Impact of Cytochrome P450 2C19 Polymorphisms on Citalopram/Escitalopram Exposure: A Systematic Review and Meta-Analysis

Pharmacogenetics testing for poor response to antidepressants: a transnosographic case series

Introduction

Pharmacogenetics (PGx) holds promise for optimizing psychotropic medication use, with CYP2D6 and CYP2C19 identified as key genes in antidepressant treatment. However, few studies have explored the genetic variants of these genes in real-world settings for patients experiencing ineffectiveness or adverse drug reactions (ADRs) to antidepressants.

Methods

This case series includes 40 patients who underwent PGx testing due to antidepressant ineffectiveness or ADRs between June 2020 and April 2022. We describe the patients' demographic, clinical, and genetic characteristics and assess the value of PGx testing based on feedback from their psychiatrists.

Results

The most common diagnoses were major depressive disorder (60.0%) and post-traumatic stress disorder (30.0%). Ineffectiveness was reported in 65.0% of patients, ADRs in 2.5%, and both in 32.5%. The antidepressants involved included SSRIs (45.0%), SNRIs (27.5%), atypical antidepressants (20.0%), and tricyclics (17.5%). Only 17.5% of patients had normal CYP2D6 and CYP2C19 metabolic activity. Actionable genetic variants were identified in 22.0% of CYP2D6/CYP2C19-antidepressant-response pairs. PGx recommendations were followed in 92.7% of cases, with significant improvement in ADRs reported in 71.4% of patients and efficacy improvement in 79.5%.

Discussion

Our findings suggest that PGx testing can guide prescribing decisions for patients with antidepressant ineffectiveness or ADRs. The relatively high prevalence of genetic variants affecting pharmacokinetics supports the broader adoption of PGx testing in psychiatric practice.

Impact of CYP2D6*2A, CYP2D6*4 and CYP3A5*3 genetic polymorphisms on Bisoprolol peak concentration and clinical response in acute coronary syndrome patients

AIMS

Acute coronary syndrome (ACS) represents a major cause of death. Bisoprolol is commonly used in the management of ACS. This study aims to investigate the impact of CYP2D6*2A, CYP2D6*4 and CYP3A5*3 genetic polymorphisms on pharmacokinetics and clinical response of bisoprolol in ACS patients.

METHODS

This is an open-label cohort study that included 127 ACS patients and studied the effect of CYP3A5*3, CYP2D6*2A and CYP2D6*4 genotyping using real-time polymerase chain reaction on steady state bisoprolol plasma peak concentration analysed by high performance liquid chromatography-fluorescence detector.

RESULTS

Regarding CYP3A5*3, the mean peak bisoprolol concentration for CC, CT and TT genotypes were 4.25 ± 1.20, 3.93 ± 1.10 and 1.79 ± 0.69 ng/mL, respectively (P < .001). Higher systolic (126 ± 5.47 mmHg), diastolic blood pressure (82 ± 2.73 mmHg) and heart rate (97.80 ± 3.03 beats/min) were also observed in CYP3A5*3 TT carriers (P < .05). In CYP2D6*2A, the peak concentration of bisoprolol was lower in CC carriers (3.54 ± 1 ng/mL) compared to GG (4.38 ± 1.25 ng/mL) and GC carriers (4.07 ± 1.29 ng/mL, P = .019). In CYP2D6*4, the mean bisoprolol peak concentration in CC carriers was 3.98 ± 1.31 ng/mL, which was lower than T allele carriers (4.5 ± 0.8, P = .02). No differences in heart rate, systolic, diastolic blood pressure or bisoprolol dose were observed among CYP2D6*2A or CYP2D6*4 variants. Smokers exhibited lower bisoprolol peak concentration (3.96 ± 1.2 ng/mL) compared to nonsmokers (4.55 ± 1.34 ng/mL, P = .037).

CONCLUSION

There is an association between CYP3A5*3, CYP2D6*4, CYP2D6*2A variants and bisoprolol peak concentration, which may serve as a guide in the future in choosing the optimum dose of bisoprolol in ACS 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.

[Therapy of mental disorders in patients with hematological malignancies]

OBJECTIVE

To assess the possibilities of therapy with minimal effective doses (MED) of psychotropic drugs for mental disorders (MD) that manifest during the treatment of hematological malignancies (HM).

MATERIAL AND METHODS

A prospective study was conducted at the National Medical Research Center for Hematology of the Russian Ministry of Health (Moscow), which included 204 (39.4%) men and 314 (60.6%) women (518 patients in total), aged 17 to 83 years (median 45 years), with various HM, in which the manifestation of MD occurred during the treatment of the underlying disease. To minimize the side-effects of psychotropic drugs and given the relatively mild level of MD, psychopharmacotherapy of patients was carried out mainly at MED. The severity of MD, manifested in patients, was assessed by the illness severity scale of the Clinical Global Impression (CGI) scale, and the effectiveness of the treatment was assessed by the improvement scale (CGI-I).

RESULTS

Mainly mild (188, 36%) and moderately pronounced (270, 52%) MD were noted in patients with HM during the treatment of the underlying disease. Severe psychopathological disorders (60, 12%) were observed much less often. Because of psychopharmacotherapy with MED, patients experienced a very significant (97, 19%) and significant improvement (354, 68%) of their mental state, less often the improvement was regarded as minimal (67, 13%). Therefore, almost all patients showed a stable relief of MD; in 87% (95% CI 84-90) of patients, this improvement was significant.

CONCLUSION

The tactics of treatment MD that manifest in patients with HM with MED of psychotropic drugs turned out to be therapeutically effective according to the results of the assessment on CGI scales.

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.

Serotonin syndrome caused by a CYP2C19-mediated interaction between low-dose escitalopram and clopidogrel: a case report

Background

Serotonin syndrome has been recognized as a serious adverse reaction to antidepressants and is characterized by sudden or severe autonomic nerve dysfunction and neuromuscular symptoms. Without an accurate diagnosis and prompt treatment, serotonin syndrome progresses rapidly and can be life-threatening. It is usually related to the dose of 5-hydroxytryptamine drugs, and the dose is the basis for diagnosis. Therefore, serotonin syndrome induced by low-dose antidepressants rarely occurs, and clinicians are more likely to misdiagnose patients who take low-dose antidepressants with similar symptoms. Here, we present a case study of serotonin syndrome caused by a relatively low dose of escitalopram, which is not common in past references.

