Effect of CYP2D6 pharmacogenetic phenotype and phenoconversion on serum concentrations of antidepressants and antipsychotics: a retrospective cohort study

Risk Phenotypes, Comorbidities, Pharmacotherapy, and Electroconvulsive Therapy (ECT) in a Cohort with Difficult-to-Treat Depression in Comparison to an Unmedicated Control Group

BACKGROUND

Approximately 15-25% of depressed patients suffer from difficult-to-treat depression (DTD). Patients with DTD require a thorough examination to avoid the oversight of treatable (psychiatric/somatic) comorbidities or (pseudo-)resistance to antidepressant drugs (ADs). Polymorphisms of the cytochrome P450 (CYP) enzymes 2D6 and 2C19, which play a major role in the metabolism of ADs, may contribute to resistance to ADs. Patients with DTD might benefit from electroconvulsive therapy (ECT).

METHODS

We enrolled 109 patients with DTD and 29 untreated depressed controls (UDC). We assessed risk phenotypes, comorbidities, and treatment, including ECT. We also performed pharmacokinetic analyses of CYP2D6 and CYP2C19.

RESULTS

DTD patients significantly more often suffered from comorbid psychiatric diseases, especially ICD-10: F40-F48 (DTD:40.4%, UDC:17.2%, OR 11.87, p=0.011) than UDC patients. DTD patients receiving ECT were more likely to achieve remission (37.7% vs. 11.8%, OR=3.96, p=0.023). Treatment with ADs did not differ between remitters and non-remitters. No significant differences were observed in the distribution of CYP2D6 and CYP2C19 variants between both groups.

CONCLUSION

Patients with DTD appear to experience comorbid neurotic stress and somatoform disorders (ICD-10: F40 - F48) more frequently. Therefore, a comprehensive differential diagnosis is crucial when patients do not respond sufficiently to antidepressant medication. Genotyping CYP2D6 and CYP2C19 should be considered.

Precision dosing for patients on tricyclic antidepressants

OBJECTIVE

We aim to develop a personalized dosing tool for tricyclic antidepressants (TCAs) that integrates CYP2D6 and CYP2C19 gene variants and their effects while also considering the polypharmacy effect.

METHODS

The study first adopted a scoring system that assigns weights to each genetic variant. A formula was then developed to compute the effect of both genes' variants on drug dosing. The output of the formula was assessed by a comparison with the clinical pharmacogenetics implementation consortium recommendation. The study also accounts for the effect of the co-administration of inhibitors and inducers on drug metabolism. Accordingly, a user-friendly tool, Clinical Dosing Tool ver.2, was created to assist clinicians in dosing patients on TCAs.

RESULTS

The study provides a comprehensive list of all alleles with corresponding activity values and phenotypes for both enzymes. The tool calculated an updated area under the curve ratio that utilizes the effects of both enzymes' variants for dose adjustment. The tool provided a more accurate individualized dosing that also integrates the polypharmacy effect.

CONCLUSION

To the best of our knowledge, the literature misses such a tool that provides a numerical adjusted dose based on continuous numerical activity scores for the considered patients' alleles and phenoconversion.

Frequencies of CYP2C19 and CYP2D6 gene variants in a German inpatient sample with mood and anxiety disorders

OBJECTIVES

Previous results demonstrated that CYP2D6 and CYP2C19 gene variants affect serum concentrations of antidepressants. We implemented a PGx service determining gene variants in CYP2D6 and CYP2C19 in our clinical routine care and report on our first patient cohort.

METHODS

We analysed CYP2D6 and CYP2C19 allele, genotype, and phenotype frequencies, and actionable pharmacogenetic variants in this German psychiatric inpatient cohort. Two-tailed z-test was used to investigate for differences in CYP2D6 and CYP2C19 phenotypes and actionable/non-actionable genetic variant frequencies between our cohort and reference cohorts.

RESULTS

Out of the 154 patients included, 44.8% of patients were classified as CYP2D6 normal metabolizer, 38.3% as intermediate metabolizers, 8.4% as poor metabolizers, and 2.6% as ultrarapid metabolizers. As for CYP2C19, 40.9% of patients were classified as normal metabolizers, 19.5% as intermediate metabolizers, 2.6% as poor metabolizers, 31.2% as rapid metabolizers, and 5.8% as ultrarapid metabolizers. Approximately, 80% of patients had at least one actionable PGx variant.

CONCLUSION

There is a high prevalence of actionable PGx variants in psychiatric inpatients which may affect treatment response. Physicians should refer to PGx-informed dosing guidelines in carriers of these variants. Pre-emptive PGx testing in general may facilitate precision medicine also for other drugs metabolised by CYP2D6 and/or CYP2C19.

