutic dose of venlafaxine has rarely been documented. A review of the literature reveals only 2 cases of venlafaxine-induced seizures, both of which were generalized tonic-clonic seizures in patients on doses at the higher end of the therapeutic range. We report the case of a 44-year-old woman undergoing antituberculosis therapy who suffered complex partial seizures after ingestion of a low therapeutic dose of venlafaxine extended release (ER). Her first seizure was observed soon after venlafaxine ER was titrated from 37.5 to 75 mg daily, with a total of 9 witnessed complex partial seizures. After titrating the dose of the venlafaxine ER back down to 37.5 mg daily and beginning lamotrigine anticonvulsant therapy, the patient exhibited no further seizures. The development of seizure activity under therapeutic dosing of venlafaxine should be brought to the attention of the health care prescriber. The potential for drug-drug interactions involving venlafazine, particularly in combination with multiple drugs, such as isoniazid and levofloxacin, needs to be recognized.

Impact of CYP2D6 on venlafaxine metabolism in Trinidadian patients with major depressive disorder

AIM

This study aimed to assess the impact of CYP2D6 and CYP2C19 variation on venlafaxine (VEN) at steady state in patients from Trinidad and Tobago of Indian and African descent with major depressive disorder.

PATIENTS & METHODS

Patients were phenotyped with dextromethorphan, genotyped for CYP2D6 and CYP2C19, and metabolic ratios for VEN obtained at 2-week intervals.

RESULTS

Of 61 patients, 55 were genotyped and phenotyped and 47 completed 8 weeks of VEN treatment. The majority of patients had metabolic ratios for VEN that were consistent with those for dextromethorphan and genotype-predicted phenotype using activity scores. One subject presented with a novel no-function allele, CYP2D6*99. No correlations were observed with CYP2C19 genotype.

CONCLUSION

CYP2D6 genotype analysis provides valuable information to individualize drug therapy with VEN.

Exploring venlafaxine pharmacokinetic variability with a phenotyping approach, a multicentric french-swiss study (MARVEL study)

Background

It is well known that the standard doses of a given drug may not have equivalent effects in all patients. To date, the management of depression remains mainly empirical and often poorly evaluated. The development of a personalized medicine in psychiatry may reduce treatment failure, intolerance or resistance, and hence the burden and costs of mood depressive disorders.

The Geneva Cocktail Phenotypic approach presents several advantages including the “in vivo” measure of different cytochromes and transporter P-gp activities, their simultaneous determination in a single test, avoiding the influence of variability over time on phenotyping results, the administration of low dose substrates, a limited sampling strategy with an analytical method developed on DBS analysis.

The goal of this project is to explore the relationship between the activity of drug-metabolizing enzymes (DME), assessed by a phenotypic approach, and the concentrations of Venlafaxine (VLX) + O-demethyl-venlafaxine (ODV), the efficacy and tolerance of VLX.

Methods/design

This study is a multicentre prospective non-randomized open trial. Eligible patients present a major depressive episode, MADRS over or equal to 20, treatment with VLX regardless of the dose during at least 4 weeks. The Phenotype Visit includes VLX and ODV concentration measurement.

Following the oral absorption of low doses of omeprazole, midazolam, dextromethorphan, and fexofenadine, drug metabolizing enzymes activity is assessed by specific metabolite/probe concentration ratios from a sample taken 2 h after cocktail administration for CYP2C19, CYP3A4, CYP2D6; and by the determination of the limited area under the curve from the capillary blood samples taken 2–3 and 6 h after cocktail administration for CYP2C19 and P-gp.

Two follow-up visits will take place between 25 and 40 days and 50–70 days after inclusion. They include assessment of efficacy, tolerance and observance.

Eleven french centres are involved in recruitment, expected to be completed within approximately 2 years with 205 patients. Metabolic ratios are determined in Geneva, Switzerland.

Discussion

By showing an association between drug metabolism and VLX concentrations, efficacy and tolerance, there is a hope that testing drug metabolism pathways with a phenotypical approach would help physicians in selecting and dosing antidepressants. The MARVEL study will provide an important contribution to increasing the knowledge of VLX variability and in optimizing the use of methods of personalized therapy in psychiatric settings.

