An analysis of allele, genotype and phenotype frequencies, actionable pharmacogenomic (PGx) variants and phenoconversion in 5408 Australian patients genotyped for CYP2D6, CYP2C19, CYP2C9 and VKORC1 genes

Pharmacogenetic guided drug therapy - how to deal with phenoconversion in polypharmacy

INTRODUCTION

The prevalence of polypharmacy and the increasing availability of pharmacogenetic information in clinical practice have raised the prospect of data-driven clinical decision-making when addressing the issues of drug-drug interactions and genetic polymorphisms in metabolizing enzymes. Inhibition of metabolizing enzymes in drug interactions can lead to genotype-phenotype discrepancies (phenoconversion) that reduce the relevance of individual pharmacogenetic information.

AREAS COVERED

The aim of this review is to provide an overview of existing models of phenoconversion, and we discuss how phenoconversion models may be developed to estimate joint drug-interactions and genetic effects. Based on a literature search in PubMed, Google Scholar, and reference lists from review articles, we provide an overview of the current models of phenoconversion. The currently applied phenoconversion models are presented and discussed to predict the effects of drug-drug interactions while accounting for the pharmacogenetic status of patients.

EXPERT OPINION

While pharmacogenetic-dose recommendations alone are most relevant for rare and extreme genotypes, phenoconversion may increase the prevalence of these phenotypes. Therefore, in polypharmacy conditions, phenoconversion assessment is especially important for personalized drug therapy.

Prevalence Estimates of Cytochrome P450 Phenoconversion in Youth Receiving Pharmacotherapy for Mental Health Conditions

Pharmacogenetics-predicted drug metabolism may not match clinically observed metabolism due to a phenomenon known as phenoconversion. Phenoconversion can occur when an inhibitor or inducer of a drug-metabolizing enzyme is present. Although estimates of phenoconversion in adult populations are available, prevalence estimates in youth populations are limited. To address this gap, we estimated the prevalence of phenoconversion in 1281 youth (6-24 years) receiving pharmacotherapy for mental health conditions and who had pharmacogenetics testing completed for four genes (CYP2B6, CYP2C19, CYP2D6, CYP3A4). Self-reported medication and cannabidiol/cannabis use were collected at the time of pharmacogenetics testing. Nearly, half (46%) of the cohort was estimated to be phenoconverted for one of the four genes examined. Comparison of metabolizer phenotype frequencies before and after adjustment for phenoconversion showed significantly more youth had actionable phenotypes for CYP2C19 (60.3% vs. 69.1%; P =< 0.001), CYP2D6 (49.3% vs. 63.0%; P =< 0.001), and CYP3A4 (8.5% vs.12.2%; P = 0.003) after phenoconversion adjustment. Of youth who were phenoconverted, 24% had a change in their metabolizer phenotype that would lead to current pharmacogenetics-based prescribing guidelines recommending a change to standard prescribing (dose adjustment, alternative medication). Our findings indicate a high prevalence of cytochrome P450 phenoconversion among youth receiving pharmacotherapy for mental health conditions. Adjustment for phenoconversion should be considered when implementing pharmacogenetics testing in youth populations to improve the clinical utility of this testing in practice.

Real-World Utilization of Medications With Pharmacogenetic Recommendations in Older Adults: A Scoping Review

Pharmacogenetic testing provides patient genotype information which could influence medication selection and dosing for optimal patient care. Insurance coverage for pharmacogenetic testing varies widely. A better understanding of the commonly used medications with clinically important pharmacogenetic recommendations can inform which medications and/or genes should be prioritized for coverage and reimbursement in the context of finite healthcare resources. The aim of this scoping review was to collate previous studies that investigated the utilization rate of medications that could be guided by pharmacogenetic testing. Included studies utilized electronic medical records or claims data to assess pharmacogenetic medication prescription rates for older adults (≥ 65 years old). Identified pharmacogenetic medications were classified according to therapeutic class and assessed for actionability based on the Clinical Pharmacogenetics Implementation Consortium guidelines. Across the 31 included studies, analgesic (n = 29), psychotropic (n = 29), and cardiovascular (n = 27) therapeutic classes were most commonly investigated. Study populations were primarily generalized (48%); however, some studies focused on specific populations, such as, cancer (n = 6), mental health (n = 1), and nursing home (n = 2) cohorts. A total of 215 unique pharmacogenetic medications were reported, of which, 82 were associated with actionable pharmacogenetic recommendations. The most frequent genes implicated in potential drug-gene interactions with these actionable pharmacogenetic drugs were CYP2D6 (25.6%), CYP2C19 (18.3%), and CYP2C9 (11%). Medications most frequently prescribed included pantoprazole (range 0%-49.6%), simvastatin (range 0%-54.9%), and ondansetron (range 0.1%-62.6%). Overall, the frequently prescribed medications and associated genes identified in this review could guide pharmacogenetic testing implementation into clinical practice, including insurer subsidization.

Clinical effects of CYP2D6 phenoconversion in patients with psychosis

BACKGROUND

Pharmacogenetics is considered a promising avenue for improving treatment outcomes, yet evidence arguing for the use of pharmacogenetics in the treatment of psychotic disorders is mixed and clinical usefulness is under debate. Many patients with psychosis use multiple medications, which can alter the metabolic capacity of CYP enzymes, a process called phenoconversion. In clinical studies, treatment outcomes of drugs for psychosis management may have been influenced by phenoconversion.

AIM

Here we evaluate the impact and predictive value of CYP2D6 phenoconversion in patients with psychotic disorders under pharmacological treatment.

METHOD

Phenoconversion-corrected phenotype was determined by accounting for inhibitor strength. Phenoconversion-corrected and genotype-predicted phenotypes were compared in association with side effects, subjective well-being and symptom severity.

RESULTS

Phenoconversion led to a large increase in poor metabolizers (PMs; 17-82, 16% of sample), due to concomitant use of the serotonin reuptake inhibitors fluoxetine and paroxetine. Neither CYP2D6-predicted nor phenoconversion-corrected phenotype was robustly associated with outcome measures. Risperidone, however, was most affected by the CYP2D6 genotype.

CONCLUSION

Polypharmacy and phenoconversion were prevalent and accounted for a significant increase in PMs. CYP2D6 may play a limited role in side effects, symptoms and well-being measures. However, due to the high frequency of occurrence, phenoconversion should be considered in future clinical trials.

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.

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.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

[Barriers for Implementation of PGx Testing in Psychiatric Hospitals in Germany: Results of the FACT-PGx Study]

OBJECTIVE

The FACT-PGx study was conducted to analyze barriers to implementation of pharmacogenetic testing in psychiatric hospitals in Germany and to propose solutions for its faster and easier implementation in all hospitals.

