Serum concentrations of sertraline and N-desmethyl sertraline in relation to CYP2C19 genotype in psychiatric patients

Trajectory and magnitude of response in adults with anxiety disorders: a Bayesian hierarchical modeling meta-analysis of selective serotonin reuptake inhibitors, serotonin norepinephrine reuptake inhibitors, and benzodiazepines

BACKGROUND

How the trajectory of response to medication (and placebo response) varies among selective serotonin reuptake inhibitors (SSRIs), serotonin norepinephrine reuptake inhibitors (SNRIs), benzodiazepines and across anxiety disorders is unknown.

METHODS

We performed a meta-analysis using weekly symptom severity data from randomized, parallel-group, placebo-controlled trials of SSRIs, SNRIs, and benzodiazepines in adults with anxiety disorders. Response was modeled for the standardized change in anxiety using Bayesian hierarchical models.

RESULTS

Across 122 trials (N=15,760), SSRIs, SNRIs, and benzodiazepines produced significant improvement in anxiety compared to placebo. Benzodiazepines produced faster improvement by the first week of treatment (p < 0.001). By week 8, the response for benzodiazepines and SSRIs (p = 0.103) and SNRIs (p = 0.911) did not differ nor did SSRIs and SNRIs differ (p = 0.057), although for patients with generalized anxiety disorder (GAD), the benzodiazepines produced greater improvement than SNRIs at week 8 (difference - 12.42, CrI: -25.05 to -0.78, p = 0.037). Medication response was similar across anxiety disorders except for benzodiazepines, which produced greater improvement over the first 4 weeks compared to SSRIs and SNRIs in panic disorder. For SSRIs and SNRIs, women improved more than men, and for benzodiazepines, older patients improved more compared to younger patients. Finally, placebo response plateaued by week 4 of treatment, and, at week 8, social anxiety disorder trials had lower placebo response compared to other anxiety disorders.

CONCLUSIONS

Benzodiazepines show early improvement compared to SSRIs and SNRIs. However, by week 8, all treatments yield similar results. Patient characteristics influence the improvement trajectory and magnitude, suggesting potential for personalized medication selection.

Population pharmacokinetic approach to guide personalized sertraline treatment in Chinese patients

Object: Sertraline is a first-line SSRI for the treatment of depression and has the same effectiveness along with a superior safety profile compared to other medications. There are few population pharmacokinetic (PPK) studies of sertraline and a lack of studies in the Chinese population. Therefore, we performed a PPK analysis of Chinese patients treated with sertraline to identify factors that can influence drug exposure. In addition, the dosing and discontinuation regimen of sertraline when applied to adolescents was explored. Methods: Sertraline serum drug concentration data were collected from 140 hospitalized patients to generate a sertraline PPK dataset, and data evaluation and examination of the effects of covariates on drug exposure in the final model were performed using nonlinear mixed-effects models (NONMEM) and first-order conditional estimation with interaction (FOCE-I). Examining rational medication administration and rational withdrawal of sertraline based on significant covariates and final modeling. Results: A one-compartment model with first-order absorption and elimination of sertraline was developed for Chinese patients with psychiatric disorders. Analysis of covariates revealed that age was a covariate that significantly affected sertraline CL/F (P < 0.01) and that sertraline clearance decreased progressively with aging, whereas other factors had no effect on CL/F and V/F of sertraline. In the age range of 11-79, there were 54 adolescent patients (about 1/3) aged 13-18 years, and the safe and effective optimal daily dose for adolescent patients based on the final model simulations was 50-250 mg/d. For adolescent patients, serum concentration fluctuations were moderate for OD doses of 50 mg and 100 mg, using a fixed dose-descent regimen. For patients with OD doses of 150-200 mg and BID doses of 100-200 mg, a more gradual decrease in serum concentration was achieved with a fixed dose interval of 7 or 14 days for 25 mg as the regimen of descent. Conclusions: To our knowledge, this may be the first PPK study of sertraline in Chinese patients. We found that age was an important factor affecting clearance in Chinese patients taking sertraline. Patients taking sertraline may be exposed to increased amounts of sertraline due to decreased clearance with increasing age. The rational dosing and safe discontinuation of sertraline in adolescent patients can be appropriately referenced to the results of the model simulation, thus providing assistance for individualized dosing in adolescents.

Escitalopram and Sertraline Population Pharmacokinetic Analysis in Pediatric Patients

BACKGROUND AND OBJECTIVE

Escitalopram and sertraline are commonly prescribed for anxiety and depressive disorders in children and adolescents. The pharmacokinetics (PK) of these medications have been evaluated in adults and demonstrate extensive variability, but studies in pediatric patients are limited. Therefore, we performed a population PK analysis for escitalopram and sertraline in children and adolescents to characterize the effects of demographic, clinical, and pharmacogenetic factors on drug exposure.

METHODS

A PK dataset was generated by extracting data from the electronic health record and opportunistic sampling of escitalopram- and sertraline-treated psychiatrically hospitalized pediatric patients aged 5-18 years. A population PK analysis of escitalopram and sertraline was performed using NONMEM. Concentration-time profiles were simulated using MwPharm++ to evaluate how covariates included in the final models influence medication exposure and compared to adult therapeutic reference ranges.

RESULTS

The final escitalopram cohort consisted of 315 samples from 288 patients, and the sertraline cohort consisted of 265 samples from 255 patients. A one-compartment model with a proportional residual error model best described the data for both medications. For escitalopram, CYP2C19 phenotype and concomitant CYP2C19 inhibitors affected apparent clearance (CL/F), and normalizing CL/F and apparent volume of distribution (V/F) to body surface area (BSA) improved estimations. The final escitalopram model estimated CL/F and V/F at 14.2 L/h/1.73 m2 and 428 L/1.73 m2, respectively. For sertraline, CYP2C19 phenotype and concomitant CYP2C19 inhibitors influenced CL/F, and empirical allometric scaling of patient body weight on CL/F and V/F was significant. The final sertraline model estimated CL/F and V/F at 124 L/h/70 kg and 4320 L/70 kg, respectively. Normalized trough concentrations (Ctrough) for CYP2C19 poor metabolizers taking escitalopram were 3.98-fold higher compared to normal metabolizers (151.1 ng/mL vs 38.0 ng/mL, p < 0.0001), and normalized Ctrough for CYP2C19 poor metabolizers taking sertraline were 3.23-fold higher compared to normal, rapid, and ultrarapid metabolizers combined (121.7 ng/mL vs 37.68 ng/mL, p < 0.0001). Escitalopram- and sertraline-treated poor metabolizers may benefit from a dose reduction of 50-75% and 25-50%, respectively, to normalize exposure to other phenotypes.

