Clinical Impact of Functional CYP2C19 and CYP2D6 Gene Variants on Treatment with Antidepressants in Young People with Depression: A Danish Cohort Study

From genes to drugs: CYP2C19 and pharmacogenetics in clinical practice

The CYP2C19 gene is frequently included in different pharmacogenomic panels tested in clinical practice, due to its involvement in the metabolism of a myriad of frequently prescribed medications. Accordingly, CYP2C19 genotyping can promote precise therapeutic decisions and avoid the occurrence of significant drug-drug-gene interactions in the clinical setting. A comprehensive examination of the role of the CYP2C19 gene in real-world medical settings is presented in this review. This review summarizes the most recent information on how genetic variants in CYP2C19 affect drug metabolism and therapeutic outcomes. It goes into the wide range of CYP2C19 phenotypes, with different degrees of metabolizing activity, and their implications for customized medication response through a review of the literature. The review also analyzes the clinical significance of CYP2C19 in several medical specialties, including cardiology, psychiatry, and gastro-enterology clinics, and illuminates how it affects pharmacological efficacy, safety, and adverse effects. Finally, CYP2C19-supported clinical decision-making is outlined, highlighting the possibility of improving therapeutic outcomes and achieving more affordable treatment options, a step towards optimizing healthcare provision through precision medicine.

Impact of Pharmacogenomics on Pediatric Psychotropic Medication Prescribing in an Ambulatory Care Setting

Objective: Evidence for pharmacogenomic (PGx) guided treatment in child and adolescent psychiatry is growing. This study evaluated the impact of PGx testing on psychotropic medication prescribing in an ambulatory child and adolescent psychiatry and a developmental pediatrics clinic. Methods: This was a single-center, retrospective, descriptive analysis of patients who underwent PGx testing between January 2015 and October 2022 at a child and adolescent psychiatry clinic or developmental pediatrics clinic. The primary outcome was the proportion of patients with at least one psychotropic medication modification made 6-month posttesting that could be attributed to CYP2C19, CYP2D6, HLA-B*15:02, or HLA-A*31:01. Secondary outcomes included reason for testing, types of therapeutic modifications made, and whether the therapeutic modifications concorded with PGx guidelines. Results: A total of 193 patients were analyzed. The average age was 10 ± 4 years old, 60% were male, 78% were Caucasian. Sixty-eight percent had a primary diagnosis of a neurodevelopmental disorder, namely autism spectrum disorder (51%), and attention-deficit/hyperactivity disorder (14%). The reasons for PGx testing included medication inefficacy (34%), medication intolerance (20%), and family request (19%). At the time of PGx testing, 37% of patients were taking ≥1 psychotropic medication with PGx annotation. Overall, 35 PGx-related therapeutic modifications were made in 32 (17%) patients. These included continuing current PGx medication (6.2%) and starting PGx medication (5.2%). These modifications mainly involved antidepressants. Out of these 35 PGx-related therapeutic modifications, 94% were concordant with PGx guidelines. Among 29 patients who were prescribed at least one CYP2D6 inhibitor, 25 (86%) underwent CYP2D6 phenoconversion. Conclusions: It is critical to apply pediatric age-specific considerations when utilizing PGx testing in child and adolescent psychiatry. PGx testing stewardship could provide a framework to guide the clinical utility of PGx in a pediatric population with mental health conditions, including neurodevelopmental disorders.

A Bibliometric and Visual Analysis of Single Nucleotide Polymorphism Studies in Depression

BACKGROUND

Genetic polymorphism has been proven to have an important association with depression, which can influence the risk of developing depression, the efficacy of medications, and adverse effects via metabolic and neurological pathways. Nonetheless, aspects of the association between single nucleotide polymorphisms and depression have not been systematically investigated by bibliometric analysis.

OBJECTIVE

The aim of this study was to analyze the current status and trends of single nucleotide polymorphism research on depression through bibliometric and visual analysis.

METHODS

The Web of Science Core Collection was used to retrieve 10,043 articles that were published between 1998 and 2021. CiteSpace (6.1 R4) was used to perform collaborative network analysis, co-citation analysis, co-occurrence analysis, and citation burst detection.

RESULTS

The most productive and co-cited journals were the Journal of Affective Disorders and Biological Psychiatry, respectively, and an analysis of the references showed that the most recent research focused on the largest thematic cluster, "5-HT", reflecting the important research base in this area. "CYP2D6" has been in the spotlight since its emergence in 2009 and has become a research hotspot since its outbreak in 2019. However, "BDNF ", "COMT ", "older adults", "loci", and "DNA methylation" are also the new frontier of research, and some of them are currently in the process of exploration.

CONCLUSION

These findings offer a useful perspective on existing research and potential future approaches in the study of the association between single nucleotide polymorphisms and depression, which may assist researchers in selecting appropriate collaborators or journals.

The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice

Precision medicine (PM), through the integration of omics and environmental data, aims to provide a more precise prevention, diagnosis, and treatment of disease. Currently, PM is one of the emerging approaches in modern healthcare and public health, with wide implications for health care delivery, public health policy making formulation, and entrepreneurial endeavors. In spite of its growing popularity and the buzz surrounding it, PM is still in its nascent phase, facing considerable challenges that need to be addressed and resolved for it to attain the acclaim for which it strives. In this article, we discuss some of the current methodological pitfalls of PM, including the use of big data, and provide a perspective on how these challenges can be overcome by bringing PM closer to evidence-based medicine (EBM). Furthermore, to maximize the potential of PM, we present real-world illustrations of how EBM principles can be integrated into a PM approach.