Case summary

The patient was a 74-year-old Asian woman with a 42-year history of schizophrenia. After 6 weeks of antidepressant treatment, our patient presented with characteristic myoclonus in the lower limbs and closed eyes with fluttering. Initially, she was misdiagnosed with neuroleptic malignant syndrome (NMS) due to antipsychotic medication and was treated accordingly, even with discontinuation of clozapine. However, her symptoms persisted, and then therapeutic drug monitoring was initiated with the involvement of a clinical pharmacist. Eventually, she was diagnosed with serotonin syndrome due to escitalopram levels reaching the warning level. Subsequently, the patient's treatment was modified, and her clinical outcome was satisfactory without any other serious adverse reactions. Gene detection was also performed, and a cytochrome P450 enzyme (CYP) 2C19-mediated interaction between low-dose escitalopram and clopidogrel seems to be a possible mechanism.

Conclusion

Data on this is extremely scarce, and to the best of our knowledge, serotonin syndrome caused by low-dose antidepressants has not yet been discussed to any great extent in the literature. Our case provides more clinical experience in the treatment of serotonin syndrome.

Escitalopram Personalized Dosing: A Population Pharmacokinetics Repository Method

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

Utility of pharmacogenetic testing to optimise antidepressant pharmacotherapy in youth: a narrative literature review

Pharmacogenetics (PGx) is the study and application of how interindividual differences in our genomes can influence drug responses. By evaluating individuals' genetic variability in genes related to drug metabolism, PGx testing has the capabilities to individualise primary care and build a safer drug prescription model than the current "one-size-fits-all" approach. In particular, the use of PGx testing in psychiatry has shown promising evidence in improving drug efficacy as well as reducing toxicity and adverse drug reactions. Despite randomised controlled trials demonstrating an evidence base for its use, there are still numerous barriers impeding its implementation. This review paper will discuss the management of mental health conditions with PGx-guided treatment with a strong focus on youth mental illness. PGx testing in clinical practice, the concerns for its implementation in youth psychiatry, and some of the barriers inhibiting its integration in clinical healthcare will also be discussed. Overall, this paper provides a comprehensive review of the current state of knowledge and application for PGx in psychiatry and summarises the capabilities of genetic information to personalising medicine for the treatment of mental ill-health in youth.

The Effects of CYP2C19 Genotype on Proxies of SSRI Antidepressant Response in the UK Biobank

Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used psychopharmaceutical treatment for major depressive disorder (MDD), but individual responses to SSRIs vary greatly. CYP2C19 is a key enzyme involved in the metabolism of several drugs, including SSRIs. Variations in the CYP2C19 gene are associated with differential metabolic activity, and thus differential SSRI exposure; accordingly, the CYP2C19 genotype may affect the therapeutic response and clinical outcomes, though existing evidence of this link is not entirely consistent. Therefore, we analysed data from the UK Biobank, a large, deeply phenotyped prospective study, to investigate the effects of CYP2C19 metaboliser phenotypes on several clinical outcomes derived from primary care records, including multiple measures of antidepressant switching, discontinuation, duration, and side effects. In this dataset, 24,729 individuals were prescribed citalopram, 3012 individuals were prescribed escitalopram, and 12,544 individuals were prescribed sertraline. Consistent with pharmacological expectations, CYP2C19 poor metabolisers on escitalopram were more likely to switch antidepressants, have side effects following first prescription, and be on escitalopram for a shorter duration compared to normal metabolisers. CYP2C19 poor and intermediate metabolisers on citalopram also exhibited increased odds of discontinuation and shorter durations relative to normal metabolisers. Generally, no associations were found between metabolic phenotypes and proxies of response to sertraline. Sensitivity analyses in a depression subgroup and metabolic activity scores corroborated results from the primary analysis. In summary, our findings suggest that CYP2C19 genotypes, and thus metabolic phenotypes, may have utility in determining clinical responses to SSRIs, particularly escitalopram and citalopram, though further investigation of such a relationship is warranted.

Impact of pharmacogenomics in achieving personalized/precision medicine in the clinical setting: a symposium report

The Indo-Swiss symposium on pharmacogenomic strategies for the implementation of personalized medicine was conducted as part of the Jawaharlal Institute of Postgraduate Medical Education and Research Integrated Pharmacogenomics Program in Puducherry, India, on 19 November 2022. The symposium was conducted in hybrid mode. The theme of symposium was the impact of pharmacogenomics on the achievement of personalized medicine/precision medicine in the clinical setting. The symposium sought to promote interaction among the participants to initiate future collaborative research projects. The symposium also served as a platform for young researchers to present their research findings as posters to the audience.

Effect of pharmacogenomic testing on pediatric mental health outcome: a 6-month follow-up

Aim: This retrospective, case-control study evaluated the effect of pharmacogenomic testing (PGT) on the management of pediatrics with anxiety, major depressive disorder (MDD) and attention-deficit/hyperactivity disorder (ADHD). Methods: The authors examined psychiatric diagnoses, medication histories, CYP450 profiles, SLC6A4, HTR2A, COMT and MTHFR. Results: The authors found no difference in clinical improvement between the two groups. However, the number of medication changes was significantly larger after PGT. The treatment response in MDD and anxiety was not different between the groups, while ADHD treatment response was substantially improved in PGT and correlated with COMT status. Conclusion: PGT had some value with ADHD with doubtful benefit for MDD or anxiety disorders. Accordingly, pediatric indications must be weighed against cost, utility and clinician experience. Limitations included sample size and selection bias.

Identification of Escitalopram Metabolic Ratios as Potential Biomarkers for Predicting CYP2C19 Poor Metabolizers

BACKGROUND

Escitalopram is metabolized by CYP2C19 to N-desmethyl escitalopram and escitalopram propionic acid. The primary aims of this study were to investigate the impact of the CYP2C19 phenotype on metabolic ratios of escitalopram in vivo and propose a biomarker for the CYP2C19 phenotype in patients treated with escitalopram.

METHODS

Median steady-state serum metabolite/parent drug ratio of N-desmethyl escitalopram and escitalopram propionic acid was investigated across CYP2C19 genotype-translated phenotype groups. The receiver operator characteristics method and the area-under-the-receiver-operator-characteristics curve was used to determine the best suited metabolic ratio for detecting CYP2C19 poor metabolizers (PMs).