Trial registration

ClinicalTrials.govNCT02590185 (10/27/2015). This study is currently recruiting participants.

Impact of New Genomic Technologies on Understanding Adverse Drug Reactions

It is well established that variations in genes can alter the pharmacokinetic and pharmacodynamic profile of a drug and immunological responses to it. Early advances in pharmacogenetics were made with traditional genetic techniques such as functional cloning of genes using knowledge gained from purified proteins, and candidate gene analysis. Over the past decade, techniques for analysing the human genome have accelerated greatly as knowledge and technological capabilities have grown. These techniques were initially focussed on understanding genetic factors of disease, but increasingly they are helping to clarify the genetic basis of variable drug responses and adverse drug reactions (ADRs). We examine genetic methods that have been applied to the understanding of ADRs, review the current state of knowledge of genetic factors that influence ADR development, and discuss how the application of genome-wide association studies and next-generation sequencing approaches is supporting and extending existing knowledge of pharmacogenetic processes leading to ADRs. Such approaches have identified single genes that are major contributing genetic risk factors for an ADR, (such as flucloxacillin and drug-induced liver disease), making pre-treatment testing a possibility. They have contributed to the identification of multiple genetic determinants of a single ADR, some involving both pharmacologic and immunological processes (such as phenytoin and severe cutaneous adverse reactions). They have indicated that rare genetic variants, often not previously reported, are likely to have more influence on the phenotype than common variants that have been traditionally tested for. The problem of genotype/phenotype discordance affecting the interpretation of pharmacogenetic screening and the future of genome-based testing applied to ADRs are also discussed.

Body mass index (BMI) but not body weight is associated with changes in the metabolism of risperidone; A pharmacokinetics-based hypothesis

OBJECTIVE

We sought to unravel the influence of body weight and body mass index (BMI), both consistently reported as pharmacokinetic relevant parameters, on metabolism of risperidone in a naturalistic sample.

METHODS

Conducting non parametrical tests we sought for correlations between plasma concentrations of RIS, 9-OH-RIS and AM and body weight and BMI in patients out of a therapeutic drug monitoring (TDM) database. Further, we stratified patients to three groups based upon BMI values and compared drug concentrations between groups.

RESULTS

Although body weight failed to correlate with pharmacokinetic parameters, BMI was positively correlated with plasma concentrations of the active metabolite (9-OH-RIS) (r_s=0.121, p=0.002) and active moiety (sum of RIS+9-OH-RIS) (r_s=0.128, p=0.001) as well as dose adjusted plasma concentrations of the active moiety (r_s=0.08, p=0.04). The comparison of pharmacokinetic parameters between different BMI groups yielded lower plasma concentrations of 9-OH-RIS in patients with low BMI (<20kg/m²) and higher plasma concentrations of the active moiety in obese patients (BMI ≥30kg/m²) when compared with the control group (30>BMI≥20kg/m²). By comparing low vs. high BMI patients, the latter group showed higher 9-OH-RIS plasma concentrations.

CONCLUSIONS AND LIMITATIONS

Considerable alterations in metabolism of risperidone were detected when comparing obese and cachectic patients with the control group in alignment with the positive correlation between BMI values and plasma concentrations of the active metabolite and active moiety as well as dose adjusted plasma concentrations of the active moiety. We suggest changes in CYP2D6 or CYP3A4 activity or differences in P-glycoprotein function in obese patients with greater BMI as a plausible mechanism underlying these alterations.

Personalizing supportive care in oncology patients using pharmacogenetic-driven treatment pathways

Cancer patients frequently suffer from disease- and treatment-related pain, nausea and depression, which severely reduces patients' quality of life. It is critical that clinicians are aware of drug-gene interactions and recognize the utility of applying pharmacogenetic information to personalize and improve supportive care. Pharmacogenetic-based algorithms may enhance clinical outcomes by allowing the clinician to select the 'least genetically vulnerable' drug. This review summarizes clinically relevant drug-gene interactions and presents pharmacogenetic-driven treatment pathways for depression, nausea/vomiting and pain. Ideally, this review provides a resource for clinicians to consult when selecting pharmacotherapy for a patient who presents with limited pharmacogenetic test results, with the hope of better controlling burdensome symptoms and improving the quality of life for cancer patients.

