The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data

APF2: an improved ensemble method for pharmacogenomic variant effect prediction

Lack of efficacy or adverse drug response are common phenomena in pharmacological therapy causing considerable morbidity and mortality. It is estimated that 20-30% of this variability in drug response stems from variations in genes encoding drug targets or factors involved in drug disposition. Leveraging such pharmacogenomic information for the preemptive identification of patients who would benefit from dose adjustments or alternative medications thus constitutes an important frontier of precision medicine. Computational methods can be used to predict the functional effects of variant of unknown significance. However, their performance on pharmacogenomic variant data has been lackluster. To overcome this limitation, we previously developed an ensemble classifier, termed APF, specifically designed for pharmacogenomic variant prediction. Here, we aimed to further improve predictions by leveraging recent key advances in the prediction of protein folding based on deep neural networks. Benchmarking of 28 variant effect predictors on 530 pharmacogenetic missense variants revealed that structural predictions using AlphaMissense were most specific, whereas APF exhibited the most balanced performance. We then developed a new tool, APF2, by optimizing algorithm parametrization of the top performing algorithms for pharmacogenomic variations and aggregating their predictions into a unified ensemble score. Importantly, APF2 provides quantitative variant effect estimates that correlate well with experimental results (R2 = 0.91, p = 0.003) and predicts the functional impact of pharmacogenomic variants with higher accuracy than previous methods, particularly for clinically relevant variations with actionable pharmacogenomic guidelines. We furthermore demonstrate better performance (92% accuracy) on an independent test set of 146 variants across 61 pharmacogenes not used for model training or validation. Application of APF2 to population-scale sequencing data from over 800,000 individuals revealed drastic ethnogeographic differences with important implications for pharmacotherapy. We thus think that APF2 holds the potential to improve the translation of genetic information into pharmacogenetic recommendations, thereby facilitating the use of Next-Generation Sequencing data for stratified medicine.

The influence of drug-induced metabolic enzyme activity inhibition and CYP3A4 gene polymorphism on aumolertinib metabolism

The purpose of this study is to clarify the drug interaction profile of aumolertinib, and the influence of CYP3A4 genetic polymorphism on aumolertinib metabolic characteristics. Through microsomal enzyme reactions, we screened 153 drugs and identified 15 that significantly inhibited the metabolism of aumolertinib. Among them, telmisartan and carvedilol exhibited potent inhibitory activities in rat liver microsomes (RLM) and human liver microsomes (HLM). In vivo, the pharmacokinetic parameters of aumolertinib, including AUC and Cmax, were significantly altered when co-administered with carvedilol, with a notable decrease in the clearance rate CLz/F. Interestingly, the pharmacokinetic parameters of the metabolite HAS-719 exhibited a similar trend as aumolertinib when co-administered. Mechanistically, both telmisartan and carvedilol exhibited a mixed-type inhibition on the metabolism of aumolertinib. Additionally, we used a baculovirus-insect cell expression system to prepare 24 recombinant CYP3A4 microsomes and obtained enzymatic kinetic parameters using aumolertinib as a substrate. Enzyme kinetic studies obtained the kinetic parameters of various CYP3A4 variant-mediated metabolism of aumolertinib. Based on the relative clearance rates, CYP3A4.4, 5, 7, 8, 9, 12, 13, 14, 17, 18, 19, 23, 24, 33, and 34 showed significantly lower clearance rates compared to the wild-type. Among the different CYP3A4 variants, the inhibitory potency of telmisartan and carvedilol on the metabolism of aumolertinib also varied. The IC50 values of telmisartan and carvedilol in CYP3A4.1 were 6.68 ± 1.76 μM and 0.60 ± 0.25 μM, respectively, whereas in CYP3A4.12, the IC50 exceeded 100 μM. Finally, we utilized adeno-associated virus to achieve liver-specific high expression of CYP3A4*1 and CYP3A4*12. In the group with high expression of the less active CYP3A4*12, the magnitude of the drug-drug interaction was significantly attenuated. In conclusion, CYP3A4 genetic polymorphism not only influences the pharmacokinetic characteristics of aumolertinib, but also the inhibitory potency of telmisartan and carvedilol on it.