RESULTS

A total of 441 patients were included in the study. The N-desmethyl escitalopram/escitalopram ratio was 67% and 44% lower in CYP2C19 PMs and intermediate metabolizers (IMs), respectively, than normal metabolizers. Furthermore, the ability of the ratio to predict CYP2C19 PMs was 92%. A metabolic ratio of <0.24 was detected in 8 of 8 PMs in the study, indicating that it is a promising biomarker of reduced CYP2C19 activity. The escitalopram propionic acid/escitalopram ratio was 77% and 48% lower in CYP2C19 PMs and IMs, respectively; however, the ability of the ratio to detect CYP2C19 PMs was only 87%.

CONCLUSIONS

These findings suggest that DECT/ECT reflects CYP2C19 activity, and a metabolic ratio of <0.24 strongly predicts CYP2C19 PM phenotype. The ratio could be a valuable alternative to genotyping in personalized dosing of escitalopram and possibly other CYP2C19 substrates. The escitalopram propionic acid/escitalopram ratio was also associated with CYP2C19 activity; however, the ratio was inferior to the DECT/ECT at predicting PMs.

Population pharmacokinetics model for escitalopram in Chinese psychiatric patients: effect of CYP2C19 and age

Objective: To establish a population pharmacokinetic model in Chinese psychiatric patients to characterize escitalopram pharmacokinetic profile to identify factors influencing drug exposure, and through simulation to compare the results with the established therapeutic reference range.

Methods: Demographic information, dosing regimen, CYP2C19 genotype, concomitant medications, and liver and kidney function indicators were retrospectively collected for inpatients taking escitalopram with therapeutic drug monitoring from 2018 to 2021. Nonlinear mixed-effects modeling was used to model the pharmacokinetic characteristics of escitalopram. Goodness-of-fit plots, bootstrapping, and normalized prediction distribution errors were used to evaluate the model. Simulation for different dosing regimens was based on the final estimations.

Results: The study comprised 106 patients and 337 measurements of serum sample. A structural model with one compartment with first-order absorption and elimination described the data adequately. The population-estimated apparent volume of distribution and apparent clearance were 815 and 16.3 L/h, respectively. Age and CYP2C19 phenotype had a significant effect on the apparent clearance (CL/F). CL/F of escitalopram decreased with increased age, and CL/F of poor metabolizer patients was significantly lower than in extensive and immediate metabolizer patients. The final model-based simulation showed that the daily dose of adolescents with poor metabolizer might be as high as 15 mg or 20 mg and referring to the therapeutic range for adults may result in overdose and a high risk of adverse effects in older patients.

Conclusion: A population pharmacokinetics model of escitalopram was successfully created for the Chinese population. Depending on the age of the patients, CYP2C19 genotype and serum drug concentrations throughout treatment are required for adequate individualization of dosing regimens. When developing a regimen for older patients, especially those who are poor metabolizers, vigilance is required.

Selective Serotonin Reuptake Inhibitor Pharmacokinetics During Pregnancy: Clinical and Research Implications

Pregnancy and associated physiologic changes affect the pharmacokinetics of many medications, including selective serotonin reuptake inhibitors—the first-line pharmacologic interventions for depressive and anxiety disorders. During pregnancy, SSRIs exhibit extensive pharmacokinetic variability that may influence their tolerability and efficacy. Specifically, compared to non-pregnant women, the activity of cytochrome P450 (CYP) enzymes that metabolize SSRIs drastically changes (e.g., decreased CYP2C19 activity and increased CYP2D6 activity). This perspective examines the impact of pharmacokinetic genes—related to CYP activity on SSRI pharmacokinetics during pregnancy. Through a simulation-based approach, plasma concentrations for SSRIs metabolized primarily by CYP2C19 (e.g., escitalopram) and CYP2D6 (e.g., fluoxetine) are examined and the implications for dosing and future research are discussed.

Perspectives from the Society for Pediatric Research: pharmacogenetics for pediatricians

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

Pharmacogenetically Guided Escitalopram Treatment for Pediatric Anxiety Disorders: Protocol for a Double-Blind Randomized Trial

Current pharmacologic treatments for pediatric anxiety disorders (e.g., selective serotonin reuptake inhibitors (SSRIs)) frequently use "one size fits all" dosing strategies based on average responses in clinical trials. However, for some SSRIs, including escitalopram, variation in CYP2C19 activity produces substantial variation in medication exposure (i.e., blood medication concentrations). This raises an important question: would refining current SSRI dosing strategies based on CYP2C19 phenotypes increase response and reduce side effect burden? To answer this question, we designed a randomized, double-blind trial of adolescents 12-17 years of age with generalized, separation, and/or social anxiety disorders (N = 132). Patients are randomized (1:1) to standard escitalopram dosing or dosing based on validated CYP2C19 phenotypes for escitalopram metabolism. Using this approach, we will determine whether pharmacogenetically-guided treatment-compared to standard dosing-produces faster and greater reduction in anxiety symptoms (i.e., response) and improves tolerability (e.g., decreased risk of treatment-related activation and weight gain). Secondarily, we will examine pharmacodynamic variants associated with treatment outcomes, thus enhancing clinicians' ability to predict response and tolerability. Ultimately, developing a strategy to optimize dosing for individual patients could accelerate response while decreasing side effects-an immediate benefit to patients and their families. ClinicalTrials.gov Identifier: NCT04623099.

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.

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.

CYP2C19 Genotyping May Provide a Better Treatment Strategy when Administering Escitalopram in Chinese Population

Depression disorder is one of the most serious mental illnesses in the world. Escitalopram is the essential first-line medication for depression disorder. It is the substrate of hepatic cytochrome P450 (CYP) enzyme CYP2C19 with high polymorphism. The effect of CYP2C19 on pharmacokinetics and pharmacodynamics on Caucasian population has been studied. The Clinical Pharmacogenetics Implementation Consortium Guideline provides dosing recommendations for escitalopram on CYP2C19 genotypes on the basis of the studies on Caucasian population. However, the gene frequency of the alleles of CYP2C19 showed racial differences between Chinese and Caucasian populations. Representatively, the frequency of the *2 and *3 allele, which were considered as poor metabolizer, has been shown to be three times higher in Chinese than in Caucasians. In addition, the environments might also lead to different degrees of impacts on genotypes. Therefore, the guidelines based on the Caucasians may not be applicable to the Chinese, which induced the establishment of a guideline in China. It is necessary to provide the evidence of individual treatment of escitalopram in Chinese by studying the effect of CYP2C19 genotypes on the pharmacokinetics parameters and steady-state concentration on Chinese. In this study, single-center, randomized, open-label, two-period, two-treatment crossover studies were performed. Ninety healthy Chinese subjects finished the trials, and they were included in the statistical analysis. The pharmacokinetics characteristics of different genotypes in Chinese were obtained. The results indicate that the poor metabolizer had higher exposure, and increased half-life than the extensive metabolizer and intermediate metabolite. The prediction of steady-state concentration based on the single dose trial on escitalopram shows that the poor metabolizer might have a higher steady-state concentration than the extensive metabolizer and intermediate metabolite in Chinese. The results indicate that the genetic testing before medication and the adjustment of escitalopram in the poor metabolizer should be considered in the clinical treatments in Chinese. The results provide the evidence of individual treatment of escitalopram in Chinese, which will be beneficial for the safer and more effective application of escitalopram in the Chinese population. Clinical Trial Registration: identifier ChiCTR1900027226.

