Pharmacogenomics of drug-metabolizing enzymes: a recent update on clinical implications and endogenous effects

Toward building a comprehensive human pan-genome: The SEN-GENOME project

The human reference genome (GRCh38), primarily sourced from individuals of European descent, falls short in capturing the vast genetic diversity across global populations. Efforts to diversify the reference genome face challenges in accessibility and representation, exacerbating the scarcity of African genomic data crucial for studying diseases prevalent in these populations. Sherman et al. proposed constructing reference genomes tailored to distinct human sub-populations. Their African Pan-Genome initiative highlighted substantial genetic variation missing from the GRCh38 human reference genome, emphasizing the necessity for population-specific genomes. In response, local initiatives like the Senegalese Genome project (SEN-GENOME) have emerged to document the genomes of historically overlooked populations. SEN-GENOME embodies community-driven decentralized research. With meticulous recruitment criteria and ethical practices, it aims to sequence 1,000 genomes from 31 ethnolinguistic groups, in the fourteen administrative regions of Senegal, fostering local genomic research tailored to the region. The key to SEN-GENOME's success is its commitment to local governance of data, capacity building, and integration with broader pan-genome projects in Africa. Despite the complexities of data harmonization and sharing, our collaborative efforts are aligned with common goals, ensuring steady progress toward a comprehensive human pan-genome. We invite and welcome collaboration with other research entities to achieve this shared vision. In summary, local initiatives such as SEN-GENOME are pivotal in bridging genomic disparities, offering pathways to equitable and inclusive genomic research. Collaborative endeavors guided by a collective vision for human health will propel us toward a more encompassing understanding of the human genome and better health through genomic medicine.

Subchronic oral toxic effects of 2,4-dinitroaniline in wistar rats: A comprehensive toxicity evaluation

2,4-dinitroaniline (2,4-D), a widely used dye intermediate, is one of the typical pollutants, and its potential health risks and toxicity are still largely unknown. To explore its subchronic oral toxicity, Wistar rats (equal numbers of males and females) were used as test animals, and a 90-day oral dosing experiment was conducted, divided into control group, low-dose group (0.055 mg/kg), medium-dose group (0.22 mg/kg), medium-high dose group (0.89 mg/kg), and high-dose group (3.56 mg/kg). The body weight data, clinical appearance, and drug reactions of each test rat within 90 days of dosing were recorded; morning urine samples were collected four times to test for eight urinary indicators; blood samples were collected to test for nineteen hematological indicators and sixteen biochemical indicators; tissue samples were collected for pathological analysis; moreover, the no-observed-adverse-effect level (NOAEL) was determined, and the benchmark dose method was used to support this determination and provide a statistical estimate of the dose corresponding. The results indicated that the chronic toxicity of 2,4-dinitroaniline showed certain gender differences, with the eyes, liver, and kidneys being the main potential target organs of toxicity. Moreover, the subchronic oral NOAEL for 2,4-dinitroaniline was determined to be 0.22 mg/kg body weight (0.22 mg/kg for males and 0.89 mg/kg for females), and a preliminary calculation of the safe exposure limit for human was 0.136 mg/kg. The research results greatly enriched the safety evaluation data of 2,4-dinitroaniline, contributing to a robust scientific foundation for the development of informed safety regulations and public health precautions.

The Diversity of CYP2C19 Polymorphisms in the Thai Population: Implications for Precision Medicine

Introduction

CYP2C19 plays a major role in the metabolism of various drugs. The most common genetic variants were the CYP2C19*2 and *3 alleles (rs4244285 and rs4986893, non-functional variants). In previous studies, we found that genetic polymorphisms in CYP2C19 variants influenced the active metabolites of clopidogrel and caused major adverse cardiovascular and cerebrovascular effects. However, the distribution of CYP2C19 varies among ethnic groups and according to adverse drug reactions. This study aimed to investigate the frequency of CYP2C19 genetic polymorphisms in the Thai population and analyze the differences in the frequency of CYP2C19 genetic polymorphisms between Thai and other populations.

Methods

This study enrolled 211 unrelated healthy Thai individuals in total. We performed a real-time polymerase chain reaction to genotype CYP2C19*2 (681G > A) and CYP2C19*3 (636G > A).

Results

In the Thai population, the CYP2C19*1 allele was the most prevalent at 70.14%, while the CYP2C19*2 and *3 alleles were found at frequencies of 25.36% and 4.50%, respectively. Conversely, the CYP2C19*3 allele was not detected in Caucasian, Hispanic, African, Italian, Macedonian, Tanzanian, or North Indian populations. The phenotypic profile of this gene revealed that the frequency of intermediate metabolizers (IMs) is nearly equal to that of extensive metabolizers (EMs), at 42.65% and 48.82% respectively, with genotypes *1/*2 (36.02%) and *1/*3 (6.63%). Likewise, poor metabolizers (PMs) with genotypes *2/*2 (6.16%), *2/*3 (2.37%), and *3/*3 (<1%) are more prevalent in our population as well.

