How to Integrate CYP2D6 Phenoconversion Into Clinical Pharmacogenetics: A Tutorial

Role of CYP2D6 and CYP3A4 polymorphisms on aripiprazole and dehydroaripiprazole concentrations in patients undergoing long-acting treatment

Aripiprazole once-monthly (AOM) exhibits an important interindividual pharmacokinetic variability with significant implications for its clinical use. CYP2D6 and CYP3A4 highly contributes to this variability, as they metabolize aripiprazole (ARI) into its active metabolite, dehydroaripiprazole (DHA) and the latter into inactive metabolites. This study aims to evaluate the effect of CYP2D6 and CYP3A4 polymorphisms in combination and the presence of concomitant inducers and inhibitors of this cytochromes on ARI and DHA plasma concentrations in a real clinical setting. An observational study of a cohort of 74 Caucasian patients under AOM treatment was conducted. Regarding CYP2D6, higher concentrations were found for active moiety (ARI plus DHA) (AM) (67 %), ARI (67 %) and ARI/DHA ratio (77 %) for poor metabolizers (PMs) compared to normal metabolizers (NMs). No differences were found for DHA. PMs for both CYP2D6 and CYP3A4 showed a 58 % higher AM and 66 % higher plasma concentration for ARI compared with PMs for CYP2D6 and NMs for CYP3A4. In addition, PMs for both CYP2D6 and CYP3A4 have 45 % higher DHA concentrations than NMs for both cytochromes and 41 % more DHA than PMs for CYP2D6 and NMs for CYP3A4, suggesting a significant role of CYP3A4 in the elimination of DHA. Evaluating the effect of CYPD26 and CYP3A4 metabolizing state in combination on plasma concentrations of ARI, DHA and parent-to-metabolite ratio, considering concomitant treatments with inducers and inhibitor, could optimize therapy for patients under AOM treatment.

Phenotypic Models of Drug-Drug-Gene Interactions Mediated by Cytochrome Drug-Metabolizing Enzymes

Genetic polymorphisms in drug metabolizing enzymes and drug-drug interactions are major sources of inadequate drug exposure and ensuing adverse effects or insufficient responses. The current challenge in assessing drug-drug gene interactions (DDGIs) for the development of precise dose adjustment recommendation systems is to take into account both simultaneously. Here, we analyze the static models of DDGI from in vivo data and focus on the concept of phenoconversion to model inhibition and genetic polymorphisms jointly. These models are applicable to datasets where pharmacokinetic information is missing and are being used in clinical support systems and consensus dose adjustment guidelines. We show that all such models can be handled by the same formal framework, and that models that differ at first sight are all versions of the same linear phenoconversion model. This model includes the linear pharmacogenetic and inhibition models as special cases. We highlight present challenges in this endeavor and the open issues for future research in developing DDGI models for recommendation systems.

Implementing a pragmatic clinical trial to tailor opioids for chronic pain on behalf of the IGNITE ADOPT PGx investigators

Chronic pain is a prevalent condition with enormous economic burden. Opioids such as tramadol, codeine, and hydrocodone are commonly used to treat chronic pain; these drugs are activated to more potent opioid receptor agonists by the hepatic CYP2D6 enzyme. Results from clinical studies and mechanistic understandings suggest that CYP2D6-guided therapy will improve pain control and reduce adverse drug events. However, CYP2D6 is rarely used in clinical practice due in part to the demand for additional clinical trial evidence. Thus, we designed the ADOPT-PGx (A Depression and Opioid Pragmatic Trial in Pharmacogenetics) chronic pain study, a multicenter, pragmatic, randomized controlled clinical trial, to assess the effect of CYP2D6 testing on pain management. The study enrolled 1048 participants who are taking or being considered for treatment with CYP2D6-impacted opioids for their chronic pain. Participants were randomized to receive immediate or delayed (by 6 months) genotyping of CYP2D6 with clinical decision support (CDS). CDS encouraged the providers to follow the CYP2D6-guided trial recommendations. The primary study outcome is the 3-month absolute change in the composite pain intensity score assessed using Patient-Reported Outcomes Measurement Information System (PROMIS) measures. Follow-up will be completed in July 2024. Herein, we describe the design of this trial along with challenges encountered during enrollment.

Phenoconversion Due to Drug-Drug Interactions in CYP2C19 Genotyped Healthy Volunteers

To compensate for drug response variability, drug metabolism phenotypes are determined based on the results of genetic testing, and if necessary, drug dosages are adjusted. In some cases, discrepancies between predicted and observed phenotypes (phenoconversion) may occur due to drug-drug interactions caused by concomitant medications. We conducted a prospective, exploratory study to evaluate the risk of CYP2C19 phenoconversion in genotyped healthy volunteers exposed to CYP2C19 inhibitors. Three groups of volunteers were enrolled: CYP2C19 g-RM, g-NM, and g-IM (g- for genetically predicted). All volunteers received as CYP2C19 phenotyping substrate 10 mg omeprazole (OME) alone at the control session and in co-administration with CYP2C19 inhibitors: voriconazole 400 mg and fluvoxamine 50 mg in second and third study sessions, respectively. Phenoconversion occurred in over 80% of healthy volunteers, with variations among genotypic groups, revealing distinct proportions in response to fluvoxamine and voriconazole. Statistically significant differences were observed in mean metabolic ratios between CYP2C19 intermediate metabolizers (g-IMs) with *1/*2 and *2/*17 genotypes, with the *2/*17 group exhibiting lower ratios, and distinctions were noted between genotypic groups, emphasizing the impact of genetic variations on drug metabolism. When reclassified according to CYP2C19 baseline-measured phenotype into p-RM, p-NM, and p-IM (p- for measured phenotype), we observed 100% phenoconversion of p-RMs and a significant phenotype switch in p-NMs, p-IMs, and p-PMs after fluvoxamine and voriconazole, and complete phenoconversion of p-IMs to p-PMs on both inhibitors, emphasizing the impact of genetic variations on the vulnerability to CYP2C19 phenoconversion and the importance of considering both genotyping and phenotyping in predicting drug response.

Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC) for CYP2D6, ADRB1, ADRB2, ADRA2C, GRK4, and GRK5 Genotypes and Beta-Blocker Therapy

Beta-blockers are widely used medications for a variety of indications, including heart failure, myocardial infarction, cardiac arrhythmias, and hypertension. Genetic variability in pharmacokinetic (e.g., CYP2D6) and pharmacodynamic (e.g., ADRB1, ADRB2, ADRA2C, GRK4, GRK5) genes have been studied in relation to beta-blocker exposure and response. We searched and summarized the strength of the evidence linking beta-blocker exposure and response with the six genes listed above. The level of evidence was high for associations between CYP2D6 genetic variation and both metoprolol exposure and heart rate response. Evidence indicates that CYP2D6 poor metabolizers experience clinically significant greater exposure and lower heart rate in response to metoprolol compared with those who are not poor metabolizers. Therefore, we provide therapeutic recommendations regarding genetically predicted CYP2D6 metabolizer status and metoprolol therapy. However, there was insufficient evidence to make therapeutic recommendations for CYP2D6 and other beta-blockers or for any beta-blocker and the other five genes evaluated (updates at www.cpicpgx.org).

