Comparative metabolic capabilities and inhibitory profiles of CYP2D6.1, CYP2D6.10, and CYP2D6.17

Effect of isotretinoin on CYP2D6 and CYP3A activity in patients with severe acne

AIMS

Previously, retinoids have decreased CYP2D6 mRNA expression in vitro and induced CYP3A4 in vitro and in vivo. This study aimed to determine whether isotretinoin administration changes CYP2D6 and CYP3A activities in patients with severe acne.

METHODS

Thirty-three patients (22 females and 11 males, 23.5 ± 6.0 years old) expected to receive isotretinoin treatment completed the study. All participants were genotyped for CYP2D6 and CYP3A5. Participants received dextromethorphan (DM) 30 mg orally as a dual-probe substrate of CYP2D6 and CYP3A activity at two study timepoints: pre-isotretinoin treatment and with isotretinoin for at least 1 week. The concentrations of isotretinoin, DM and their metabolites were measured in 2-h postdose plasma samples and in cumulative 0-4-h urine collections using liquid chromatography-mass spectrometry.

RESULTS

In CYP2D6 extensive metabolizers, the urinary dextrorphan (DX)/DM metabolic ratio (MR) (CYP2D6 activity marker) was numerically, but not significantly, lower with isotretinoin administration compared to pre-isotretinoin (geometric mean ratio [GMR] [90% confidence interval (CI)] 0.78 [0.55, 1.11]). The urinary 3-hydroxymorphinan (3HM)/DX MR (CYP3A activity marker) was increased (GMR 1.18 [1.03, 1.35]) and the urinary DX-O-glucuronide/DX MR (proposed UGT2B marker) was increased (GMR 1.22 [1.06, 1.39]) with isotretinoin administration compared to pre-isotretinoin.

CONCLUSIONS

Administration of isotretinoin did not significantly reduce CYP2D6 activity in extensive metabolizers, suggesting that the predicted downregulation of CYP2D6 based on in vitro data does not translate into humans. We observed a modest increase in CYP3A activity (predominantly CYP3A4) with isotretinoin treatment. The data also suggest that DX glucuronidation is increased following isotretinoin administration.

Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation

Introduction

Pharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort.

Methods

Buffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models' performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites.

Results

Overall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model.

Discussion

The development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing.

Leveraging in Vitro Models for Clinically Relevant Rare CYP2D6 Variants in Pharmacogenomics

Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of up to 20% of small-molecule drugs and therefore, may impact the safety and efficacy of medicines in broad therapeutic areas. CYP2D6 is highly polymorphic, and the frequency of variants can differ across racial and ethnic populations, significantly affecting enzymatic function and drug metabolism. However, rare variants of CYP2D6 present a unique challenge for academia, industry, and regulatory agencies alike due to the lack of feasibility of characterizing their clinical relevance in clinical trials, particularly in variants that exhibit population-specific frequencies in racial and ethnic groups that are poorly represented in clinical trials. Despite significant advancement in pharmacogenomics, the substrate specificity and related clinical relevance of these CYP2D6 rare variants remain largely unclear, and further efforts are warranted to characterize the burden of these variants on adverse drug reactions and drug efficacy. Thus, cell-based in vitro systems can be used to inform substrate-specific effects and the overall relevance of a rare variant. Liver microsomes, cell-based expression systems, ex vivo primary samples, and purified variant protein have all been used with various substrates to potentially predict the clinical impact of new substrates. In this review, we identify rare variants of CYP2D6 that demonstrate differences across races in prevalence and thus are often unassessed in clinical trials. Accordingly, we examine current pharmacogenomic in vitro models used to analyze the functional impact of these rare variants in a substrate-specific manner. SIGNIFICANCE STATEMENT: Variants of CYP2D6 play a clinically relevant role in drug metabolism, leading to potential safety and efficacy concerns. Although the influence of prevalent variants is often well characterized, rare variants are traditionally not included in clinical trials. This review captures the clinical relevance of rare variants in CYP2D6 by highlighting in vitro models that analyze their impact on the metabolism of CYP2D6 substrates.

Tetrandrine for Targeting Therapy Resistance in Cancer

During the last five decades, there has been tremendous development in our understanding of cancer biology and the development of new and novel therapeutics to target cancer. However, despite these advances, cancer remains the second leading cause of death across the globe. Most cancer deaths are attributed to the development of resistance to current therapies. There is an urgent and unmet need to address cancer therapy resistance. Tetrandrine, a bis-benzyl iso-quinoline, has shown a promising role as an anti-cancer agent. Recent work from our laboratory and others suggests that tetrandrine and its derivatives could be an excellent adjuvant to the current arsenal of anti-cancer drugs. Herein, we provide an overview of resistance mechanisms to current therapeutics and review the existing literature on the anti-cancer effects of tetrandrine and its potential use for overcoming therapy resistance in cancer.

Drug repurposing: A novel strategy to target cancer stem cells and therapeutic resistance

Chemotherapy is an effortless and frequently used approach in cancer therapy. However, in most cases, it can only prolong life expectancy and does not guarantee a complete cure. Furthermore, chemotherapy is associated with severe adverse effects, one of the major complications of effective cancer therapy. In addition, newly published research outputs show that cancer stem cells are involved in cancer disease progression, drug resistance, metastasis, and recurrence and that they are functional in the trans-differentiation capacity of cancer stem cells to cancer cells in response to treatments. Novel strategies are therefore required for better management of cancer therapy. The prime approach would be to synthesize and develop novel drugs that need extensive resources, time, and endurance to be brought into therapeutic use. The subsequent approach would be to screen the anti-cancer activity of available non-cancerous drugs. This concept of repurposing non-cancer drugs as an alternative to current cancer therapy has become popular in recent years because using existing anticancer drugs has several adverse effects. Micronutrients have also been investigated for cancer therapy due to their significant anti-cancer effects with negligible or no side effects and availability in food sources. In this paper, we discuss an ideal hypothesis for screening available non-cancerous drugs with anticancer activity, with a focus on cancer stem cells and their clinical application for cancer treatment. Further, drug repurposing and the combination of micronutrients that can target both cancers and cancer stem cells may result in a better therapeutic approach leading to maximum tumor growth control.

Brain Tumors: Development, Drug Resistance, and Sensitization - An Epigenetic Approach

In this article, we describe contrasting developmental aspects of paediatric and adult brain tumours. We hypothesize that the formation of cancer progenitor cells, for both paediatric and adult, could be due to epigenetic events. However, the progression of adult brain tumours selectively involves more mutations compared to paediatric tumours. We further discuss epigenetic switches, comprising both histone modifications and DNA methylation, and how they can differentially regulate transcription and expression of oncogenes and tumour suppressor genes. Next, we summarize the currently available therapies for both types of brain tumours, explaining the merits and failures leading to drug resistance. We analyse different mechanisms of drug resistance and the role of epigenetics in this process. We then provide a rationale for combination therapy, which includes epigenetic drugs. In the end, we postulate a concept which describes how a combination therapy could be initiated. The timing, doses, and order of individual drug regimens will depend on the individual case. This type of combination therapy will be part of a personalized medicine which will differ from patient to patient.