Comparison of genetic variation in drug ADME-related genes in Thais with Caucasian, African and Asian HapMap populations

The objectives of this study are to investigate allele frequencies of drug absorption, distribution, metabolism and elimination (ADME)-related genes in the Thai population and to compare these genes to HapMap populations including Caucasians (CEU), Africans (YRI) and Asians (CHB/JPT). Genetic variations of drug ADME-related genes in 190 Thais were investigated using drug metabolizing enzymes and transporters (DMET) plus genotyping system. We examined 1936 single nucleotide polymorphisms (SNPs) of 225 genes that have documented functional and clinical significances in phase I and phase II drug metabolism enzymes, drug transporters and other genes involved in ADME processes. Distributions of genotyping data from Thai were compared with other HapMap populations including Caucasian, African and Asian populations. The analysis demonstrated 43 SNPs with statistical significance comparing among five populations. However, only 26 SNPs showed statistical significance in pair-wise comparisons between Thai versus CEU and Thai versus CHB/JPT. These 26 SNPs belong to 13 groups of drug ADME-related genes which are CYP2A6, CYP3A5, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, VKORC1, COMT, NAT2, TPMT, UGT1A1 and SLCO1B1. These genes demonstrated clinical significances as previously observed in many studies. The results could explain clinical variability in pharmacokinetics and pharmacodynamics of drugs in Thais based on genetic variations in drug ADME-related gene emphasized in this article.

Insomnia and somnolence associated with second-generation antidepressants during the treatment of major depression: a meta-analysis

BACKGROUND

Sleep reduction or enhancement is frequently observed with second-generation antidepressant treatments, and they can be beneficial or harmful depending on the symptom profile of each subject. Nevertheless, relatively little attention has been given so far to rank those effects across compounds. The aim of this meta-analysis is to provide quantitative data about short-term rates of insomnia and somnolence associated with 14 second-generation antidepressants during the treatment of major depression.

METHODS

A literature search and a search of unpublished documents were performed. Eligible studies focusing on MD patients treated with second-generation antidepressants were entered in the analysis. Our primary outcome measures were insomnia and somnolence rates induced by antidepressants as compared with those associated with placebo. Sensitivity analyses were carried out as well.

RESULTS

Ten second-generation antidepressants showed higher rates of insomnia than placebo. The highest incidence was found for bupropion and desvenlafaxine. Agomelatine was the only antidepressant with a lower likelihood of inducing insomnia than placebo. Eleven antidepressants were associated with higher rates of somnolence than placebo. Fluvoxamine and mirtazapine showed the highest frequency of somnolence. Bupropion induced somnolence to a lower extent than placebo. Sensitivity analyses showed a degree of variation of those findings.

DISCUSSION

Antidepressants are associated with different insomnia and somnolence rates, mainly depending on their mechanisms of action. Despite some limitations, we underscore that the treatment-emergent insomnia and/or somnolence are frequent, and they could be used in clinical practice to face the specific needs of each patient.

Venlafaxine pharmacokinetics focused on drug metabolism and potential biomarkers

Venlafaxine (VEN) is one of the safest and most effective drugs used in the treatment of selective serotonin reuptake inhibitors-resistant depression, and thereby it is nowadays one of the most commonly prescribed antidepressants. Nevertheless, patients treated with antidepressant drugs including VEN have exhibited large inter-individual variability in drug outcomes, possibly due to the influence of genetic and nongenetic factors on the drug pharmacokinetics and/or pharmacodynamics. Among them, an increased interest has emerged over the last few years on the genetic and/or phenotypic profile for drug-metabolizing cytochrome P450 isoenzymes and drug transporters such as potential predictive pharmacokinetic-based biomarkers of the variability found in drug biodisposition and antidepressant response. The integration of some of these key therapeutic biomarkers with classic therapeutic drug monitoring constitutes a promising way to individualization of VEN's pharmacotherapy, offering to clinicians the ability to better predict and manage pharmacological treatments to maximize the drug effectiveness. Thus, this review provides an extensive discussion of the pharmacokinetics of VEN focusing in particular on metabolism issues, without forgetting the clinically relevant sources of pharmacokinetics variability (mainly the genetic sources) and aiming on the identification of phenotypic and/or genetic biomarkers for therapy optimization.