Effect of CYP2D6 genetic variation on patient-reported symptom improvement and side effects among children and adolescents treated with amphetamines

OBJECTIVES

Amphetamine-based medications are recommended as a first-line pharmacotherapy for the treatment of attention-deficit/hyperactivity disorder in children and adolescents. However, the efficacy and tolerability of these medications vary across individuals, which could be related to interindividual differences in amphetamine metabolism. This study examined if genotype-predicted phenotypes of the cytochrome P450 isozyme CYP2D6 were associated with self-reported side effects and symptom improvement in youth treated with amphetamines.

METHODS

Two hundred fourteen participants aged 6-24 who had a history of past or current amphetamine treatment were enrolled from Western Canada. Amphetamine dose and duration information was collected from the participants along with questions regarding adherence, concomitant medications, symptom improvement and side effects. DNA was extracted from saliva samples and genotyped for CYP2D6 . Binomial logistic regression models were used to determine the effect of CYP2D6 metabolizer phenotype with and without correction for phenoconversion on self-reported symptom improvement and side effects.

RESULTS

Genotype-predicted CYP2D6 poor metabolizers had significantly higher odds of reporting symptom improvement when compared to intermediate metabolizers (OR = 3.67, 95% CI = 1.15-11.7, P  = 0.029) after correction for phenoconversion and adjusting for sex, age, dose, duration, and adherence. There was no association between CYP2D6 metabolizer phenotype and self-reported side effects.

CONCLUSION

Our findings indicate that phenoconverted and genotype-predicted CYP2D6 poor metabolizer phenotype is significantly associated with higher odds of symptom improvement in children and adolescents treated with amphetamine. If replicated, these results could inform the development of future dosing guidelines for amphetamine treatment in children and adolescents.

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.

Rationale and design for a pragmatic randomized trial to assess gene-based prescribing for SSRIs in the treatment of depression

Specific selective serotonin reuptake inhibitors (SSRIs) metabolism is strongly influenced by two pharmacogenes, CYP2D6 and CYP2C19. However, the effectiveness of prospectively using pharmacogenetic variants to select or dose SSRIs for depression is uncertain in routine clinical practice. The objective of this prospective, multicenter, pragmatic randomized controlled trial is to determine the effectiveness of genotype-guided selection and dosing of antidepressants on control of depression in participants who are 8 years or older with ≥3 months of depressive symptoms who require new or revised therapy. Those randomized to the intervention arm undergo pharmacogenetic testing at baseline and receive a pharmacy consult and/or automated clinical decision support intervention based on an actionable phenotype, while those randomized to the control arm have pharmacogenetic testing at the end of 6-months. In both groups, depression and drug tolerability outcomes are assessed at baseline, 1 month, 3 months (primary), and 6 months. The primary end point is defined by change in Patient-Reported Outcomes Measurement Information System (PROMIS) Depression score assessed at 3 months versus baseline. Secondary end points include change inpatient health questionnaire (PHQ-8) measure of depression severity, remission rates defined by PROMIS score < 16, medication adherence, and medication side effects. The primary analysis will compare the PROMIS score difference between trial arms among those with an actionable CYP2D6 or CYP2C19 genetic result or a CYP2D6 drug-drug interaction. The trial has completed accrual of 1461 participants, of which 562 were found to have an actionable phenotype to date, and follow-up will be complete in April of 2024.

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.

Use of CYP2D6 Inhibitors with CYP2D6 Opioids: Association with Emergency Department Visits for Pain

Hydrocodone, tramadol, codeine, and oxycodone are commonly prescribed opioids that rely on activation by cytochrome P450 2D6 (CYP2D6). CYP2D6 inhibitors can significantly decrease CYP2D6 activity, leading to reduced generation of active metabolites, and impairing pain control. To understand this impact, we assessed emergency department (ED) visits in patients initiating these CYP2D6-dependent opioids while on CYP2D6-inhibitor antidepressants vs. antidepressants that do not inhibit CYP2D6. This retrospective cohort study included adult patients prescribed CYP2D6-dependent opioids utilizing electronic health records data from the University of Florida Health (2015-2021). The association between ED visits and inhibitor exposure was tested using multivariable logistic regression. The primary analysis had 12,118 patients (72% female; mean (SD) age, 55 (13.4)) in the hydrocodone/tramadol/codeine cohort and 5,547 patients (64% female; mean (SD) age, 53.6 (14.2)) in the oxycodone cohort. Hydrocodone/tramadol/codeine-treated patients exposed to CYP2D6-inhibitor antidepressants (n = 7,043) had a higher crude rate of pain-related ED visits than those taking other antidepressants (n = 5,075) (3.28% vs. 1.87%), with an adjusted odds ratio (aOR) of 1.75 (95% CI: 1.36 to 2.24). Similarly, in the oxycodone cohort, CYP2D6-inhibitor antidepressant-exposed individuals (n = 3,206) had a higher crude rate of ED visits than individuals exposed to other antidepressants (n = 2,341) (5.02% vs. 3.37%), with aOR of 1.70 (95% CI: 1.27-2.27). Similar findings were observed in secondary and sensitivity analyses. Our findings suggest patients with concomitant use of hydrocodone/tramadol/codeine or oxycodone and CYP2D6 inhibitors have more frequent ED visits for pain, which may be due to inadequate pain control.

Assessing user perspectives on clinical pharmacogenomics consultation documentation: a user-centered evaluation

The University of Florida Health Precision Medicine Program plays a crucial role in delivering pharmacogenomics (PGx) result notes to providers who request PGx testing. Despite this, there is currently a lack of a formal assessment of provider needs and established best practice design principles to guide the ongoing development of PGx result notes. This study aims to enhance the content and format of the PGx consult note at UF Health by incorporating valuable feedback from healthcare providers. Through in-depth user sessions involving 11 participants, we evaluated the usability of our consult note template. While overall satisfaction with the content was noted, specific sections, including those addressing phenoconversion and the medication list, were identified for revision to enhance clarity based on insightful provider feedback.