CONCLUSION

To our knowledge, this is the largest population PK analysis of escitalopram and sertraline in pediatric patients. Significant PK variability for both medications was observed and was largely explained by CYP2C19 phenotype. Slower CYP2C19 metabolizers taking escitalopram or sertraline may benefit from dose reductions given increased exposure.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A Genotypes and Serotonin Reuptake Inhibitor Antidepressants

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI-like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin-2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing.

Pharmacogenomics in allogeneic hematopoietic stem cell transplantation: Implications on supportive therapies and conditioning regimens

Allogeneic hematopoietic stem cell transplantation mortality has declined over the years, though prevention and management of treatment-related toxicities and post-transplant complications remains challenging. Applications of pharmacogenomic testing can potentially mitigate adverse drug outcomes due to interindividual variability in drug metabolism and response. This review summarizes clinical pharmacogenomic applications relevant to hematopoietic stem cell transplantation, including antifungals, immunosuppressants, and supportive care management, as well as emerging pharmacogenomic evidence with conditioning regimens.

Effect of CYP2C19 polymorphisms on antidepressant prescription patterns and treatment emergent mania in bipolar disorder

Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005-2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04-1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05-2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.

Precision Medicine in Antidepressants Treatment

Precision medicine uses innovative approaches to improve disease prevention and treatment outcomes by taking into account people's genetic backgrounds, environments, and lifestyles. Treatment of depression is particularly challenging, given that 30-50% of patients do not respond adequately to antidepressants, while those who respond may experience unpleasant adverse drug reactions (ADRs) that decrease their quality of life and compliance. This chapter aims to present the available scientific data that focus on the impact of genetic variants on the efficacy and toxicity of antidepressants. We compiled data from candidate gene and genome-wide association studies that investigated associations between pharmacodynamic and pharmacokinetic genes and response to antidepressants regarding symptom improvement and ADRs. We also summarized the existing pharmacogenetic-based treatment guidelines for antidepressants, used to guide the selection of the right antidepressant and its dose based on the patient's genetic profile, aiming to achieve maximum efficacy and minimum toxicity. Finally, we reviewed the clinical implementation of pharmacogenomics studies focusing on patients on antidepressants. The available data demonstrate that precision medicine can increase the efficacy of antidepressants and reduce the occurrence of ADRs and ultimately improve patients' quality of life.

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.

Pediatric considerations for pharmacogenetic selective serotonin reuptake inhibitors clinical decision support

Pharmacogenetic testing for psychiatry is growing at a rapid pace, with multiple sites utilizing results to help clinical decision-making. Genotype-guided dosing and drug selection have been implemented at several sites, including Vanderbilt University Medical Center, where clinical decision support (CDS) based on pharmacogenetic results went live for selective serotonin reuptake inhibitors in 2020 for both adult and pediatric patients. Effective and appropriate implementation of CYP2D6- and CYP2C19-guided CDS for the pediatric population requires consideration of the evidence for the pharmacogenetic associations, medication indications, and appropriate alternative therapies to be used when a pharmacogenetic contraindication is identified. In this article, we review these pediatric pharmacogenetic considerations for selective serotonin reuptake inhibitor CDS. We include a case study, the current literature supporting clinical recommendations, considerations when designing pediatric CDS, future implications, and examples of sertraline, (es)citalopram, paroxetine, and fluvoxamine alerts.

Changes in Sertraline Plasma Concentrations Across Pregnancy and Postpartum

Major depressive disorder (MDD) is a common disorder in pregnancy. Although sertraline is the most frequently prescribed antidepressant for pregnant people in the United States, limited information about its pharmacokinetics in pregnancy is available. Our objectives were to characterize plasma sertraline concentration to dose (C/D) ratios across pregnancy and postpartum and investigate the effect of pharmacogenetic variability on sertraline elimination. We performed a prospective observational cohort study in people with a singleton pregnancy ≤ 18 weeks gestation and a lifetime diagnosis of MDD at the 3 Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)-funded Obstetrical-Fetal Pharmacology Research Center sites. Subjects (N = 47) were receiving maintenance sertraline therapy and chose to continue it during pregnancy. Blood samples were obtained 24-hours postdose every 4 weeks across pregnancy and twice postpartum for measurement of plasma concentrations of sertraline and desmethylsertraline. Overall mean sertraline C/D ratios were decreased at study onset and remained consistently low until after delivery. During the last 4 weeks of pregnancy the mean sertraline C/D ratio (95% confidence interval (CI)), 0.25 (95% CI, 0.19, 0.3) ng/mL/dose (mg/day), was smaller than the mean ratio at ≥ 8 weeks after delivery, 0.32 (95% CI, 0.27, 0.37) ng/mL/dose (mg/day), a 22% difference. Mean sertraline/desmethylsertraline ratios were highest after birth, which confirmed increased sertraline elimination during pregnancy. Sertraline C/D ratios in participants with functional CYP2C19 activity did not change significantly during pregnancy, whereas ratios in participants with poor or intermediate CYP2C19 activity decreased by 51%. Exploratory pharmacogenomic analysis indicated that pregnant people with poor or intermediate CYP2C19 activity are at risk for subtherapeutic sertraline concentrations during pregnancy.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2C19 and CYP2D6 and SSRIs

The Dutch Pharmacogenetics Working Group (DPWG) guideline presented here, presents the gene-drug interaction between the genes CYP2C19 and CYP2D6 and antidepressants of the selective serotonin reuptake inhibitor type (SSRIs). Both genes' genotypes are translated into predicted normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), or ultra-rapid metabolizer (UM). Evidence-based dose recommendations were obtained, based on a structured analysis of published literature. In CYP2C19 PM patients, escitalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 75% of the normal maximum dose. Escitalopram should be avoided in UM patients. In CYP2C19 PM patients, citalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 70% (65-75%) of the normal maximum dose. In contrast to escitalopram, no action is needed for CYP2C19 UM patients. In CYP2C19 PM patients, sertraline dose should not exceed 37.5% of the normal maximum dose. No action is needed for CYP2C19 IM and UM patients. In CYP2D6 UM patients, paroxetine should be avoided. No action is needed for CYP2D6 PM and IM patients. In addition, no action is needed for the other gene-drug combinations. Clinical effects (increase in adverse events or decrease in efficacy) were lacking for these other gene-drug combinations. DPWG classifies CYP2C19 genotyping before the start of escitalopram, citalopram, and sertraline, and CYP2D6 genotyping before the start of paroxetine as "potentially beneficial" for toxicity/effectivity predictions. This indicates that genotyping prior to treatment can be considered on an individual patient basis.