Polymorphisms in drug-metabolizing genes and urinary bladder cancer susceptibility and prognosis: Possible impacts and future management

Epidemiological studies have shown the association of genetic variants with risks of occupational and environmentally induced cancers, including bladder (BC). The current review summarizes the effects of variants in genes encoding phase I and II enzymes in well-designed studies to highlight their contribution to BC susceptibility and prognosis. Polymorphisms in genes codifying drug-metabolizing proteins are of particular interest because of their involvement in the metabolism of exogenous genotoxic compounds, such as tobacco and agrochemicals. The prognosis between muscle-invasive and non-muscle-invasive diseases is very different, and it is difficult to predict which will progress worse. Web of Science, PubMed, and Medline were searched to identify studies published between January 1, 2010, and February 2023. We included 73 eligible studies, more than 300 polymorphisms, and 46 genes/loci. The most studied candidate genes/loci of phase I metabolism were CYP1B1, CYP1A1, CYP1A2, CYP3A4, CYP2D6, CYP2A6, CYP3E1, and ALDH2, and those in phase II were GSTM1, GSTT1, NAT2, GSTP1, GSTA1, GSTO1, and UGT1A1. We used the 46 genes to construct a network of proteins and to evaluate their biological functions based on the Reactome and KEGG databases. Lastly, we assessed their expression in different tissues, including normal bladder and BC samples. The drug-metabolizing pathway plays a relevant role in BC, and our review discusses a list of genes that could provide clues for further exploration of susceptibility and prognostic biomarkers.

Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment

Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.

Meta-analysis of the global distribution of clinically relevant CYP2C8 alleles and their inferred functional consequences

BACKGROUND

CYP2C8 is responsible for the metabolism of 5% of clinically prescribed drugs, including antimalarials, anti-cancer and anti-inflammatory drugs. Genetic variability is an important factor that influences CYP2C8 activity and modulates the pharmacokinetics, efficacy and safety of its substrates.

RESULTS

We profiled the genetic landscape of CYP2C8 variability using data from 96 original studies and data repositories that included a total of 33,185 unrelated participants across 44 countries and 43 ethnic groups. The reduced function allele CYP2C8*2 was most common in West and Central Africa with frequencies of 16-36.9%, whereas it was rare in Europe and Asia (< 2%). In contrast, CYP2C8*3 and CYP2C8*4 were common throughout Europe and the Americas (6.9-19.8% for *3 and 2.3-7.5% for *4), but rare in African and East Asian populations. Importantly, we observe pronounced differences (> 2.3-fold) between neighboring countries and even between geographically overlapping populations. Overall, we found that 20-60% of individuals in Africa and Europe carry at least one CYP2C8 allele associated with reduced metabolism and increased adverse event risk of the anti-malarial amodiaquine. Furthermore, up to 60% of individuals of West African ancestry harbored variants that reduced the clearance of pioglitazone, repaglinide, paclitaxel and ibuprofen. In contrast, reduced function alleles are only found in < 2% of East Asian and 8.3-12.8% of South and West Asian individuals.

CONCLUSIONS

Combined, the presented analyses mapped the genetic and inferred functional variability of CYP2C8 with high ethnogeographic resolution. These results can serve as a valuable resource for CYP2C8 allele frequencies and distribution estimates of CYP2C8 phenotypes that could help identify populations at risk upon treatment with CYP2C8 substrates. The high variability between ethnic groups incentivizes high-resolution pharmacogenetic profiling to guide precision medicine and maximize its socioeconomic benefits, particularly for understudied populations with distinct genetic profiles.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

INTRODUCTION

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.

RESEARCH DESIGN AND METHODS

We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.

RESULTS

Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).

CONCLUSIONS

Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia

Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.

Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism

BACKGROUND

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes.

METHODS

Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8 weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants.

RESULTS

Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel.

CONCLUSION

In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

A call for increased inclusivity and global representation in pharmacogenetic testing

Commercial pharmacogenetic testing panels capture a fraction of the genetic variation underlying medication metabolism and predisposition to adverse reactions. In this study we compared variation in six pharmacogenes detected by whole genome sequencing (WGS) to a targeted commercial panel in a cohort of 308 individuals with family history of pediatric heart disease. In 1% of the cohort, WGS identified rare variants that altered the interpretation of metabolizer status and would thus prevent potential errors in gene-based dosing.