Conclusion

The distribution of CYP2C19 genotype and phenotype influenced by non-functional alleles has potential as a pharmacogenomics biomarker for precision medicine and is dependent on an ethnic-specific genetic variation database.

Implementation of whole-exome sequencing for pharmacogenomics profiling and exploring its potential clinical utilities

Whole-exome sequencing (WES) is widely used in clinical settings; however, the exploration of its use in pharmacogenomic analysis remains limited. Our study compared the variant callings for 28 core absorption, distribution, metabolism and elimination genes by WES and array-based technology using clinical trials samples. The results revealed that WES had a positive predictive value of 0.71-0.92 and a sensitivity of single-nucleotide variants between 0.68 and 0.95, compared with array-based technology, for the variants in the commonly targeted regions of the WES and PhamacoScan™ assay. Besides the common variants detected by both assays, WES identified 200-300 exclusive variants per sample, totalling 55 annotated exclusive variants, including important modulators of metabolism such as rs2032582 (ABCB1) and rs72547527 (SULT1A1). This study highlights the potential clinical advantages of using WES to identify a wider range of genetic variations and enabling precision medicine.

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.

Impact of Pharmacogenomics in Clinical Practice

Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.

Integrating Concentration-Dependent Toxicity Data and Toxicokinetics To Inform Hepatotoxicity Response Pathways

Failure of animal models to predict hepatotoxicity in humans has created a push to develop biological pathway-based alternatives, such as those that use in vitro assays. Public screening programs (e.g., ToxCast/Tox21 programs) have tested thousands of chemicals using in vitro high-throughput screening (HTS) assays. Developing pathway-based models for simple biological pathways, such as endocrine disruption, has proven successful, but development remains a challenge for complex toxicities like hepatotoxicity, due to the many biological events involved. To this goal, we aimed to develop a computational strategy for developing pathway-based models for complex toxicities. Using a database of 2171 chemicals with human hepatotoxicity classifications, we identified 157 out of 1600+ ToxCast/Tox21 HTS assays to be associated with human hepatotoxicity. Then, a computational framework was used to group these assays by biological target or mechanisms into 52 key event (KE) models of hepatotoxicity. KE model output is a KE score summarizing chemical potency against a hepatotoxicity-relevant biological target or mechanism. Grouping hepatotoxic chemicals based on the chemical structure revealed chemical classes with high KE scores plausibly informing their hepatotoxicity mechanisms. Using KE scores and supervised learning to predict in vivo hepatotoxicity, including toxicokinetic information, improved the predictive performance. This new approach can be a universal computational toxicology strategy for various chemical toxicity evaluations.

Warfarin pharmacogenetics in a black Zimbabwean cohort: an observational prospective study

Aim: A prospective observational study was conducted to evaluate the feasibility of implementing clinical guidelines for warfarin dosing in black Zimbabwean patients. Methods: CYP2C9*5, CYP2C9*6, CYP2C9*8 and CYP2C9*11 and VKORC1 c. 1639 G>A variations were observed in 62 study patients. Results & Conclusion: Overall, 39/62 (62.90%) participants did not receive a warfarin starting dose as would have been recommended by Clinical Pharmacogenetics Implementation Consortium guidelines. US FDA and Dutch Pharmacogenetics Working Group guidelines are based on CYP2C9*2 and CYP2C9*3 only, hence, unlikely useful in this cohort, where such variants were not detected. Clinical Pharmacogenetics Implementation Consortium guidelines, on the other hand, have a specific recommendation on the African-specific variants CYP2C9*5, CYP2C9*6 and CYP2C9*11, and are hence suitable for implementation in Zimbabwe and would help optimize warfarin doses in patients in the study cohort.

Targeted next-generation sequencing of genes involved in Warfarin Pharmacodynamics and pharmacokinetics pathways using the Saudi Warfarin Pharmacogenetic study (SWAP)

BACKGROUND

Warfarin is an oral anticoagulant commonly used for treatment and prophylaxis against thromboembolic events. Warfarins's narrow therapeutic index window is one of the main challenges in clinical practice; thus, it requires frequent monitoring and dose adjustment to maintain patients' therapeutic range. Warfarin dose variation and response are attributed to several inter-and intra-individuals factors, including genetic variants in enzymes involved in warfarin pharmacokinetics (PK) and pharmacodynamics (PD) pathways. Thus, we aim to utilize the next-generation sequencing (NGS) approach to identify rare and common genetic variants that might be associated with warfarin responsiveness.