Sertraline dosing trends in children and adolescents stratified by CYP2C19 genotype

Aim: Sertraline is a CYP2C19 substrate commonly prescribed to children with anxiety. Materials & methods: This medical record review examined dosing trends and treatment discontinuation in children prescribed sertraline with documented CYP2C19 genotypes. Variables collected included age, weight, diagnosis, concomitant medications, initial sertraline dose, dose changes and CYP2C19 genotypes. Results: A total of 90 individuals (average age: 10.5 years; 40% female) were included. Nearly 80% were prescribed sertraline for anxiety. Initial weight-adjusted doses were similar, but mean weight-adjusted doses of sertraline were 65% higher in increased metabolizers (1.5 mg/kg/day) compared with normal metabolizers (0.91 mg/kg/day; p = 0.067) at the second dose change. Conclusion: While all children started at a similar sertraline dose, different trends in prescribed doses were observed across CYP2C19 genotypes at subsequent dose changes.

The Influence of CYP2D6 and CYP2C19 Genetic Variation on Diabetes Mellitus Risk in People Taking Antidepressants and Antipsychotics

CYP2D6 and CYP2C19 enzymes are essential in the metabolism of antidepressants and antipsychotics. Genetic variation in these genes may increase risk of adverse drug reactions. Antidepressants and antipsychotics have previously been associated with risk of diabetes. We examined whether individual genetic differences in CYP2D6 and CYP2C19 contribute to these effects. We identified 31,579 individuals taking antidepressants and 2699 taking antipsychotics within UK Biobank. Participants were classified as poor, intermediate, or normal metabolizers of CYP2D6, and as poor, intermediate, normal, rapid, or ultra-rapid metabolizers of CYP2C19. Risk of diabetes mellitus represented by HbA1c level was examined in relation to the metabolic phenotypes. CYP2D6 poor metabolizers taking paroxetine had higher Hb1Ac than normal metabolizers (mean difference: 2.29 mmol/mol; p < 0.001). Among participants with diabetes who were taking venlafaxine, CYP2D6 poor metabolizers had higher HbA1c levels compared to normal metabolizers (mean differences: 10.15 mmol/mol; p < 0.001. Among participants with diabetes who were taking fluoxetine, CYP2D6 intermediate metabolizers and decreased HbA1c, compared to normal metabolizers (mean difference -7.74 mmol/mol; p = 0.017). We did not observe any relationship between CYP2D6 or CYP2C19 metabolic status and HbA1c levels in participants taking antipsychotic medication. Our results indicate that the impact of genetic variation in CYP2D6 differs depending on diabetes status. Although our findings support existing clinical guidelines, further research is essential to inform pharmacogenetic testing for people taking antidepressants and antipsychotics.

Citalopram and Cannabidiol: In Vitro and In Vivo Evidence of Pharmacokinetic Interactions Relevant to the Treatment of Anxiety Disorders in Young People

BACKGROUND

Cannabidiol (CBD), a major nonintoxicating constituent of cannabis, exhibits anxiolytic properties in preclinical and human studies and is of interest as a novel intervention for treating anxiety disorders. Existing first-line pharmacotherapies for these disorders include selective serotonin reuptake inhibitor and other antidepressants. Cannabidiol has well-described inhibitory action on cytochrome P450 (CYP450) drug-metabolizing enzymes and significant drug-drug interactions (DDIs) between CBD and various anticonvulsant medications (eg, clobazam) have been described in the treatment of epilepsy. Here, we examined the likelihood of DDIs when CBD is added to medications prescribed in the treatment of anxiety.

METHODS

The effect of CBD on CYP450-mediated metabolism of the commonly used antidepressants fluoxetine, sertraline, citalopram, and mirtazapine were examined in vitro. Cannabidiol-citalopram interactions were also examined in vivo in patients (n = 6) with anxiety disorders on stable treatment with citalopram or escitalopram who received ascending daily doses of adjunctive CBD (200-800 mg) over 12 weeks in a recent clinical trial.

RESULTS

Cannabidiol minimally affected the metabolism of sertraline, fluoxetine, and mirtazapine in vitro. However, CBD significantly inhibited CYP3A4 and CYP2C19-mediated metabolism of citalopram and its stereoisomer escitalopram at physiologically relevant concentrations, suggesting a possible in vivo DDI. In patients on citalopram or escitalopram, the addition of CBD significantly increased citalopram plasma concentrations, although it was uncertain whether this also increased selective serotonin reuptake inhibitor-mediated adverse events.

CONCLUSIONS

Further pharmacokinetic examination of the interaction between CBD and citalopram/escitalopram is clearly warranted, and clinicians should be vigilant around the possibility of treatment-emergent adverse effects when CBD is introduced to patients taking these antidepressants.

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.

Association of CYP2C19 and CYP2D6 Poor and Intermediate Metabolizer Status With Antidepressant and Antipsychotic Exposure: A Systematic Review and Meta-analysis

IMPORTANCE

Precise estimation of the drug metabolism capacity for individual patients is crucial for adequate dose personalization.

OBJECTIVE

To quantify the difference in the antipsychotic and antidepressant exposure among patients with genetically associated CYP2C19 and CYP2D6 poor (PM), intermediate (IM), and normal (NM) metabolizers.

DATA SOURCES

PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to June 30, 2020, with no language restrictions.

STUDY SELECTION

Two independent reviewers performed study screening and assessed the following inclusion criteria: (1) appropriate CYP2C19 or CYP2D6 genotyping was performed, (2) genotype-based classification into CYP2C19 or CYP2D6 NM, IM, and PM categories was possible, and (3) 3 patients per metabolizer category were available.

DATA EXTRACTION AND SYNTHESIS

The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for extracting data and quality, validity, and risk of bias assessments. A fixed-effects model was used for pooling the effect sizes of the included studies.

MAIN OUTCOMES AND MEASURES

Drug exposure was measured as (1) dose-normalized area under the plasma level (time) curve, (2) dose-normalized steady-state plasma level, or (3) reciprocal apparent total drug clearance. The ratio of means (RoM) was calculated by dividing the mean drug exposure for PM, IM, or pooled PM plus IM categories by the mean drug exposure for the NM category.