Cytochrome P450 2C19 gene polymorphisms (CYP2C19*2 and CYP2C19*3) in chronic myeloid leukemia patients: in vitro and in silico studies

Polymorphisms in the CYP2C19 have a huge impact on drug processing, out of which CYP2C19*2 and CYP2C19*3 are the most common variants associated with reduced metabolism of drugs. Mechanism by which two variants contribute in poor metabolization of drugs and cancer is not well understood. Here, we hypothesized that the mutations in CYP2C19 gene might affect the risk of chronic myeloid leukemia patients (CML). Present study has two main objectives: first to investigate the allele frequencies of CYP2C19*2 and CYP2C19*3 associated gene polymorphisms in CML patients and to elucidate the structural stability, conformation and functions of protein encoded by such variants. Genotyping of CYP2C19 was performed in 103 CML patients and 103 matched healthy controls. Heterozygous genotype of CYP2C19*2 was higher in CML patients (13.59%) than the controls (4.85%). Whereas, CYP2C19*3 allele frequency was not observed in cases as well as in controls. Furthermore, molecular dynamics (MD) simulation was applied to monitor the structural and conformational effect of above mutants. MD simulation results demonstrated that these mutants formed unstable proteins with distorted conformations, altered residues network and affected drug binding site which led to malfunction of mutant proteins. Hence, the study provides the role of CYP2C19 gene polymorphisms in susceptibility to CML population and explored the molecular basis of malignancies caused which may aid in the development of precise medicine or adjusting the drug dosages so as to reduce the chemotherapeutic side effects.Communicated by Ramaswamy H. Sarma.

The Influence of Pharmacogenetics on the Clinical Relevance of Pharmacokinetic Drug-Drug Interactions: Drug-Gene, Drug-Gene-Gene and Drug-Drug-Gene Interactions

Drug interactions are a well-known cause of adverse drug events, and drug interaction databases can help the clinician to recognize and avoid such interactions and their adverse events. However, not every interaction leads to an adverse drug event. This is because the clinical relevance of drug-drug interactions also depends on the genetic profile of the patient. If inhibitors or inducers of drug metabolising enzymes (e.g., CYP and UGT) are added to the drug therapy, phenoconcversion can occur. This leads to a genetic phenotype that mismatches the observable phenotype. Drug-drug-gene and drug-gene-gene interactions influence the toxicity and/or ineffectivness of the drug therapy. To date, there have been limited published studies on the impact of genetic variations on drug-drug interactions. This review discusses the current evidence of drug-drug-gene interactions, as well as drug-gene-gene interactions. Phenoconversion is explained, the and methods to calculate the phenotypes are described. Clinical recommendations are given regarding the integratation of the PGx results in the assessment of the relevance of drug interactions in the future.

Pharmacogenetic testing in psychiatry and neurology: an overview of reviews

Pharmacogenetic testing is available to healthcare professionals to guide drug selection and prevent adverse events. However, its implementation in the clinical practice of psychiatry/neurology still has barriers, mainly due to a lack of evidence. We conducted a literature search on Cochrane Library, Embase and Pubmed, from their inception to 18 June 2020. We included 16 published systematic reviews. The most studied drug categories were anticonvulsants and selective serotonin reuptake inhibitors associated with human leukocyte antigen and cytochrome P450 genes (HLA-A, HLA-B, CYP2C9, CYP2D6, CYP2C19), classified as critically low quality/low quality. There is a need for more robust studies with adequate design to assess the potential benefits of adopting pharmacogenetics in health systems and services.

Population pharmacokinetic/pharmacodynamic modeling of delayed effect of escitalopram-induced QT prolongation

BACKGROUND

A thorough QT study identified that escitalopram-induced QT prolongation was delayed. This study thus aimed to develop a population pharmacokinetic (PK)/pharmacodynamic (PD) model to characterize the relationship between escitalopram concentrations and the delayed effect on QT prolongation.

METHODS

The data of completed subjects who had placebo (n=36) and a single dose of 20 mg escitalopram (n=33) from a previous thorough QT study were used. Population PK/PD analysis was performed by nonlinear mixed-effects modeling. A escitalopram concentration-drug effect model was developed with estimated individual PK and baseline QT parameters. To explain the relationship between escitalopram concentrations and QT prolongation delay, an effect compartment model was utilized.

RESULTS

A two-compartment model with first-order absorption and lag time and first-order elimination adequately described the PK of escitalopram. The circadian rhythm of baseline QT interval was best explained by two harmonic cosine functions. A linear model properly characterized escitalopram-induced QT prolongation. The average estimated maximal QT prolongation was 5.4 ms (range: 1.9-7.6 ms). The equilibrium half-life of delayed QT prolongation was 1.9 h. The drug effect of QTc change compared with that at baseline remained relatively constant from 1.3 to 3.5 ms over 24 h, and the maximum QTc change occurred with a 3-h delay after the time to the maximum plasma concentration.

LIMITATIONS

We did not include genetic polymorphisms, such as CYP2C19, as potential covariates owing to limited information.

CONCLUSIONS

These results may provide useful information on when to monitor electrocardiogram in patients who require intensive care after drug administration.