Proportion of Antipsychotics with CYP2D6 Pharmacogenetic (PGx) Associations Prescribed in an Early Intervention in Psychosis (EIP) Cohort: A Cross-Sectional Study

BACKGROUND

Prescribing drugs for psychosis (antipsychotics) is challenging due to high rates of poor treatment outcomes, which are in part explained by an individual's genetics. Pharmacogenomic (PGx) testing can help clinicians tailor the choice or dose of psychosis drugs to an individual's genetics, particularly psychosis drugs with known variable response due to CYP2D6 gene variants ('CYP2D6-PGx antipsychotics').

AIMS

This study aims to investigate differences between demographic groups prescribed 'CYP2D6-PGx antipsychotics' and estimate the proportion of patients eligible for PGx testing based on current pharmacogenomics guidance.

METHODS

A cross-sectional study took place extracting data from 243 patients' medical records to explore psychosis drug prescribing, including drug transitions. Demographic data such as age, sex, ethnicity, and clinical sub-team were collected and summarised. Descriptive statistics explored the proportion of 'CYP2D6-PGx antipsychotic' prescribing and the nature of transitions. We used logistic regression analysis to investigate associations between demographic variables and prescription of 'CYP2D6-PGx antipsychotic' versus 'non-CYP2D6-PGx antipsychotic'.

RESULTS

Two-thirds (164) of patients had been prescribed a 'CYP2D6-PGx antipsychotic' (aripiprazole, risperidone, haloperidol or zuclopenthixol). Over a fifth (23%) of patients would have met the suggested criteria for PGx testing, following two psychosis drug trials. There were no statistically significant differences between age, sex, or ethnicity in the likelihood of being prescribed a 'CYP2D6-PGx antipsychotic'.

CONCLUSIONS

This study demonstrated high rates of prescribing 'CYP2D6-PGx-antipsychotics' in an EIP cohort, providing a rationale for further exploration of how PGx testing can be implemented in EIP services to personalise the prescribing of drugs for psychosis.

Effect of CYP2D6, 2C19, and 3A4 Phenoconversion in Drug-Related Deaths

Molecular autopsy is a very important tool in forensic toxicology. However, many determinants, such as co-medication and physiological parameters, should be considered for optimal results. These determinants could cause phenoconversion (PC), a discrepancy between the real metabolic profile after phenoconversion and the phenotype determined by the genotype. This study's objective was to assess the PC of drug-metabolizing enzymes, namely CYP2D6, 2C19, and 3A4, in 45 post-mortem cases where medications that are substrates, inducers, or inhibitors of these enzymes were detected. It also intended to evaluate how PC affected the drug's metabolic ratio (MR) in four cases. Blood samples from 45 cases of drug-related deaths were analyzed to detect and determine drug and metabolite concentrations. Moreover, all the samples underwent genotyping utilizing the HaloPlex Target Enrichment System for CYP2D6, 2C19, and 3A4. The results of the present study revealed a statistically significant rate of PC for the three investigated enzymes, with a higher frequency of poor metabolizers after PC. A compatibility was seen between the results of the genomic evaluation after PC and the observed MRs of venlafaxine, citalopram, and fentanyl. This leads us to focus on the determinants causing PC that may be mainly induced by drug interactions. This complex phenomenon can have a significant impact on the analysis, interpretation of genotypes, and accurate conclusions in forensic toxicology. Nevertheless, more research with more cases in the future is needed to confirm these results.

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.

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.

Influence of CYP2D6 Metabolizer Status on Risperidone and Paliperidone Tolerability in Children and Adolescents

Background: Risperidone and, to a lesser extent, paliperidone are metabolized by CYP2D6; however, there are limited data related to variation in CYP2D6 phenotypes and the tolerability of these medications in children and adolescents. Furthermore, the impact of CYP2D6 on the association of risperidone and paliperidone with hyperprolactinemia in youth is not well understood. Methods: A retrospective chart review was performed in psychiatrically hospitalized children and adolescents prescribed risperidone (n = 263, age = 3-18 years, mean age = 13 ± 3 years, 49% female) or paliperidone (n = 124, age = 5-18 years, mean age = 15 ± 2 years, 44% female) who had CYP2D6 genotyping performed as part of routine care. CYP2D6 phenotypes were determined based on Clinical Pharmacogenetics Implementation Consortium guidelines and CYP2D6 inhibitors causing phenoconversion. Adverse effects were obtained from a review of the electronic health record, and patients were selected, in part, to enrich non-normal metabolizers. Results: Among risperidone-treated patients, 45% experienced an adverse effect, whereas 36% of paliperidone-treated patients experienced adverse effects. Discontinuation of risperidone due to lack of efficacy was more frequent in the CYP2D6 normal metabolizers and ultrarapid metabolizers compared with intermediate metabolizers (IMs) and phenoconverted poor metabolizers (pPMs) (54.5% vs. 32.7%, p < 0.001). Discontinuation due to weight gain was more common among risperidone- than paliperidone-treated patients (17% vs. 7%, p = 0.011). Among those taking paliperidone, CYP2D6 was associated with discontinuation due to side effects (p = 0.008), and youth with slower CYP2D6 metabolism (i.e., pPMs and IMs) were more likely to discontinue. Hyperprolactinemia was found in 10% of paliperidone-treated patients and 5% of risperidone-treated patients, and slower CYP2D6 metabolizers required higher risperidone doses to cause hyperprolactinemia (p = 0.011). Conclusions: CYP2D6 phenotype is associated with discontinuation of risperidone due to lack of efficacy and the dose of risperidone that induced hyperprolactinemia, as well as discontinuation of paliperidone due to adverse effects. Future studies should evaluate exposure-response and toxicity relationships in risperidone- and paliperidone-treated youth.

Assessment of Substrate Status of Drugs Metabolized by Polymorphic Cytochrome P450 (CYP) 2 Enzymes: An Analysis of a Large-Scale Dataset

BACKGROUND

The analysis of substrates of polymorphic cytochrome P450 (CYP) enzymes is important information to enable drug-drug interactions (DDIs) analysis and the relevance of pharmacogenetics in this context in large datasets. Our aim was to compare different approaches to assess the substrate properties of drugs for certain polymorphic CYP2 enzymes.

METHODS

A standardized manual method and an automatic method were developed and compared to assess the substrate properties for the metabolism of drugs by CYP2D6, 2C9, and 2C19. The automatic method used a matching approach to three freely available resources. We applied the manual and automatic methods to a large real-world dataset deriving from a prospective multicenter study collecting adverse drug reactions in emergency departments in Germany (ADRED).