Identification and Functional Assessment of Eight CYP3A4 Allelic Variants *39-*46 Detected in the Chinese Han Population

Cytochrome P450 3A4 (CYP3A4), a key enzyme, is pivotal in metabolizing approximately half of the drugs used clinically. The genetic polymorphism of the CYP3A4 gene significantly influences individual variations in drug metabolism, potentially leading to severe adverse drug reactions (ADRs). In this study, we conducted a genetic analysis on CYP3A4 gene in 1163 Chinese Han individuals to identify the genetic variations that might affect their drug metabolism capabilities. For this purpose, a multiplex polymerase chain reaction (PCR) amplicon sequencing technique was developed, enabling us to perform the genotyping of CYP3A4 gene efficiently and economically on a large scale. As a result, a total of 14 CYP3A4 allelic variants were identified, comprising six previously reported alleles and eight new nonsynonymous variants that were nominated as new allelic variants *39-*46 by the PharmVar Association. Further, functional assessments of these novel CYP3A4 variants were undertaken by coexpressing them with cytochromes P450 oxidoreductase (CYPOR) in Saccharomyces cerevisiae microsomes. Immunoblot analysis indicated that with the exception of CYP3A4.40 and CYP3A4.45, the protein expression levels of most new variants were similar to that of the wild-type CYP3A4.1 in yeast cells. To evaluate their catalytic activities, midazolam was used as a probe drug. The results showed that variant CYP3A4.45 had almost no catalytic activity, whereas the other variants exhibited significantly reduced drug metabolism abilities. This suggests that the majority of the CYP3A4 variants identified in the Chinese population possess markedly altered capacities for drug metabolism. SIGNIFICANCE STATEMENT: In this study, we established a multiplex polymerase chain reaction (PCR) amplicon sequencing method and detected the maximum number of new CYP3A4 variants in a single ethnic population. Additionally, we performed the functional characterizations of these eight novel CYP3A4 allele variants in vitro. This study not only contributes to the understanding of CYP3A4 genetic polymorphism in the Chinese Han population but also holds substantial reference value for their potential clinical applications in personalized medicine.

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

Gene Polymorphisms and Drug-Drug Interactions Determine the Metabolic Profile of Blonanserin

This study aimed to evaluate the effects of cytochrome P450 3A4 (CYP3A4) gene polymorphism and drug interaction on the metabolism of blonanserin. Human recombinant CYP3A4 was prepared using the Bac-to-Bac baculovirus expression system. A microsomal enzyme reaction system was established, and drug-drug interactions were evaluated using Sprague-Dawley rats. Ultra-performance liquid chromatography-tandem mass spectrometry was used to detect the concentrations of blonanserin and its metabolite. Compared with wild type CYP34A, the relative clearance of blonanserin by CYP3A4.29 significantly increased to 251.3%, while it decreased notably with CYP3A4.4, 5, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 23, 24, 28, 31, 33, and 34, ranging from 6.09% to 63.34%. Among 153 tested drugs, nimodipine, felodipine, and amlodipine were found to potently inhibit the metabolism of blonanserin. Moreover, the inhibitory potency of nimodipine, felodipine, and amlodipine varied with different CYP3A4 variants. The half-maximal inhibitory concentration and enzymatic kinetics assay demonstrated that the metabolism of blonanserin was noncompetitively inhibited by nimodipine in rat liver microsomes and was inhibited in a mixed manner by felodipine and amlodipine in both rat liver microsomes and human liver microsomes. When nimodipine and felodipine were coadministered with blonanserin, the area under the blood concentration-time curve (AUC)(0-t), AUC(0-∞), and C max of blonanserin increased. When amlodipine and blonanserin were combined, the C max of blonanserin C increased remarkably. The vast majority of CYP3A4 variants have a low ability to catalyze blonanserin. With combined administration of nimodipine, felodipine, and amlodipine, the elimination of blonanserin was inhibited. This study provides the basis for individualized clinical use of blonanserin. SIGNIFICANCE STATEMENT: The enzyme kinetics of novel CYP3A4 enzymes for metabolizing blonanserin were investigated. Clearance of blonanserin by CYP3A4.4, 5, 7-10, 12-14, 16-18, 23-24, 28, 31, 33, and 34 decreased notably, but increased with CYP3A4.29. Additionally, we established a drug interaction spectrum for blonanserin, in which nimodipine, felodipine, and amlodipine kinetics exhibited mixed inhibition. Moreover, their inhibitory potencies decreased with CYP3A4.4 and 5 compared to CYP3A4.1. This study provides essential data for personalized clinical use of blonanserin.