CYP2C19 loss-of-function alleles are not associated with higher prevalence of gastrointestinal bleeds in those who have been prescribed antidepressants: Analysis in a British-South Asian cohort

AIMS

CYP2C19 is a hepatic enzyme involved in the metabolism of antidepressants associated with increased gastrointestinal bleed (GIB) risk. The aim of our study was to explore a possible association between loss-of-function CYP2C19 genotypes and GIB in South Asian ancestry participants prescribed antidepressants.

METHODS

Genes & Health participants with a record in Barts Health NHS Trust (N 22 753) were studied using a cross-sectional approach. CYP2C19 diplotypes were assessed and metabolizer type inferred from consortia guidance. Fisher's exact test was used to compare the prevalence of GIB in different metabolizer categories. Multivariable regression was used to test for association between antidepressant prescriptions and GIB, and between CYP2C19 metabolizer state and GIB in the subcohort prescribed antidepressants.

RESULTS

Antidepressants were frequently prescribed (47%, N = 10 612). A total of 864 participants (4%) had a GIB; 534 (62%) had been prescribed a CYP2C19 metabolized antidepressant. There was an independent association between antidepressant prescriptions and GIB events (odds ratio 1.8, confidence interval 1.5-2.0, P < 0.0001). There was no relationship between CYP2C19 inferred poor (P 0.56) or intermediate (P 0.53) metabolizer status and GIB in those prescribed an antidepressant in unadjusted analysis. A multivariable logistic regression model did not show an independent association between poor (P 0.54) or intermediate (P 0.62) CYP2C19 metabolizers and GIB in the subcohort prescribed antidepressants.

CONCLUSIONS

CYP2C19 dependent antidepressants are associated with increased GIB prevalence. GIB appeared independent from CYP2C19 metabolizer genotype in individuals who had been prescribed antidepressants. Precision dosing based on CYP2C19 genetic information alone is unlikely to reduce GIB prevalence.

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.

The pharmacogenetics of CYP2D6 and CYP2C19 in a case series of antidepressant responses

Pharmacogenetics has potential for optimizing use of psychotropics. CYP2D6 and CYP2C19 are two clinically relevant pharmacogenes in the prescribing of antidepressants. Using cases recruited from the Understanding Drug Reactions Using Genomic Sequencing (UDRUGS) study, we aimed to evaluate the clinical utility of genotyping CYP2D6 and CYP2C19 in antidepressant response. Genomic and clinical data for patients who were prescribed antidepressants for mental health disorders, and experienced adverse reactions (ADRs) or ineffectiveness, were extracted for analysis. Genotype-inferred phenotyping of CYP2D6 and CYP2C19 was carried out as per Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A total of 52 patients, predominantly New Zealand Europeans (85%) with a median age (range) of 36 years (15-73), were eligible for analysis. Thirty-one (60%) reported ADRs, 11 (21%) ineffectiveness, and 10 (19%) reported both. There were 19 CYP2C19 NMs, 15 IMs, 16 RMs, one PM and one UM. For CYP2D6, there were 22 NMs, 22 IMs, four PMs, three UMs, and one indeterminate. CPIC assigned a level to each gene-drug pair based on curated genotype-to-phenotype evidence. We analyzed a subgroup of 45 cases, inclusive of response type (ADRs/ineffectiveness). Seventy-nine (N = 37 for CYP2D6, N = 42 for CYP2C19) gene-drug/antidepressant-response pairs with CPIC evidence levels of A, A/B, or B were identified. Pairs were assigned as 'actionable' if the CYP phenotypes potentially contributed to the observed response. We observed actionability in 41% (15/37) of CYP2D6-antidepressant-response pairs and 36% (15/42) of CYP2C19-antidepressant-response pairs. In this cohort, CYP2D6 and CYP2C19 genotypes were actionable for a total of 38% pairs, consisting of 48% in relation to ADRs and 21% in relation to drug ineffectiveness.

Pediatric considerations for pharmacogenetic selective serotonin reuptake inhibitors clinical decision support

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

Validation of Pharmacogenomic Interaction Probability (PIP) Scores in Predicting Drug-Gene, Drug-Drug-Gene, and Drug-Gene-Gene Interaction Risks in a Large Patient Population

Utilizing pharmacogenomic (PGx) testing and integrating evidence-based guidance in drug therapy enables an improved treatment response and decreases the occurrence of adverse drug events. We conducted a retrospective analysis to validate the YouScript^® PGx interaction probability (PIP) algorithm, which predicts patients for whom PGx testing would identify one or more evidence-based, actionable drug-gene, drug-drug-gene, or drug-gene-gene interactions (EADGIs). PIP scores generated for 36,511 patients were assessed according to the results of PGx multigene panel testing. PIP scores versus the proportion of patients in whom at least one EADGI was found were 22.4% vs. 22.4% (p = 1.000), 23.5% vs. 23.4% (p = 0.6895), 30.9% vs. 29.4% (p = 0.0667), and 27.3% vs. 26.4% (p = 0.3583) for patients tested with a minimum of 3-, 5-, 14-, and 25-gene panels, respectively. These data suggest a striking concordance between the PIP scores and the EAGDIs found by gene panel testing. The ability to identify patients most likely to benefit from PGx testing has the potential to reduce health care costs, enable patient access to personalized medicine, and ultimately improve drug efficacy and safety.