METHODS

104 patients (50% female) were genotyped and participated in the study. 67 completed a survey. To analyze the correlation between continuous data (age) of the survey, the wilcoxon rank test and for categorial data (education level, history of treatment and episodes), t-test was used.

RESULTS

No patient declined to be genotyped. 99% believed that genotyping could help to shorten their hospital stay. Patients >40 years of age and with higher educational levels were willing to pay for the PGx (p=0.009). On average, patients were willing to pay 117.42€ +/-140.49€ and to wait 15.83+/- 8.92 days for the results. Processes differed significantly between routine laboratory screening and PGx testing which could be a barrier for implementation.

CONCLUSION

Patients are not barriers to but enablers of an implementation of PGx. New process flows can be barriers, but can be overcome by optimization.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Pharmacogenomics - a minor rather than major force in clinical medicine

INTRODUCTION

Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making.

AREAS COVERED

Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides.

EXPERT OPINION

Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.

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.

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.

Frequencies of VKORC1-1639G>A and rs397509427 in Patients on Warfarin and Healthy Syrian Subjects

Background

Vitamin K epoxide reductase complex subunit 1 (VKORC1) gene encodes a key enzyme with multiple cellular activities, namely, the reduction of vitamin K to its active form. VKORC1-1639G>A (rs9923231) is a common single nucleotide polymorphism with a crucial impact on warfarin dosing and possibly other physiological functions. This study aimed at investigating the frequencies of VKORC1-1639G>A alleles and genotypes in Syrian healthy subjects and patients on warfarin for different indications.

Methods

A total of 138 individuals were enrolled in this cross-sectional study. Genomic DNA was extracted from both patients on warfarin and healthy subjects, and polymerase chain reaction (PCR) specific amplicons were genotyped via standard sequencing which also allowed the detection of rs397509427. Comparisons of -1639G>A frequency with other populations were drawn.

Results

Of 94 patients on warfarin, 53 (56.38%) were with idiopathic venous thromboembolism (VTE). Despite comparable frequencies of the -1639A allele (47% and 50%), the AA and GA genotypes were at disparate frequencies of 93.2% versus 79.8% in the healthy subjects (n = 44) versus patients on warfarin, respectively. Carriers of the GG genotype were at a four-fold increased risk of VTE in comparison with those of the AA and GA genotypes (odds ratio (OR) = 4, 95% CI = 1.105 - 13.6, P = 0.0469). All study subjects were wild-type for the rs397509427 variant.

Conclusions

Our results prove a high -1639A prevalence in Syrian healthy subjects and patients on warfarin at frequencies comparable to other Mediterranean and Middle Eastern populations. The A allele carriers are at a lower VTE risk, whereas a global prevalence gradient of the G allele is suggested to be associated with VTE risk.

Cytochrome P450-2D6 activity in people with codeine use disorder

Compound-analgesics containing codeine (CACC) have been a common source of codeine for people seeking opioid replacement therapy (ORT) for codeine use disorder (CUD). Our previous work demonstrated no relationship between pre-treatment CACC and ORT buprenorphine doses; we hypothesised that CYP2D6 activity would partially account for this disconnection. One hundred six participants with CUD were compared to a published population sample of 5408 Australian patients. Mean age of participants with CUD at treatment entry was 35 years, with mean 6.1 years duration of CUD. Mean codeine dose was 660 mg/day (range 40-2700 mg). Mean calculated CYP2D6 activity scores were significantly higher in the codeine group (CUD 1.65 + 0.63 vs. Gen pop 1.39 + 0.65, Wilcoxon W = 347,001, p < 0.001). Pre-treatment CACC dose weakly predicted sublingual buprenorphine doses overall; there was a stronger relationship within ultrarapid metabolisers. While normal and ultrarapid metabolisers of codeine were more likely to have a diagnosis of CUD, poor or intermediate CYP2D6 metaboliser status may protect against CUD.

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.

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 impact of CYP2C19 genotype on phenoconversion by concomitant medication

Introduction: Pharmacogenetics-informed drug prescribing is increasingly applied in clinical practice. Typically, drug metabolizing phenotypes are determined based on genetic test results, whereupon dosage or drugs are adjusted. Drug-drug-interactions (DDIs) caused by concomitant medication can however cause mismatches between predicted and observed phenotypes (phenoconversion). Here we investigated the impact of CYP2C19 genotype on the outcome of CYP2C19-dependent DDIs in human liver microsomes. Methods: Liver samples from 40 patients were included, and genotyped for CYP2C19*2, *3 and *17 variants. S-mephenytoin metabolism in microsomal fractions was used as proxy for CYP2C19 activity, and concordance between genotype-predicted and observed CYP2C19 phenotype was examined. Individual microsomes were subsequently co-exposed to fluvoxamine, voriconazole, omeprazole or pantoprazole to simulate DDIs. Results: Maximal CYP2C19 activity (V_max) in genotype-predicted intermediate metabolizers (IMs; *1/*2 or *2/*17), rapid metabolizers (RMs; *1/*17) and ultrarapid metabolizers (UMs; *17/*17) was not different from V_max of predicted normal metabolizers (NMs; *1/*1). Conversely, CYP2C19*2/*2 genotyped-donors exhibited V_max rates ∼9% of NMs, confirming the genotype-predicted poor metabolizer (PM) phenotype. Categorizing CYP2C19 activity, we found a 40% concordance between genetically-predicted CYP2C19 phenotypes and measured phenotypes, indicating substantial phenoconversion. Eight patients (20%) exhibited CYP2C19 IM/PM phenotypes that were not predicted by their CYP2C19 genotype, of which six could be linked to the presence of diabetes or liver disease. In subsequent DDI experiments, CYP2C19 activity was inhibited by omeprazole (-37% ± 8%), voriconazole (-59% ± 4%) and fluvoxamine (-85% ± 2%), but not by pantoprazole (-2 ± 4%). The strength of CYP2C19 inhibitors remained unaffected by CYP2C19 genotype, as similar percental declines in CYP2C19 activity and comparable metabolism-dependent inhibitory constants (K_inact/K_I) of omeprazole were observed between CYP2C19 genotypes. However, the consequences of CYP2C19 inhibitor-mediated phenoconversion were different between CYP2C19 genotypes. In example, voriconazole converted 50% of *1/*1 donors to a IM/PM phenotype, but only 14% of *1/*17 donors. Fluvoxamine converted all donors to phenotypic IMs/PMs, but *1/*17 (14%) were less likely to become PMs than *1/*1 (50%) or *1/*2 and *2/*17 (57%). Conclusion: This study suggests that the differential outcome of CYP2C19-mediated DDIs between genotypes are primarily dictated by basal CYP2C19 activity, that may in part be predicted by CYP2C19 genotype but likely also depends on disease-related factors.

