Estimation of CYP2D6*10 genotypes on citalopram disposition in Chinese subjects by population pharmacokinetic assay

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.

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

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

High Emotional and Sexual Satisfaction Among Partnered Midlife Canadians: Associations with Relationship Characteristics, Sexual Activity and Communication, and Health

Despite midlife adults accounting for a substantial and growing segment of the population, few large-scale studies have investigated factors which distinguish highly satisfying relationships from less satisfying ones in midlife. In a subsample of partnered 40-59-year-old Canadians (705 men, 743 women), relationship characteristics, sexual activity and communication, and health were investigated individually and simultaneously as predictors of high emotional and sexual satisfaction. Though the vast majority of participants reported being at least somewhat satisfied in their current relationship, less than half reported high satisfaction. For men and women, high emotional and sexual satisfactions were strongly linked. Logistic regressions indicated that longer relationships, dating relationships, and greater subjective overall health predicted high emotional satisfaction for men, whereas older age, married or cohabiting relationships, and frequent sexual communication predicted high emotional satisfaction for women. All types of sexual activities (minus penile-anal intercourse) were bivariately related to high emotional and sexual satisfaction. More frequent partnered sexual activity predicted high emotional and sexual satisfaction for men and women in regression analyses. More frequent sexual communication predicted high emotional satisfaction for women and high sexual satisfaction for both men and women. Newer relationships were more sexually satisfying for men. Postmenopausal women were less likely to be highly sexually satisfied. Findings suggest that physical health conditions are not generally related to high levels of satisfaction in midlife couples and that frequently discussing sex and engaging in (any) sexual activity with a partner are key components of highly satisfying relationships.

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.