Impact of sex on antidepressant discontinuation in groups of similar cytochrome P450 phenotypes

Introduction

Although there are studies assessing reasons for antidepressant discontinuation, little is known about the impact of sex differences or cytochrome P450 phenotypes. Our objective is to assess discontinuation rates between males and females and whether CYP450 phenotype influences discontinuation.

Methods

This is a retrospective review of patients previously enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment database with major depressive disorder. Patients were evaluated for antidepressants trialed between January 1, 2009, and September 30, 2019. Survival analyses with competing risks were used to analyze discontinuation reasons. A Kaplan-Meier estimation method was used to assess the time to discontinuation and discontinuation rates. Analyses were also completed to assess discontinuation between men and women by phenotypic groups. All tests were two-sided, and p-values ≤ .05 were considered statistically significant.

Results

There were 620 antidepressant discontinuation events discovered from 1015 antidepressant trials included. Overall, the median time to discontinuation for males was 2.6 years and 1.9 years for females (hazard ratio [HR] 0.97 [95% confidence interval (CI): 0.80, 1.19], p = .77). The risk of discontinuation was not different between males and females in any of the phenotype groups, which was consistent in the multivariable analyses. Concomitant use of medications that inhibited or induced antidepressant metabolism increased the overall risk of discontinuation (HR 1.45, 95% CI [1.06, 1.99], p = .020) in a time-dependent analysis.

Discussion

We did not detect a significant difference in risk of antidepressant discontinuation rates between males and females even when accounting for cytochrome P450 phenotype. Future studies should account for whether medications that inhibit or induce antidepressant metabolism may be a crucial factor in antidepressant discontinuation.

Ethnopsychopharmacology: Clinical and scientific writing pearls

The concept of ethnopsychopharmacology aims to predict or explain the pharmacologic response to psychiatric medications based on the influence of biologic and nonbiologic factors. Interactions involving these factors are complex and influence patient outcomes in health care. Pharmacists and other clinicians working in patient care environments, research, or medical education should engage in lifelong learning to enhance ethnopsychopharmacologic knowledge gaps, which ultimately may improve and individualize care across diverse populations. Through two cases, this paper provides pearls on how biogeographical ancestry and cytochrome P450 status may influence pharmacotherapy selection, dosing, or response. A third scenario highlights a publication, like many other published works, with deficiencies in how data on ancestry, race, and ethnicity are collected or reported. Current recommendations on the use of inclusive language in scientific writing are reviewed, with attention to specific examples.

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

P450Rdb: a manually curated database of reactions catalyzed by cytochrome P450 enzymes

INTRODUCTION

Cytochrome P450 enzymes (P450s) are recognized as the most versatile catalysts worldwide, playing vital roles in numerous biological metabolism and biosynthesis processes across all kingdoms of life. Despite the vast number of P450 genes available in databases (over 300,000), only a small fraction of them (less than 0.2%) have undergone functional characterization.

OBJECTIVES

To provide a convenient platform with abundant information on P450s and their corresponding reactions, we introduce the P450Rdb database, a manually curated resource compiles literature-supported reactions catalyzed by P450s.

METHODS

All the P450s and Reactions were manually curated from the literature and known databases. Subsequently, the P450 reactions organized and categorized according to their chemical reaction type and site. The website was developed using HTML and PHP languages, with the MySQL server utilized for data storage.

RESULTS

The current version of P450Rdb catalogs over 1,600 reactions, involving more than 590 P450s across a diverse range of over 200 species. Additionally, it offers a user-friendly interface with comprehensive information, enabling easy querying, browsing, and analysis of P450s and their corresponding reactions. P450Rdb is free available at http://www.cellknowledge.com.cn/p450rdb/.

CONCLUSIONS

We believe that this database will significantly promote structural and functional research on P450s, thereby fostering advancements in the fields of natural product synthesis, pharmaceutical engineering, biotechnological applications, agricultural and crop improvement, and the chemical industry.