RESULTS

Based on the data derived from 94 unique studies and 8379 unique individuals, the most profound differences were observed in the patients treated with aripiprazole (CYP2D6 PM plus IM vs NM RoM, 1.48; 95% CI, 1.41-1.57; 12 studies; 1038 patients), haloperidol lactate (CYP2D6 PM vs NM RoM, 1.68; 95% CI, 1.40-2.02; 9 studies; 423 patients), risperidone (CYP2D6 PM plus IM vs NM RoM, 1.36; 95% CI, 1.28-1.44; 23 studies; 1492 patients), escitalopram oxalate (CYP2C19 PM vs NM, RoM, 2.63; 95% CI, 2.40-2.89; 4 studies; 1262 patients), and sertraline hydrochloride (CYP2C19 IM vs NM RoM, 1.38; 95% CI, 1.27-1.51; 3 studies; 917 patients). Exposure differences were also observed for clozapine, quetiapine fumarate, amitriptyline hydrochloride, mirtazapine, nortriptyline hydrochloride, fluoxetine hydrochloride, fluvoxamine maleate, paroxetine hydrochloride, and venlafaxine hydrochloride; however, these differences were marginal, ambiguous, or based on less than 3 independent studies.

CONCLUSIONS AND RELEVANCE

In this systematic review and meta-analysis, the association between CYP2C19/CYP2D6 genotype and drug levels of several psychiatric drugs was quantified with sufficient precision as to be useful as a scientific foundation for CYP2D6/CYP2C19 genotype-based dosing recommendations.

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.

Pharmacogenetic testing in psychiatric inpatients with polypharmacy is associated with decreased medication side effects but not via medication changes

In psychiatric patients, medication adverse effects are regularly attributed to psychosomatic causes. However, many psychotropic medications are metabolized by cytochrome P450 (CYP450) enzymes. In the setting of polypharmacy, the activity of these enzymes may produce unfavorable drug-drug interactions (DDI) and drug-genotype interactions (DGI) that contribute to morbidity and mortality. This study sought to estimate the risk of adverse DDI and DGI in psychiatric inpatients with polypharmacy. We assessed whether medication changes made after pharmacogenetics (PGx) testing correlated with changes in side effects and overall improvement. Adult psychiatry inpatients with polypharmacy, defined as 5 or more scheduled prescription medications, completed the 24-item Antidepressant Side Effect Checklist (ASEC) questionnaire on enrollment and underwent PGx testing. Analysis of PGx results focused on whether the CYP2D6 and CYP2C19 phenotypes were "extreme," defined as poor, poor to intermediate, or ultrarapid. Approximately 30 days after PGx results were sent to outpatient providers, patients were contacted to obtain their current medication list and ASEC and Clinical Global Impression Improvement (CGI-I) scores. A total of 80 patients were enrolled, and 52 (65%) completed follow-up. ASEC scores improved from 11.5 (±8.1) to 7.2 (±6.0) (p = 0.0009). Mean CGI-I score was 2.7 (±1.4), between "minimal" to "much improved." However, linear regression revealed that these improvements were not correlated with whether medications were changed. We concluded that the impact of drug-genotype interactions in this small sample of inpatients with polypharmacy was low, and that patient improvement was related not to PGx-guided medication changes but to other treatments during hospitalization.

Impact of CYP2C19 genotype on sertraline exposure in 1200 Scandinavian patients

Sertraline is an (SSRI-)antidepressant metabolized by the polymorphic CYP2C19 enzyme. The aim of this study was to investigate the impact of CYP2C19 genotype on the serum concentrations of sertraline in a large patient population. Second, the proportions of patients in the various CYP2C19 genotype-defined subgroups obtaining serum concentrations outside the therapeutic range of sertraline were assessed. A total of 2190 sertraline serum concentration measurements from 1202 patients were included retrospectively from the drug monitoring database at Diakonhjemmet Hospital in Oslo. The patients were divided into CYP2C19 genotype-predicted phenotype subgroups, i.e. normal (NMs), ultra rapid (UMs), intermediate (IMs), and poor metabolisers (PMs). The differences in dose-harmonized serum concentrations of sertraline and N-desmethylsertraline-to-sertraline metabolic ratio were compared between the subgroups, with CYP2C19 NMs set as reference. The patient proportions outside the therapeutic concentration range were also compared between the subgroups with NMs defined as reference. Compared with the CYP2C19 NMs, the sertraline serum concentration was increased 1.38-fold (95% CI 1.26-1.50) and 2.68-fold (95% CI 2.16-3.31) in CYP2C19 IMs and PMs, respectively (p < 0.001), while only a marginally lower serum concentration (-10%) was observed in CYP2C19 UMs (p = 0.012). The odds ratio for having a sertraline concentration above the therapeutic reference range was 1.97 (95% CI 1.21-3.21, p = 0.064) and 8.69 (95% CI 3.88-19.19, p < 0.001) higher for IMs and PMs vs. NMs, respectively. CYP2C19 IMs and PMs obtain significantly higher serum concentrations of sertraline than NMs. Based on the relative differences in serum concentrations compared to NMs, dose reductions of 60% and 25% should be considered in PMs and IMs, respectively, to reduce the risk of sertraline overexposure in these patients.

Gene-Based Dose Optimization in Children

Pharmacogenetics is a key component of precision medicine. Genetic variation in drug metabolism enzymes can lead to variable exposure to drugs and metabolites, potentially leading to inefficacy and drug toxicity. Although the evidence for pharmacogenetic associations in children is not as extensive as for adults, there are several drugs across diverse therapeutic areas with robust pediatric data indicating important, and relatively common, drug-gene interactions. Guidelines to assist gene-based dose optimization are available for codeine, thiopurine drugs, selective serotonin reuptake inhibitors, atomoxetine, tacrolimus, and voriconazole. For each of these drugs, there is an opportunity to clinically implement precision medicine approaches with children for whom genetic test results are known or are obtained at the time of prescribing. For many more drugs that are commonly used in pediatric patients, additional investigation is needed to determine the genetic factors influencing appropriate dose.