The pharmacogenomic landscape of an Indigenous Australian population

Background: Population genomic studies of individuals of Indigenous ancestry have been extremely limited comprising <0.5% of participants in international genetic databases and genome-wide association studies, contributing to a "genomic gap" that limits their access to personalised medicine. While Indigenous Australians face a high burden of chronic disease and associated medication exposure, corresponding genomic and drug safety datasets are sorely lacking. Methods: To address this, we conducted a pharmacogenomic study of almost 500 individuals from a founder Indigenous Tiwi population. Whole genome sequencing was performed using short-read Illumina Novaseq6000 technology. We characterised the pharmacogenomics (PGx) landscape of this population by analysing sequencing results and associated pharmacological treatment data. Results: We observed that every individual in the cohort carry at least one actionable genotype and 77% of them carry at least three clinically actionable genotypes across 19 pharmacogenes. Overall, 41% of the Tiwi cohort were predicted to exhibit impaired CYP2D6 metabolism, with this frequency being much higher than that for other global populations. Over half of the population predicted an impaired CYP2C9, CYP2C19, and CYP2B6 metabolism with implications for the processing of commonly used analgesics, statins, anticoagulants, antiretrovirals, antidepressants, and antipsychotics. Moreover, we identified 31 potentially actionable novel variants within Very Important Pharmacogenes (VIPs), five of which were common among the Tiwi. We further detected important clinical implications for the drugs involved with cancer pharmacogenomics such as thiopurines and tamoxifen, immunosuppressants like tacrolimus and certain antivirals used in the hepatitis C treatment due to potential differences in their metabolic processing. Conclusion: The pharmacogenomic profiles generated in our study demonstrate the utility of pre-emptive PGx testing and have the potential to help guide the development and application of precision therapeutic strategies tailored to Tiwi Indigenous patients. Our research provides valuable insights on pre-emptive PGx testing and the feasibility of its use in ancestrally diverse populations, emphasizing the need for increased diversity and inclusivity in PGx investigations.

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.

An updated examination of the perception of barriers for pharmacogenomics implementation and the usefulness of drug/gene pairs in Latin America and the Caribbean

Pharmacogenomics (PGx) is considered an emergent field in developing countries. Research on PGx in the Latin American and the Caribbean (LAC) region remains scarce, with limited information in some populations. Thus, extrapolations are complicated, especially in mixed populations. In this paper, we reviewed and analyzed pharmacogenomic knowledge among the LAC scientific and clinical community and examined barriers to clinical application. We performed a search for publications and clinical trials in the field worldwide and evaluated the contribution of LAC. Next, we conducted a regional structured survey that evaluated a list of 14 potential barriers to the clinical implementation of biomarkers based on their importance. In addition, a paired list of 54 genes/drugs was analyzed to determine an association between biomarkers and response to genomic medicine. This survey was compared to a previous survey performed in 2014 to assess progress in the region. The search results indicated that Latin American and Caribbean countries have contributed 3.44% of the total publications and 2.45% of the PGx-related clinical trials worldwide thus far. A total of 106 professionals from 17 countries answered the survey. Six major groups of barriers were identified. Despite the region's continuous efforts in the last decade, the primary barrier to PGx implementation in LAC remains the same, the "need for guidelines, processes, and protocols for the clinical application of pharmacogenetics/pharmacogenomics". Cost-effectiveness issues are considered critical factors in the region. Items related to the reluctance of clinicians are currently less relevant. Based on the survey results, the highest ranked (96%-99%) gene/drug pairs perceived as important were CYP2D6/tamoxifen, CYP3A5/tacrolimus, CYP2D6/opioids, DPYD/fluoropyrimidines, TMPT/thiopurines, CYP2D6/tricyclic antidepressants, CYP2C19/tricyclic antidepressants, NUDT15/thiopurines, CYP2B6/efavirenz, and CYP2C19/clopidogrel. In conclusion, although the global contribution of LAC countries remains low in the PGx field, a relevant improvement has been observed in the region. The perception of the usefulness of PGx tests in biomedical community has drastically changed, raising awareness among physicians, which suggests a promising future in the clinical applications of PGx in LAC.

Calculation of the pharmacogenomics benefit score for patients with medication-related problems

Unexpected poor efficacy and intolerable adverse effects are medication-related problems that may result from genetic variation in genes encoding key proteins involved in pharmacokinetics or pharmacodynamics. Pharmacogenomic (PGx) testing can be used in medical practice "pre-emptively" to avoid future patient harm from medications and "reactively" to diagnose medication-related problems following their occurrence. A structured approach to PGx consulting is proposed to calculate the pharmacogenomics benefit score (PGxBS), a patient-centered objective measure of congruency between medication-related problems and patient genotypes. An example case of poor efficacy with multiple medications is presented, together with comments on the potential benefits and limitations of using the PGxBS in medical practice.

A review of pharmacogenetic studies in the Bangladeshi population

Pharmacogenetics (PGx)-guided prescribing is an evidence-based precision medicine strategy. Although the past two decades have reported significant advancements in both the quality and quantity of PGx research studies, they are seldom done in developing countries like Bangladesh. This review identified and summarized PGx studies conducted in the Bangladeshi population by searching PubMed and Google Scholar. Additionally, a quality evaluation of the identified studies was also carried out. Eleven PGx studies were identified that looked at the effects of genetic variants on blood thinners (CYP2C9, VKORC1, and ITGB3), cancer drugs (TPMT, MTHFR, DPYD, ERCC1, GSTP1, XPC, XRCC1, TP53, XPD, and ABCC4), statins (COQ2, CYP2D6, and CYP3A5), and prednisolone (ABCB1, CYP3A5, and NR3C1) in the Bangladeshi population. Most studies were of low to moderate quality. Although the identified studies demonstrated the potential for PGx testing, the limited PGx literature in the Bangladeshi population poses a significant challenge in the widespread implementation of PGx testing in Bangladesh.

Reflections on the Lack of Consideration of Ethnic Ancestry to Stratify Clozapine Dosing

This review article argues against trusting standard clozapine references, including the US package insert, because they do not include advances in the sciences of pharmacokinetics and pharmacovigilance and ignore the effects of ethnic ancestry on therapeutic dosing. The minimum therapeutic dose leading to the minimum therapeutic concentration of 350 ng/mL in serum/plasma can be used to compare individuals/groups with treatment-resistant schizophrenia. The US clozapine package insert recommends targeting doses of 300-450 mg/day and, subsequently, increments of up to 100 mg with a maximum dose of 900 mg/day. Ethnic ancestry is defined by DNA ancestry group. Asians (people with ancestry ranging from Pakistan to Japan) and Indigenous Americans are similar in clozapine dosing; their average clozapine minimum therapeutic dose ranged from 166 mg/day (female non-smokers) to 270 mg/day (male smokers). For those with European ancestry, average clozapine minimum therapeutic doses ranged from 236 mg/day (female non-smokers) to 368 mg/day (male smokers). Based on limited studies, Black (African sub-Saharan ancestry) patients may be treated with typical US doses (300-600 mg/day), assuming no poor metabolism (PM) status. Ancestry's impact on clozapine lethality in four countries is discussed (two countries with highly homogenous populations, Denmark and Japan, and two countries with increasingly heterogenous populations due to immigration, Australia and the UK). An international guideline with 104 authors from 50 countries/regions was recently published, providing 6 personalized clozapine titration schedules for adult inpatients (3 ancestry groups and PM/non-PM schedules) and recommending c-reactive protein monitoring at baseline and weekly for 4 weeks.