Estimating the In Vivo Function of CYP2D6 Alleles through Population Pharmacokinetic Modeling of Brexpiprazole

Accurate prediction of CYP2D6 phenotype from genotype information is important to support safe and efficacious pharmacotherapy with CYP2D6 substrates. To facilitate accurate CYP2D6 genotype-phenotype translation, there remains a need to investigate the enzyme activity associated with individual CYP2D6 alleles using large clinical data sets. This study aimed to quantify and compare the in vivo function of different CYP2D6 alleles through population pharmacokinetic (PopPK) modeling of brexpiprazole using data from 13 clinical studies. A PopPK model of brexpiprazole and its two metabolites, DM-3411 and DM-3412, was developed based on plasma concentration samples from 826 individuals. As the minor metabolite, DM-3412, is formed via CYP2D6, the metabolic ratio of DM-3412:brexpiprazole calculated from the PopPK parameter estimates was used as a surrogate measure of CYP2D6 activity. A CYP2D6 genotype-phenotype analysis based on 496 subjects showed that the CYP2D6*2 allele (n = 183) was associated with only 10% enzyme activity relative to the wild-type allele (CYP2D6*1) and a low enzyme activity was consistently observed across genotypes containing CYP2D6*2. Among the decreased function alleles, the following enzyme activities relative to CYP2D6*1 were estimated: 23% for CYP2D6*9 (n = 20), 32% for CYP2D6*10 (n = 62), 64% for CYP2D6*14 (n = 1), 4% for CYP2D6*17 (n = 37), 4% for CYP2D6*29 (n = 13), and 9% for CYP2D6*41 (n = 64). These findings imply that a lower functional value would more accurately reflect the in vivo function of many reduced function CYP2D6 alleles in the metabolism of brexpiprazole. The low enzyme activity observed for CYP2D6*2, which has also been reported by others, suggests that the allele exhibits substrate-specific enzyme activity.

Relevance of CYP2D6 Gene Variants in Population Genetic Differentiation

A significant portion of the variability in complex features, such as drug response, is likely caused by human genetic diversity. One of the highly polymorphic pharmacogenes is CYP2D6, encoding an enzyme involved in the metabolism of about 25% of commonly prescribed drugs. In a directed search of the 1000 Genomes Phase III variation data, 86 single nucleotide polymorphisms (SNPs) in the CYP2D6 gene were extracted from the genotypes of 2504 individuals from 26 populations, and then used to reconstruct haplotypes. Analyses were performed using Haploview, Phase, and Arlequin softwares. Haplotype and nucleotide diversity were high in all populations, but highest in populations of African ancestry. Pairwise F_ST showed significant results for eleven SNPs, six of which were characteristic of African populations, while four SNPs were most common in East Asian populations. A principal component analysis of CYP2D6 haplotypes showed that African populations form one cluster, Asian populations form another cluster with East and South Asian populations separated, while European populations form the third cluster. Linkage disequilibrium showed that all African populations have three or more haplotype blocks within the CYP2D6 gene, while other world populations have one, except for Chinese Dai and Punjabi in Pakistan populations, which have two.

Important Drug-Drug Interactions for the Addiction Psychiatrist

The misuse of illicit substances, prescribed medications, and alcohol poses obvious health risks to afflicted individuals. When addressing these health risks, the overarching concerns generally relate to the direct effects that various substances can have on the functioning of multiple organ systems: cardiac, pulmonary, central nervous system, and others. What is not always evident, but potentially equally or even more dire, are the risks arising from drug-drug interactions involving illicit drugs and alcohol, whether with each other, or with prescribed medications. This review provides some basics that enable the reader to fruitfully approach the broad topic of drug-drug interactions.

Simultaneous determination of some opioid drugs using Cu-hemin MOF@MWCNTs as an electrochemical sensor

Due to its toxicological and pharmacological activity, the misuse and overuse of morphine (MO), codeine (CO), and heroine have attracted attention in the medical and forensic toxicology fields. This study proposed a new electrochemical sensor with an acceptable detection limit, linear range, and selectivity for simultaneous determination of MO and CO. This sensor is based on Cu-Hemin metal-organic framework (CHM) and multiwall carbon nanotubes (MWCNTs). First, a facile chemical method was chosen to synthesize CHM and then composite it with MWCNTs. Afterward, the structure of CHM@MWCNTs was verified by XRD, FT-IR, Raman spectroscopy, UV-vis, ICP-OES, FE-SEM, EDX, and elemental mapping. In the next step, under optimal conditions, this electrochemical sensor can sensitive simultaneous determination of MO and CO, showing a dynamic concentration range from 0.09 to 30 μM for both species and a low detection limit of 9.2 nM and 11.2 nM for MO and CO, respectively. Moreover, the applicability in real samples was confirmed by the simultaneous determination of MO and CO in human urine and MO injection. This work reveals a trustable sensor based on MOF and MWCNTs to simultaneously determine opioid drugs in clinical application.

Physiologically Based Pharmacokinetic Modeling to Describe the CYP2D6 Activity Score-Dependent Metabolism of Paroxetine, Atomoxetine and Risperidone

The cytochrome P450 2D6 (CYP2D6) genotype is the single most important determinant of CYP2D6 activity as well as interindividual and interpopulation variability in CYP2D6 activity. Here, the CYP2D6 activity score provides an established tool to categorize the large number of CYP2D6 alleles by activity and facilitates the process of genotype-to-phenotype translation. Compared to the broad traditional phenotype categories, the CYP2D6 activity score additionally serves as a superior scale of CYP2D6 activity due to its finer graduation. Physiologically based pharmacokinetic (PBPK) models have been successfully used to describe and predict the activity score-dependent metabolism of CYP2D6 substrates. This study aimed to describe CYP2D6 drug–gene interactions (DGIs) of important CYP2D6 substrates paroxetine, atomoxetine and risperidone by developing a substrate-independent approach to model their activity score-dependent metabolism. The models were developed in PK-Sim^®, using a total of 57 plasma concentration–time profiles, and showed good performance, especially in DGI scenarios where 10/12, 5/5 and 7/7 of DGI AUC_last ratios and 9/12, 5/5 and 7/7 of DGI C_max ratios were within the prediction success limits. Finally, the models were used to predict their compound’s exposure for different CYP2D6 activity scores during steady state. Here, predicted DGI AUC_ss ratios were 3.4, 13.6 and 2.0 (poor metabolizers; activity score = 0) and 0.2, 0.5 and 0.95 (ultrarapid metabolizers; activity score = 3) for paroxetine, atomoxetine and risperidone active moiety (risperidone + 9-hydroxyrisperidone), respectively.

Correlation of 1846G>A Polymorphism of CYP2D6 Gene with Haloperidol Efficacy and Safety in Patients with Alcoholic Hallucinoses

BACKGROUND

Previous studies have shown that haloperidol biotransformation occurs with participation of the CYP2D6 isoenzyme. The CYP2D6 gene is highly polymorphic, which may contribute to differences in its activity and in the haloperidol biotransformation rates across different individuals, resulting in variable drug efficacy and safety profiles.

PURPOSE

The study aimed to investigate the correlation of the 1846G> A polymorphism of CYP2D6 gene with the efficacy and safety rates of haloperidol in patients with alcoholic hallucinoses.

MATERIAL AND METHODS

One hundred male patients received 5-10 mg/day haloperidol by injections for 5 days. The efficacy and safety assessments were performed using the validated psychometric scales PANSS, UKU, and SAS. For genotyping, the real-time polymerase chain reaction was performed.

RESULTS

We revealed no statistically significant results in terms of haloperidol efficacy in patients with different genotypes (dynamics of the PANSS scores: (GG) -13.00 [-16.00; -11.00], (GA) -15.00 [-16.75; -13.00], p = 0,728). Our findings revealed the statistically significant results in terms of treatment safety evaluation (dynamics of the UKU scores: (GG) 8.00 [7.00; 10.00], (GA) 15.0 [9.25; 18.0], p < 0.001; dynamics of the SAS scores: (GG) 11.0 [9.0; 14.0], (GA) 14.50 [12.0; 18.0], p < 0.001.

CONCLUSION

These results suggest that genotyping for common CYP3A variants might have the potential to guide benzodiazepine withdrawal treatment. The effect of of the 1846G>A polymorphism of CYP2D6 gene on the safety profile of haloperidol was demonstrated in a group of 100 patients with alcoholic hallucinoses.