METHOD AND RESULTS

A predesigned NGS panel that included 16 genes involved in Warfarin PK/PD pathways was used to sequence 786 patients from the Saudi Warfarin Pharmacogenetic Cohort (SWAP). Identified variants were annotated using several annotation tools to identify the pathogenicity and allele frequencies of these variants. We conducted variants-level association tests with warfarin dose. We identified 710 variants within the sequenced genes; 19% were novel variants, with the vast majority being scarce variants. The genetic association tests showed that VKORC1 (rs9923231, and rs61742245), CYP2C9 (rs98332238, rs9332172, rs1057910, rs9332230, rs1799853, rs1057911, and rs9332119), CYP2C19 (rs28399511, and rs3758581), and CYP2C8 (rs11572080 and rs10509681) were significantly associated with warfarin weekly dose. Our model included genetics, and non-genetic factors explained 40.1% of warfarin dose variation.

CONCLUSION

The study identifies novel variants associated with warfarin dose in the Saudi population. These variants are more likely to be population-specific variants, suggesting that population-specific studies should be conducted before adopting a universal warfarin genotype-guided dosing algorithm.

A paradigm shift in pharmacogenomics: From candidate polymorphisms to comprehensive sequencing

Genetic factors have long been recognized as important determinants of interindividual variability in drug efficacy and toxicity. However, despite the increasing number of established gene-drug associations, candidate polymorphisms can only explain a fraction of the genetically encoded functional variability in drug disposition. Advancements in genetic profiling methods now allow to analyse the landscape of human pharmacogenetic variations comprehensively, which opens new opportunities to identify novel factors that could explain the "missing heritability." Here, we provide an updated overview of the landscape of pharmacogenomic variability based on recent analyses of population-scale sequencing projects. We then summarize the current state-of-the-art how the functional consequences of variants with unknown effects can be quantitatively estimated while discussing challenges and peculiarities that are specific to pharmacogenes. In the last sections, we discuss the importance of considering ethnogeographic diversity to provide equitable benefits of pharmacogenomics and summarize current roadblocks for the implementation of sequencing-based guidance of clinical decision-making. Based on the current state of the field, we conclude that testing is likely to gradually shift from the interrogation of selected candidate polymorphisms to comprehensive sequencing, which allows to consider the full spectrum of pharmacogenomic variations for a true personalization of genomic prescribing.

Role of Genetic Polymorphisms in Drug-Metabolizing Enzyme-Mediated Toxicity and Pharmacokinetic Resistance to Anti-Cancer Agents: A Review on the Pharmacogenomics Aspect

The inter-individual differences in cancer susceptibility are somehow correlated with the genetic differences that are caused by the polymorphisms. These genetic variations in drug-metabolizing enzymes/drug-inactivating enzymes may negatively or positively affect the pharmacokinetic profile of chemotherapeutic agents that eventually lead to pharmacokinetic resistance and toxicity against anti-cancer drugs. For instance, the CYP1B1*3 allele is associated with CYP1B1 overexpression and consequent resistance to a variety of taxanes and platins, while 496T>G is associated with lower levels of dihydropyrimidine dehydrogenase, which results in severe toxicities related to 5-fluorouracil. In this context, a pharmacogenomics approach can be applied to ascertain the role of the genetic make-up in a person's response to any drug. This approach collectively utilizes pharmacology and genomics to develop effective and safe medications that are devoid of resistance problems. In addition, recently reported genomics studies revealed the impact of many single nucleotide polymorphisms in tumors. These studies emphasized the importance of single nucleotide polymorphisms in drug-metabolizing enzymes on the effect of anti-tumor drugs. In this review, we discuss the pharmacogenomics aspect of polymorphisms in detail to provide an insight into the genetic manipulations in drug-metabolizing enzymes that are responsible for pharmacokinetic resistance or toxicity against well-known anti-cancer drugs. Special emphasis is placed on different deleterious single nucleotide polymorphisms and their effect on pharmacokinetic resistance. The information provided in this report may be beneficial to researchers, especially those who are working in the field of biotechnology and human genetics, in rationally manipulating the genetic information of patients with cancer who are undergoing chemotherapy to avoid the problem of pharmacokinetic resistance/toxicity associated with drug-metabolizing enzymes.