Pharmacogenomics: current status and future perspectives

Inter-individual variability in drug response, be it efficacy or safety, is common and likely to become an increasing problem globally given the growing elderly population requiring treatment. Reasons for this inter-individual variability include genomic factors, an area of study called pharmacogenomics. With genotyping technologies now widely available and decreasing in cost, implementing pharmacogenomics into clinical practice - widely regarded as one of the initial steps in mainstreaming genomic medicine - is currently a focus in many countries worldwide. However, major challenges of implementation lie at the point of delivery into health-care systems, including the modification of current clinical pathways coupled with a massive knowledge gap in pharmacogenomics in the health-care workforce. Pharmacogenomics can also be used in a broader sense for drug discovery and development, with increasing evidence suggesting that genomically defined targets have an increased success rate during clinical development.

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.

Public perceptions of pharmacogenomic services in Ireland - Are people with chronic disease more likely to want service availability than those without? A questionnaire study

Background

As pharmacogenomic services begin to emerge in primary care, the insight of the public is crucial for its integration into clinical practice.

Objectives

To establish perceptions of pharmacogenomics (awareness, understanding, openness to availability, perceived benefits and concerns, willingness to pay, and service setting) and investigate if they differ between those with and without chronic disease(s).

Methods

An anonymous, online questionnaire generated using Qualtrics® and circulated via social media and posters placed in eight participating community pharmacies was conducted with Irish adults. The questions were designed to consider existing literature on patient perceptions of pharmacogenomics. Descriptive statistics were used to summarize questionnaire responses. Chi-square test was used to compare categorical variables, while independent sample t-test and one-way ANOVA were used to compare the mean values of two (with and without chronic disease) and three groups (multimorbidity (two or more chronic conditions) and polypharmacy (prescribed four or more regular medicines) (MMPP), a single chronic disease, and those without existing medical conditions) respectively Logistic regression was used to evaluate age and gender adjusted associations of chronic disease(s) with responses. A p-value <0.05 was considered statistically significant.

Results

A total of 421 responses were received, 30% (n = 120) of whom reported having a chronic disease. Overall, respondents reported low awareness (44%, n = 166) and poor knowledge (55%, n = 212) of pharmacogenomics. After explaining pharmacogenomics to respondents, patients with chronic disease(s) were 2.17 times more likely (p < 0.001) to want pharmacogenomic services availability than those without existing conditions, adjusted for age and gender (driven by preferences of those with MMPP than those with single chronic disease). Respondents demonstrated a high level of interest and noted both the potential benefits and downsides of pharmacogenomic testing. Willingness-to-pay was not associated with having a chronic disease and respondents were more positive about primary care (community pharmacy or general practice) rather than hospital-based pharmacogenomics implementation.

Conclusion

The Irish public in general and those with chronic disease in particular are strongly supportive of pharmacogenomic testing, highlighting an unmet need for its incorporation in medicines optimization. These data underline the need for more research on the implementation of community-based pharmacogenomics services for MMPP patients and ubiquitous pharmacogenomics education programs.

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Rates of Divergent Pharmacogenes in a Psychiatric Cohort of Inpatients with Depression-Arguments for Preemptive Testing

Background: The international drug agencies annotate pharmacogenes for many years. Pharmacogenetic testing is thus far only established in few settings, assuming that only few patients are actually affected by drug-gene interactions. Methods: 108 hospitalized patients with major depressive disorder were genotyped for CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NAT2, DPYD; VKORC1 and TMTP. Results: We found 583 (mean 5.4, median 5) divergent phenotypes (i.e., divergent from the common phenotypes considered normal, e.g., extensive metabolizer) in the 12 analyzed pharmacokinetic genes. The rate for at least one divergent phenotype was 100% in our cohort for CYP, but also for all 12 important pharmacogenes: patients had at least two divergent phenotypes. Compared to a large Danish cohort, CYP2C9 NM and IM status, CYP2C19 UM, CYP2D6 UM and DYPD (GAS 0, 1, 2) genotypes differed statistical significantly. For CYP2D6 and CYP2C19, 13% of the patients were normal metabolizers for both enzymes in our cohort, but this value was 27.3% in the Danish cohort, which is a highly significant difference (p < 0.0001). Conclusion: Divergent phenotypes in pharmacogenes are not the exception, but the rule. Patients with divergent phenotypes seem more prone for hospitalization, emphasizing the need for pre-emptive testing to avoid inefficacy and adverse drug effects in all patients.

Clozapine-associated myocarditis in the World Health Organization's pharmacovigilance database: Focus on reports from various countries

INTRODUCTION

The incidence of clozapine-associated myocarditis varies by country. These variations were explored in VigiBase, the World Health Organization's global database which has >25 million spontaneously reported adverse drug reaction (ADR) reports from 145 national drug agencies.

METHODS

On January 15, 2021, a search of VigiBase since inception focused on myocarditis in clozapine patients. The 3572 individual reports were studied using the standard VigiBase logarithmic measure of disproportionality called information component (IC). The IC measures the disproportionality between the expected and the reported rates. After duplicates were eliminated there were 3274 different patients with myocarditis studied in logistic regression models.

RESULTS

The first case was published in 1980 but since 1993 the VigiBase clozapine-myocarditis IC has been significant; moreover, currently it is very strong (IC=6.0, IC₀₀₅-IC₉₉₅=5.9-6.1) and statistically significantly different from other antipsychotics. Of the 3274 different patients with myocarditis, 43.4% were non-serious cases, 51.8% were serious but non-fatal, and 4.8% were fatal. More than half (1621/3274) of the reports came from Australia, of which 69.2% were non-serious, 27.7% serious but non-fatal, and 3.1% fatal. Asian countries contributed only 41 cases.

CONCLUSIONS

In pharmacovigilance studies, confounding factors may explain statistical associations, but the strength and robustness of these results are compatible with the hypothesis that myocarditis is definitively associated with early clozapine treatment (84% [1309/1560] and 5% [82/1560] in the first and second months). Myocarditis reports from Australia are over-represented to a major degree. Asian countries may be underreporting myocarditis to their drug agencies.

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.