Pharmacogenomics for the efficacy and side effects of antihistamines

Antihistamines, especially H1 antihistamines, are widely used in the treatment of allergic diseases such as urticaria and allergic rhinitis, mainly for reversing elevated histamine and anti-allergic effects. Antihistamines are generally safe, but some patients experience adverse reactions, such as cardiotoxicity, central inhibition, and anticholinergic effects. There are also individual differences in antihistamine efficacy in clinical practice. The concept of individualized medicine has been deeply rooted in people's minds since it was put forward. Pharmacogenomics is the study of the role of inheritance in individual variations in drug response. In recent decades, pharmacogenomics has been developing rapidly, which provides new ideas for individualized medicine. Polymorphisms in the genes encoding metabolic enzymes, transporters, and target receptors have been shown to affect the efficacy of antihistamines. In addition, recent evidence suggests that gene polymorphisms influence urticaria susceptibility and antihistamine therapy. Here, we summarize current reports in this area, aiming to contribute to future research in antihistamines and clinical guidance for antihistamines use in individualized medicine.

Physiologically-based pharmacokinetic modeling of dextromethorphan to investigate interindividual variability within CYP2D6 activity score groups

This study provides a whole‐body physiologically‐based pharmacokinetic (PBPK) model of dextromethorphan and its metabolites dextrorphan and dextrorphan O‐glucuronide for predicting the effects of cytochrome P450 2D6 (CYP2D6) drug‐gene interactions (DGIs) on dextromethorphan pharmacokinetics (PK). Moreover, the effect of interindividual variability (IIV) within CYP2D6 activity score groups on the PK of dextromethorphan and its metabolites was investigated. A parent‐metabolite‐metabolite PBPK model of dextromethorphan, dextrorphan, and dextrorphan O‐glucuronide was developed in PK‐Sim and MoBi. Drug‐dependent parameters were obtained from the literature or optimized. Plasma concentration‐time profiles of all three analytes were gathered from published studies and used for model development and model evaluation. The model was evaluated comparing simulated plasma concentration‐time profiles, area under the concentration‐time curve from the time of the first measurement to the time of the last measurement (AUC_last) and maximum concentration (C_max) values to observed study data. The final PBPK model accurately describes 28 population plasma concentration‐time profiles and plasma concentration‐time profiles of 72 individuals from four cocktail studies. Moreover, the model predicts CYP2D6 DGI scenarios with six of seven DGI AUC_last and seven of seven DGI C_max ratios within the acceptance criteria. The high IIV in plasma concentrations was analyzed by characterizing the distribution of individually optimized CYP2D6 k_cat values stratified by activity score group. Population simulations with sampling from the resulting distributions with calculated log‐normal dispersion and mean parameters could explain a large extent of the observed IIV. The model is publicly available alongside comprehensive documentation of model building and model evaluation.

Perspectives from the Society for Pediatric Research: pharmacogenetics for pediatricians

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

Role of P34S, G169R, R296C, and S486T Substitutions in Ligand Access and Catalysis for Cytochrome P450 2D6 Allelic Variants CYP2D6*14A and CYP2D6*14B

BACKGROUND

Genetic polymorphism of cytochrome P450 (CYP) contributes to variability in drug metabolism, clearance, and response. This study aimed to investigate the functional and molecular basis for altered ligand binding and catalysis in CYP2D6*14A and CYP2D6*14B, two unique alleles common in the Asian population.

METHODS

CYP proteins expressed in Escherichia coli were studied using the substrate 3-cyano-7- ethoxycoumarin (CEC) and inhibitor probes (quinidine, fluoxetine, paroxetine, terbinafine) in the enzyme assay. Computer modelling was additionally used to create three-dimensional structures of the CYP2D6*14 variants.

RESULTS

Kinetics data indicated significantly reduced intrinsic clearance in CYP2D6*14 variants, suggesting that P34S, G169R, R296C, and S486T substitutions worked cooperatively to alter the conformation of the active site that negatively impacted the deethylase activity of CYP2D6. For the inhibition studies, IC50 values decreased in quinidine, paroxetine, and terbinafine but increased in fluoxetine, suggesting a varied ligand-specific susceptibility to inhibition. Molecular docking further demonstrated the role of P34S and R296C in altering access channel dimensions, thereby affecting ligand access and binding and subsequently resulting in varied inhibition potencies.

CONCLUSION

In summary, the differential selectivity of CYP2D6*14 variants for the ligands (substrate and inhibitor) was governed by the alteration of the active site and access channel architecture induced by the natural mutations found in the alleles.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.

Substrate specificity of CYP2D6 genetic variants

Genetic variation in the gene encoding CYP2D6 is used to guide drug prescribing in clinical practice. However, genetic variants in CYP2D6 show substrate-specific effects that are currently not accounted for. With a systematic literature, we retrieved 22 original studies describing in vitro experiments focusing on CYP2D6 alleles (CYP2D6*1, *2, *10 and *17) and substrates. Allele activity (clearance of the allele of interest divided by the clearance of the wildtype) was extracted. The results support the hypothesis of the existence of substrate specificity of the CYP2D6*17-allele (higher debrisoquine clearance), a subtle effect of the CYP2D6*10-allele (lower dextromethorphan clearance) but no substrate-specific effect of the CYP2D6*2-allele. Although our results support substrate specificity, for most substrates data are too sparse and require further studies.

Variability in Human In Vitro Enzyme Kinetics

There are many factors which are known to cause variability in human in vitro enzyme kinetic data. Factors such as the source of enzyme and how it was prepared, the genetics and background of the donor, how the in vitro studies are designed, and how the data are analyzed contribute to variability in the resulting kinetic parameters. It is important to consider not only the factors which cause variability within an experiment, such as selection of a probe substrate, but also those that cause variability when comparing kinetic data across studies and laboratories. For example, the artificial nature of the microsomal lipid membrane and microenvironment in some recombinantly expressed enzymes, relative to those found in native tissue microsomes, has been shown to influence enzyme activity and thus can be a source of variability when comparing across the two different systems. All of these factors, and several others, are discussed in detail in the chapter below. In addition, approaches which can be used to visualize the uncertainty arising from the use of enzyme kinetic data within the context of predicting human pharmacokinetics are discussed.

Evaluation of the CYP2D6 Haplotype Activity Scores Based on Metabolic Ratios of 4,700 Patients Treated With Three Different CYP2D6 Substrates

The metabolic activity of the polymorphic CYP2D6 enzyme is dependent on the CYP2D6 genotype; however, the guidelines for translating the genotype into phenotype, which are of relevance for adequate drug dose personalization, are ambiguous. In the present study, retrospective therapeutic drug monitoring data from 4,700 CYP2D6 genotyped patients treated with risperidone, venlafaxine, and/or aripiprazole were analyzed to quantify the effect of CYP2D6 genotype on the CYP2D6 metabolic activities, as measured by metabolic ratios of these substrates. The patients were categorized into diplotypes based on the presence of normal function (CYP2D6Norm), nonfunctional (CYP2D6Nonf), and decreased function (CYP2D6Decr; i.e., CYP2D6*9, CYP2D6*10, and CYP2D6*41) CYP2D6 haplotypes. Significant correlations between the metabolic ratios were observed in patients (n = 77-103) cotreated with risperidone and venlafaxine, risperidone and aripiprazole, or venlafaxine and aripiprazole (ρ = 0.874, 0.785, and 0.644, respectively; P < 0.001 for all). Relative metabolic CYP2D6 diplotype activity was calculated based on that the metabolic ratios, where median values for CYP2D6Nonf/Nonf and CYP2D6Norm/Norm subgroups were set to 0% and 100%, respectively. The relative CYP2D6 activities were: 7.0% for CYP2D6Nonf/*41, 16.7% for CYP2D6Nonf/*9-10, 13.2% for CYP2D6*41/*41, 24.9% for CYP2D6*41/*9-10, 33.1% for CYP2D6*9-10/*9-10, 41.3% for CYP2D6Nonf/Norm, 55.0% for CYP2D6*41/Norm, 58.9% for CYP2D6*9-10/Norm, and 149.2% for CYP2D6Norm/Normx2. Compared with the CYP2D6Norm alleles, the activity scores of CYP2D6*41 and CYP2D6*9-10 alleles were estimated to be one sixth and one third, respectively. The results of this highly powered study provide a solid basis for the translation of the CYP2D6 genotype into a drug metabolic phenotype.