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

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

Comparison of genetic susceptibility to lung adenocarcinoma and squamous cell carcinoma in Japanese patients using a novel panel for cancer-related drug-metabolizing enzyme genes

The differences in genetic susceptibility to lung adenocarcinoma and squamous cell carcinoma remain unclear. We developed a customized, targeted gene sequencing panel for efficient and sensitive identification of germline variants, including whole-gene deletion types for cancer-related drug-metabolizing enzyme genes in lung adenocarcinoma and squamous cell carcinoma. The minor allele frequencies of the variants, confirmed as clinically significant in the Japanese population, did not differ significantly from those of normal participants listed in the public database. Genotype analysis comparing lung adenocarcinoma (n = 559) and squamous cell carcinoma (n = 151) indicated that the variants of DPYD (rs190771411, Fisher's exact test, P = 0.045; rs200562975, P = 0.045) and ALDH2 (rs568781254, P = 0.032) were associated with an increased risk of squamous cell carcinoma compared to adenocarcinoma. Conversely, whole-gene deletion of CYP2A6 was associated with adenocarcinoma but not squamous cell carcinoma. Notably, whole-gene deletion of CYP2A6 was confirmed in 22 patients with lung adenocarcinoma but not in any patients with squamous cell carcinoma. Most patients with whole-gene deletion of CYP2A6 were female non-smokers. The discovery of a whole-gene deletion of CYP2A6 in patients with lung adenocarcinoma may have an important role in clinical practice and advance our understanding of CYP2A6 germline variants and their association with carcinogenesis or their susceptibility to lung adenocarcinoma.

A one-year follow-up study of treatment-compliant suicide attempt survivors: relationship of CYP2D6-CYP2C19 and polypharmacy with suicide reattempts

This study of a cohort of 1-year treatment-compliant survivors of a suicide attempt examined for the first time whether a high CYP2D6-CYP2C19 metabolic capacity (pharmacogenes related to psychopathology, suicide, and attempt severity) and/or polypharmacy treatments predicted repeat suicide attempts, adjusting for sociodemographic and clinical factors as confounders. Of the 461 (63% women) consecutively hospitalized patients who attempted suicide and were evaluated and treated after an index attempt, 191 (67.5% women) attended their 6- and 12-month follow-up sessions. Clinicians were blinded to the activity scores (AS) of their genotypes, which were calculated as the sum of the values assigned to each allele (CYP2C19 *2, *17; CYP2D6 *3, *4, *4xN, *5, *6, *10, wtxN). No differences were found in polypharmacy prescription patterns and the variability of CYP2D6 and CYP2C19 genotypes between adherents and dropouts, but the formers were older, with a higher frequency of anxiety and bipolar disorders and fewer alcohol and substance use disorders. The risk of reattempts was higher for CYP2D6 ultrarapid (AS > 2) metabolizers (β = 0.561, p = 0.005) and violent suicide survivors (β = -0.219, p = 0.042) if the attempt occurred during the first 6-month period, individuals with an increased number of MINI DSM-IV Axis I mental disorders (β = 0.092, p = 0.032) during the second 6-month period and individuals with a combined high CYP2D6-CYP2C19 metabolic capacity (AS > 4) (β = 0.345, p = 0.024) and an increased use of drugs other than antidepressants, anxiolytics-depressants and antipsychotics-lithium (β = 0.088, p = 0.005) in multiple repeaters during both periods. CYP2D6 and CYP2C19 rapid metabolism and polypharmacy treatment for somatic comorbidities must be considered to prevent the severe side effects of short-term multiple suicide reattempts after a previous attempt.

Epigenetics in drug disposition & drug therapy: symposium report of the 24th North American meeting of the International Society for the Study of Xenobiotics (ISSX)

The 24th North American International Society for the Study of Xenobiotics (ISSX) meeting, held virtually from September 13 to 17, 2021, embraced the theme of "Broadening Our Horizons." This reinforces a key mission of ISSX: striving to share innovative science related to drug discovery and development. Session speakers and the ISSX New Investigators Group, which supports the scientific and professional development of student and early career ISSX members, elected to highlight the scientific content presented during the captivating session titled, "Epigenetics in Drug Disposition & Drug Therapy." The impact genetic variation has on drug response is well established; however, this session underscored the importance of investigating the role of epigenetics in drug disposition and drug discovery. Session speakers, Drs. Ning, McClay, and Lazarus, detailed mechanisms by which epigenetic players including long non-coding RNA (lncRNAs), microRNA (miRNAs), DNA methylation, and histone acetylation can alter the expression of genes involved in pharmacokinetics, pharmacodynamics, and toxicity. Dr. Ning detailed current knowledge about miRNAs and lncRNAs and the mechanisms by which they can affect the expression of drug metabolizing enzymes (DMEs) and nuclear receptors. Dr. Lazarus discussed the potential role of miRNAs on UDP-glucuronosyltransferase (UGT) expression and activity. Dr. McClay provided evidence that aging alters methylation and acetylation of DMEs in the liver, affecting gene expression and activity. These topics, compiled by the symposium organizers, presenters, and the ISSX New Investigators Group, are herein discussed, along with exciting future perspectives for epigenetics in drug disposition and drug discovery research.