RESULTS

In total, 23,878 medication entries relating to 895 different drugs were analyzed in the real-world dataset. The manual method was able to assess 12.2% (n = 109) of drugs, and the automatic method between 12.1% (n = 109) and 88.9% (n = 796), depending on the resource used. The CYP substrate classifications demonstrated moderate to almost perfect agreements for CYP2D6 and CYP2C19 (Cohen's Kappa (κ) 0.48-0.90) and fair to moderate agreements for CYP2C9 (κ 0.20-0.48).

CONCLUSION

A closer look at different classifications between methods revealed that both methods are prone to error in different ways. While the automated method excels in time efficiency, completeness, and actuality, the manual method might be better able to identify CYP2 substrates with clinical relevance.

The emergence, implementation, and future growth of pharmacogenomics in psychiatry: a narrative review

Psychotropic medication efficacy and tolerability are critical treatment issues faced by individuals with psychiatric disorders and their healthcare providers. For some people, it can take months to years of a trial-and-error process to identify a medication with the ideal efficacy and tolerability profile. Current strategies (e.g. clinical practice guidelines, treatment algorithms) for addressing this issue can be useful at the population level, but often fall short at the individual level. This is, in part, attributed to interindividual variation in genes that are involved in pharmacokinetic (i.e. absorption, distribution, metabolism, elimination) and pharmacodynamic (e.g. receptors, signaling pathways) processes that in large part, determine whether a medication will be efficacious or tolerable. A precision prescribing strategy know as pharmacogenomics (PGx) assesses these genomic variations, and uses it to inform selection and dosing of certain psychotropic medications. In this review, we describe the path that led to the emergence of PGx in psychiatry, the current evidence base and implementation status of PGx in the psychiatric clinic, and finally, the future growth potential of precision psychiatry via the convergence of the PGx-guided strategy with emerging technologies and approaches (i.e. pharmacoepigenomics, pharmacomicrobiomics, pharmacotranscriptomics, pharmacoproteomics, pharmacometabolomics) to personalize treatment of psychiatric disorders.

Pharmacogenetic Guidelines for Psychotropic Drugs: Optimizing Prescriptions in Clinical Practice

The modalities for prescribing a psychotropic (dose and choice of molecule) are currently unsatisfactory, which can lead to a lack of efficacy of the treatment associated with prolonged exposure of the patient to the symptoms of his or her illness and the side effects of the molecule. In order to improve the quality of treatment prescription, a part of the current biomedical research is dedicated to the development of pharmacogenetic tools for individualized prescription. In this guideline, we will present the genes of interest with level 1 clinical recommendations according to PharmGKB for the two major families of psychotropics: antipsychotics and antidepressants. For antipsychotics, there are CYP2D6 and CYP3A4, and for antidepressants, CYP2B6, CYP2D6, and CYP2C19. The study will focus on describing the role of each gene, presenting the variants that cause functional changes, and discussing the implications for prescriptions in clinical practice.

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

BACKGROUND

Pharmacogenetics (PGx), especially in regard to CYP2D6, is gaining more importance in routine clinical settings. Including phenoconversion effects (PC) in result interpretation could maximize its potential benefits. However, studies on genetics of pharmacokinetic genes including the functional enzyme status are lacking.

AIM

The retrospective analyses of clinical routine data aimed to investigating how the CYP2D6 functional enzyme status affects serum concentrations and metabolite-to-parent ratios of seven common psychotropic drugs and allows an evaluation of the relevance of this information for patient care.

METHOD

Two patient cohorts (total n = 316; 44.2 ± 15.4 years) were investigated for the CYP2D6 functional enzyme status and its associations with drug exposure and metabolism of venlafaxine, amitriptyline, mirtazapine, sertraline, escitalopram, risperidone and quetiapine.

RESULTS

We found an increase in intermediate and poor metabolizers, as well as a decrease in normal metabolizers of CYP2D6 when including PC. Moreover, we found associations between amitriptyline exposure with the phenoconversion-corrected activity score of CYP2D6 (Spearman correlation; p = 0.03), and risperidone exposure with CYP2D6 functional enzyme status (Kruskal-Wallis test; p = 0.01), as well as between metabolite-to-parent ratio of venlafaxine and risperidone with CYP2D6 functional enzyme status (Kruskal-Wallis test; p < 0.001; p = 0.05).

CONCLUSION

The data stress the relevance of PC-informed PGx in psychopharmacological treatment and suggest that PC should be included in PGx result interpretation when PGx is implemented in routine clinical care, especially before initiating amitriptyline- or risperidone-treatment, to start with a dose adequate to the respective CYP2D6 functional enzyme status. Moreover, PGx and therapeutic drug monitoring should be used complementary but not alternatively.

A precision medicine approach to personalized prescribing using genetic and nongenetic factors for clinical decision-making

Screening potential drug-drug interactions, drug-gene interactions, contraindications, and other factors is crucial in clinical practice. However, implementing these screening concepts in real-world settings poses challenges. This work proposes an approach towards precision medicine that combines genetic and nongenetic factors to facilitate clinical decision-making. The approach focuses on raising the performance of four potential interaction screenings in the prescribing process, including drug-drug interactions, drug-gene interactions, drug-herb interactions, drug-social lifestyle interactions, and two potential considerations for patients with liver or renal impairment. The work describes the design of a curated knowledge-based model called the knowledge model for potential interaction and consideration screening, the screening logic for both the detection module and inference module, and the personalized prescribing report. Three case studies have demonstrated the proof-of-concept and effectiveness of this approach. The proposed approach aims to reduce decision-making processes for healthcare professionals, reduce medication-related harm, and enhance treatment effectiveness. Additionally, the recommendation with a semantic network is suggested to assist in risk-benefit analysis when health professionals plan therapeutic interventions with new medicines that have insufficient evidence to establish explicit recommendations. This approach offers a promising solution to implementing precision medicine in clinical practice.

Current Practices in Pharmacogenomics

Pharmacogenomics, where genomic information is used to tailor medication management, is a strategy to maximize drug efficacy and minimize toxicity. Although pediatric evidence is less robust than for adults, medications influenced by pharmacogenomics are prescribed to children and adolescents. Evidence-based guidelines and drug label annotations are available from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Pharmacogenomics Knowledgebase (PharmGKB). Some pediatric health care facilities use pharmacogenomics to provide dosing recommendations to pediatricians. Herein, we use a case-based approach to illustrate the use of pharmacogenomic data in pediatric clinical care and provide resources for finding and using pharmacogenomic guidelines.