Cytochrome P450 2D6 genotype-phenotype characterization through population pharmacokinetic modeling of tedatioxetine

The cytochrome P450 (CYP) 2D6 enzyme exhibits large interindividual differences in metabolic activity. Patients are commonly assigned a CYP2D6 phenotype based on their CYP2D6 genotype, but there is a lack of consensus on how to translate genotypes into phenotypes, causing inconsistency in genotype‐based dose recommendations. The aim of this study was to quantify and compare the impact of different CYP2D6 genotypes and alleles on CYP2D6 metabolism using a large clinical data set. A population pharmacokinetic (popPK) model of tedatioxetine and its CYP2D6‐dependent metabolite was developed based on pharmacokinetic data from 578 subjects. The CYP2D6‐mediated metabolism was quantified for each subject based on estimates from the final popPK model, and CYP2D6 activity scores were calculated for each allele using multiple linear regression. The activity scores estimated for the decreased function alleles were 0.46 (CYP2D6*9), 0.34 (CYP2D6*10), 0.01 (CYP2D6*17), 0.65 (CYP2D6*29), and 0.21 (CYP2D6*41). The CYP2D6*17 and CYP2D6*41 alleles were thus associated with the lowest CYP2D6 activity, although only the difference to the CYP2D6*9 allele was shown to be statistically significant (p = 0.02 and p = 0.05, respectively). The study provides new in vivo evidence of the enzyme function of different CYP2D6 genotypes and alleles. Our findings suggest that the activity score assigned to CYP2D6*41 should be revisited, whereas CYP2D6*17 appears to exhibit substrate‐specific behavior. Further studies are needed to confirm the findings and to improve the understanding of CYP2D6 genotype–phenotype relationships across substrates.

In vitro inhibitory effects of glucosamine, chondroitin and diacerein on human hepatic CYP2D6

OBJECTIVES

Glucosamine, chondroitin and diacerein are natural compounds commonly used in treating osteoarthritis. Their concomitant intake may trigger drug-natural product interactions. Cytochrome P450 (CYP) has been implicated in such interactions. Cytochrome P450 2D6 (CYP2D6) is a major hepatic CYP involved in metabolism of 25% of the clinical drugs. This study aimed to investigate the inhibitory effect of these antiarthritic compounds on CYP2D6.

METHODS

CYP2D6 was heterologously expressed in Escherichia coli. CYP2D6-antiarthritic compound interactions were studied using in vitro enzyme kinetics assay and molecular docking.

RESULTS

The high-performance liquid chromatography (HPLC)-based dextromethorphan O-demethylase assay was established as CYP2D6 marker. All glucosamines and chondroitins weakly inhibited CYP2D6 (IC₅₀ values >300 µM). Diacerein exhibited moderate inhibition with IC₅₀ and K _i values of 34.99 and 38.27 µM, respectively. Its major metabolite, rhein displayed stronger inhibition potencies (IC₅₀=26.22 μM and K _i =32.27 μM). Both compounds exhibited mixed-mode of inhibition. In silico molecular dockings further supported data from the in vitro study. From in vitro-in vivo extrapolation, rhein presented an area under the plasma concentration-time curve (AUC) ratio of 1.5, indicating low potential to cause in vivo inhibition.

CONCLUSIONS

Glucosamine, chondroitin and diacerein unlikely cause clinical interaction with the drug substrates of CYP2D6. Rhein, exhibits only low potential to cause in vivo inhibition.

In vitro inhibitory effects of glucosamine, chondroitin and diacerein on human hepatic CYP2D6

OBJECTIVES

Glucosamine, chondroitin and diacerein are natural compounds commonly used in treating osteoarthritis. Their concomitant intake may trigger drug-natural product interactions. Cytochrome P450 (CYP) has been implicated in such interactions. Cytochrome P450 2D6 (CYP2D6) is a major hepatic CYP involved in metabolism of 25% of the clinical drugs. This study aimed to investigate the inhibitory effect of these antiarthritic compounds on CYP2D6.

METHODS

CYP2D6 was heterologously expressed in Escherichia coli. CYP2D6-antiarthritic compound interactions were studied using in vitro enzyme kinetics assay and molecular docking.

RESULTS

The high-performance liquid chromatography (HPLC)-based dextromethorphan O-demethylase assay was established as CYP2D6 marker. All glucosamines and chondroitins weakly inhibited CYP2D6 (IC50 values >300 µM). Diacerein exhibited moderate inhibition with IC50 and K i values of 34.99 and 38.27 µM, respectively. Its major metabolite, rhein displayed stronger inhibition potencies (IC50=26.22 μM and K i =32.27 μM). Both compounds exhibited mixed-mode of inhibition. In silico molecular dockings further supported data from the in vitro study. From in vitro-in vivo extrapolation, rhein presented an area under the plasma concentration-time curve (AUC) ratio of 1.5, indicating low potential to cause in vivo inhibition.

CONCLUSIONS

Glucosamine, chondroitin and diacerein unlikely cause clinical interaction with the drug substrates of CYP2D6. Rhein, exhibits only low potential to cause in vivo inhibition.

Quantification of In Vivo Metabolic Activity of CYP2D6 Genotypes and Alleles Through Population Pharmacokinetic Analysis of Vortioxetine

Assignment of CYP2D6 phenotype from genotype data can be challenging and despite efforts to standardize translation, there is currently no universally accepted method. To facilitate standardization, there remains a need to precisely quantify the in vivo function of different CYP2D6 genotypes. Vortioxetine is metabolized to its major metabolite, Lu AA34443, primarily via CYP2D6. The aim of this study was to quantify the in vivo CYP2D6 activity of different CYP2D6 alleles and genotypes through population pharmacokinetic (PopPK) modeling of vortioxetine and Lu AA34443. Plasma concentration data of vortioxetine and Lu AA34443 from 1,140 subjects originating from 29 clinical pharmacology studies were pooled for the analysis. A joint PopPK model described the pharmacokinetics of vortioxetine and Lu AA34443 simultaneously and provided estimates of the CYP2D6-mediated metabolism for each subject. Subjects normally classified as CYP2D6 intermediate metabolizers (IMs) showed different levels of CYP2D6 activity with carriers of one fully functional allele and one null function allele having 77% higher CYP2D6 activity compared with carriers of two decreased function alleles (P < 0.0001). The decreased function alleles were associated with different levels of reduction of CYP2D6 activity. Fixing the activity of fully functional alleles to 1.0, the relative activities of CYP2D6*9, CYP2D6*10, CYP2D6*17, and CYP2D6*41 were 0.22, 0.37, 0.17, and 0.21, respectively. The activity of CYP2D6*10 was shown to be significantly greater than that of CYP2D6*17 (P = 0.01) and CYP2D6*41 (P = 0.02). These results warrant further discussion of current CYP2D6 genotype-phenotype classification systems particularly regarding decreased function alleles and the IM phenotype.