Cytochrome P450 polymorphism: From evolution to clinical use

The cytochromes P450s can be divided in two groups, those of high importance for endogenous functions being evolutionary quite stable and those participating in detoxification of drugs and other xenobiotics having less important endogenous functions. In the latter group extensive genetic diversity has been allowed and in addition this is of high importance for survival in different environments. The genetic polymorphisms in these genes have evolved to some extent based on dietary restrictions and environmental factors and have not been subject of conservation due to less importance for survival. In cases of high dietary selection events, gene multiplication and amplification events have been seen. The different variants in genes encoding drug metabolizing enzymes can be used as genetic biomarkers (pharmacogenomic labels) for adjustment of drug treatment leading to less adverse drug reactions and better response. Indeed, this has improved the use of personalized medicine, although the missing heredity seen based on twin studies indicates that there are indeed many more genetic variants to be discovered before one can achieve a satisfactory relationship between genotype and phenotype with respect to drug metabolism and toxicity.

Evaluation of a six-probe cocktail (caffeine, tolbutamide, omeprazole, dextromethorphan, midazolam, and digoxin) approach to estimate hepatic drug detoxification capability and dosage requirements after a single oral dosing in healthy Chinese volunteers

The primary objectives of this study were to investigate the suitability of a 6-probe cocktail (caffeine, tolbutamide, omeprazole, dextromethorphan, midazolam, and digoxin) to be used as a tool for assessing the activity of drug metabolizing enzymes and transporters, and examine differences in the way drugs are handled among groups with different genetic regulation of these processes. This was a single-center, open-label, phase I clinical study involving 20 young, healthy Chinese volunteers (equal gender distribution). The subjects were administered a single, oral dose of the 6-probe cocktail and serum samples were collected to assess the disposition of the different probe substrates and produced metabolites. The serum samples were analyzed using ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry technology. The DNA samples were subjected to whole exome sequencing. Nineteen healthy volunteers completed the study. The 6-probe cocktail was safe and well-tolerated by all the subjects. The parent substrates and metabolites-caffeine (paraxanthine), dextromethorphan (dextrorphan), digoxin, midazolam (1-hydroxy-midazolam), omeprazole (5-hydroxy-omeprazole), and tolbutamide (4-hydroxy-tolbutamide)-were within the detectable window. Genetic variations known to alter drug metabolism (CYP2D6*10, CYP2C19*2, CYP2C19*3, and CYP2C9*3) were identified and generally correlated with phenotypic status. The 6-probe cocktail appeared to be suitable for assessing drug metabolizing activities. This, in conjunction with individual genetics, will pave the way for the implementation of personalized medicine in clinical practice. This will hopefully improve efficacy and reduce the incidence of adverse drug reactions.

Exome sequencing allows detection of relevant pharmacogenetic variants in epileptic patients

Beyond the identification of causal genetic variants in the diagnosis of Mendelian disorders, exome sequencing can detect numerous variants with potential relevance for clinical care. Clinical interventions can thus be conducted to improve future health outcomes for patients and their at-risk relatives, such as predicting late-onset genetic disorders accessible to prevention, treatment or identifying differential drug efficacy and safety. To evaluate the interest of such pharmacogenetic information, we designed an "in house" pipeline to determine the status of 122 PharmGKB (Pharmacogenomics Knowledgebase) variant-drug combinations in 31 genes. This pipeline was applied to a cohort of 90 epileptic patients who had previously an exome sequencing (ES) analysis, to determine the frequency of pharmacogenetic variants. We performed a retrospective analysis of drug plasma concentrations and treatment efficacy in patients bearing at least one relevant PharmGKB variant. For PharmGKB level 1A variants, CYP2C9 status for phenytoin prescription was the only relevant information. Nineteen patients were treated with phenytoin, among phenytoin-treated patients, none were poor metabolizers and four were intermediate metabolizers. While being treated with a standard protocol (10-23 mg/kg/30 min loading dose followed by 5 mg/kg/8 h maintenance dose), all identified intermediate metabolizers had toxic plasma concentrations (20 mg/L). In epileptic patients, pangenomic sequencing can provide information about common pharmacogenetic variants likely to be useful to guide therapeutic drug monitoring, and in the case of phenytoin, to prevent clinical toxicity caused by high plasma levels.