Phenytoin Metabolic Ratio, a Marker of CYP2C9 Activity, is Superior to the CYP2C9 Genotype as a Predictor of (S)-Warfarin Clearance

BACKGROUND

CYP2C9 is a member of the cytochrome P450 (CYP) superfamily responsible for the metabolism of 16% of drugs that undergo oxidative metabolism. The activity of CYP2C9 exhibits marked inter-individual variability, which translates into prominent differences in the pharmacokinetics of CYP2C9 substrates, some of which are characterized by a narrow therapeutic window. Genetic polymorphisms in the gene encoding for CYP2C9 account for a fraction of the variability in CYP2C9 activity. The phenytoin metabolic ratio (PMR) is a marker of CYP2C9 activity in vivo, which correlates with CYP2C9 genetic polymorphisms.

OBJECTIVE

The purpose of the current study was to evaluate the ability of the PMR to predict the oral clearance of (S)-warfarin (SWOCL) and its formation clearance towards its CYP2C9-mediated metabolites (SWCLf) [i.e., 6- and 7-hydroxy-(S)-warfarin].

METHODS

The study was conducted in 150 healthy non-smoker subjects (segment 1) and 60 patients treated with warfarin (segment 2). In the first segment, the participants received on two separate occasions a single 300-mg dose of phenytoin and at least 7 days later a single dose of warfarin (5 or 10 mg). The same PMR procedure was performed in the second segment, except that it was performed either before warfarin initiation or after the patients had reached stable anticoagulation. The PMR was derived from the ratio of 5-(4-hydroxyphenyl)-5-phenyl-hydantoin content in a 24-hour urine collection to plasma phenytoin concentration 12- (PMR24/12) or 24- (PMR24/24) post-dosing. In segment 1, SWOCL was calculated from the ratio of (S)-warfarin dose to the warfarin area under the plasma concentration-time curve extrapolated to infinity and the SWCLf from the ratio of urine content of 6- and 7-hydroxy-(S)-warfarin to (S)-warfarin area under the (S)-warfarin plasma concentration-time curve until the last measured timepoint. In segment 2, estimated SWOCL was derived from the ratio of (S)-warfarin dose to the mid-interval plasma concentration of (S)-warfarin.

RESULTS

The PMR, SWOCL, and SWCLf varied significantly between carriers of different CYP2C9 genotypes in both healthy subjects (p < 0.001) and patients (p < 0.005). However, PMR and SWOCL values exhibited substantial intra-genotypic variability. PMR24/12 and PMR24/24 were significantly correlated with SWOCL both in healthy subjects (r = 0.62 and r = 0.67, respectively, p < 0.001) and in patients (r = 0.57 and r = 0.61, respectively, p < 0.001). In a multiple regression model that included all variables that correlated with SWOCL, PMR was the strongest predictor, explaining 44% and 38% of the variability in SWOCL among healthy subjects and patients, respectively, and accounting for 95.7% (44%/46%) and 90.5% (38%/42%) of the total explained variability in SWOCL among healthy subjects and patients, respectively.

CONCLUSIONS

The PMR is the strongest predictor of SWOCL, and as such, it exhibits a significant advantage over the CYP2C9 genotype. The inclusion of PMR in future dosing algorithms of CYP2C9 substrates characterized by a narrow therapeutic window should be encouraged and further investigated.

The Frequency of Rh Phenotype and Its Probable Genotype

Aims and objectives: Our goal is to disseminate data on the distribution pattern of Rh antigen, its phenotypes, and the likely genotypes of these genetic variants in the Pakistani population.

Methodology: This study was a cross-sectional research project. Patients’ demographic statistics, such as age and gender, were gathered from their medical information. Blood group, disease, RhD, and other antigen frequency, phenotype, and probable genotype were considered variables. All blood samples were phenotyped for Rhesus antigens (D, C, c, E, and e), and the test was carried out using the tubing technique.

Results: According to gender distribution, most of the patients were males, with 131 frequencies (57.7%), while females had 42.35%. The most common phenotype was DCCee, with its probable genotype DCe/DCe (R1 R1) (34%), followed by DCcee, with probable genotype DCe/ce (R1 r) (29.1%); the least common phenotype was ddCcee, with its probable genotype Ce/ce (r ' r) (0.4%).

Conclusion: It is concluded that the DCCee phenotype was the most common with its probable genotype DCe/DCe, while the least common phenotype was ddCcee with its probable genotype Ce/ce.

What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings?

In psychiatry, the selection of antipsychotics and antidepressants is generally led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). These both contribute to poor levels of adherence. Pharmacogenetics (PGx) considers how genetic variation can influence an individual’s response to a drug. Pharmacogenetic testing is a tool that could aid clinicians when selecting psychotropic medications, as part of a more personalized approach to prescribing. This may improve the use of and adherence to these medications. Yet to date, the implementation of PGx in mental health environments in the United Kingdom has been slow. This review aims to identify the current barriers and enablers to the implementation of PGx in psychiatry and determine how this can be applied to the uptake of PGx by NHS mental health providers. A systematic searching strategy was developed, and searches were carried out on the PsychInfo, EmBase, and PubMed databases, yielding 11 appropriate papers. Common barriers to the implementation of PGx included cost, concerns over incorporation into current workflow and a lack of knowledge about PGx; whilst frequent enablers included optimism that PGx could lead to precision medicine, reduce ADRs and become a more routine part of psychiatric clinical care. The uptake of PGx in psychiatric care settings in the NHS should consider and overcome these barriers, while looking to capitalize on the enablers identified in this review.

How to Integrate CYP2D6 Phenoconversion Into Clinical Pharmacogenetics: A Tutorial

CYP2D6 genotype is increasingly being integrated into practice to guide prescribing of certain medications. The CYP2D6 drug metabolizing enzyme is susceptible to inhibition by concomitant drugs, which can lead to a clinical phenotype that is different from the genotype-based phenotype, a process referred to as phenoconversion. Phenoconversion is highly prevalent but not widely integrated into practice because of either limited experience on how to integrate or lack of knowledge that it has occurred. We built a calculator tool to help clinicians integrate a standardized method of assessing CYP2D6 phenoconversion into practice. During tool-building, we identified several clinical factors that need to be considered when implementing CYP2D6 phenoconversion into clinical practice. This tutorial shares the steps that the University of Florida Health Precision Medicine Program took to build the calculator tool and identified clinical factors to consider when implementing CYP2D6 phenoconversion in clinical practice.