Physiologically Based Pharmacokinetic Modeling of Metoprolol Enantiomers and α-Hydroxymetoprolol to Describe CYP2D6 Drug-Gene Interactions

The beta-blocker metoprolol (the sixth most commonly prescribed drug in the USA in 2017) is subject to considerable drug–gene interaction (DGI) effects caused by genetic variations of the CYP2D6 gene. CYP2D6 poor metabolizers (5.7% of US population) show approximately five-fold higher metoprolol exposure compared to CYP2D6 normal metabolizers. This study aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model to predict CYP2D6 DGIs with metoprolol. The metoprolol (R)- and (S)-enantiomers as well as the active metabolite α-hydroxymetoprolol were implemented as model compounds, employing data of 48 different clinical studies (dosing range 5–200 mg). To mechanistically describe the effect of CYP2D6 polymorphisms, two separate metabolic CYP2D6 pathways (α-hydroxylation and O-demethylation) were incorporated for both metoprolol enantiomers. The good model performance is demonstrated in predicted plasma concentration–time profiles compared to observed data, goodness-of-fit plots, and low geometric mean fold errors of the predicted AUC_last (1.27) and C_max values (1.23) over all studies. For DGI predictions, 18 out of 18 DGI AUC_last ratios and 18 out of 18 DGI C_max ratios were within two-fold of the observed ratios. The newly developed and carefully validated model was applied to calculate dose recommendations for CYP2D6 polymorphic patients and will be freely available in the Open Systems Pharmacology repository.

A Tutorial for Pharmacogenomics Implementation Through End-to-End Clinical Decision Support Based on Ten Years of Experience from PREDICT

Vanderbilt University Medical Center implemented pharmacogenomics (PGx) testing with the Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT) initiative in 2010. This tutorial reviews the laboratory considerations, technical infrastructure, and programmatic support required to deliver panel-based PGx testing across a large health system with examples and experiences from the first decade of the PREDICT initiative. From the time of inception, automated clinical decision support (CDS) has been a critical capability for delivering PGx results to the point-of-care. Key features of the CDS include human-readable interpretations and clinical guidance that is anticipatory, actionable, and adaptable to changes in the scientific literature. Implementing CDS requires that structured results from the laboratory be encoded in standards-based messages that are securely ingested by electronic health records. Translating results to guidance also requires an informatics infrastructure with multiple components: (1) to manage the interpretation of raw genomic data to "star allele" results to expected phenotype, (2) to define the rules that associate a phenotype with recommended changes to clinical care, and (3) to manage and update the knowledge base. Knowledge base management is key to processing new results with the latest guidelines, and to ensure that historical genomic results can be reinterpreted with revised CDS. We recommend that these components be deployed with institutional authorization, programmatic support, and clinician education to govern the CDS content and policies around delivery.

Using a pharmacogenetic clinical decision support system to improve psychopharmacotherapy dosing in patients with affective disorders

Objectives Although pharmacogenetic tests provide the information on a genotype and the predicted phenotype, these tests do not themselves provide the interpretation of data for a physician. Currently, there are approximately two dozen pharmacogenomic clinical decision support systems (CDSSs) used in psychiatry. Implementation of the CDSSs forming the recommendations on drug and dose selection according to the results of pharmacogenetic testing is an urgent task. Fulfillment of this task will allow increasing the efficacy of therapy and decreasing the risk of undesirable side effects. Methods The study included 118 male patients (48 in the main group and 70 in the control group) with affective disorders and comorbid alcohol use disorder. To evaluate the efficacy and safety of therapy, several international psychometric scales and rating scales to measure side effects were used. Genotyping was performed using the real-time polymerase chain reaction with allele-specific hybridization. Pharmacogenetic testing results were interpreted using free software PGX2 (LLE Medicine, Russian Federation, Biomedical Cluster of Skolkovo, Moscow Innovative Cluster; www.pgx2.com). Results The statistically significant differences across the scores on psychometric scales were revealed. For instance, the total score on the Hamilton Rating Scale for Depression by day 9 was 9.0 [8.0; 10.0] for the main group and 11.0 [10.0; 12.0] (p<0.001) for the control group and by day 16 it was 4.0 [2.0; 6.0] for the main group and 14.0 [13.0; 14.0] (p<0.001) for the control group. The UKU Side-Effect Rating Scale (UKU) also revealed a statistically significant difference. The total score on the UKU scale by day 9 was 4.0 [4.0; 5.0] for the main group and 5.0 [5.0; 6.0] (p<0.001) for the control group and by day 16 this difference grew significantly: 3.0 [0.0; 4.2] for the main group and 9.0 [7.0; 11.0] (p<0.001) for the control group. Conclusions Pharmacogenetic-guided personalization of the drug dose in patients with affective disorders and comorbid alcohol use disorder can reduce the risk of undesirable side effects and pharmacoresistance. It allows recommending the use of pharmacogenetic CDSSs for optimizing drug dosage.

Genetic and Epigenetic Modulation of Drug Resistance in Cancer: Challenges and Opportunities

Cancer is a complex disease that has the ability to develop resistance to traditional therapies. The current chemotherapeutic treatment has become increasingly sophisticated, yet it is not 100% effective against disseminated tumours. Anticancer drugs resistance is an intricate process that ascends from modifications in the drug targets suggesting the need for better targeted therapies in the therapeutic arsenal. Advances in the modern techniques such as DNA microarray, proteomics along with the development of newer targeted drug therapies might provide better strategies to overcome drug resistance. This drug resistance in tumours can be attributed to an individual's genetic differences, especially in tumoral somatic cells but acquired drug resistance is due to different mechanisms, such as cell death inhibition (apoptosis suppression) altered expression of drug transporters, alteration in drug metabolism epigenetic and drug targets, enhancing DNA repair and gene amplification. This review also focusses on the epigenetic modifications and microRNAs, which induce drug resistance and contributes to the formation of tumour progenitor cells that are not destroyed by conventional cancer therapies. Lastly, this review highlights different means to prevent the formation of drug resistant tumours and provides future directions for better treatment of these resistant tumours.

Divergence of an association between depressive symptoms and a dopamine polygenic score in Caucasians and Asians

A recent study reported a negative association between a putatively functional dopamine (DA) polygenic score, indexing higher levels of DA signaling, and depressive symptoms. We attempted to replicate this association using data from the Duke Neurogenetics Study. Our replication attempt was made in a subsample of 520 non-Hispanic Caucasian volunteers (277 women, mean age 19.78 ± 1.24 years). The DA polygenic score was based on the following five loci: rs27072 (SLC6A3/DAT1), rs4532 (DRD1), rs1800497 (DRD2/ANKK1), rs6280 (DRD3), and rs4680 (COMT). Because the discovery sample in the original study consisted mostly of Asian participants, we also conducted a post hoc analysis in a smaller subsample of Asian volunteers (N = 316, 179 women, mean age 19.61 ± 1.32 years). In the primary sample of non-Hispanic Caucasians, a linear regression analysis controlling for sex, age, socioeconomic status (SES), body mass index, genetic ancestry, and both early and recent life stress, revealed that higher DA polygenic scores were associated with higher self-reported symptoms of depression. This was in contrast to the original association of higher DA polygenic scores and lower depressive symptoms. However, the direction of the association in our Asian subsample was consistent with this original finding. Our results also suggested that compared to the Asian subsample, the non-Hispanic Caucasian subsample was characterized by higher SES, lower early and recent life stress, and lower depressive symptoms. These differences may have contributed to the observed divergence in associations. Collectively, the current findings add to evidence that specific genetic associations may differ between populations and further encourage explicit modeling of race/ethnicity in examining the polygenic nature of depressive symptoms and depression.