Meta-analysis of probability estimates of worldwide variation of CYP2D6 and CYP2C19

Extensive migration has led to the necessity of knowledge regarding the treatment of migrants with different ethnical backgrounds. This is especially relevant for pharmacological treatment, because of the significant variation between migrant groups in their capacity to metabolize drugs. For psychiatric medications, CYP2D6 and CYP2C19 enzymes are clinically relevant. The aim of this meta-analysis was to analyze studies reporting clinically useful information regarding CYP2D6 and CYP2C19 genotype frequencies, across populations and ethnic groups worldwide. To that end, we conducted a comprehensive meta-analysis using Embase, PubMed, Web of Science, and PsycINFO (>336,000 subjects, 318 reports). A non-normal metabolizer (non-NM) probability estimate was introduced as the equivalent of the sum-prevalence of predicted poor, intermediate, and ultrarapid metabolizer CYP2D6 and CYP2C19 phenotypes. The probability of having a CYP2D6 non-NM predicted phenotype was highest in Algeria (61%) and lowest in Gambia (2.7%) while the probability for CYP2C19 was highest in India (80%) and lowest in countries in the Americas, particularly Mexico (32%). The mean total probability estimates of having a non-NM predicted phenotype worldwide were 36.4% and 61.9% for CYP2D6 and CYP2C19, respectively. We provide detailed tables and world maps summarizing clinically relevant data regarding the prevalence of CYP2D6 and CYP2C19 predicted phenotypes and demonstrating large inter-ethnic differences. Based on the documented probability estimates, pre-emptive pharmacogenetic testing is encouraged for every patient who will undergo therapy with a drug(s) that is metabolized by CYP2D6 and/or CYP2C19 pathways and should be considered in case of treatment resistance or serious side effects.

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

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

Escitalopram in Adolescents With Generalized Anxiety Disorder: A Double-Blind, Randomized, Placebo-Controlled Study

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) are commonly used to treat pediatric anxiety disorders, including generalized anxiety disorder (GAD); however, their efficacy and tolerability are difficult to predict. This study evaluated the efficacy and tolerability of escitalopram in adolescents with GAD (DSM-IV-TR) and the impact of variants in HTR2A and serotonin transporter (SLC6A4) genes and cytochrome P450 2C19 (CYP2C19) phenotypes on response as well as CYP2C19 phenotype on escitalopram pharmacokinetics from February 2015 through November 2018.

METHODS

Patients were treated with escitalopram (forced titration to 15 mg/d, then flexible titration to 20 mg/d) (n = 26, mean ± SD age: 14.8 ± 1.7 years) or placebo (n = 25, mean ± SD age: 14.9 ± 1.6 years) for 8 weeks. Outcomes were the change in scores on the Pediatric Anxiety Rating Scale (PARS) and Clinical Global Impressions (CGI) scales as well as vital signs and adverse events. Plasma escitalopram and desmethylcitalopram area under the curve during 24 hours (AUC0-24) and maximum concentration (Cmax) were determined and compared across CYP2C19 phenotypes.

RESULTS

Escitalopram was superior to placebo for mean ± SD baseline-to-endpoint change in PARS (-8.65 ± 1.3 vs -3.52 ± 1.1, P = .005) and CGI scores, and increasing CYP2C19 metabolism was associated with decreases in escitalopram Cmax (P = .07) and AUC0-24 (P < .05). Vital signs, corrected QT interval, and adverse events were similar in patients who received escitalopram and placebo.

CONCLUSIONS

Escitalopram reduces anxiety symptoms, and pharmacogenetics variables influence the trajectory and magnitude of improvement. Variation in CYP2C19 metabolism accounts for significant differences in escitalopram pharmacokinetics, raising the possibility that CYP2C19 phenotype should be considered when prescribing escitalopram.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02818751.

Effect of High Selective Serotonin-Reuptake Inhibitor Doses on the Development and Treatment of Sarcoid-Like Reaction

Sarcoidosis is a systemic disorder characterized by the presence of noncaseating granulomas that are most commonly observed in the lungs. Sarcoid-like reaction has been reported to develop in response to several immune modulator agents and antidepressants. In this report, a case of pulmonary sarcoidosis that was strongly related to the use of more than the average recommended dose of selective serotonin-reuptake inhibitor (SSRI) medications has been described. The patient, a 37-year-old, single, Caucasian woman, who suffered from severe depression and who presented to the emergency department with shortness of breath, low-grade fever, a dry cough, fatigue, and the loss of appetite, was diagnosed with this condition, and she failed to respond to the administered sarcoidosis treatment until the SSRI medications that she was using were discontinued; furthermore, she relapsed when one of these medications was reintroduced. Based on these observations, we were able to show a possible relationship between sarcoid-like reaction and SSRIs, and therefore, in the case of patients with interstitial lung diseases who are using SSRIs, we recommend that meticulous precautions be taken while planning their treatment and careful follow-ups be implemented to monitor their progress.

A population pharmacokinetic model for escitalopram and its major metabolite in depressive patients during the perinatal period: Prediction of infant drug exposure through breast milk

BACKGROUND AND OBJECTIVES

Escitalopram (SCIT) is frequently prescribed to breastfeeding women. Available information on SCIT excretion into breast milk is based on heterogeneous and incomplete data. A population pharmacokinetic model that aimed to better characterize maternal and infant exposure to SCIT and its metabolite was developed.

METHODS

The study population was composed of women treated by SCIT or racemic citalopram and enrolled in the multicenter prospective cohort study SSRI-Breast Milk study (ClinicalTrial.gov NCT01796132). A joint structural model was first built for SCIT and S-desmethylcitalopram (SDCIT) in plasma using NONMEM and the milk-to-plasma ratio (MPR) was estimated by adding the drug breast milk concentrations. The effect of different influential covariates was tested and the average drug exposure with variability through breastfeeding was predicted under various conditions by simulation.

RESULTS

The study enrolled 33 patients treated with SCIT or racemic citalopram who provided 80 blood and 104 milk samples. Mean MPR for both parent drug and metabolite was 1.9. Increased milk fat content was significantly associated with an increased drug transfer into breast milk (+28% for SCIT and +18% for SDCIT when fat amount doubles from 3.1 to 6.2 g/100 mL). Simulations suggested that an exclusively breastfed infant would ingest daily through breast milk 3.3% of the weight-adjusted maternal SCIT dose on average.

CONCLUSION

The moderate between-subject variability in milk concentration of SCIT and the limited exposure to escitalopram through breast milk observed provide reassurance for treated mothers of breastfed healthy infants.

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.