Impact of genetic and non-genetic factors on hepatic CYP2C9 expression and activity in Hungarian subjects

CYP2C9, one of the most abundant hepatic cytochrome P450 enzymes, is involved in metabolism of 15–20% of clinically important drugs (warfarin, sulfonylureas, phenytoin, non-steroid anti-inflammatory drugs). To avoid adverse events and/or impaired drug-response, CYP2C9 pharmacogenetic testing is recommended. The impact of CYP2C9 polymorphic alleles (CYP2C9*2, CYP2C9*3) and phenoconverting non-genetic factors on CYP2C9 function and expression was investigated in liver tissues from Caucasian subjects (N = 164). The presence of CYP2C9*3 allele was associated with CYP2C9 functional impairment, and CYP2C9*2 influenced tolbutamide 4′-hydroxylase activity only in subjects with two polymorphic alleles, whereas the contribution of CYP2C8*3 was not confirmed. In addition to CYP2C9 genetic polymorphisms, non-genetic factors (co-medication with CYP2C9-specific inhibitors/inducers and non-specific factors including amoxicillin + clavulanic acid therapy or chronic alcohol consumption) contributed to the prediction of hepatic CYP2C9 activity; however, a CYP2C9 genotype–phenotype mismatch still existed in 32.6% of the subjects. Substantial variability in CYP2C9 mRNA levels, irrespective of CYP2C9 genotype, was demonstrated; however, CYP2C9 induction and non-specific non-genetic factors potentially resulting in liver injury appeared to modify CYP2C9 expression. In conclusion, complex implementation of CYP2C9 genotype and non-genetic factors for the most accurate estimation of hepatic CYP2C9 activity may improve efficiency and safety of medication with CYP2C9 substrate drugs in clinical practice.

An Analysis of Pharmacogenomic-Guided Pathways and Their Effect on Medication Changes and Hospital Admissions: A Systematic Review and Meta-Analysis

Ninety-five percent of the population are estimated to carry at least one genetic variant that is discordant with at least one medication. Pharmacogenomic (PGx) testing has the potential to identify patients with genetic variants that puts them at risk of adverse drug reactions and sub-optimal therapy. Predicting a patient's response to medications could support the safe management of medications and reduce hospitalization. These benefits can only be realized if prescribing clinicians make the medication changes prompted by PGx test results. This review examines the current evidence on the impact PGx testing has on hospital admissions and whether it prompts medication changes. A systematic search was performed in three databases (Medline, CINAHL and EMBASE) to search all the relevant studies published up to the year 2020, comparing hospitalization rates and medication changes amongst PGx tested patients with patients receiving treatment-as-usual (TAU). Data extracted from full texts were narratively synthesized using a process model developed from the included studies, to derive themes associated to a suggested workflow for PGx-guided care and its expected benefit for medications optimization and hospitalization. A meta-analysis was undertaken on all the studies that report the number of PGx tested patients that had medication change(s) and the number of PGx tested patients that were hospitalized, compared to participants that received TAU. The search strategy identified 5 hospitalization themed studies and 5 medication change themed studies for analysis. The meta-analysis showed that medication changes occurred significantly more frequently in the PGx tested arm across 4 of 5 studies. Meta-analysis showed that all-cause hospitalization occurred significantly less frequently in the PGx tested arm than the TAU. The results show proof of concept for the use of PGx in prescribing that produces patient benefit. However, the review also highlights the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems; namely patient involvement in PGx prescribing decisions, thus a better understanding of the perspective of patients and prescribers. We highlight the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems.

Clozapine-associated myocarditis in the World Health Organization's pharmacovigilance database: Focus on reports from various countries

INTRODUCTION

The incidence of clozapine-associated myocarditis varies by country. These variations were explored in VigiBase, the World Health Organization's global database which has >25 million spontaneously reported adverse drug reaction (ADR) reports from 145 national drug agencies.

METHODS

On January 15, 2021, a search of VigiBase since inception focused on myocarditis in clozapine patients. The 3572 individual reports were studied using the standard VigiBase logarithmic measure of disproportionality called information component (IC). The IC measures the disproportionality between the expected and the reported rates. After duplicates were eliminated there were 3274 different patients with myocarditis studied in logistic regression models.

RESULTS

The first case was published in 1980 but since 1993 the VigiBase clozapine-myocarditis IC has been significant; moreover, currently it is very strong (IC=6.0, IC005-IC995=5.9-6.1) and statistically significantly different from other antipsychotics. Of the 3274 different patients with myocarditis, 43.4% were non-serious cases, 51.8% were serious but non-fatal, and 4.8% were fatal. More than half (1621/3274) of the reports came from Australia, of which 69.2% were non-serious, 27.7% serious but non-fatal, and 3.1% fatal. Asian countries contributed only 41 cases.

CONCLUSIONS

In pharmacovigilance studies, confounding factors may explain statistical associations, but the strength and robustness of these results are compatible with the hypothesis that myocarditis is definitively associated with early clozapine treatment (84% [1309/1560] and 5% [82/1560] in the first and second months). Myocarditis reports from Australia are over-represented to a major degree. Asian countries may be underreporting myocarditis to their drug agencies.

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

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

Pharmacogenetic genotype and phenotype frequencies in a large Danish population-based case-cohort sample

Pharmacogenetics aims to improve clinical care by studying the relationship between genetic variation and variable drug response. Large population-based datasets could improve our current understanding of pharmacogenetics from selected study populations. We provide real-world pharmacogenetic frequencies of genotypes and (combined) phenotypes of a large Danish population-based case-cohort sample (iPSYCH2012; data of the Integrative Psychiatric Research consortium). The genotyped sample consists of 77,684 individuals, of which 51,464 individuals had diagnoses of severe mental disorders (SMD case-cohort) and 26,220 were individuals randomly selected from the Danish population (population cohort). Array-based genotype data imputed to 8.4 million genetic variants was searched for a selected pharmacogenetic panel of 42 clinically relevant variants and a CYP2D6 gene deletion and duplication. We identified 19 of 42 variants. Minor allele frequencies (MAFs) were consistent with previously reported MAFs, and did not differ between SMD cases and population cohorts. Almost all individuals carried at least one genetic variant (> 99.9%) and 87% carried three or more genetic variants. When genotypes were translated into phenotypes, also > 99.9% of individuals had at least one divergent phenotype (i.e. divergent from the common phenotypes considered normal, e.g. extensive metabolizer). The high number of identified individuals with at least one pharmacogenetic variant or divergent phenotype indicates the importance of pharmacogenetic panel-based genotyping. Combined CYP2C19-CYP2D6 phenotypes revealed that 72.7% of individuals had divergent phenotypes for one or both enzymes. As CYP2D6 and CYP2C19 have an important role in the metabolism of psychotropic drugs, this indicates the relevance of pharmacogenetic testing specifically in individuals using psychotropic drugs.

Estimating the potential impact of implementing pre-emptive pharmacogenetic testing in primary care across the UK

AIMS

Pharmacogenetics (PGx) in the UK is currently implemented in secondary care for a small group of high-risk medicines. However, most prescribing takes place in primary care, with a large group of medicines influenced by commonly occurring genetic variations. The goal of this study is to quantitatively estimate the volumes of medicines impacted by implementation of a population-level, pre-emptive pharmacogenetic screening programme for nine genes related to medicines frequently dispensed in primary care in 2019.