Orexin/Hypocretin Type 2 Receptor (HCRTR2) Gene as a Candidate Gene in Sertraline-Associated Insomnia in Depressed Patients

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) are considered as first-line drugs for treating depressive disorders. Among the adverse effects reported with sertraline is sleep disturbances; however, the etiology lying beneath is obscure. Orexin, the most recently discovered neurotransmitter, is involved in the sleep cycle. It exerts its physiological actions through orexin or hypocretin type 1 and 2 receptors (HCRTR1 and HCRTR2). Dysfunction of the orexin system contributes to various psychiatric, neurologic and neuropsychiatric disorders. Thus, our study aimed to assess the possible association of genetic variation of HCRTR2 G1246A with hypersomnia reported with sertraline in a group of major depressive disorder (MDD) patients.

PATIENTS AND METHODS

Ninety-six newly diagnosed MDD patients were enrolled in our cohort study. MDD was assessed using DSM-V criteria. Insomnia Severity Index (ISI) was used to assess insomnia at baseline (week 0) and week 4. Blood samples were collected for further genotyping of HCRTR2 G1246A (rs2653349) using polymerase chain reaction-restriction fragment length polymorphism.

RESULTS

A significant association between G1264A polymorphism of HCRTR2 and insomnia was observed. Insomnia with sertraline happens by 2.5-fold (P=0.022; odds ratio (OR)=2.5; 95% confidence interval (CI): 1.1-5.7) in patients having GG genotype. Patients with G allele experience insomnia by 2.1-fold more than A allele carriers (P=0.022; OR=2.1; 95% CI= 1.1-4.0). Subgroup analysis showed a significant association between GG genotype as well as the G allele and insomnia only in female MDD patients (P=0.011; OR=4.0; 95% CI=1.3-12.0 and P=0.033; OR=2.4; 95% CI=1.02-5.7, respectively).

CONCLUSION

In conclusion, the G1246A variant might be a predictor for insomnia in MDD patients treated with sertraline. Our findings support the idea that some variants of the HCRTR might contribute to inter-individual variability in the sleep pattern of patients receiving antidepressants.

Pharmacogenetics of Sertraline Tolerability and Response in Pediatric Anxiety and Depressive Disorders

Objective: To determine whether genetic variants in a pharmacokinetic gene (the number of CYP2C19 reduced function alleles [RFAs]), and in pharmacodynamic genes (HTR2A, SLC6A4, and GRIK4) influence sertraline tolerability and response in a cohort of pediatric patients with anxiety and depressive disorders. Methods: A retrospective analysis was performed using the electronic medical record data of 352 patients <19 years of age being treated for anxiety and/or depressive disorders with sertraline and who underwent routine clinical CYP2C19 genotyping. Additional genotyping and analysis of variants in HTR2A, SLC6A4, and GRIK4 were conducted for 249 patients. Multivariate regression models testing for associations with CYP2C19 were adjusted for concomitant use of interacting medications. Combinatorial classification and regression tree (CART) analyses containing all pharmacokinetic and pharmacodynamic genes and clinical factors were performed. Results: The maximum sertraline dose during the initial titration period of sertraline was inversely associated with the number of CYP2C19 RFAs and sertraline dose at 60 (p = 0.025) and 90 days (p = 0.025). HTR2A rs6313 was associated with sertraline dose (p = 0.011) and time to the average maximum sertraline dose (p = 0.039). Regarding efficacy, the number of CYP2C19 RFAs was not associated with the sertraline dose at the time of response (p = 0.22), whereas for the pharmacodynamic genes, only HTR2A rs6313 was associated with response dose (p = 0.022). An association was observed between predicted expression levels of SLC6A4 and the duration on sertraline (p = 0.025). Combinatorial CART and multivariate regression analyses implicated that pharmacodynamic genes and clinical factors influence the maximum sertraline dose and response dose. The total number of side effects was not associated with any of the variants tested. Conclusion: Both pharmacokinetic and pharmacodynamic factors, in addition to clinical and demographic components, influence sertraline dose, response, and tolerability, thereby necessitating further research to assess for the validity of these pharmacogenetic associations in children and adolescents.

CYP2C19-Guided Escitalopram and Sertraline Dosing in Pediatric Patients: A Pharmacokinetic Modeling Study

Objective: Cytochrome P4502C19 (CYP2C19) is a highly polymorphic gene that encodes an enzyme that metabolizes escitalopram and sertraline, two selective serotonin reuptake inhibitors (SSRIs) that are FDA approved for pediatric use and commonly used to treat anxiety and depressive disorders in youth. Using pharmacokinetic (PK) models in adolescents, we sought to (1) model SSRI dosing across CYP2C19 phenotypes to compare SSRI exposure (area under curve, AUC) and maximum concentration (Cmax), (2) evaluate the impact of b.i.d. dosing (in rapid metabolizers [RM] and ultrarapid metabolizers [UM]) on SSRI exposure and Cmax, and (3) determine pharmacogenomically-informed dosing strategies to provide similar exposure across CYP2C19 phenotypes in adolescents. Methods: Using PK parameters in CYP2C19 phenotype groups and previously reported pediatric PK data for escitalopram and sertraline, we modeled exposure (AUC0-24) and Cmax and determined CYP2C19-guided dosing strategies. Results: Compared with normal CYP2C19 metabolizers treated with either escitalopram or sertraline, Cmax and AUC0-24 were higher in slower metabolizers and lower in patients with increased CYP2C19 activity, although the magnitude of these differences was more pronounced for escitalopram than for sertraline. For escitalopram, poor metabolizers (PMs) require 10 mg/day and UMs require 30 mg/day to achieve an exposure that is equivalent to 20 mg/day in a normal metabolizer (NM). For sertraline, to achieve AUC0-24 and Cmax similar to NMs receiving 150 mg/day, PMs require 100 mg/day, whereas a dose of 200 mg/day was required in rapid and UMs. For UMs, b.i.d. escitalopram dosing was necessary to achieve comparable trough levels and exposure to NMs. Conclusions: This simulation study raises the possibility that achieving similar escitalopram and sertraline plasma concentrations could require dose adjustments in CYP2C19 poor metabolizers and UMs, although the magnitude of these differences were more pronounced for escitalopram than for sertraline. However, prospective trials of pharmacogenomically guided dosing in the pediatric population are needed to extend the findings of these modeling studies.

Effects of Cytochrome P450 2C19 Genetic Polymorphisms on Responses to Escitalopram and Levels of Brain-Derived Neurotrophic Factor in Patients With Panic Disorder

PURPOSE/BACKGROUND

The purpose of this study was to examine the relationships between ytochrome P450 family 2 subfamily C member 19 (CYP2C19) polymorphisms, brain-derived neurotrophic factor (BDNF) plasma levels, and treatment responses to escitalopram in Chinese patients with panic disorder (PD).