Pharmacogenetic Variants Associated with Fluoxetine Pharmacokinetics from a Bioequivalence Study in Healthy Subjects

Fluoxetine is one of the most prescribed antidepressants, yet it still faces challenges due to high intersubject variability in patient response. Mainly metabolized by the highly polymorphic gene CYP2D6, important differences in plasma concentrations after the same doses are found among individuals. This study investigated the association of fluoxetine pharmacokinetics (PK) with pharmacogenetic variants. A bioequivalence crossover trial (two sequences, two periods) was conducted with fluoxetine 20 mg capsules, in 24 healthy subjects. Blood samples for fluoxetine determination were collected up to 72 h post-dose. Subjects were genotyped and single nucleotide variants (SNV) were selected using a candidate gene approach, and then associated with the PK parameters. Bioequivalence was confirmed for the test formulation. We found 34 SNV on 10 genes with a quantifiable impact on the PK of fluoxetine in the randomized controlled trial. Out of those, 29 SNVs belong to 7 CYPs (CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5), and 5 SNVs to 3 genes impacting the pharmacodynamics and efficacy of fluoxetine (SLC6A4, TPH1, ABCB1). Moreover, decreased/no function SNVs of CYP2D6 (rs1065852, rs28371703, rs1135840) and CYP2C19 (rs12769205) were confirmed phenotypically. Our research contributes to deepening the catalog of genotype-phenotype associations in pharmacokinetics, aiming to increase pharmacogenomics knowledge for rational treatment schemes of antidepressants.

Pharmacogenetics and phenoconversion: the influence on side effects experienced by psychiatric patients

Introduction: Preventing side effects is important to ensure optimal psychopharmacotherapy and therapeutic adherence among psychiatric patients. Obtaining the pharmacogenetic profile of CYP2C19 and CYP2D6 can play an important role in this. When the genotype-predicted phenotype shifts because of the use of co-medication, this is called phenoconversion. The aim was to study the influence of the pharmacogenetic (PGx) profile and phenoconversion on side effects experienced by psychiatric patients. Methods: A retrospective cohort study was performed using data from 117 patients from a psychiatric outpatient clinic. Patients were genotyped with a psychiatric PGx panel and side effects were evaluated using the Udvalg for Kliniske Undersølgelser side effects rating scale (UKU). Results: Of all patients, 10.3% and 9.4% underwent phenoconversion (any shift in predicted phenotype) for CYP2C19 and CYP2D6 respectively. No significant associations were found between the phenotype and UKU-score. 75% of the patients with an Intermediate metabolizer (IM) or Poor metabolizer (PM) phenoconverted phenotype of CYP2C19 experienced nausea and vomiting compared to 9.1% of the Normal metabolizer (NM) and Ultrarapid metabolizer (UM) patients (p = 0.033). 64% of the patients with an IM or PM phenoconverted phenotype of CYP2D6 experienced the side effect depression compared to 30.4% NMs and UMs (p = 0.020). CYP2D6 IM and PM patients had a higher concentration-dose ratio than NM patients (p < 0.05). Discussion: This study underlines the importance to consider phenoconversion when looking at a patient's genotype. This is important for a better prediction of the phenotype and preventing possible side effects under a specific psychopharmacotherapy.

The Evaluation of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 Phenoconversion in Post-Mortem Casework: The Challenge of Forensic Toxicogenetics

In toxicogenetics, an integrative approach including the prediction of phenotype based on post-mortem genotyping of drug-metabolising enzymes might help explain the cause of death (CoD) and manner of death (MoD). The use of concomitant drugs, however, might lead to phenoconversion, a mismatch between the phenotype based on the genotype and the metabolic profile actually observed after phenoconversion. The aim of our study was to evaluate the phenoconversion of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 drug-metabolising enzymes in a series of autopsy cases tested positive for drugs that are substrates, inducers, or inhibitors of these enzymes. Our results showed a high rate of phenoconversion for all enzymes and a statistically significant higher frequency of poor and intermediate metabolisers for CYP2D6, CYP2C9, and CYP2C19 after phenoconversion. No association was found between phenotypes and CoD or MoD, suggesting that, although phenoconversion might be useful for a forensic toxicogenetics approach, more research is needed to overcome the challenges arising from the post-mortem setting.

Associations of antidepressants and antipsychotics with lipid parameters: Do CYP2C19/CYP2D6 genes play a role? A UK population-based study

BACKGROUND

Dyslipidaemia is an important cardiovascular risk factor for people with severe mental illness, contributing to premature mortality. The link between antipsychotics and dyslipidaemia is well established, while evidence on antidepressants is mixed.

AIMS

To investigate if antidepressant/antipsychotic use was associated with lipid parameters in UK Biobank participants and if CYP2C19 and CYP2D6 genetic variation plays a role.

METHODS

Review of self-reported prescription medications identified participants taking antidepressants/antipsychotics. Total, low-, and high-density lipoprotein cholesterol (L/HDL-C) and triglycerides derived from blood samples. CYP2C19 and CYP2D6 metabolic phenotypes were assigned from genetic data. Linear regression investigated aims, adjusted for key covariates.

RESULTS

Of 469,739 participants, 36,043 took antidepressants (53% female, median age 58, 17% taking cholesterol-lowering medications) and 3255 took antipsychotics (58% female, median age 57, 27% taking cholesterol-lowering medications). Significant associations were found between use of each amitriptyline, fluoxetine, citalopram/escitalopram, sertraline, paroxetine and venlafaxine with higher total cholesterol, LDL-C, and triglycerides and lower HDL-C, compared to participants not taking each medication. Venlafaxine was associated with the worst lipid profile (total cholesterol, adjusted mean difference: 0.21 mmol/L, 95% confidence interval (CI): 0.17 to 0.26, p < 0.001). Antipsychotic use was significantly associated with lower HDL-C and higher triglycerides. In participants taking sertraline, CYP2C19 intermediate metabolisers had higher HDL-C (0.05 mmol/L, 95% CI: 0.01 to 0.09, p = 0.007) and lower triglycerides (-0.17 mmol/L, 95% CI: -0.29 to -0.05, p = 0.007), compared to normal metabolisers.

CONCLUSIONS

Antidepressants were significantly associated with adverse lipid profiles, potentially warranting baseline and regular monitoring. Further research should investigate the mechanistic pathways underlying the protective effects of the CYP2C19 intermediate metaboliser phenotype on HDL-C and triglycerides in people taking sertraline.

Study protocol of the HD-MED study aiming to personalize drug treatment in Huntington's disease: a longitudinal, observational study to assess medication use and efficacy in relation to pharmacogenetics

Background

Huntington's disease (HD) is a hereditary, neurodegenerative disorder characterized by motor, cognitive, and psychiatric symptoms. Currently, HD can only be managed symptomatically, including a large variety of prescribed drugs. Many HD patients experience negative medication effects (e.g. side effects or non-response). Pharmacogenetic (PGx) studies show how genetic variation affects both medication efficacy and toxicity and holds the potential to improve these outcomes of drug treatment.