Adverse pharmacokinetic interactions between illicit substances and clinical drugs

Adverse pharmacokinetic interactions between illicit substances and clinical drugs are of a significant health concern. Illicit substances are taken by healthy individuals as well as by patients with medical conditions such as mental illnesses, acquired immunodeficiency syndrome, diabetes mellitus and cancer. Many individuals that use illicit substances simultaneously take clinical drugs meant for targeted treatment. This concomitant usage can lead to life-threatening pharmacokinetic interactions between illicit substances and clinical drugs. Optimal levels and activity of drug-metabolizing enzymes and drug-transporters are crucial for metabolism and disposition of illicit substances as well as clinical drugs. However, both illicit substances and clinical drugs can induce changes in the expression and/or activity of drug-metabolizing enzymes and drug-transporters. Consequently, with concomitant usage, illicit substances can adversely influence the therapeutic outcome of coadministered clinical drugs. Likewise, clinical drugs can adversely affect the response of coadministered illicit substances. While the interactions between illicit substances and clinical drugs pose a tremendous health and financial burden, they lack a similar level of attention as drug-drug, food-drug, supplement-drug, herb-drug, disease-drug, or other substance-drug interactions such as alcohol-drug and tobacco-drug interactions. This review highlights the clinical pharmacokinetic interactions between clinical drugs and commonly used illicit substances such as cannabis, cocaine and 3, 4-Methylenedioxymethamphetamine (MDMA). Rigorous efforts are warranted to further understand the underlying mechanisms responsible for these clinical pharmacokinetic interactions. It is also critical to extend the awareness of the life-threatening adverse interactions to both health care professionals and patients.

PharmVar GeneFocus: CYP2D6

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

An Explorative Study of CYP2D6’s Polymorphism in a Sample of Chronic Pain Patients

Background

A proper antalgic treatment is based on the use of titrated drugs to provide adequate relief and a good tolerability profile. Therapies have a variable effectiveness among subjects depending on medical and genetic conditions. CYP2D6 variations determine a different clinical response to most analgesic drugs commonly used in daily clinical practice by influencing the drugs’ pharmacokinetics. This study was a monocentric clinical trial exploring the CYP2D6 variants in 100 patients with a diagnosis of chronic pain.

Methods

DNA was extracted to evaluate the genotype and to classify patients as normal-fast (gNMs-F), normal-slow (gNMs-S), ultrarapid (gUMs), intermediate (gIMs), and poor metabolizers (gPMs) using the Activity Score (AS). Information on therapies and general side effects experienced by patients was collected. Nongenetic co-factors were evaluated to examine the discrepancy between metabolic profile predicted from genotype (gPh) and metabolic profile (phenocopying).

Results

The distribution of our data underlined the prevalence of the gNMs-F (67%), whereas gNMs-S were 24%, gIMs 6%, gPMs 3%, and no gUMs were found, resulting in 33% of patients with reduced metabolic activity. In the analyzed population sample, 86% and 56% of patients, respectively, took at least one or two drugs inhibiting in vitro activity of the CYP2D6 enzyme.

Conclusions

Over one-third of the enrolled patients showed altered CYP2D6 enzymatic metabolic activity, with a risk of phenocopying potentially due to polypharmacology.

Trial registration

ClinicalTrials.gov ID: NCT03411759.

Effects of 24 CYP2D6 variants found in Chinese population on the metabolism of clonidine in vitro

BACKGROUND AND OBJECTIVES

Clonidine has been clinically used to treat Tourette's syndrome for decades. There was research finding that clonidine possessed the best risk-benefit ratio, especially for patients associated with attention deficit hyperactivity disorder. CYP2D6 is a significant member of Cytochrome P450 enzymes. The genetic polymorphisms of CYP2D6 greatly affect the clinical effects of drugs even lead to side effects and medical malpractice. Our goal is to research the effect of CYP2D6 genetic polymorphism on the metabolism of clonidine and evaluate the functions of 22 CYP2D6 allelic variants in vitro, which were discovered in Chinese Han population recently.

METHODS

This study was carried out through a mature incubation system. The wild-type CYP2D6*1 and 24 variants (CYP2D6*2, CYP2D6*10 and 22 novel CYP2D6 variants) were expressed in insect cells, and the catalytic activity of all the variants were assessed by substrate clonidine. Metabolite 4-OH clonidine was accurately detected via ultra-performance liquid-chromatography tandem mass spectrometry to evaluate the effect of CYP2D6 genetic polymorphism on the clonidine.

RESULT

Among the 22 novel CYP2D6 variants, the intrinsic clearance (Vmax/Km) of 21 variants were significantly decreased (from 1.53% to 83.25%) compared to the wild-type. In particular, the following seven variants (CYP2D6* 2, CYP2D6* 10, CYP2D6* 93, CYP2D6* 95, E215K, V327 M and R497C) attract more attention, of which the intrinsic clearance decreased more than 70% compared to the wild-type. Because the variants with significantly reduced intrinsic clearance are more likely to cause adverse reactions than the variants with increased or little changed intrinsic clearance. In addition, the related pharmacokinetic parameters of CYP2D6*92 and CYP2D6*96 could not be acquired for the defect of CYP2D6 nucleotide.

CONCLUSION

We comprehensively evaluated the effect of 22 novel CYP2D6 variants on the metabolism of clonidine for the first time and hoped corresponding data provide a reference for metabolism of clonidine for further studies in vivo, and extend our understanding of the clinical drug toxicity or ineffectiveness by CYP2D6 genetic polymorphism.

Multi-drug cocktails: Impurities in commonly used illicit drugs seized by police in Queensland, Australia

BACKGROUND

Impurities in commonly used illicit drugs raise concerns for unwitting consumers when pharmacologically active adulterants, especially new psychoactive substances (NPS), are used. This study examines impurities detected in illicit drugs seized in one Australian jurisdiction.

METHODS

Queensland Health Forensic and Scientific Services provided analytical data. Data described the chemical composition of 9346 samples of 11 illicit drugs seized by police during 2015-2016. Impurities present in primary drugs were summarized and tabulated. A systematic search for published evidence reporting similar analyses was conducted.

RESULTS

Methamphetamine was the primary drug in 6608 samples, followed by MDMA (1232 samples) and cocaine (516 samples). Purity of primary drugs ranged from ∼30% for cocaine, 2-CB and GHB to >90% for THC, methamphetamine, heroin and MDMA. Methamphetamine and MDMA contained the largest variety of impurities: 22 and 18 variants, respectively. Drug adulteration patterns were broadly similar to those found elsewhere, including NPS, but in some primary drugs impurities were found which had not been reported elsewhere. Psychostimulants were adulterated with each other. Levamisole was a common impurity in cocaine. Psychedelics were adulterated with methamphetamine and NPS. Opioids were quite pure, but some samples contained methamphetamine and synthetic opioids.

CONCLUSIONS

Impurities detected were mostly pharmacologically active adulterants probably added to enhance desired effects or for active bulking. Given the designer nature of these drug cocktails, the effects of the adulterated drugs on users from possible complex multi-drug interactions is unpredictable. Awareness-raising among users, research into complex multi-drug effects and ongoing monitoring is required.

Effects of CYP2D6 activity on the efficacy and safety of mirtazapine in patients with depressive disorders and comorbid alcohol use disorder

The objective of the study was to investigate the effects of CYP2D6 activity on the efficacy and safety of mirtazapine in patients with depressive disorders and comorbid alcohol use disorder who received mirtazapine. The study included 109 Russian patients who received mirtazapine at a dose of 30.0 [15.0; 45.0] mg per day. Genotyping of CYP2D6*4 (1846G > A, rs3892097) was performed using real-time polymerase chain reaction with allele-specific hybridization. The activity of CYP2D6 was evaluated by determining the concentration of endogenous substrate of the enzyme and its urinary metabolite - pinoline to 6-hydroxy-1,2,3,4-tetrahydro-beta-carboline ratio, using high-performance liquid chromatography - mass spectrometry. The statistically significant differences between the scores on the Hamilton Depression Rating Scale (HAMD) in patients with different genotypes were revealed by day 16: (GG) 5.0 [3.0; 6.0], (GA) 1.5 [1.0; 3.2] (p < 0.001), and for the The UKU Side Effects Rating Scale (UKU): (GG) 6.0 [6.0; 7.0], (GA) 8.5 [8.0; 10.0] (p < 0.001). The calculation of correlation coefficients between the differences in scale scores and metabolic rate showed the presence of statistically significant weak inverse correlation with the efficacy indicator evaluated by HAMD (r = -0.278, p < 0.05), but not by UKU (r = 0.274, p > 0.05). This study demonstrated that an increased CYP2D6 activity reduces the efficacy of treatment with mirtazapine.