Reviewing Data Integrated for PBPK Model Development to Predict Metabolic Drug-Drug Interactions: Shifting Perspectives and Emerging Trends

Physiologically-based pharmacokinetics (PBPK) modeling is a robust tool that supports drug development and the pharmaceutical industry and regulatory authorities. Implementation of predictive systems in the clinics is more than ever a reality, resulting in a surge of interest for PBPK models by clinicians. We aimed to establish a repository of available PBPK models developed to date to predict drug-drug interactions (DDIs) in the different therapeutic areas by integrating intrinsic and extrinsic factors such as genetic polymorphisms of the cytochromes or environmental clues. This work includes peer-reviewed publications and models developed in the literature from October 2017 to January 2021. Information about the software, type of model, size, and population model was extracted for each article. In general, modeling was mainly done for DDI prediction via Simcyp^® software and Full PBPK. Overall, the necessary physiological and physio-pathological parameters, such as weight, BMI, liver or kidney function, relative to the drug absorption, distribution, metabolism, and elimination and to the population studied for model construction was publicly available. Of the 46 articles, 32 sensibly predicted DDI potentials, but only 23% integrated the genetic aspect to the developed models. Marked differences in concentration time profiles and maximum plasma concentration could be explained by the significant precision of the input parameters such as Tissue: plasma partition coefficients, protein abundance, or Ki values. In conclusion, the models show a good correlation between the predicted and observed plasma concentration values. These correlations are all the more pronounced as the model is rich in data representative of the population and the molecule in question. PBPK for DDI prediction is a promising approach in clinical, and harmonization of clearance prediction may be helped by a consensus on selecting the best data to use for PBPK model development.

Medication-related adverse events in health care-what have we learned? A narrative overview of the current knowledge

Purpose

Although medication-related adverse events (MRAEs) in health care are vastly studied, high heterogeneity in study results complicates the interpretations of the current situation. The main objective of this study was to form an up-to-date overview of the current knowledge of the prevalence, risk factors, and surveillance of MRAEs in health care.

Methods

Electronic databases (PubMed, MEDLINE, Web of Science, and Scopus) were searched with applicable search terms to collect information on medication-related adverse events. In order to obtain an up-to-date view of MRAEs, only studies published after 2000 were accepted.

Results

The prevalence rates of different MRAEs vary greatly between individual studies and meta-analyses. Study setting, patient population, and detection methods play an important role in determining detection rates, which should be regarded while interpreting the results. Medication-related adverse events are more common in elderly patients and patients with lowered liver or kidney function, polypharmacy, and a large number of additional comorbidities. However, the risk of MRAEs is also significantly increased by the use of high-risk medicines but also in certain care situations. Preventing MRAEs is important as it will decrease patient mortality and morbidity but also reduce costs and functional challenges related to them.

Conclusions

Medication-related adverse events are highly common and have both immediate and long-term effects to patients and healthcare systems worldwide. Conclusive solutions for prevention of all medication-related harm are impossible to create. In the future, however, the development of efficient real-time detection methods can provide significant improvements for event prevention and forecasting.

Sex-Biased Expression of Pharmacogenes across Human Tissues

Individual response to drugs is highly variable and largely influenced by genetic variants and gene-expression profiles. In addition, it has been shown that response to drugs is strongly sex-dependent, both in terms of efficacy and toxicity. To expand current knowledge on sex differences in the expression of genes relevant for drug response, we generated a catalogue of differentially expressed human transcripts encoded by 289 genes in 41 human tissues from 838 adult individuals of the Genotype-Tissue Expression project (GTEx, v8 release) and focused our analysis on relevant transcripts implicated in drug response. We detected significant sex-differentiated expression of 99 transcripts encoded by 59 genes in the tissues most relevant for human pharmacology (liver, lung, kidney, small intestine terminal ileum, skin not sun-exposed, and whole blood). Among them, as expected, we confirmed significant differences in the expression of transcripts encoded by the cytochromes in the liver, CYP2B6, CYP3A7, CYP3A5, and CYP1A1. Our systematic investigation on differences between male and female in the expression of drug response-related genes, reinforce the need to overcome the sex bias of clinical trials.

Precision Medicine and Triple-Negative Breast Cancer: Current Landscape and Future Directions

Simple Summary

The implementation of precision medicine will revolutionize cancer treatment paradigms. Notably, this goal is not far from reality: genetically similar cancers can be treated similarly. The heterogeneous nature of triple-negative breast cancer (TNBC) made it a suitable candidate to practice precision medicine. Using TNBC molecular subtyping and genomic profiling, a precision medicine-based clinical trial is ongoing. This review summarizes the current landscape and future directions of precision medicine and TNBC.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous subtype of breast cancer associated with a high recurrence and metastasis rate that affects African-American women disproportionately. The recent approval of targeted therapies for small subgroups of TNBC patients by the US ‘Food and Drug Administration’ is a promising development. The advancement of next-generation sequencing, particularly somatic exome panels, has raised hopes for more individualized treatment plans. However, the use of precision medicine for TNBC is a work in progress. This review will discuss the potential benefits and challenges of precision medicine for TNBC. A recent clinical trial designed to target TNBC patients based on their subtype-specific classification shows promise. Yet, tumor heterogeneity and sub-clonal evolution in primary and metastatic TNBC remain a challenge for oncologists to design adaptive precision medicine-based treatment plans.