Primary objective

To classify the effect of the PGx profile of CYP2C19 and CYP2D6 in HD gene expansion carriers on negative medication effects of HD-related medication.

Design

Multicenter, observational study with 1-year follow-up. Adult HD gene expansion carriers who use one or more HD-related medications are eligible to participate.

Methods and analysis

A detailed overview of medication use, medication efficacy, and side effects is retrospectively and prospectively collected via medication diaries, questionnaires, phone calls, and pharmacy medication verification schemes. PGx analysis on whole blood-extracted DNA is performed with Agena Bioscience VeriDose® Core Panel and long-range polymerase chain reaction copy number variation analysis. Per the study protocol-defined negative medication effects in HD gene expansion carriers with a genotype predicted poor or ultrarapid metabolizer phenotype will be compared with HD gene expansion carriers with a predicted intermediate and normal metabolizer phenotype. Frequencies will be analyzed via χ2 and logistic multivariate regression analysis. In addition, we summarize in this manuscript HD-relevant PGx prescription recommendations to improve drug therapy.

Ethics

The original study protocol was approved by the medical research ethics committee Leiden Den Haag Delft on 26 November 2019.

Discussion

HD-MED is a low-risk study that will generate personalized PGx results that can immediately be implemented in clinical practice, thus potentially improving pharmacovigilance and patients' quality of life.

Registration

This study is registered in the International Clinical Trial Registry Platform under registration number NL8251, URL https://trialsearch.who.int/Trial2.aspx?TrialID=NL8251.

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.

How to Implement a Pharmacogenetics Service at your Institution

The vast majority of patients possess one or more pharmacogenetic variants that can influence optimal medication use. When pharmacogenetic data are used to guide drug choice and dosing, evidence points to improved disease outcomes, fewer adverse effects, and lower healthcare spending. Although its science is well established, clinical use of pharmacogenetic data to guide drug therapy is still in its infancy. Pharmacogenetics essentially involves the intersection of an individual's genetic data with their medications, which makes pharmacists uniquely qualified to provide clinical support and education in this field. In fact, most pharmacogenetics implementations, to date, have been led by pharmacists as leaders or members of a multidisciplinary team or as individual practitioners. A successful large-scale pharmacogenetics implementation requires coordination and synergy among administrators, clinicians, informatics teams, laboratories, and patients. Because clinical implementation of pharmacogenetics is in its early stages, there is an urgent need for guidance and dissemination of shared experiences to provide a framework for clinicians. Many early adopters of pharmacogenetics have explored various strategies among diverse practice settings. This article relies on the experiences of early adopters to provide guidance for critical steps along the pathway to implementation, including strategies to engage stakeholders; evaluate pharmacogenetic evidence; coordinate laboratory testing, results interpretation and their integration into the electronic health record; identify reimbursement avenues; educate providers and patients; and maintain a successful program. Learning from early adopters' published experiences and strategies can allow clinicians leading a new pharmacogenetics implementation to avoid pitfalls and adapt and apply lessons learned by others to their own practice.

CYP2D6 pharmacogenetics and phenoconversion in personalized medicine

INTRODUCTION

CYP2D6 contributes to the metabolism of approximately 20-25% of drugs. However, CYP2D6 is highly polymorphic and different alleles can lead to impacts ranging from null to increase in activity. Moreover, there are commonly used drugs that potently inhibit the CYP2D6, thus causing 'phenoconversion' which can convert the genotypic normal metabolizer into phenotypic poor metabolizer. Despite growing literature on the clinical implications of non-normal CYP2D6 genotype and phenoconversion on patient-related outcomes, implementation of CYP2D6 pharmacogenetics and phenoconversion to guide prescribing is rare. This review focuses on providing the clinical importance of CYP2D6 pharmacogenetics and phenoconversion in precision medicine and summarizes the challenges and approaches to implement these into clinical practice.

AREAS COVERED

A literature search was performed using PubMed and clinical studies documenting the effects of CYP2D6 genotypes and/or CYP2D6 inhibitors on pharmacokinetics, pharmacodynamics or treatment outcomes of CYP2D6-metabolized drugs, and studies on implementation challenges and approaches.

EXPERT OPINION

Considering the extent and impact of genetic polymorphisms of CYP2D6, phenoconversion by the comedications, and contribution of CYP2D6 in drug metabolism, CYP2D6 pharmacogenetics is essential to ensure drug safety and efficacy. Utilization of proper guidelines incorporating both CYP2D6 pharmacogenetics and phenoconversion in clinical care assists in optimizing drug therapy.

Pharmacogenes that demonstrate high association evidence according to CPIC, DPWG, and PharmGKB

BACKGROUND

Different levels of evidence related to the variable responses of individuals to drug treatment have been reported in various pharmacogenomic (PGx) databases. Identification of gene-drug pairs with strong association evidence can be helpful in prioritizing the implementation of PGx guidelines and focusing on a gene panel. This study aimed to determine the pharmacogenes with the highest evidence-based association and to indicate their involvement in drug-gene interactions.

METHODOLOGY

The publicly available datasets CPIC, DPWG, and PharmGKB were selected to determine the pharmacogenes with the highest drug outcome associations. The upper two levels of evidence rated by the three scoring methods were specified (levels A-B in CPIC, 3-4 in DPWG, or 1-2 levels in PharmGKB). The identified pharmacogenes were further ranked in this study based on the number of medications they interacted with.

RESULTS

Fifty pharmacogenes, with high to moderately high evidence of associations with drug response alterations, with potential influence on the therapeutic and/or toxicity outcomes of 152 drugs were identified. CYP2D6, CYP2C9, CYP2C19, G6PD, HLA-B, SLCO1B1, CACNA1S, RYR1, MT-RNR1, and IFNL4 are the top 10 pharmacogenes, where each is predicted to impact patients' responses to ≥5 drugs.

CONCLUSION

This study identified the most important pharmacogenes based on the highest-ranked association evidence and their frequency of involvement in affecting multiple drugs. The obtained data is useful for customizing a gene panel for PGx testing. Identifying the strength of scientific evidence supporting drug-gene interactions aids drug prescribers in making the best clinical decision.