A pharmacogenetic risk score for the evaluation of major depression severity under treatment with antidepressants

The severity of symptoms as well as efficacy of antidepressants in major depressive disorder (MDD) is modified by single nucleotide polymorphisms (SNPs) in different genes, which may contribute in an additive or synergistic fashion. We aimed to investigate depression severity in participants with MDD under treatment with antidepressants in relation to the combinatory effect of selected genetic variants combined using a genetic risk score (GRS). The sample included 150 MDD patients on regular AD therapy from the population‐based Swiss PsyCoLaus cohort. We investigated 44 SNPs previously associated with antidepressant response by ranking them with regard to their association to the Center for Epidemiologic Studies Short Depression Scale (CES‐D) score using random forest. The three top scoring SNPs (rs12248560, rs878567, rs17710780) were subsequently combined into an unweighted GRS, which was included in linear and logistic regression models using the CES‐D score, occurrence of a major depressive episode (MDE) during follow‐up and regular antidepressant treatment during the 6 months preceding follow‐up assessment as outcomes. The GRS was associated with MDE occurrence (p = .02) and ln CES‐D score (p = .001). The HTR1A rs878567 variant was associated with ln CES‐D after adjustment for demographic and clinical variables [p = .02, lower scores for minor allele (G) carriers]. Additionally, rs12248560 (CYP2C19) CC homozygotes showed a six‐fold higher likelihood of regular AD therapy at follow‐up compared to minor allele homozygotes [TT; ultrarapid metabolizers (p = .03)]. Our study suggests that the cumulative consideration of pharmacogenetic risk variants more reliably reflects the impact of the genetic background on depression severity than individual SNPs.

The Association Between Selective Serotonin Reuptake Inhibitors and Glycemia: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

OBJECTIVE

Individual studies have reported conflicting effects of selective serotonin reuptake inhibitors (SSRIs) on glycemia. We systematically reviewed the effects of SSRIs on glycemia and whether metabolic and psychological factors moderated these effects.

METHODS

We systematically searched for placebo-controlled randomized controlled trials investigating the effect of SSRIs on glycemia (fasting blood glucose or HbA1c) as a primary or secondary outcome. Random effects meta-analysis was conducted to compute an overall treatment effect. Meta-regression tested whether depression, type 2 diabetes, insulin resistance, treatment duration, and weight loss moderated treatment effects.

RESULTS

Sixteen randomized controlled trials (n = 835) were included and glycemia was usually a secondary outcome. Overall, SSRIs improved glycemia versus placebo (pooled effect size (ES) = -0.34, 95% confidence interval (CI) = -0.48 to -0.21; p < .001, I = 0%). Individually, fluoxetine (ES = -0.29, 95% CI = -0.54 to -0.05; p = .018) and escitalopram/citalopram (ES = -0.33, 95% CI = -0.59 to -0.07; p = .012) outperformed placebo, but paroxetine (ES = -0.19, 95% CI = -0.58 to 0.19; p = .33) did not. Results were similar in populations selected for depression as those not. Across studies, baseline insulin resistance (p = .46), treatment duration (p = .47), diabetes status (p = .41), and weight loss (p = .93) did not moderate changes. Heterogeneity for all analyses was nonsignificant.

CONCLUSIONS

SSRIs seem to have an association with improvement in glycemia, which is not moderated by depression status, diabetes status, or change in weight across studies. Future powered trials with longer treatment duration are needed to confirm these findings.

REGISTRATION

PROSPERO ID: CRD4201809239.

Escitalopram population pharmacokinetics in people living with human immunodeficiency virus and in the psychiatric population: Drug-drug interactions and probability of target attainment

AIMS

The aims of this study were to characterize escitalopram pharmacokinetic profile, to identify factors influencing drug exposure, notably drug-drug interactions with antiretrovirals, and to simulate expected exposure under standard dosage regimen.

METHODS

A population pharmacokinetic analysis was performed using NONMEM. A total of 159 plasma concentration measurements were obtained from 39 human immunodeficiency virus (HIV)-infected and 71 uninfected psychiatric patients. The influence of age, weight, sex, HIV and psychiatric cohorts, racemic citalopram treatment, and comedications on oral clearance was examined. Simulations served to calculate the percentage of patients expected to be under- or over-exposed, considering established therapeutic targets (15-80 ng/mL).

RESULTS

A 1-compartment model with first-order absorption and elimination described the data adequately. The average escitalopram clearance and volume of distribution were 23.1 L/h (interindividual variability 51%), and 920 L, respectively. Escitalopram disposition did not differ between HIV-infected and uninfected patients, and was not affected by antiretroviral treatments. Coadministration of at least 1 proton-pump inhibitor (CYP2C19 inhibitor) modestly influenced escitalopram elimination (clearance decreased by 19%), with limited clinical relevance. Model-based simulations showed that, under a standard regimen of 10 mg once daily, a significant proportion of patients (56%) might be under-exposed.

CONCLUSION

The variability in escitalopram disposition is large and poorly explained by demographic, clinical and environmental covariates, thus suggesting a role for dosage individualization based on therapeutic drug monitoring in case of poor clinical response. Escitalopram disposition is modestly impacted by comedications and therefore no a priori dosage adjustments are needed in patients receiving antiretroviral treatments, including boosted regimens.

Pharmacogenomics-Driven Prediction of Antidepressant Treatment Outcomes: A Machine-Learning Approach With Multi-trial Replication

We set out to determine whether machine learning–based algorithms that included functionally validated pharmacogenomic biomarkers joined with clinical measures could predict selective serotonin reuptake inhibitor (SSRI) remission/response in patients with major depressive disorder (MDD). We studied 1,030 white outpatients with MDD treated with citalopram/escitalopram in the Mayo Clinic Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN‐AMPS; n = 398), Sequenced Treatment Alternatives to Relieve Depression (STAR*D; n = 467), and International SSRI Pharmacogenomics Consortium (ISPC; n = 165) trials. A genomewide association study for PGRN‐AMPS plasma metabolites associated with SSRI response (serotonin) and baseline MDD severity (kynurenine) identified single nucleotide polymorphisms (SNPs) in DEFB1,ERICH3,AHR, and TSPAN5 that we tested as predictors. Supervised machine‐learning methods trained using SNPs and total baseline depression scores predicted remission and response at 8 weeks with area under the receiver operating curve (AUC) > 0.7 (P < 0.04) in PGRN‐AMPS patients, with comparable prediction accuracies > 69% (P ≤ 0.07) in STAR*D and ISPC. These results demonstrate that machine learning can achieve accurate and, importantly, replicable prediction of SSRI therapy response using total baseline depression severity combined with pharmacogenomic biomarkers.