Drug-drug-gene interactions as mediators of adverse drug reactions to diclofenac and statins: a case report and literature review

Concomitant treatment with drugs that inhibit drug metabolising enzymes and/or transporters, such as commonly prescribed statins and nonsteroidal anti-inflammatory drugs (NSAIDs), has been associated with prolonged drug exposure and increased risk of adverse drug reactions (ADRs) due to drug-drug interactions. The risk is further increased in patients with chronic diseases/comorbidities who are more susceptible because of their genetic setup or external factors. In that light, we present a case of a 46-year-old woman who had been experiencing acute renal and hepatic injury and myalgia over two years of concomitant treatment with diclofenac, atorvastatin, simvastatin/fenofibrate, and several other drugs, including pantoprazole and furosemide. Our pharmacogenomic findings supported the suspicion that ADRs, most notably the multi-organ toxicity experienced by our patient, may be owed to drug-drug-gene interactions and increased bioavailability of the prescribed drugs due to slower detoxification capacity and decreased hepatic and renal elimination. We also discuss the importance of CYP polymorphisms in the biotransformation of endogenous substrates such as arachidonic acid and their modulating role in pathophysiological processes. Yet even though the risks of ADRs related to the above mentioned drugs are substantially evidenced in literature, pre-emptive pharmacogenetic analysis has not yet found its way into common clinical practice.

Prevalence of five pharmacologically most important CYP2C9 and CYP2C19 allelic variants in the population from the Republic of Srpska in Bosnia and Herzegovina

The enzymes of the cytochrome P450 superfamily play a critical role in phase I drug metabolism. Among them, CYP2C9 and CYP2C19 are clinically important, as they can mediate severe toxicity, therapy failure, and increased susceptibility to cancer and other diseases caused by chemicals. The aim of this study was to determine the prevalence of pharmacologically most important allelic variants of the CYP2C9 and CYP2C19 genes in the general population of the Republic of Srpska (Bosnia and Herzegovina) and to compare them with other populations. For this purpose we determined the genotype profile and allele frequency of 216 randomly selected healthy volunteers using real-time polymerase chain reaction (RT-PCR). The prevalence of the CYP2C9 *2 and *3 alleles was 13.6 and 7.4 %, respectively. Based on these frequencies, of the 216 participants four (1.86 %) were predicted to be poor metabolisers, 78 (36.11 %) intermediate, and the remaining 134 (62.03 %) normal metabolisers. Based on the prevalence of CYP2C19 *2 and *17 variants – 16.2 and 20.4 %, respectively – nine (4.17 %) were predicted to be poor, 57 (26.39 %) rapid, and nine (4.17 %) ultra-rapid metabolisers. We found no significant differences in allele frequencies in our population and populations from other European countries. These findings suggest that genetically determined phenotypes of CYP2C9 and CYP2C19 should be taken into consideration to minimise individual risk and improve benefits of drug therapy in the Republic of Srpska.

Pharmacogenomics of NSAID-Induced Upper Gastrointestinal Toxicity

Non-steroidal anti-inflammatory drugs (NSAIDs) are a group of drugs which are widely used globally for the treatment of pain and inflammation, and in the case of aspirin, for secondary prevention of cardiovascular disease. Chronic non-steroidal anti-inflammatory drug use is associated with potentially serious upper gastrointestinal adverse drug reactions (ADRs) including peptic ulcer disease and gastrointestinal bleeding. A few clinical and genetic predisposing factors have been identified; however, genetic data are contradictory. Further research is needed to identify clinically relevant genetic and non-genetic markers predisposing to NSAID-induced peptic ulceration.