Assessing Pharmacokinetic Correlates of Escitalopram-Related Adverse Drug Reactions

BACKGROUND

To assess the pharmacokinetic correlates of reported adverse drug reactions (ADRs) under antidepressant treatment with escitalopram (ESC) using a large therapeutic drug monitoring database.

METHODS

A large naturalistic sample of inpatients and outpatients prescribed ESC was analyzed. ADRs were classified using the Udvalg for Kliniske Undersogelser side effect rating scale. We compared ESC-treated patients with (n = 35) and without ADRs (n = 273) using ESC plasma concentrations as the primary outcome. We also compared ADR rates in the 2 groups based on 2 cut-off ESC levels reflecting the recommended upper thresholds of the therapeutic reference range of 80 ng/mL, suggested by the consensus therapeutic drug monitoring guidelines, and 40 ng/mL, based on recent meta-analysis data. The effects of age, sex, smoking, daily ESC dose, plasma concentrations, and concentrations corrected for daily dose were included in a binary logistic regression model to predict ADRs.

RESULTS

No differences in clinical, demographic, or pharmacokinetic parameters were observed between patients with and without ADRs ( P > 0.05). Patients with ESC-related ADRs were more frequently diagnosed with psychotic disorders than those without (25% vs. 7.1%, P = 0.004). None of the variables was associated with ADR risk. Overall, ADR rates were not significantly different in patients above versus below thresholds of ESC concentrations (ESC concentrations >40 [n = 59] vs. ≤40 ng/mL [n = 249] and >80 [n = 8] vs. ≤80 ng/mL [n = 300]; P = 0.56 and P = 1.0, respectively).

CONCLUSIONS

No distinct pharmacokinetic patterns underlying ESC-associated ADRs were observed. Further studies with more specific assessments of ADRs in larger cohorts are required to better identify potential underlying patterns.

The Relevance of Integrating CYP2C19 Phenoconversion Effects into Clinical Pharmacogenetics

INTRODUCTION

CYP2D6 and CYP2C19 functional status as defined by genotype is modulated by phenoconversion (PC) due to pharmacokinetic interactions. As of today, there is no data on the effect size of PC for CYP2C19 functional status. The primary aim of this study was to investigate the impact of PC on CYP2C19 functional status.

METHODS

Two patient cohorts (total n=316; 44.2±15.4 years) were investigated for the functional enzyme status of CYP2C19 applying two different correction methods (PCBousman, PCHahn&Roll) as well as serum concentration and metabolite-to-parent ratio of venlafaxine, amitriptyline, mirtazapine, sertraline, escitalopram, risperidone, and quetiapine.

RESULTS

There was a decrease in the number of normal metabolizers of CYP2C19 and an increase in the number of poor metabolizers. When controlled for age, sex, and, in the case of amitriptyline, venlafaxine, and risperidone, CYP2D6 functional enzyme status, an association was observed between the CYP2C19 phenotype/functional enzyme status and serum concentration of amitriptyline, sertraline, and escitalopram.

DISCUSSION

PC of CYP2C19 changes phenotypes but does not improve correlations with serum concentrations. However, only a limited number of patients received perturbators of CYP2C19. Studies with large numbers of patients are still lacking, and thus, it cannot be decided if there are minor differences and which method of correction to use. For the time being, PC is relevant in individual patients treated with CYP2C19-affecting drugs, for example, esomeprazole. To ensure adequate serum concentrations in these patients, this study suggests the use of therapeutic drug monitoring.

Clinical Utility and Implementation of Pharmacogenomics for the Personalisation of Antipsychotic Treatments

Decades of pharmacogenetic research have revealed genetic biomarkers of clinical response to antipsychotics. Genetic variants in antipsychotic targets, dopamine and serotonin receptors in particular, and in metabolic enzymes have been associated with the efficacy and toxicity of antipsychotic treatments. However, genetic prediction of antipsychotic response based on these biomarkers is far from accurate. Despite the clinical validity of these findings, the clinical utility remains unclear. Nevertheless, genetic information on CYP metabolic enzymes responsible for the biotransformation of most commercially available antipsychotics has proven to be effective for the personalisation of clinical dosing, resulting in a reduction of induced side effects and in an increase in efficacy. However, pharmacogenetic information is rarely used in psychiatric settings as a prescription aid. Lack of studies on cost-effectiveness, absence of clinical guidelines based on pharmacogenetic biomarkers for several commonly used antipsychotics, the cost of genetic testing and the delay in results delivery hamper the implementation of pharmacogenetic interventions in clinical settings. This narrative review will comment on the existing pharmacogenetic information, the clinical utility of pharmacogenetic findings, and their current and future implementations.

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.