Polyamidoamine dendrimers-based nanomedicine for combination therapy with siRNA and chemotherapeutics to overcome multidrug resistance

Multidrug resistance (MDR) significantly decreases the therapeutic efficiency of anti-cancer drugs. Its reversal could serve as a potential method to restore the chemotherapeutic efficiency. Downregulation of MDR-related proteins with a small interfering RNA (siRNA) is a promising way to reverse the MDR effect. Additionally, delivery of small molecule therapeutics simultaneously with siRNA can enhance the efficiency of chemotherapy by dual action in MDR cell lines. Here, we conjugated the dendrimer, generation 4 polyamidoamine (G4 PAMAM), with a polyethylene glycol (PEG)-phospholipid copolymer. The amphiphilic conjugates obtained spontaneously self-assembled into a micellar nano-preparation, which can be co-loaded with siRNA onto PAMAM moieties and sparingly water-soluble chemotherapeutics into the lipid hydrophobic core. This system was co-loaded with doxorubicin (DOX) and therapeutic siRNA (siMDR-1) and tested for cytotoxicity against MDR cancer cells: human ovarian carcinoma (A2780 ADR) and breast cancer (MCF7 ADR). The combination nanopreparation effectively downregulated P-gp in MDR cancer cells and reversed the resistance towards DOX.

Analysis of Lithuanian CYP2D6 polymorphism and its relevance to psychiatric care of the local population

BACKGROUND

CYP450 system gene CYP2D6 polymorphisms have been associated with an altered response to psychotropic drugs. While there exists interindividual and interethnic differences of clinical significance, there is no data concerning the Lithuanian population.

AIMS

To determine the distribution of CYP2D6 alleles and predicted phenotype in the Lithuanian population, compare it to other Europeans and find the differences between patients with affective disorders and the healthy population.

METHODS

Our study sample consisted of 179 subjects that included 104 healthy volunteers and 75 patients with clinical diagnosis of affective disorders according to ICD-10AM classification, treated in hospital settings. DNA samples were taken from the blood and alleles of the CYP2D6 gene were determined for each participant. Frequencies were compared to other Europeans.

RESULTS

The frequency of the most common alleles *1 and *2 was 45.0% and 28.8% accordingly. Dysfunctional *5 (1 vs. 30, p < .002) allele was less frequent in Lithuania inhabitants than previously established in other Europeans. There were no polymorphisms of the CYP2D6 gene that could be associated with changes in drug metabolism in the patients. The functional CYP2D6 *2 allele was more prevalent in the control group, while the non functional CYP2D6 *4 allele was more prevalent in the patient group (p < .05 for both cases).

CONCLUSION

The genetic makeup of Lithuanians was generally comparable to other Europeans, but fewer Lithuanians had non-functional *5 allele. More patients had non-functional alleles. Study findings contradict previous results from other countries, where CYP2D6 gene polymorphism was associated with treatment outcomes.

Sensitization of Drug Resistant Cancer Cells: A Matter of Combination Therapy

Cancer drug resistance is an enormous problem. It is responsible for most relapses in cancer patients following apparent remission after successful therapy. Understanding cancer relapse requires an understanding of the processes underlying cancer drug resistance. This article discusses the causes of cancer drug resistance, the current combination therapies, and the problems with the combination therapies. The rational design of combination therapy is warranted to improve the efficacy. These processes must be addressed by finding ways to sensitize the drug-resistant cancers cells to chemotherapy, and to prevent formation of drug resistant cancer cells. It is also necessary to prevent the formation of cancer progenitor cells by epigenetic mechanisms, as cancer progenitor cells are insensitive to standard therapies. In this article, we emphasize the role for the rational development of combination therapy, including epigenetic drugs, in achieving these goals.

Molecular Dynamics Simulations Reveal Structural Differences among Allelic Variants of Membrane-Anchored Cytochrome P450 2D6

Cytochrome P450 2D6 (CYP2D6) is an enzyme that is involved in the metabolism of roughly 25% of all marketed drugs and therefore belongs to the most important enzymes in drug metabolism. CYP2D6 features a high degree of genetic polymorphism that can significantly affect the metabolic activity of an individual. In extreme cases, structural changes at the level of single amino acids can either increase its enzymatic activity abolishing the drug therapeutic effect or completely disable the enzyme and elevate drug plasma level potentially leading to adverse effects. In this study, starting from the crystal structure, we built a full-length membrane-anchored all-atom model of the wild-type CYP2D6 as well as five of its variants differing in the enzymatic activity. We validated our models with available experimental data and compared their structural properties with molecular dynamics simulations. The main focus of this study was to identify differences that could mechanistically explain the altered activity of the variants and improve our understanding of their functioning. We observed differences in the opening frequencies and minimal diameters of tunnels that connect the buried active site to the surrounding solvent environment. The variants CYP2D6*4 and CYP2D6*10 associated with missing or decreased activity showed less frequent opening of the tunnels compared to the wild-type. Both CYP2D6*10 and CYP2D6*17 showed a deprivation of an important ligand tunnel suggesting a feasible reason for their altered substrate specificity. Next, the altered fold at the N-terminal anchor region and the decreased active site volume caused by the amino acid mutations of the CYP2D6*4 variant offer an explanation for the absence of its metabolic activity. The mutations in CYP2D6*53 contributed to a significant enlargement of an important ligand tunnel and an extension of the active site cavity. This could explain the altered metabolic profile as well as the enhanced metabolic rates of this particular variant supporting its designation as a possible cause for the ultrarapid metabolizer phenotype. We believe these novel structural insights could advance the fields of personalized medicine and enzyme engineering. Furthermore, they could aid in guiding laboratory as well as computational experiments in the future.

Biotransformation, Using Recombinant CYP450-Expressing Baker's Yeast Cells, Identifies a Novel CYP2D6.10A122V Variant Which Is a Superior Metabolizer of Codeine to Morphine Than the Wild-Type Enzyme

CYP2D6, a cytochrome P450 (CYP) enzyme, metabolizes codeine to morphine. Within the human body, 0-15% of codeine undergoes O-demethylation by CYP2D6 to form morphine, a far stronger analgesic than codeine. Genetic polymorphisms in wild-type CYP2D6 (CYP2D6-wt) are known to cause poor-to-extensive metabolism of codeine and other CYP2D6 substrates. We have established a platform technology that allows stable expression of human CYP genes from chromosomal loci of baker's yeast cells. Four CYP2D6 alleles, (i) chemically synthesized CYP2D6.1, (ii) chemically synthesized CYP2D6-wt, (iii) chemically synthesized CYP2D6.10, and (iv) a novel CYP2D6.10 variant CYP2D6-C (i.e., CYP2D6.10^A122V) isolated from a liver cDNA library, were cloned for chromosomal integration in yeast cells. When expressed in yeast, CYP2D6.10 enzyme shows weak activity compared with CYP2D6-wt and CYP2D6.1 which have moderate activity, as reported earlier. Surprisingly, however, the CYP2D6-C enzyme is far more active than CYP2D6.10. More surprisingly, although CYP2D6.10 is a known low metabolizer of codeine, yeast cells expressing CYP2D6-C transform >70% of codeine to morphine, which is more than twice that of cells expressing the extensive metabolizers, CYP2D6.1, and CYP2D6-wt. The latter two enzymes predominantly catalyze formation of codeine's N-demethylation product, norcodeine, with >55% yield. Molecular modeling studies explain the specificity of CYP2D6-C for O-demethylation, validating observed experimental results. The yeast-based CYP2D6 expression systems, described here, could find generic use in CYP2D6-mediated drug metabolism and also in high-yield chemical reactions that allow the formation of regio-specific dealkylation products.