METHODS

A large community pharmacy database was analysed to estimate the national incidence of first prescriptions for 56 PGx drugs used in the UK for the period 1 January-31 December 2019. These estimated prescription volumes were combined with phenotype frequency data to estimate the occurrence of actionable drug-gene interactions (DGI) in daily practice in community pharmacies.

RESULTS

In between 19.1 and 21.1% (n = 5 233 353-5 780 595) of all new prescriptions for 56 drugs (n = 27 411 288 new prescriptions/year), an actionable drug-gene interaction (DGI) was present according to the guidelines of the Dutch Pharmacogenetics Working Group and/or the Clinical Pharmacogenetics Implementation Consortium. In these cases, the DGI would result in either increased monitoring, guarding against a maximum ceiling dose or an optional or immediate drug/dose change. An immediate dose adjustment or change in drug regimen accounted for 8.6-9.1% (n = 2 354 058-2 500 283) of these prescriptions.

CONCLUSIONS

Actionable drug-gene interactions frequently occur in UK primary care, with a large opportunity to optimise prescribing.

Retrospective Review of Pharmacogenetic Testing at an Academic Children's Hospital

There is limited evidence to support pharmacogenetic (PGx) testing in children. We conducted a retrospective review of PGx testing among 452 patients at an academic children's hospital to determine the potential utility of PGx in diseases of childhood and to identify targets for future pediatric pharmacogenetic research. An actionable gene-drug pair associated with the 28 genes tested (Clinical Pharmacogenetics Implementation Consortium (CPIC) level A or B, Pharmacogenomics Knowledge Base (PharmGKB) level 1A or B, or US Food and Drug Administration (FDA) recommendation and a PharmGKB level) was present in 98.7% of patients. We identified 203 actionable gene-drug-diagnosis groups based on the indications for each actionable drug listed in Lexicomp. Among patients with an actionable gene-drug-diagnosis group, 49.3% had a diagnosis where the drug was a therapeutic option and PGx could be used to guide treatment selection. Among patients with an associated diagnosis, 30.9% had a prescription for the actionable drug allowing PGx guided dosing. Three genes (CYP2C19, CYP2D6, and CYP3A5) accounted for all the gene-drug-diagnosis groups with matching diagnoses and prescriptions. The most common gene-drug-diagnosis groups with matching diagnoses and prescriptions were CYP2C19-citalopram-escitalopram-depression 3.3% of patients tested; CYP2C19-dexlansoprazole-gastritis-esophagitis 3.1%; CYP2C19-omeprazole-gastritis-esophagitis 2.4%; CYP2D6-atomoxetine-attention deficit hyperactivity disorder 2.2%; and CYP2C19-citalopram-escitalopram-obsessive-compulsive disorder 1.5%. PGx could be used to guide selection of current treatment options or medication dosing in almost half (48.7%) of pediatric patients tested. Mood disorders and gastritis/esophagitis are promising targets for future study of PGx testing because of the high prevalence of these diagnoses and associated actionable gene-drug pairs in the pediatric population.

Quantifying the Impact of Phenoconversion on Medications With Actionable Pharmacogenomic Guideline Recommendations in an Acute Aged Persons Mental Health Setting

Introduction: Polypharmacy and genetic variants that strongly influence medication response (pharmacogenomics, PGx) are two well-described risk factors for adverse drug reactions. Complexities arise in interpreting PGx results in the presence of co-administered medications that can cause cytochrome P450 enzyme phenoconversion. Aim: To quantify phenoconversion in a cohort of acute aged persons mental health patients and evaluate its impact on the reporting of medications with actionable PGx guideline recommendations (APRs). Methods: Acute aged persons mental health patients (N = 137) with PGx and medication data at admission and discharge were selected to describe phenoconversion frequencies for CYP2D6, CYP2C19 and CYP2C9 enzymes. The expected impact of phenoconversion was then assessed on the reporting of medications with APRs. Results: Post-phenoconversion, the predicted frequency at admission and discharge increased for CYP2D6 intermediate metabolisers (IMs) by 11.7 and 16.1%, respectively. Similarly, for CYP2C19 IMs, the predicted frequency at admission and discharge increased by 13.1 and 11.7%, respectively. Nineteen medications with APRs were prescribed 120 times at admission, of which 50 (42%) had APRs pre-phenoconversion, increasing to 60 prescriptions (50%) post-phenoconversion. At discharge, 18 medications with APRs were prescribed 122 times, of which 48 (39%) had APRs pre-phenoconversion, increasing to 57 prescriptions (47%) post-phenoconversion. Discussion: Aged persons mental health patients are commonly prescribed medications with APRs, but interpretation of these recommendations must consider the effects of phenoconversion. Adopting a collaborative care model between prescribers and clinical pharmacists should be considered to address phenoconversion and ensure the potential benefits of PGx are maximised.

Pharmacogenomics at the Point of Care: A Community Pharmacy Project in British Columbia

In this study 180 patients were consented and enrolled for pharmacogenomic testing based on current antidepressant/antipsychotic usage. Samples from patients were genotyped by PCR, MassArray, and targeted next generation sequencing. We also conducted a quantitative, frequency-based analysis of participants’ perceptions using simple surveys. Pharmacogenomic information, including medication changes and altered dosing recommendations were returned to the pharmacists and used to direct patient therapy. Overwhelmingly, patients perceived pharmacists/pharmacies as an appropriate healthcare provider to deliver pharmacogenomic services. In total, 81 medication changes in 33 unique patients, representing 22% of all genotyped participants were recorded. We performed a simple drug cost analysis and found that medication adjustments and dosing changes across the entire cohort added $24.15CAD per patient per year for those that required an adjustment. Comparing different platforms, we uncovered a small number, 1.7%, of genotype discrepancies. We conclude that: (1). Pharmacists are competent providers of pharmacogenomic services. (2). The potential reduction in adverse drug responses and optimization of drug selection and dosing comes at a minimal cost to the health care system. (3). Changes in drug therapy, based on PGx tests, result in inconsequential changes in annual drug therapy cost with small cost increases just as likely as costs savings. (4). Pharmacogenomic services offered by pharmacists are ready for wide commercial implementation.