Pharmacogenomics and the Management of Mood Disorders-A Review

Due to the chronic relapsing nature of mental disorders and increased life expectancy, the societal burden of these non-communicable diseases will increase even further. Treatments for mental disorders, such as depression, are available, but their effect is limited due to patients' (genetic) heterogeneity, low treatment compliance and frequent side effects. In general, only one-third of the patients respond to treatment. Today, medication selection in psychiatry relies on a trial-and-error approach based mainly on physicians' experience. Pharmacogenetic (PGx) testing can help in this process by determining the person-specific genetic factors that may predict clinical response and side effects associated with genetic variants that impact drug-metabolizing enzymes, drug transporters or drug targets. PGxis a discipline that investigates genetic factors that affect the absorption, metabolism, and transport of drugs, thereby affecting therapy outcome. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Studies in depressed patients show that genotyping of drug-metabolizing enzymes can increase the effectiveness of treatment, which could benefit millions of patients worldwide. This review highlights these studies, gives recommendations and provides future perspectives on how to proceed with PGx testing. Finally, it is recommended to consider genotyping for CYP2D6 and CYP2C19, when there is an indication (side effects or inefficacy).

Association between CYP2B6 genetic variability and cyclophosphamide therapy in pediatric patients with neuroblastoma

Cyclophosphamide, an oxazaphosphorine prodrug is frequently used in treatment of neuroblastoma, which is one of the most prevalent solid organ malignancies in infants and young children. Cytochrome P450 2B6 (CYP2B6) is the major catalyst and CYP2C19 is the minor enzyme in bioactivation and inactivation pathways of cyclophosphamide. CYP-mediated metabolism may contribute to the variable pharmacokinetics of cyclophosphamide and its toxic byproducts leading to insufficient response to the therapy and development of clinically significant side effects. The aim of the study was to reveal the contribution of pharmacogenetic variability in CYP2B6 and CYP2C19 to the treatment efficacy and cyclophosphamide-induced side effects in pediatric neuroblastoma patients under cyclophosphamide therapy (N = 50). Cyclophosphamide-induced hematologic toxicities were pivotal in all patients, whereas only moderate hepatorenal toxicity was developed. The patients' CYP2B6 metabolizer phenotypes were associated with the occurrence of lymphopenia, thrombocytopenia, and monocytopenia as well as of liver injury, but not with kidney or urinary bladder (hemorrhagic cystitis) toxicities. Furthermore, the patients' age (< 1.5 years, P = 0.03) and female gender (P ≤ 0.02), but not CYP2B6 or CYP2C19 metabolizer phenotypes appeared as significant prognostic factors in treatment outcomes. Our results may contribute to a better understanding of the impact of CYP2B6 variability on cyclophosphamide-induced side effects.

Genotype-guided dual antiplatelet therapy in cerebrovascular disease: assessing the risk and benefits for ethnic populations

INTRODUCTION

Cerebrovascular disease is a leading cause of morbidity and mortality in the world and antiplatelet therapy is a main pharmacologic means of secondary prevention. Clinical information has accumulated about benefit of dual antiplatelet therapy in certain clinical scenarios, genetic causes of antiplatelet resistance and its effect on clinical outcomes, and ethnic and geographic distributions of genetic polymorphisms.

AREAS COVERED

This review covers literature related to the pharmacogenomics of antiplatelet agents with a focus on ethnic variability, antiplatelet resistance, and dual antiplatelet therapy in cerebrovascular disease.

EXPERT OPINION

Selecting patients for dual antiplatelet therapy and specific agents require consideration of multiple factors. Ethnic factors should be considered in certain circumstances, but additional research is needed to determine the generalizability of the findings.

Characterizing the combined effects of cytochrome P450 missense variation within star allele definitions

Background: Cytochrome P450 (CYP) genetic variation largely impacts drug response. However, many CYP star alleles (haplotypes) lack functional annotation, impeding our understanding of drug metabolism mechanisms. We aimed to investigate the impact of missense variant combinations on CYP protein structures. Methods: Normal mode analysis was conducted on 261 missense variants within 91 CYP haplotypes. CYP2D6*2 and CYP2D6*17 were prioritized for molecular dynamics simulation. Results: Normal mode analysis and molecular dynamics highlight the effects of known CYP missense variants on protein stability and conformational dynamics. Missense variants within haplotypes may have intermodulating effects on protein structure and function. Conclusion: This study highlights the utility of multiscale modeling in interpreting CYP missense variants and particularly their combinations within various star alleles.