Implementing a pragmatic clinical trial to tailor opioids for acute pain on behalf of the IGNITE ADOPT PGx investigators

Opioid prescribing for postoperative pain management is challenging because of inter-patient variability in opioid response and concern about opioid addiction. Tramadol, hydrocodone, and codeine depend on the cytochrome P450 2D6 (CYP2D6) enzyme for formation of highly potent metabolites. Individuals with reduced or absent CYP2D6 activity (i.e., intermediate metabolizers [IMs] or poor metabolizers [PMs], respectively) have lower concentrations of potent opioid metabolites and potentially inadequate pain control. The primary objective of this prospective, multicenter, randomized pragmatic trial is to determine the effect of postoperative CYP2D6-guided opioid prescribing on pain control and opioid usage. Up to 2020 participants, age ≥8 years, scheduled to undergo a surgical procedure will be enrolled and randomized to immediate pharmacogenetic testing with clinical decision support (CDS) for CYP2D6 phenotype-guided postoperative pain management (intervention arm) or delayed testing without CDS (control arm). CDS is provided through medical record alerts and/or a pharmacist consult note. For IMs and PM in the intervention arm, CDS includes recommendations to avoid hydrocodone, tramadol, and codeine. Patient-reported pain-related outcomes are collected 10 days and 1, 3, and 6 months after surgery. The primary outcome, a composite of pain intensity and opioid usage at 10 days postsurgery, will be compared in the subgroup of IMs and PMs in the intervention (n = 152) versus the control (n = 152) arm. Secondary end points include prescription pain medication misuse scores and opioid persistence at 6 months. This trial will provide data on the clinical utility of CYP2D6 phenotype-guided opioid selection for improving postoperative pain control and reducing opioid-related risks.

Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing

Pharmacogenomic (PGx) testing of cytochrome P450 (CYP) enzymes may improve the efficacy and/or safety of some medications. This is facilitated by increased availability and affordability of genotyping, the development of clinical practice PGx guidelines and regulatory support. However, the common occurrence of CYP phenoconversion, a mismatch between genotype-predicted CYP phenotype and the actual CYP phenotype, currently limits the application of PGx testing for precision dosing in psychiatry. This review proposes a stepwise approach to assist precision dosing in psychiatry via the introduction of PGx stewardship programs and innovative PGx education strategies. A future perspective on delivering precision dosing for psychiatrists is discussed that involves innovative clinical decision support systems powered by model-informed precision dosing.

The importance of phenoconversion when using the CYP2D6 genotype in clinical practice

Tweetable abstract Clinical phenoconversion needs to be incorporated when interpreting and applying CYP2D6 results in clinical care. This article describes how this can be performed either manually or by utilizing online tools and resources. #Phenoconversion #Pharmacogenomics.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

Drug metabolic enzyme genotype-phenotype discrepancy: High phenoconversion rate in patients treated with antidepressants

Cytochromes from the P450 family (CYP) play a central role in the primary metabolism of frequently prescribed antidepressants, potentially affecting their efficacy and tolerance. There are however important differences in the drug metabolic capacities of each individual resulting from a combination of intrinsic and environmental factors. This variability can present an important risk for patients and increases the difficulty of drug prescription in clinical practice. Pharmacogenetic studies have uncovered a number of alleles defining the intrinsic metabolizer status, however, additional factors affecting cytochrome activity can modify this activity and result in a phenoconversion. The present study investigates the discrepancy between the genetically predicted and actually measured activities for the six most important liver cytochromes (CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) in a cohort of patients under antidepressant treatment, previously shown to have a high proportion of patients with low metabolizing activities. We now performed the genetic characterization of this cohort to determine the extent of the genetic versus environmental contribution in these decreased activities. For all enzyme tested, we observed an important rate of phenoconversion, affecting between 33 % and 65 % of the patients, as well as a significant (p < 1E-06) global reduction in the effective but not predicted activities of CYP2D6, CYP2C9 and CYP2C19 compared to the general population. Our results highlight the advantages of phenotyping versus genotyping as well as the increased risk of treatment failure or adverse effect occurrence in a polymedicated population.

Sub-Analysis of CYP-GUIDES Data: Assessing the Prevalence and Impact of Drug-Gene Interactions in an Ethnically Diverse Cohort of Depressed Individuals

Introduction: Minority groups are underrepresented in pharmacogenomics (PGx) research. Recent sub-analysis of CYP-GUIDES showed reduced length of stay (LOS) in depressed patients with CYP2D6 sub-functional status. Our primary objective was to determine whether PGx guided (G) versus standard treatment (S) influenced LOS among different race/ethnic groups. Secondary objectives included prevalence of drug-gene interactions (DGIs) and readmission rates (RAR).

Methods: Retrospective sub-analysis of CYP-GUIDES data comprising CYP2D6 phenotypes was reclassified using standardized CYP2D6 genotype to phenotype recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG). The Mann-Whitney test was used to determine differences in LOS between groups G and S and Kruskal Wallis test to compare LOS among different race/ethnic groups. Logistic regression was used to determine covariates associated with RAR.

Results: This study included 1,459 patients with 67.3% in G group (n = 982). The majority of patients were White (57.5%), followed by Latinos (25.6%) and Blacks (12.3%). Although there were no differences in LOS between G and S groups, Latinos had significant shorter LOS than Whites (p = 0.002). LOS was significantly reduced by 5.6 days in poor metabolizers in group G compared to S (p = 0.002). The proportion of supra functional and ultra-rapid metabolizers (UMs) were 6 and 20.3% using CYP-GUIDES and CPIC/DPWG definitions, respectively. Prevalence of DGIs was 40% with significantly fewer DGIs in Blacks (p < 0.001). Race/ethnicity was significantly associated with RAR (aOR 1.30; p = 0.003).

Conclusion: A greater number of patients were classified as CYP2D6 UMs using CPIC/DPWG definitions as compared to CYP-GUIDES definitions. This finding may have clinical implications for using psychotropics metabolized by CYP2D6.

Multidisciplinary Consulting Team for Complicated Cases of Neurodevelopmental and Neurobehavioral Disorders: Assessing the Opportunities and Challenges of Integrating Pharmacogenomics into a Team Setting

Neurodevelopmental disorders have steadily increased in incidence in the United States. Over the past decade, there have been significant changes in clinical diagnoses and treatments some of which are due to the increasing adoption of pharmacogenomics (PGx) by clinicians. In this pilot study, a multidisciplinary team at the Arkansas Children’s Hospital North West consulted on 27 patients referred for difficult-to-manage neurodevelopmental and/or neurobehavioral disorders. The 27 patients were evaluated by the team using records review, team discussion, and pharmacogenetic testing. OneOme RightMed^® (Minneapolis, MN, USA) and the Arkansas Children’s Hospital comprehensive PGx test were used for drug prescribing guidance. Of the 27 patients’ predicted phenotypes, the normal metabolizer was 11 (40.8%) for CYP2C19 and 16 (59.3%) for CYP2D6. For the neurodevelopmental disorders, the most common comorbid conditions included attention-deficit hyperactivity disorder (66.7%), anxiety disorder (59.3%), and autism (40.7%). Following the team assessment and PGx testing, 66.7% of the patients had actionable medication recommendations. This included continuing current therapy, suggesting an appropriate alternative medication, starting a new therapy, or adding adjunct therapy (based on their current medication use). Moreover, 25.9% of patients phenoconverted to a CYP2D6 poor metabolizer. This retrospective chart review pilot study highlights the value of a multidisciplinary treatment approach to deliver precision healthcare by improving physician clinical decisions and potentially impacting patient outcomes. It also shows the feasibility to implement PGx testing in neurodevelopmental/neurobehavioral disorders.