METHODS/PROCEDURES

Ninety patients with PD were administered the Panic Disorder Severity Scale-Chinese Version (PDSS-CV) and Hamilton Anxiety Scale (HAMA-14) from baseline to 8 weeks. Escitalopram treatment (10 mg/d) was administered for 8 consecutive weeks. Three CYP2C19 metabolizers, including extensive metabolizers, intermediate metabolizers, and poor metabolizers (PMs), and 5 CYP2C19 genotypes were detected by polymerase chain reaction-genotyping microarray analysis. Baseline plasma BDNF levels were tested using human BDNF enzyme-linked immunosorbent assay kits.

FINDINGS/RESULTS

Our findings showed no significant differences in demographic data, baseline PDSS-CV scores, or HAMA-14 scores between the 3 CYP2C19 metabolizer groups (P's > 0.05). Repeated-measures analysis showed a significant reduction in PDSS-CV (F = 221.49, df = 3, P < 0.001) and HAMA-14 (F = 260.47, df = 3, P < 0.001) scores over 8 weeks in PD patients. In addition, patients with PMs had a greater reduction in HAMA-14 scores (F = 2.14, P = 0.049) than did those with extensive metabolizers and intermediate metabolizers. Moreover, our findings showed that patients with *2/*2 genotypes had a greater reduction in PDSS-CV scores than did those with other genotypes (F = 2.14, df = 12, P = 0.015).

IMPLICATIONS/CONCLUSIONS

Our study provides preliminary evidence of the effects of CYP2C19 PMs on treatment responses to escitalopram in Chinese PD patients, but no significant correlation between treatment responses and BDNF levels was found.

Pharmacotherapy for generalized anxiety disorder in adult and pediatric patients: an evidence-based treatment review

INTRODUCTION

Generalized anxiety disorder (GAD) often begins during adolescence or early adulthood and persists throughout the lifespan. Randomized controlled trials support the efficacy of selective serotonin and selective serotonin norepinephrine reuptake inhibitors (SSRIs and SNRIs, respectively), as well as benzodiazepines, azapirones, anti-adrenergic medications, melatonin analogs, second-generation antipsychotics, kava, and lavender oil in GAD. However, psychopharmacologic treatment selection requires clinicians to consider multiple factors, including age, co-morbidity, and prior treatment. Areas covered: The authors review the literature concerning pharmacotherapy for pediatric and adult patients with GAD with specific commentary on the efficacy and tolerability of selected agents in these age groups. The authors describe an algorithmic approach to the pediatric and adult patient with GAD and highlight considerations for the use of selected medications in these patients. Expert opinion: In adults with GAD, SSRIs and SNRIs represent the first-line psychopharmacologic treatment while second-line pharmacotherapies include buspirone, benzodiazepines, SGAs, and pregabalin. In pediatric patients with GAD, SSRIs should be considered the first line pharmacotherapy and psychotherapy enhances antidepressant response.

Effect of Polymorphisms on the Pharmacokinetics, Pharmacodynamics and Safety of Sertraline in Healthy Volunteers

Sertraline is a selective serotonin reuptake inhibitor widely metabolized in the liver by cytochrome P450 (CYP) enzymes. Besides, it is a P-glycoprotein substrate. Moreover, serotonin transporters and serotonin receptors are involved in its efficacy and safety. The aim of this study was to evaluate the role of polymorphisms of metabolizing enzymes, transporters and receptors on the pharmacokinetics, pharmacodynamics and tolerability of sertraline in healthy volunteers. Forty-six healthy volunteers (24 men and 22 women) receiving a 100-mg single oral dose of sertraline were genotyped for 17 genetic variants of CYP enzymes (CYP2B6, CYP2C9, CYP2C19, CYP2D6), ATP-binding cassette subfamily B member 1 (ABCB1), solute carrier family 6 member 4 (SLC6A4), 5-hydroxytryptamine receptor 2A (HTR2A) and 5-hydroxytryptamine receptor 2C (HTR2C) genes. Pharmacokinetic and pharmacodynamic parameters were similar in men and women. Polymorphisms in CYP2C19 and CYP2B6 genes influenced sertraline pharmacokinetics, with a greater effect of CYP2C19. Individuals carrying defective alleles for CYP2C19 and CYP2B6 showed higher area under the curve (AUC) and half-life (T_1/2 ). Moreover, CYP2C19*17 was related to a decreased AUC and T_1/2 . No significant effect was found for polymorphisms in CYP2C9, CYP2D6 and ABCB1 on sertraline pharmacokinetics. Sertraline had a small heart rate-lowering effect, directly related to maximum concentration (C_max ) and the presence of ABCB1 minor alleles. Sertraline had no significant effect on blood pressure and QTc. There was a tendency to present more adverse drug reactions in women and individuals with higher AUC of sertraline, such as CYP2C19 intermediate metabolizers and CYP2B6 G516T T/T individuals.

Clinical Pharmacogenetics of Cytochrome P450-Associated Drugs in Children

Cytochrome P450 (CYP) enzymes are commonly involved in drug metabolism, and genetic variation in the genes encoding CYPs are associated with variable drug response. While genotype-guided therapy has been clinically implemented in adults, these associations are less well established for pediatric patients. In order to understand the frequency of pediatric exposures to drugs with known CYP interactions, we compiled all actionable drug-CYP interactions with a high level of evidence using Clinical Pharmacogenomic Implementation Consortium (CPIC) data and surveyed 10 years of electronic health records (EHR) data for the number of children exposed to CYP-associated drugs. Subsequently, we performed a focused literature review for drugs commonly used in pediatrics, defined as more than 5000 pediatric patients exposed in the decade-long EHR cohort. There were 48 drug-CYP interactions with a high level of evidence in the CPIC database. Of those, only 10 drugs were commonly used in children (ondansetron, oxycodone, codeine, omeprazole, lansoprazole, sertraline, amitriptyline, citalopram, escitalopram, and risperidone). For these drugs, reports of the drug-CYP interaction in cohorts including children were sparse. There are adequate data for implementation of genotype-guided therapy for children for three of the 10 commonly used drugs (codeine, omeprazole and lansoprazole). For the majority of commonly used drugs with known CYP interactions, more data are required to support pharmacogenomic implementation in children.