Clinical drug-drug interactions: focus on venlafaxine

Venlafaxine (VEN) is an antidepressant agent widely used nowadays as an alternative to selective serotonin reuptake inhibitors (SSRIs), particularly for the treatment of SSRI-resistant depression. As the co-administration of antidepressant drugs with other medications is very common in clinical practice, the potential risk for pharmacokinetic and/or pharmacodynamic drug interactions that may be clinically meaningful increases. Bearing in mind that VEN has exhibited large variability in antidepressant response, besides the individual genetic background, several other factors may contribute to those variable clinical outcomes, such as the occurrence of significant drug-drug interactions. Indeed, the presence of drug interactions is possibly one of the major reasons for interindividual variability, and their anticipation should be considered in conjugation with other specific patients' characteristics to optimize the antidepressant therapy. Hence, a comprehensive overview of the pharmacokinetic- and pharmacodynamic-based drug interactions involving VEN is herein provided, particularly addressing their clinical relevance.

SLC6A2 variants may predict remission from major depression after venlafaxine treatment in Han Chinese population

OBJECTIVE

Venlafaxine, an antidepressant of the serotonin-norepinephrine reuptake inhibitor (SNRI) type, is used to treat patients with major depressive disorder (MDD). Much evidence suggests that genetic polymorphisms may modulate serotonergic and noradrenergic function, thereby affecting the treatment efficacy of venlafaxine. The aim of this study was to examine whether polymorphisms in the norepinephrine transporter gene (SLC6A2) associate with remission after venlafaxine treatment for MDD.

METHOD

An 8-week naturalistic treatment study with venlafaxine was carried out in 243 Han Chinese patients with MDD. The patients were screened for seven single-nucleotide polymorphisms of the SLC6A2 gene. Of the enrolled patients, 161 completed the 8-week treatment. The 21-item Hamilton Depression Rating Scale (HDRS) was used to assess the improvement of depressive symptoms in each subject from baseline to the endpoint. For better presentation of time-course change of remission status, a Cox regression analysis for remission incidence during the 8-week treatment was conducted.

RESULTS

Between remitters and non-remitters, significant differences in genotype frequencies were observed in five of the investigated SLC6A2 variants (rs28386840, rs1532701, rs40434, rs13333066, rs187714). GCG haplotype (rs40434 - rs13333066 - rs187714) in the SLC6A2 gene showed a association with non-remission. A Cox regression analysis for remission incidence during the 8-week treatment course significantly depends on SLC6A2 variants (rs28386840, rs40434, and rs187714).

CONCLUSION

Our results suggest that the variation of the SLC6A2 gene is associated with treatment remission after venlafaxine in patients with MDD.

Accelerated hypertension after venlafaxine usage

Venlafaxine is the first antidepressant that acts via inhibiting serotonin and noradrenaline reuptake. Hypertension is observed in doses exceeding 300 mg/day and is the most feared complication. We report a patient with accelerated hypertension after venlafaxine use observed at a dose of 150 mg/day. A 23-year-old patient with symptoms of insomnia, depression, anhedonia, fatigue admitted our clinic. Venlafaxine at a dose of 75 mg/day was initiated after he was diagnosed with major depressive disorder. After 5 months, venlafaxine dose was uptitrated to 150 mg/day due to inadequate response to drug. After using venlafaxine for ten months at the dose of 150 mg/day, he admitted our clinic with headache and epistaxis. He was hospitalized after his blood pressure was measured as 210/170 mmHg. No secondary causes for hypertension were found, and venlafaxine treatment was considered possible etiologic factor. After stopping venlafaxine treatment, his blood pressure was reverted back to normal limits. While mild elevation of blood pressure could be observed after venlafaxine treatment, this case shows that accelerated hypertension with a diastolic blood pressure rise above 120 mmHg could be observed at relatively low doses of venlafaxine. Close monitoring of blood pressure is necessary after initiation of treatment, as accelerated hypertension could cause endorgan damage with potentially catastrophic results.