Citalopram overdose and severe serotonin syndrome in an intermediate metabolizing patient

INTRODUCTION

Citalopram is a selective serotonin reuptake inhibitor used for treatment of depression. Metabolism is primarily through CYP3A4 and CYP2C19; activity of the latter can vary depending on genetics. Although rare after single agent exposure, large citalopram ingestions can lead to serotonin syndrome. We report a case of citalopram overdose in an intermediate CYP2C19 metabolizer complicated by severe serotonin syndrome.

CASE DETAILS

A 25-year-old female presented after intentional citalopram overdose with seizures, tachycardia, persistent neuromuscular findings, and severe hyperthermia requiring aggressive sedation and cooling. Protracted symptoms required critical care services throughout a 14 day hospital stay despite traditional treatment of serotonin syndrome. Pharmacogenomic studies revealed intermediate CYP2C19 metabolism which reduces citalopram inactivation and may cause increased levels and toxicity.

DISCUSSION

In the majority of serotonin syndrome cases, symptoms resolve rapidly after treatment initiation and discontinuation of the offending agents. Severe cases are typically associated with ingestion of multiple serotonergic agents. Our patient had severe toxicity after single agent ingestion. Pharmacogenetic testing identified abnormal CYP2C19 activity and previous cases have associated enzyme dysfunction and citalopram toxicity.

CONCLUSION

Citalopram overdose may be associated with severe serotonin syndrome and further investigation is warranted to understand the impact of enzyme genotype on toxicity.

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.

Influence of CYP2C19 Metabolizer Status on Escitalopram/Citalopram Tolerability and Response in Youth With Anxiety and Depressive Disorders

In pediatric patients, the selective serotonin reuptake inhibitors (SSRIs) escitalopram and citalopram (es/citalopram) are commonly prescribed for anxiety and depressive disorders. However, pharmacogenetic studies examining CYP2C19 metabolizer status and es/citalopram treatment outcomes have largely focused on adults. We report a retrospective study of electronic medical record data from 263 youth < 19 years of age with anxiety and/or depressive disorders prescribed escitalopram or citalopram who underwent routine clinical CYP2C19 genotyping. Slower CYP2C19 metabolizers experienced more untoward effects than faster metabolizers (p = 0.015), including activation symptoms (p = 0.029) and had more rapid weight gain (p = 0.018). A larger proportion of slower metabolizers discontinued treatment with es/citalopram than normal metabolizers (p = 0.007). Meanwhile, faster metabolizers responded more quickly to es/citalopram (p = 0.005) and trended toward less time spent in subsequent hospitalizations (p = 0.06). These results highlight a disparity in treatment outcomes with es/citalopram treatment in youth with anxiety and/or depressive disorders when standardized dosing strategies were used without consideration of CYP2C19 metabolizer status. Larger, prospective trials are warranted to assess whether tailored dosing of es/citalopram based on CYP2C19 metabolizer status improves treatment outcomes in this patient population.

Effects of Cytochrome P450 (CYP) 2C19 Genotypes on Steady-State Plasma Concentrations of Escitalopram and its Desmethyl Metabolite in Japanese Patients With Depression

Background:

Plasma concentrations of the S-enantiomer of citalopram were different between extensive and poor CYP2C19 metabolizers in healthy subjects and depressed patients. However, most studies applied dose-corrected concentrations. Thus, we studied the effects of polymorphisms of the CYP2C19 gene on raw plasma drug concentrations in Japanese patients with depression.

Methods:

Subjects in this study consisted of 412 depressed patients receiving 5, 10, 15, or 20 mg of escitalopram once a day. Plasma concentrations of escitalopram and desmethylescitalopram were quantified using HPLC. CYP2C19 genotypes were identified using polymerase chain reaction methods.

Results:

There were no differences in the steady-state plasma concentrations of escitalopram or desmethylescitalopram in each dose group (5, 10, 15, or 20 mg of escitalopram) among CYP2C19 genotype groups. However, 1-way analysis of variance showed significant effects of CYP2C19 genotypes on the dose-adjusted plasma concentration of escitalopram but not in the dose-adjusted plasma concentration of desmethylescitalopram. Analysis of covariance including age, sex, and body weight showed significant effects of CYP2C19 genotypes on the dose-adjusted plasma concentration of escitalopram and the ratio of desmethylescitalopram to escitalopram.

Conclusions:

These findings suggest that the CYP2C19 variants are associated with steady-state plasma concentrations of escitalopram to some extent but are not associated with desmethylescitalopram.

Completed suicides of citalopram users-the role of CYP genotypes and adverse drug interactions

Depression is known to be a risk factor for suicide. Currently, the most used antidepressants are selective serotonin reuptake inhibitors (SSRIs). Not all users, however, benefit from them. In such cases, treatment failure can be explained in part by genetic differences. In this study, we investigated the role of pharmacogenetic factors in citalopram-positive completed suicides (n = 349). Since citalopram is metabolized by CYP2C19 and CYP2D6 enzymes, the study population was genotyped for clinically relevant CYP2C19 and CYP2D6 polymorphisms and CYP2D6 copy number variation. To assess genetic differences between suicide cases and Finns in general, Finnish population samples (n = 855) were used as controls. Also, the role of drug interactions among suicide cases was evaluated. We found enrichment of a combined group of genetically predicted poor and ultrarapid metabolizer phenotypes (gMPs) of CYP2C19 among suicide victims compared to controls 0.356 [0.31-0.41] vs. 0.265 [0.24-0.30] (p = 0.0065). In CYP2D6 gMPs, there was no difference between cases and controls when the study population was analyzed as a whole. However, there were significantly more poor metabolizers among females who committed suicide by poisoning compared to female controls. In 8% of all drug poisoning deaths, lifetime drug-drug interaction was evaluated having a contribution to the fatal outcome. From clinical perspective, pharmacogenetic testing prior to initiation of SSRI drug could be beneficial. It may also be useful in medico-legal settings as it may elucidate obscure poisoning cases. Also, the possibility of unintentional drug interactions should be taken into account in drug poisoning deaths.