Alcohol intake potentiates clozapine adverse effects associated to CYP1A2*1C in patients with refractory psychosis

Clozapine (CLZ) is an atypical antipsychotic and the gold standard for refractory psychosis treatment. However, there is little information regarding pharmacogenetics of CLZ in patients with refractory psychosis and its clinical correlation with alcohol intake. Although neurological effects of CLZ in patients with concomitant alcohol intake are documented, its use is very common in patients with psychosis. We explored the impact of CYP1A2, CYP2D6, CYP2C19, and CYP3A4 genetic variants on CLZ pharmacokinetics and side effects, along with coffee/alcohol/tobacco consumption habits and clinical data of 48 adult patients with refractory psychosis on CLZ antipsychotic monotherapy. Relevant CYP variants in CLZ metabolism were evaluated by targeted genotyping and multiplex ligation-dependent probe amplification. CLZ and its main metabolite plasma concentrations were determined by high performance liquid chromatography. Biochemical and molecular data, along with other potential confounders, were included in the analysis by linear regression. Overall, CYP variants showed no effect on CLZ pharmacokinetics. The rs2069514 variant in homozygous genotype (also known as CYP1A2*1C/*1C) was associated with CLZ adverse reactions in Mexican patients with refractory psychosis (OR = 3.55 CI₉₅  = 1.041-12.269, p = .043) and demonstrated that this effect is doubled by concomitant alcohol consumption (OR = 7.9 CI₉₅  = 1.473-42.369, p = .016). Clinicians should be aware of this information before starting CLZ use, when treating patients with refractory psychosis, who are alcohol drinkers and carriers of this genetic variant in order to prevent CLZ-related adverse reactions. Nevertheless, our findings should be replicated in larger samples.

Multimorbidity, polypharmacy, and drug-drug-gene interactions following a non-ST elevation acute coronary syndrome: analysis of a multicentre observational study

BACKGROUND

The number of patients living with co-existing diseases is growing. This study aimed to assess the extent of multimorbidity, medication use, and drug- and gene-based interactions in patients following a non-ST elevation acute coronary syndrome (NSTE-ACS).

METHODS

In 1456 patients discharged from hospital for a NSTE-ACS, comorbidities and multimorbidity (≥ 2 chronic conditions) were assessed. Of these, 698 had complete drug use recorded at discharge, and 652 (the 'interaction' cohort) had drug use and actionable genotypes available for CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5, DPYD, F5, SLCO1B1, TPMT, UGT1A1, and VKORC1. The following drug interactions were investigated: pharmacokinetic drug-drug (DDIs) involving CYPs (CYPs above, plus CYP1A2, CYP2C8, CYP3A4), SLCO1B1, and P-glycoprotein; drug-gene (DGIs); drug-drug-gene (DDGIs); and drug-gene-gene (DGGIs). Interactions predicted to be 'substantial' were defined as follows: DDIs due to strong inhibitors/inducers, DGIs due to variant homozygous/compound heterozygous genotypes, and DDGIs/DGGIs where the constituent DDI/DGI(s) both influenced the victim drug in the same direction.

RESULTS

In the whole cohort, 727 (49.9%) patients had multimorbidity. Non-linear relationships between age and increasing comorbidities and decreasing coronary intervention were observed. There were 98.1% and 39.8% patients on ≥ 5 and ≥ 10 drugs, respectively (from n = 698); women received more non-cardiovascular drugs than men (median (IQR) 3 (1-5) vs 2 (1-4), p = 0.014). Overall, 98.7% patients had at least one actionable genotype. Within the interaction cohort, 882 interactions were identified in 503 patients (77.1%), of which 346 in 252 patients (38.7%) were substantial: 59.2%, 11.6%, 26.3%, and 2.9% substantial interactions were DDIs, DGIs, DDGIs, and DGGIs, respectively. CYP2C19 (49.5% of all interactions) and SLCO1B1 (18.4%) were involved in the largest number of interactions. Multimorbidity (p = 0.019) and number of drugs (p = 9.8 × 10-10) were both associated with patients having ≥ 1 substantial interaction. Multimorbidity (HR 1.76, 95% CI 1.10-2.82, p = 0.019), number of drugs (HR 1.10, 95% CI 1.04-1.16, p = 1.2 × 10-3), and age (HR 1.05, 95% CI 1.03-1.07, p = 8.9 × 10-7), but not drug interactions, were associated with increased subsequent major adverse cardiovascular events.

CONCLUSIONS

Multimorbidity, polypharmacy, and drug interactions are common after a NSTE-ACS. Replication of results is required; however, the high prevalence of DDGIs suggests integrating co-medications with genetic data will improve medicines optimisation.

How precise is quantitative prediction of pharmacokinetic effects due to drug-drug interactions and genotype from in vitro data? A comprehensive analysis on the example CYP2D6 and CYP2C19 substrates

Drug-drug interactions (DDI) and genomic variation (PG) can lead to dangerously high blood and tissue concentrations with some drugs but may be negligible with other drugs. Using a quantitative metaanalysis, we analyzed on the example of CYP2D6 and CYP2C19 substrates, how well the effects of DDI and PG can be predicted by in vitro methods. In addition, we analyzed the quantitative effect of prototypic inhibitors of the two enzymes in relation to their genetic deficiency. More than 600 published studies were screened which compared either human pharmacokinetics with and without comedication, or which compared human pharmacokinetics of deficient with extensive metabolizers, or which assessed metabolism by in vitro approaches. With human liver microsomes, the in vitro to in vivo agreement of fractional clearances was reasonably high if loss of substrate was quantified in the in vitro assays performed with and without enzyme specific inhibitors. Also a generally very high correlation between the clinical pharmacokinetic effects of inherited deficiency and inhibition by drug-drug interactions could be demonstrated. Most cases of poor correlation were explained by the lack of CYP2D6 versus CYP2C19 specificity of fluoxetine or by a poor knowledge of the quantitative contribution of the metabolic pathways if metabolite formation was quantified in the in vitro assays. The good correspondence of the in vitro data with clinical DDI and clinical PG studies may be a good basis for future application of these methods in drug development and drug therapy.

Pharmacogenomics of anticancer drugs: Personalising the choice and dose to manage drug response

The field of pharmacogenomics has made great strides in oncology over the last 20 years and indeed a significant number of pre-emptive genetic tests are now routinely undertaken prior to anticancer drug administration. Many of these gene-drug interactions are the fruits of candidate gene and genome-wide association studies, which have largely focused on common genetic variants (allele frequency>1%). Examples where there is clinical utility include genotyping or phenotyping for G6PD to prevent rasburicase-induced RBC haemolysis, and TPMT to prevent thiopurine-induced bone marrow suppression. Other associations such as CYP2D6 status in determining the efficacy of tamoxifen are more controversial because of contradictory evidence from different sources, which has led to variability in the implementation of testing. As genomic technology becomes ever cheaper and more accessible, we must look to the additional data our genome can provide to explain interindividual variability in anticancer drug response. Clearly genes do not act on their own and it is therefore important to investigate genetic factors in conjunction with clinical factors, interacting concomitant drug therapies and other factors such as the microbiome, which can all affect drug disposition. Taking account of all of these factors, in conjunction with the somatic genome, is more likely to provide better predictive accuracy in determining anticancer drug response, both efficacy and safety. This review summarises the existing knowledge related to the pharmacogenomics of anticancer drugs and discusses areas of opportunity for further advances in personalisation of therapy in order to improve both drug safety and efficacy.