Pharmacogenomic variation in the Malagasy population: implications for the antimalarial drug primaquine metabolism

Aim: Antimalarial primaquine (PQ) eliminates liver hypnozoites of Plasmodium vivax. CYP2D6 gene variation contributes to PQ therapeutic failure. Additional gene variation may contribute to PQ efficacy. Information on pharmacogenomic variation in Madagascar, with vivax malaria and a unique population admixture, is scanty. Methods: The authors performed genome-wide genotyping of 55 Malagasy samples and analyzed data with a focus on a set of 28 pharmacogenes most relevant to PQ. Results: Mainly, the study identified 110 coding or splicing variants, including those that, based on previous studies in other populations, may be implicated in PQ response and copy number variation, specifically in chromosomal regions that contain pharmacogenes. Conclusion: With this pilot information, larger genome-wide association analyses with PQ metabolism and response are substantially more feasible.

The frequency of major ABCG2, SLCO1B1 and CYP2C9 variants in Asian, Native Hawaiian and Pacific Islander women subgroups: implications for personalized statins dosing

Aim: The frequencies of SLCO1B1*5 and CYP2C9*2 and *3 in specific Asian, Native Hawaiian and Pacific Islander (NHPI) subgroups are unknown. Patients & methods: Repository DNA samples from 1064 women self-identifying as Filipino, Korean, Japanese, Native Hawaiian, Marshallese or Samoan and aged 18 years or older were used for targeted sequencing of three genetic variants (rs4149056, rs1799853 and rs1057910). Results: SLCO1B1*5 was significantly less frequent in NHPI women (0.5-6%) than in Europeans (16%). Except for Koreans, CYP2C9*2 (0-1.4%) and *3 (0.5-3%) were significantly less frequent in all subgroups than in Europeans (8 and 12.7%, respectively). Prior reports showed that Asian and NHPI individuals have significantly higher ABCG2 Q141K allele frequency (13-46%) than Europeans (9.4%). Combined phenotype rates for rosuvastatin and fluvastatin revealed that Filipinos and Koreans had the highest frequencies of statin-associated myopathy symptoms risk alleles. Conclusion: Differences in ABCG2, SLCO1B1 and CYP2C9 allele frequencies among different racial and ethnic subgroups highlight the need for increased diversity in pharmacogenetic research. Risk alleles for statin-associated myopathy symptoms are more prevalent in Filipinos, underscoring the importance of genotype-based statin dosing.

Cross-Ancestry Genome-Wide Association Study Defines the Extended CYP2D6 Locus as the Principal Genetic Determinant of Endoxifen Plasma Concentrations

The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (n = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (n = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (n = 287, n = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (ρ = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (n = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R² ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.

Global distribution of functionally important CYP2C9 alleles and their inferred metabolic consequences

BACKGROUND

Genetic variability in the cytochrome P450 CYP2C9 constitutes an important predictor for efficacy and safety of various commonly prescribed drugs, including coumarin anticoagulants, phenytoin and multiple non-steroidal anti-inflammatory drugs (NSAIDs). A global map of CYP2C9 variability and its inferred functional consequences has been lacking.

RESULTS

Frequencies of eight functionally relevant CYP2C9 alleles (*2, *3, *5, *6, *8, *11, *13 and *14) were analyzed. In total, 108 original articles were identified that included genotype data from a total of 81,662 unrelated individuals across 70 countries and 40 unique ethnic groups. The results revealed that CYP2C9*2 was most abundant in Europe and the Middle East, whereas CYP2C9*3 was the main reason for reduced CYP2C9 activity across South Asia. Our data show extensive variation within superpopulations with up to tenfold differences between geographically adjacent populations in Malaysia, Thailand and Vietnam. Translation of genetic CYP2C9 variability into functional consequences indicates that up to 40% of patients in Southern Europe and the Middle East might benefit from warfarin and phenytoin dose reductions, while 3% of patients in Southern Europe and Israel are recommended to reduce starting doses of NSAIDs.

CONCLUSIONS

This study provides a comprehensive map of the genetic and functional variability of CYP2C9 with high ethnogeographic resolution. The presented data can serve as a useful resource for CYP2C9 allele and phenotype frequencies and might guide the optimization of genotyping strategies, particularly for indigenous and founder populations with distinct genetic profiles.