Complications of Psychotropic and Pain Medications in an Ultrarapid Metabolizer Patient at the Upper 1% of Cytochrome P450 (CYP450) Function Quantified by Combinatorial CYP450 Genotyping

A 44-year-old Caucasian woman presented with a history of empirical treatment with 20 pain and psychotropic medications, as well as dual comorbidity of intractable pain and depression. A multiple gain-of-function profile in the CYP450 family of cytochrome P450 (CYP450) drug metabolism isoenzymes was discovered. The patient was a homozygote of suprafunctional alleles for both CYP2D6 (^*35/^*35) and CYP2C19 (^*17/^*17) genes and functional alleles for CYP2C9 (^*1/^*1), which account for aggregate drug metabolism function at the upper 1% of the population. The patient improved clinically with discontinuation of psychotropics and pain medications that were substrates of CYP2D6 and/or CYP2C19, suggesting that much of her symptomatology was drug induced. Combinatorial genotyping of CYP450 genes is diagnostically useful in individuals with histories of multiple side effects or drug resistance, which could be avoided by genetically informed therapeutics in behavioral health.

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.

Influence of CYP2B6 and CYP2C19 polymorphisms on sertraline metabolism in major depression patients

BACKGROUND

Genetic polymorphisms in CYP2B6 and CYP2C19 may cause variability in the metabolism of sertraline, a widely used antidepressant in major depressive disorder treatment.

OBJECTIVE

This study investigates the impact of CYP2B6*4 (785A > G), CYP2B6*9 (516G > T), CYP2B6*6 (516G > T + 685G > A) CYP2C19*2 (685G > A), CYP2C19*17 (-3402C > T) polymorphisms on plasma concentrations of sertraline and N-desmethyl sertraline in major depression patients treated with sertraline [n = 50].

SETTING

Participants were patients who admitted to an adult psychiatry outpatient unit at a university hospital. These were DSM-IV major depression diagnosed patients with a stable sertraline medication regimen [for at least one month].

METHODS

CYP2B6*4 (rs 2279343; 785A > G), CYP2B6*9 (516G > T; rs 3745274), CYP2B6*6 (516G > T + 685G > A) CYP2C19*2 (rs 4244285; 685G > A), CYP2C19*17 (rs 11188072; -3402C > T), polymorphisms were analyzed by polymerase chain reaction and restriction fragment length polymorphism. Plasma concentrations were measured by high-performance liquid chromatography in patients treated with SERT.

MAIN OUTCOME MEASURE

The distribution of CYP2B6*4, *6, *9 and CYP2C19*2, *17 among patient group and the association between genotype and sertraline metabolism.

RESULTS

Sertraline, N-desmethyl sertraline, N-desmethyl sertraline/sertraline and dose-adjusted plasma concentrations were statistically compared between individuals with wild-type and variant alleles both for CYP2B6 and CYP2C19 enzymes. The mean N-desmethyl sertraline/sertraline value, was significantly lower in all subgroups with *6 and *9 variant alleles (p < 0.05). Sertraline/C values were significantly higher (p < 0.05) and N-desmethyl sertraline/C values were lower in all subgroups with *6 and *9 variant alleles compared to wild-type subgroup.

CONCLUSION

CYP2B6*6 and *9 variant alleles had a significant decreasing effect on sertraline metabolism in major depression patients which might result as variations in sertraline therapy.

Clinically relevant genetic variants of drug-metabolizing enzyme and transporter genes detected in Thai children and adolescents with autism spectrum disorder

Single-nucleotide polymorphisms (SNPs) among drug-metabolizing enzymes and transporters (DMETs) influence the pharmacokinetic profile of drugs and exhibit intra- and interethnic variations in drug response in terms of efficacy and safety profile. The main objective of this study was to assess the frequency of allelic variants of drug absorption, distribution, metabolism, and elimination-related genes in Thai children and adolescents with autism spectrum disorder. Blood samples were drawn from 119 patients, and DNA was extracted. Genotyping was performed using the DMET Plus microarray platform. The allele frequencies of the DMET markers were generated using the DMET Console software. Thereafter, the genetic variations of significant DMET genes were assessed. The frequencies of SNPs across the genes coding for DMETs were determined. After filtering the SNPs, 489 of the 1,931 SNPs passed quality control. Many clinically relevant SNPs, including CYP2C19*2, CYP2D6*10, CYP3A5*3, and SLCO1B1*5, were found to have frequencies similar to those in the Chinese population. These data are important for further research to investigate the interpatient variability in pharmacokinetics and pharmacodynamics of drugs in clinical practice.

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.

Effect of proton pump inhibitors on the serum concentrations of the selective serotonin reuptake inhibitors citalopram, escitalopram, and sertraline

Background:

The selective serotonin reuptake inhibitors (SSRIs) citalopram, escitalopram, and sertraline are all metabolized by the cytochrome P-450 isoenzyme CYP2C19, which is inhibited by the proton pump inhibitors (PPIs) omeprazole, esomeprazole, lansoprazole, and pantoprazole. The aim of the present study was to evaluate the effect of these PPIs on the serum concentrations of citalopram, escitalopram, and sertraline.

Methods:

Serum concentrations from patients treated with citalopram, escitalopram, or sertraline were obtained from a routine therapeutic drug monitoring database, and samples from subjects concomitantly using PPIs were identified. Dose-adjusted SSRI serum concentrations were calculated to compare data from those treated and those not treated with PPIs.

Results:

Citalopram concentrations were significantly higher in patients treated with omeprazole (+35.3%; P < 0.001), esomeprazole (+32.8%; P < 0.001), and lansoprazole (+14.7%; P = 0.043). Escitalopram concentrations were significantly higher in patients treated with omeprazole (+93.9%; P < 0.001), esomeprazole (+81.8%; P < 0.001), lansoprazole (+20.1%; P = 0.008), and pantoprazole (+21.6%; P = 0.002). Sertraline concentrations were significantly higher in patients treated with esomeprazole (+38.5%; P = 0.0014).

Conclusions:

The effect of comedication with PPIs on the serum concentration of SSRIs is more pronounced for omeprazole and esomeprazole than for lansoprazole and pantoprazole, and escitalopram is affected to a greater extent than are citalopram and sertraline. When omeprazole or esomeprazole are used in combination with escitalopram, a 50% dose reduction of the latter should be considered.

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.