Interaction of valproic acid and the antidepressant drugs doxepin and venlafaxine: analysis of therapeutic drug monitoring data under naturalistic conditions

Valproic acid and the antidepressants doxepin and venlafaxine are frequently used psychotropic drugs. In the literature, an influence of valproic acid on serum levels of antidepressants has been described, although studies have focused on amitriptyline. The authors assessed their therapeutic drug monitoring (TDM) database for patients receiving a combination of doxepin or venlafaxine and valproic acid and compared these samples with matched controls without valproic acid comedication in terms of the serum concentration of antidepressants. The mean dose-corrected serum concentration of doxepin+N-doxepin in 16 patients who received valproic acid comedication was higher (2.171±1.482 ng/ml/mg) than that in the matched controls (0.971±0.857 ng/ml/mg, P<0.003). We also found a significant correlation between valproic acid serum level and dose-corrected doxepin+N-doxepin serum level (Spearman's ρ r=0.602, P<0.014). The mean dose-corrected serum level of venlafaxine+O-desmethylvenlafaxine in 41 patients who received valproic acid comedication did not differ significantly from that of the matched controls (P<0.089), but there was a significant difference between both groups in the dose-corrected serum level of O-desmethylvenlafaxine (1.403±0.665 vs. 1.102±0.444, P<0.017). As a consequence, if a combination of valproic acid with doxepin or venlafaxine is administered, cautious dosing is advisable and TDM should be performed.

Clinical validity of cytochrome P450 metabolism and serotonin gene variants in psychiatric pharmacotherapy

Adverse events, response failures and medication non-compliance are common in patients receiving medications for the treatment of mental illnesses. A systematic literature review assessed whether pharmacokinetic (PK) or pharmacodynamic (PD) responses to 26 commonly prescribed antipsychotic and antidepressant medications, including efficacy or side effects, are associated with nucleotide polymorphisms in eight commonly studied genes in psychiatric pharmacotherapy: CYP2D6, CYP2C19, CYP2C9, CYP1A2, CYP3A4, HTR2C, HTR2A, and SLC6A4. Of the 294 publications included in this review, 168 (57%) showed significant associations between gene variants and PK or PD outcomes. Other studies that showed no association often had insufficient control for confounding variables, such as co-medication use, or analysis of medications not substrates of the target gene. The strongest gene-outcome associations were for the PK profiles of CYP2C19 and CYP2D6 (93% and 90%, respectively), for the PD associations between HTR2C and weight gain (57%), and for SLC6A4 and clinical response (54%), with stronger SLC6A4 response associations for specific drug classes (60-83%). The preponderance of evidence supports the validity of analyzing nucleotide polymorphisms in CYP and pharmacodynamic genes to predict the metabolism, safety, or therapeutic efficacy of psychotropic medications commonly used for the treatment of depression, schizophrenia, and bipolar illness.

Towards the implementation of CYP2D6 and CYP2C19 genotypes in clinical practice: update and report from a pharmacogenetic service clinic

Genetic testing may help to improve treatment outcomes in order to avoid non-response or severe side effects to psychotropic medication. Most robust data have been obtained for gene variants in CYP2D6 and CYP2C19 enzymes for antipsychotics and antidepressant treatment. We reviewed original articles indexed in PubMed from 2008-2013 on CYP2D6 and CYP2C19 gene variants and treatment outcome to antidepressant or antipsychotic medication. We have started providing CYP2D6 and CYP2C19 genotype information to physicians and conducted a survey where preliminary results are reported. Studies provided mixed results regarding the impact of CYP2D6 and CYP2C19 gene variation on treatment response. Plasma levels were mostly found associated with CYP metabolizer status. Higher occurrence/severity of side effects were reported in non-extensive CYP2D6 or CYP2C19 metabolizers. Results showed that providing genotypic information is feasible and generally well accepted by both patients and physicians. Although currently available studies are limited by small sample sizes and infrequent plasma drug level assessment, research to date indicates that CYP2D6 and CYP2C19 testing may be beneficial particularly for non-extensive metabolizing patients. In summary, clinical assessment of CYP2D6 and CYP2C19 metabolizer status is feasible, well accepted and optimizes drug treatment in psychiatry.