Physiologically based pharmacokinetic modelling of atomoxetine with regard to CYP2D6 genotypes

Atomoxetine is a norepinephrine reuptake inhibitor indicated in the treatment of attention-deficit/hyperactivity disorder. It is primarily metabolized by CYP2D6 to its equipotent metabolite, 4-hydroxyatomoxetine, which promptly undergoes further glucuronidation to an inactive 4-HAT-O-glucuronide. Clinical trials have shown that decreased CYP2D6 activity leads to substantially elevated atomoxetine exposure and increase in adverse reactions. The aim of this study was to to develop a pharmacologically based pharmacokinetic (PBPK) model of atomoxetine in different CYP2D6 genotypes. A single 20 mg dose of atomoxetine was given to 19 healthy Korean individuals with CYP2D6*wt/*wt (*wt = *1 or *2) or CYP2D6*10/*10 genotype. Based on the results of this pharmacokinetic study, a PBPK model for CYP2D6*wt/*wt individuals was developed. This model was scaled to those with CYP2D6*10/*10 genotype, as well as CYP2D6 poor metabolisers. We validated this model by comparing the predicted pharmacokinetic parameters with diverse results from the literature. The presented PBPK model describes the pharmacokinetics after single and repeated oral atomoxetine doses with regard to CYP2D6 genotype and phenotype. This model could be utilized for identification of appropriate dosages of atomoxetine in patients with reduced CYP2D6 activity to minimize the adverse events, and to enable personalised medicine.

CYP2D6 Genotype Phenotype Discordance Due to Drug-Drug Interaction

Drug-drug interactions have been demonstrated to alter cytochrome 2D6 (CYP2D6) enzyme phenotype due to inhibitor ingestion, although it is unclear how substrate interactions affect phenotype. This was a pragmatic clinical trial examining the kinetics of a CYP2D6 enzyme probe drug with and without CYP2D6-dependent substrates. Patients were enrolled into an inpatient study unit, and orally administered a 2 mg microdose of dextromethorphan (DM) to probe enzyme activity with and without CYP2D6-dependent drug-drug interactions. Thirty-nine subjects were enrolled in this trial. Twelve subjects were on no CYP2D6-dependent drugs and 27 were on one or more CYP2D6-dependent drugs. There were 1 poor metabolizer, 5 intermediate metabolizers, 31 normal metabolizers, and 2 ultra-rapid metabolizers. Those with co-ingestion of another CYP2D6-dependent drug were 9.49 (95% confidence interval (CI): 1.54-186.41; P = 0.01) times more likely to have genotype-phenotype discordance based upon the 3 hours dextrophan/dextromethorphan (DX/DM) ratio. CYP2D6 substrate co-ingestions can cause genotype-phenotype discordance.

Effects of CYP2D6 genetic polymorphisms on the efficacy and safety of fluvoxamine in patients with depressive disorder and comorbid alcohol use disorder

Background

Fluvoxamine therapy is used for treatment of patients with depressive disorder, but it is often ineffective, and some patients suffer from dose-dependent undesirable side effects such as vertigo, headache, indigestion, xerostomia, increased anxiety, etc. CYP2D6 is involved in the biotransformation of fluvoxamine. Meanwhile, the genes encoding these isoenzymes have a high level of polymorphism, which may affect the protein synthesis.

Objective

The primary objective of our study was to investigate the effects of CYP2D6 genetic polymorphisms on the efficacy and safety of fluvoxamine in patients with depressive disorder and comorbid alcohol use disorder, in order to develop the algorithms of optimization of fluvoxamine therapy for reducing the risk of dose-dependent undesirable side effects and pharmacoresistance.

Methods

The study involved 45 male patients (average age: 36.44±9.96 years) with depressive disorder and comorbid alcohol use disorder. A series of psychometric scales was used in the research. Genotyping of CYP2D6 (1846G>A) was performed using real-time polymerase chain reaction.

Results

According to results of Mann–Whitney U-test, statistically significant differences between the efficacy and safety of fluvoxamine were obtained on 9th and 16th days of therapy in patients with GG and GA genotypes (The Hamilton Rating Scale for Depression: 10.0 [10.0; 23.0] vs 25.0 [24.0; 16.0] (P<0.001) on the 9th day and 4.0 [2.0; 5.0] vs 6.0 [6.0; 7.0] on the 16th day; The UKU Side Effect Rating Scale: 6.0 [4.0; 6.0] vs 9.0 [9.0; 10.0] (P<0.001) on the 9th day and 5.0 [1.0; 9.0] vs 19.0 [18.0; 22.0] on the 16th day).

Conclusion

This study demonstrated the lower efficacy and safety of fluvoxamine in patients with depressive disorder and comorbid alcohol use disorders with GA genotype in CYP2D6 1846G>A polymorphic marker.

CYP2D6 Allelic Variants *34, *17-2, *17-3, and *53 and a Thr309Ala Mutant Display Altered Kinetics and NADPH Coupling in Metabolism of Bufuralol and Dextromethorphan and Altered Susceptibility to Inactivation by SCH 66712

Metabolic phenotype can be affected by multiple factors, including allelic variation and interactions with inhibitors. Human CYP2D6 is responsible for approximately 20% of cytochrome P450-mediated drug metabolism but consists of more than 100 known variants; several variants are commonly found in the population, whereas others are quite rare. Four CYP2D6 allelic variants-three with a series of mutations distal to the active site (*34, *17-2, *17-3) and one ultra-metabolizer with mutations near the active site (*53), along with reference *1 and an active site mutant of *1 (Thr309Ala)-were expressed, purified, and studied for interactions with the typical substrates dextromethorphan and bufuralol and the inactivator SCH 66712. We found that *34, *17-2, and *17-3 displayed reduced enzyme activity and NADPH coupling while producing the same metabolites as *1, suggesting a possible role for Arg296 in NADPH coupling. A higher-activity variant, *53, displayed similar NADPH coupling to *1 but was less susceptible to inactivation by SCH 66712. The Thr309Ala mutant showed similar activity to that of *1 but with greatly reduced NADPH coupling. Overall, these results suggest that kinetic and metabolic analysis of individual CYP2D6 variants is required to understand their possible contributions to variable drug response and the complexity of personalized medicine.

Ten Years' Experience with the CYP2D6 Activity Score: A Perspective on Future Investigations to Improve Clinical Predictions for Precision Therapeutics

The seminal paper on the CYP2D6 Activity Score (AS) was first published ten years ago and, since its introduction in 2008, it has been widely accepted in the field of pharmacogenetics. This scoring system facilitates the translation of highly complex CYP2D6 diplotype data into a patient’s phenotype to guide drug therapy and is at the core of all CYP2D6 gene/drug pair guidelines issued by the Clinical Pharmacogenetics Implementation Consortium (CPIC). The AS, however, only explains a portion of the variability observed among individuals and ethnicities. In this review, we provide an overview of sources in addition to CYP2D6 genotype that contribute to the variability in CYP2D6-mediated drug metabolism and discuss other factors, genetic and non-genetic, that likely contribute to the observed variability in CYP2D6 enzymatic activity.

A Pooled Analysis of Pharmacokinetic Variability Information for Common Probe Substrates Used in Drug-Drug Interaction Studies

Sample size estimates for drug-drug interaction (DDI) studies are often based on variability information from the literature or from historical studies, but small sample sizes in these sources may limit the precision of the estimates obtained. This project aimed to create an intra-subject variability library of the pharmacokinetic (PK) exposure parameters, area under the curve, and maximum plasma concentration, for probes commonly used in DDI studies. Data from 66 individual DDI studies in healthy subjects relating to 18 common probe substrates were pooled to increase the effective sample size for the identified probes by 1.5- to 9-fold, with corresponding improvements in precision of the intra-subject PK variability estimates in this library. These improved variability estimates will allow better assessment of the sample sizes needed for DDI studies in future.