The effect of induction of CYP3A4 by St John's wort on ambrisentan plasma pharmacokinetics in volunteers of known CYP2C19 genotype

To evaluate the impact of CYP2C19 polymorphisms on ambrisentan exposure and to assess its modification by St. John's wort (SJW), 20 healthy volunteers (10 CYP2C19 extensive, four poor and six ultrarapid metabolizers) received therapeutic doses of ambrisentan (5 mg qd po) for 20 days and concomitantly SJW (300 mg tid po) for the last 10 days. To quantify changes of CYP3A4 activity, midazolam (3 mg po) as a probe drug was used. Ambrisentan pharmacokinetics was assessed on days 1, 10 and 20, and midazolam pharmacokinetics before and on days 1, 10, 17 and 20. At steady state, ambrisentan exposure was similar in extensive and ultrarapid metabolizers but 43% larger in poor metabolizers (p < 0.01). In all volunteers, SJW reduced ambrisentan exposure and the relative change (17-26%) was similar in all genotype groups. The extent of this interaction did not correlate with the changes in CYP3A activity (midazolam clearance) (rs = 0.23, p = 0.34). Ambrisentan had no effect on midazolam pharmacokinetics. In conclusion, SJW significantly reduced exposure with ambrisentan irrespective of the CYP2C19 genotype. The extent of this interaction was small and thus likely without clinical relevance.

A combined high CYP2D6-CYP2C19 metabolic capacity is associated with the severity of suicide attempt as measured by objective circumstances

This study examined, for the first time, whether a high CYP2D6-CYP2C19 metabolic capacity combination increases the likelihood of suicidal intent severity in a large study cohort. Survivors of a suicide attempt (n=587; 86.8% women) were genotyped for CYP2C19 (*2, *17) and CYP2D6 (*3, *4, *4xN, *5, *6, *10, wtxN) genetic variation and evaluated with the Beck Suicide Intent Scale (SIS). Patients with a high CYP2D6-CYP2C19 metabolic capacity showed an increased risk for a severe suicide attempt (P<0.01) as measured by the SIS-objective circumstance subscale (odds ratio (OR)=1.37; 95% confidence interval (CI)=1.05-1.78; P=0.02) after adjusting for confounders (gender, age, level of studies, marital status, mental disorders, tobacco use, family history of suicide, personal history of attempts and violence of the attempt). Importantly, the risk was greater in those without a family history of suicide (OR=1.82; CI=1.19-2.77; P=0.002). Further research is warranted to evaluate whether the observed relationship is mediated by the role of CYP2D6 and CYP2C19 involvement in the endogenous physiology or drug metabolism or both.

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.

Evaluation of the pharmacokinetics, safety and clinical efficacy of sertraline used to treat social anxiety

INTRODUCTION

Social anxiety disorder (SAD) is an emerging, often invalidating, syndrome with deep personal, social and psychological implications. While multiple treatment strategies exist, presently none of them can be considered superior to all others.

AREAS COVERED

The aim of this review is to provide the latest information on sertraline (SRT), one of the most important selective serotonin reuptake inhibitors (SSRIs) currently used for the pharmacological therapy of SAD. A literature search was carried out with the keywords 'sertraline', 'social anxiety', 'social phobia' and 'clinical trials'. In this process, particular attention is paid to the pharmacokinetic characteristics of the drug and its safety in clinical use.

EXPERT OPINION

SRT is an effective drug in the treatment of SAD, especially when used in combination with some form of psychological support. While it does not seem to be significantly more effective than other SSRIs, SRT could offer some peculiar advantages: for example, it has a long half-life, allowing a single daily administration, and seems to be particularly indicated for the control of specific symptoms of SAD.

Interaction of ambrisentan with clarithromycin and its modulation by polymorphic SLCO1B1

PURPOSE

We assessed the effect of cytochrome P450 (CYP) 3A4 and the OATP1B1 inhibitor clarithromycin on ambrisentan steady-state kinetics and its relationship to the SLCO1B1 15 haplotype in healthy volunteers.

METHODS

In this open-label, monocenter, one-sequence crossover clinical trial ten male healthy participants were stratified according to CYP2C19 and SLCO1B1 (encoding for OATP1B1) genotype into two groups: group 1 (n = 6), with CYP2C19 1/1 (extensive metabolizer, EM) and SLCO1B1 wild-type; group 2 (n = 4), with CYP2C19 EM and homozygous (n = 3) or heterozygous for SLCO1B1 15 (n = 1). The participants were administered a once-daily oral dose of 5 mg ambrisentan on study days 1 and days 3-14 and twice-daily oral doses of 500 mg clarithromycin on study days 11-14. To monitor CYP3A activity 3 mg midazolam was given orally 1 day before the first ambrisentan administration and on days 1, 10, and 14 of ambrisentan treatment. Ambrisentan plasma kinetics was assessed on days 1 (single dose), 10 (steady-state), and 14 (CYP3A4/OATP1B1 inhibition by clarithromycin).

RESULTS

Consistent with the expectation that ambrisentan does not induce its own metabolism, ambrisentan exposure and peak concentration (Cmax) were similar after the first dose and at steady-state. Clarithromycin increased the area under the plasma concentration-time curve of ambrisentan by 41 % and Cmax by 27 % (n = 10, both p < 0.05). No contribution of SLCO1B1*15 to the extent of this interaction was observed.

CONCLUSIONS

Clarithromycin increased ambrisentan exposure to a similar extent to ketoconazole, namely, clinically minor and likely irrelevant.

Influence of CYP2D6 and CYP2C19 gene variants on antidepressant response in obsessive-compulsive disorder

Numerous studies have reported on pharmacogenetics of antidepressant response in depression. In contrast, little is known of response predictors in obsessive-compulsive disorder (OCD), a disorder with among the lowest proportion of responders to medication (40-60%). Our study is the largest investigation to date (N=184) of treatment response and side effects to antidepressants in OCD based on metabolizer status for CYP2D6 and CYP2C19. We observed significantly more failed medication trials in CYP2D6 non-extensive compared with extensive metabolizers (P=0.007). CYP2D6 metabolizer status was associated with side effects to venlafaxine (P=0.022). There were nonsignificant trends for association of CYP2D6 metabolizer status with response to fluoxetine (P=0.056) and of CYP2C19 metabolizer status with response to sertraline (P=0.064). Our study is the first to indicate that CYP genes may have a role in antidepressant response in OCD. More research is required for a future clinical application of genetic testing, which could lead to improved treatment outcomes.

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.