Drug-drug-gene interaction risk among opioid users in the U.S. Department of Veterans Affairs

ABSTRACT

Response to analgesic therapy is influenced by several factors including genetics and drug-drug interactions. Pharmacogenetic (PGx) variants in the CYP2D6 gene modify response to opioids by altering drug metabolism. We sought to determine the potential impact of PGx testing on the care of Veterans with noncancer pain prescribed opioids metabolized by CYP2D6 (codeine, hydrocodone, or tramadol). A retrospective analysis was performed within the Veterans Health Administration (VHA) evaluating prescription records for pain medications metabolized by CYP2D6 and interacting drugs from 2012-2017. Among 2,436,654 VHA pharmacy users with at least one opioid prescription, 34% met the definition of chronic use (longer than 90 days with more than 10 prescriptions or 120 days- supply). Opioids were commonly co-prescribed with antidepressants interacting with CYP2D6 (28%). An estimated 21.6% (n=526,905) of these patients are at elevated risk of an undesirable response to their opioid medication based on predicted phenotypes and drug-drug interactions: 3.5% are predicted CYP2D6 ultrarapid metabolizers and at increased risk for toxicity, 5.4% are poor metabolizer at higher risk for nonresponse, and 12.8% are normal or intermediate metabolizers co-prescribed a CYP2D6 inhibitor leading to phenoconversion into poor metabolizer. Despite the high rate of co-prescription of opioids and interacting drugs, CYP2D6 testing was infrequent in the sample (0.02%) and chart review suggest that test results were used to optimize antidepressant treatments rather than pain medications. Using pharmacogenetic testing combined with consideration of phenoconversion may allow for an enhanced precision medicine approach to pain management in Veterans.

Leveraging large observational studies to discover genetic determinants of drug concentrations: A proof-of-concept study

Large, observational genetic studies are commonly used to identify genetic factors associated with diseases and disease‐related traits. Such cohorts have not been commonly used to identify genetic predictors of drug dosing or concentrations, perhaps because of the heterogeneity in drug dosing and formulation, and the random timing of blood sampling. We hypothesized that large sample sizes relative to traditional pharmacokinetic studies would compensate for this variability and enable the identification of pharmacogenetic predictors of drug concentrations. We performed a cross‐sectional, proof‐of‐concept association study to replicate the well‐established association between metoprolol concentrations and CYP2D6 genotype‐inferred metabolizer phenotypes in participants from the Montreal Heart Institute Hospital Cohort undergoing metoprolol therapy. Plasma concentrations of metoprolol and α‐hydroxymetoprolol (α‐OH‐metoprolol) were measured in samples collected randomly regarding the previous metoprolol dose. A total of 999 individuals were included. The metoprolol daily dose ranged from 6.25 to 400 mg (mean 84.3 ± 57.1 mg). CYP2D6‐inferred phenotype was significantly associated with both metoprolol and α‐OH‐metoprolol in unadjusted and adjusted models (all p < 10⁻¹⁴). Models for metoprolol daily dose showed consistent results. Our study suggests that randomly drawn blood samples from biobanks can serve as a new approach to discover genetic associations related to drug concentrations and dosing, with potentially broader implications for genomewide association studies on the pharmacogenomics of drug metabolism.

Pharmacogenetics: A Precision Medicine Approach to Combatting the Opioid Epidemic

Ineffective pain control is the most commonly cited reason for misuse of prescription opioids and is influenced by genetics. In particular, the gene encoding the CYP2D6 enzyme, which metabolizes some of the most commonly prescribed opioids (e.g., tramadol, hydrocodone) to their more potent forms, is highly polymorphic and can lead to reduced concentrations of the active metabolites and decreased opioid effectiveness. Consideration of the CYP2D6 genotype may allow for predicting opioid response and identifying patients who are likely to respond well to lower potency opioids as well as those who may derive greater pain relief from non-opioid analgesics versus certain opioids. There is emerging evidence that a CYP2D6-guided approach to pain management improves pain control and reduces opioid consumption and thus may be a promising means for combating opioid misuse. Clinical practice guidelines are available for select opioids and other analgesics to support medication and dose selection based on pharmacogenetic data. This article describes the evidence supporting genotype-guided pain management as a means of improving pain control and reducing opioid misuse and clinical recommendations for genotype-guided analgesic prescribing. In addition, a "how to" guide using patient case examples is provided to demystify the process for implementing pharmacogenetics-guided pain management in order to optimize analgesia and minimize adverse effects. Optimizing pain management through genotype-guided approaches may ultimately provide safer and more effective therapy for pain control while decreasing the risk for opioid misuse.

Effect of pharmacogenomic testing on pharmacotherapy decision making in patients with symptoms of depression in an interprofessional primary care clinic

BACKGROUND

Variability in individual drug response may delay time to relief of symptoms for various disease states. As pharmacogenomic (PGx) testing becomes more widespread, providers are tasked with determining when and in who PGx testing is most appropriate. The use of PGx testing in patients with depressive symptoms has shown some utility, but how this translates to a general population within a primary care setting has yet to be determined.

OBJECTIVE

The objective of this pilot study was to determine the effect of PGx testing on treatment decisions in patients with depressive symptoms in an interprofessional primary care setting.

METHODS

This was a retrospective observational study in which patients who underwent PGx testing for psychotropic medications between April 2019 and March 2021 at a private interprofessional primary care clinic were identified. Charts were reviewed to determine whether a resultant change was made to the prescribed psychotropic medication regimen based on PGx testing results. The number of antidepressants trialed before and after testing was also reviewed. Data were analyzed using descriptive statistics and t test where appropriate.

RESULTS

A total of 78 patients were included in the study. A total of 42 patients (53.8%) experienced a change to their antidepressant regimen after PGx testing. The most frequent change identified was the addition of another antidepressant (50%). This was followed by switching the antidepressant and then by an increase in dose of the prescribed antidepressant. No difference between the number of antidepressants trialed before and after testing was identified.

CONCLUSION

PGx testing in an interprofessional primary care setting leads to a medication change in most patients in this study. Based on the changes identified, testing may be most useful in those beginning treatment with an antidepressant or in those who experience an inadequate response to their prescribed regimen.