Pharmacogenomic Testing in Child and Adolescent Psychiatry: An Evidence-Based Review

Significant advances have been made in the application of pharmacogenomic testing for the treatment of patients with psychiatric disorders. Over the past decade, a number of studies have evaluated the utility of pharmacogenomic testing in pediatric patients with psychiatric disorders. The evidence base for pharmacogenomic testing in youth with depressive and anxiety disorders as well as attention/deficit hyperactivity disorder (ADHD) is reviewed in this article. General pharmacogenomic principles are summarized and functional polymorphisms in P450 enzymes (and associated metabolizer phenotypes), the serotonin transporter promoter polymorphisms, serotonin 2A receptor genes (e.g., HT2AR) and catecholamine pathway genes (e.g., COMT) are reviewed. These commonly tested pharmacogenomic markers are discussed with regard to studies of drug levels, efficacy and side effects. The translation of pharmacogenomics to individualized/precision medicine in pediatric patients with ADHD, anxiety and depressive disorders has accelerated; however, its application remains challenging given that there are numerous divergent pathways between medication/medication dose and clinical response and side effects. Nonetheless, by leveraging variations in individual genes that may be relevant to medication metabolism or medication target engagement, pharmacogenomic testing may have a role in predicting treatment response, side effects and medication selection in youth with ADHD, depressive and anxiety disorders.

Functional characterization of CYP2C19 variants in nebivolol 4-hydroxlation in vitro

Cytochrome P450 2C19 (CYP2C19) allelic variants are thought to play an important part in inter-individual variability in drug metabolism. We evaluated the in vitro hydroxylation of nebivolol by 31 CYP2C19 alleles identified in a Chinese Han population recently. Wild-type CYP2C19*1B and 30 isoforms were highly expressed in insect cells, and the enzymatic activities of CYP2C19 variants towards nebivolol hydroxylation were characterized. Among the 30 CYP2C19 alleles, most of the recombinant CYP2C19 variants exhibited no or significantly low activity compared with CYP2C19*1B. Three variants, CYP2C19*29 (K28I), L16F, and CYP2C19*23 (G91R), showed increased intrinsic clearance of >140% CYP2C19*1B. Combined with a previous study on the effects of CYP2D6 variants on nebivolol metabolism, our comprehensive analyses on the enzymatic activities of CYP2C19 variants towards nebivolol in the present study may contribute to determination of the optimal doses of nebivolol for the treatment of hypertension and understanding of "individualized" medication.

The relationship of SSRI and SNRI usage with interstitial lung disease and bronchiectasis in an elderly population: a case-control study

Background

The association between interstitial lung disease (ILD) and selective serotonin reuptake inhibitors and serotonin norepinephrine reuptake inhibitors (SSRI/SNRI) has been previously described in published case reports. However, its prevalence may be more common than expected. We examined the association between SSRI/SNRI usage and presence of ILD and or bronchiectasis (ILD/B) in an elderly population.

Methods

We conducted a retrospective case series and case–control study involving all 296 eligible elderly patients in one primary care geriatric practice in Victoria, BC, Canada. Cases required the presence of ILD/B on computed tomography (CT) or chest X-ray (CXR). Cases were excluded if they had other causes for ILD/B on CXR or CT such as exposure to known pneumotoxic drugs, metastatic cancer, rheumatoid lung disease, sarcoidosis, previous pulmonary tuberculosis, or pneumoconiosis. Data were abstracted from the patients’ medical record. The exposure variable was standardized cumulative person-month (p-m) dose of SSRI/SNRI. The study was approved by the Clinical Research Ethics Board of University of British Columbia with a waiver of informed consent.

Results

A total of 12 cases and 273 controls were identified. Their mean ages were 89.0 and 88.7 years, respectively (p=0.862). A total of 10/12 cases and 99/273 controls were exposed to SSRI/SNRI. The odds ratio was 8.79, 95% confidence interval 2.40–32.23 (p=0.001). The median p-m exposure to SSRI/SNRI was 110.0 months for cases and 29.5 for controls (p=0.003).

Conclusion

SSRIs and SNRIs were significantly associated with the risk of ILD/B in this elderly population. Because of their widespread usage, further studies should be done to validate these findings. Prescribers should cautiously monitor patients for development of insidious pulmonary symptoms when these drugs are used.

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.

CYP2C19*17 protects against metabolic complications of clozapine treatment

OBJECTIVES

Clozapine (CZ) is the most effective drug for managing treatment-resistant schizophrenic disorders. Its use has been limited due to adverse effects, which include weight gain and new-onset diabetes, but the incidence of these varies between patients.

METHODS

We investigated 187 Clozapine Clinic patients (of whom 137 consented for genotyping) for the presence of CYP2C19*17 and its association with CZ and norclozapine (NCZ) levels, and clinical outcomes.

RESULTS

Thirty-nine percent of genotyped patients were carriers of the CYP2C 19*17 polymorphism. This group demonstrated significantly higher NCZ serum levels, and significantly lower fasting glucose (5.66 ± 1.19 vs 6.72 ± 3.01 mmol/l, P = 0.009) and Hb1Ac (35.36 ± 4.78 vs 49.40 ± 20.60 mmol/mol, P = 0.006) levels compared to non-carriers of this polymorphism. CZ-treated patients with CYP2C19*17/*17 had a significantly lower prevalence of diabetes as well as a higher likelihood of clinical improvement of their schizophrenia, compared to those without this polymorphism (P = 0.012 and P = 0.031, respectively).

CONCLUSIONS

Our data suggest that CYP2C19*17 ultra-rapid-metaboliser status is a protective factor against the development of diabetes during clozapine treatment, and increases the likelihood of improvement in schizophrenia. The role of NCZ in treatment response and side effects, including metabolic syndrome, warrants further pharmacogenetic, pharmacokinetic and pharmacodynamic studies.

Personalized prescribing: a new medical model for clinical implementation of psychotropic drugs

The use of pharmacogenetic tests was already being proposed in psychiatry in the early 2000s because genetic factors were known to influence drug pharmacokinetics and pharmacodynamics. However, sufficient levels of evidence to justify routine use have been achieved for only a few tests (eg, major histocompatibility complex, class I, B, allele 1502 [HLA-B*1502] for carbamazepine in epilepsy and bipolar disorders); many findings are too preliminary or, when replicated, of low clinical relevance because of a small effect size. Although drug selection and dose adaptation according to cytochrome P450 genotypes are sound, a large number of patients need to be genotyped in order to prevent one case of severe side effect and/or nonresponse. The decrease in cost for genetic analysis shifts the cost: benefit ratio toward increasing use of pharmacogenetic tests. However, they have to be combined with careful clinical evaluations and other tools (eg, therapeutic drug monitoring and phenotyping) to contribute to the general aim of providing the best care for psychiatric patients.