Computational Tools to Assess the Functional Consequences of Rare and Noncoding Pharmacogenetic Variability

Interindividual differences in drug response are a common concern in both drug development and across layers of care. While genetics clearly influences drug response and toxicity of many drugs, a substantial fraction of the heritable pharmacological and toxicological variability remains unexplained by known genetic polymorphisms. In recent years, population-scale sequencing projects have unveiled tens of thousands of coding and noncoding pharmacogenetic variants with unclear functional effects that might explain at least part of this missing heritability. However, translating these personalized variant signatures into drug response predictions and actionable advice remains challenging and constitutes one of the most important frontiers of contemporary pharmacogenomics. Conventional prediction methods are primarily based on evolutionary conservation, which drastically reduces their predictive accuracy when applied to poorly conserved pharmacogenes. Here, we review the current state-of-the-art of computational variant effect predictors across variant classes and critically discuss their utility for pharmacogenomics. Besides missense variants, we discuss recent progress in the evaluation of synonymous, splice, and noncoding variations. Furthermore, we discuss emerging possibilities to assess haplotypes and structural variations. We advocate for the development of algorithms trained on pharmacogenomic instead of pathogenic data sets to improve the predictive accuracy in order to facilitate the utilization of next-generation sequencing data for personalized clinical decision support and precision pharmacogenomics.

Pharmacogenomics in the era of next generation sequencing - from byte to bedside

Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.

Extracellular Vesicles: A Novel Tool Facilitating Personalized Medicine and Pharmacogenomics in Oncology

Biomarkers that can guide cancer therapy based on patients' individual cancer molecular signature can enable a more effective treatment with fewer adverse events. Data on actionable somatic mutations and germline genetic variants, studied by personalized medicine and pharmacogenomics, can be obtained from tumor tissue or blood samples. As tissue biopsy cannot reflect the heterogeneity of the tumor or its temporal changes, liquid biopsy is a promising alternative approach. In recent years, extracellular vesicles (EVs) have emerged as a potential source of biomarkers in liquid biopsy. EVs are a heterogeneous population of membrane bound particles, which are released from all cells and accumulate into body fluids. They contain various proteins, lipids, nucleic acids (miRNA, mRNA, and DNA) and metabolites. In cancer, EV biomolecular composition and concentration are changed. Tumor EVs can promote the remodeling of the tumor microenvironment and pre-metastatic niche formation, and contribute to transfer of oncogenic potential or drug resistance during chemotherapy. This makes them a promising source of minimally invasive biomarkers. A limited number of clinical studies investigated EVs to monitor cancer progression, tumor evolution or drug resistance and several putative EV-bound protein and RNA biomarkers were identified. This review is focused on EVs as novel biomarker source for personalized medicine and pharmacogenomics in oncology. As several pharmacogenes and genes associated with targeted therapy, chemotherapy or hormonal therapy were already detected in EVs, they might be used for fine-tuning personalized cancer treatment.

TLR4 and TLR9 polymorphism: Probable role in susceptibility among the population of Bihar for Indian visceral leishmaniasis

Genetic variations in the host TLRs genes play an important role in susceptibility and/or resistance to visceral leishmaniasis by altering the host-pathogen interaction. In this study, we investigated the association between polymorphisms of TLR4 (Asp299Gly, Thr399Ile) and TLR-9 (T-1237C), with susceptibility to visceral leishmaniasis. A bi-directional PCR amplification of specific alleles technique was used to characterize the distribution of TLR4 (Asp299Gly and Thr399Ile) and TLR9 (T-1237C) polymorphisms. A total of 60 samples were randomly selected from confirmed visceral leishmaniasis patients and 24 endemic healthy volunteers. The samples were genotyped and allele frequencies were determined. We observed that TLR4 Asp299Gly and Thr399Ile genotypes were more frequent in visceral leishmaniasis patients (10% and 15% respectively) compared to controls (4.2% and 8.3% respectively). However, the differences were not significant in TLR4 Asp299Gly and Thr399Ile alleles and genotypes. In the case of TLR9, we observed the frequency of T1237C genotype was higher in visceral leishmaniasis patients (43.3%) than in healthy controls (33.3%). Statistically significant differences were observed in TLR9 T1237C alleles and genotypes. We concluded that TLR9 T1237C, but not TLR4, gene polymorphisms can be regarded as contributors to visceral leishmaniasis susceptibility among the Indian population of Bihar state.

Glossary and tutorial of xenobiotic metabolism terms used during small molecule drug discovery and development (IUPAC Technical Report)

This project originated more than 15 years ago with the intent to produce a glossary of drug metabolism terms having definitions especially applicable for use by practicing medicinal chemists. A first-draft version underwent extensive beta-testing that, fortuitously, engaged international audiences in a wide range of disciplines involved in drug discovery and development. It became clear that the inclusion of information to enhance discussions among this mix of participants would be even more valuable. The present version retains a chemical structure theme while expanding tutorial comments that aim to bridge the various perspectives that may arise during interdisciplinary communications about a given term. This glossary is intended to be educational for early stage researchers, as well as useful for investigators at various levels who participate on today’s highly multidisciplinary, collaborative small molecule drug discovery teams.

A retrospective analysis of actionable pharmacogenetic/genomic biomarker language in FDA labels

The primary goal of precision medicine is to maximize the benefit‐risk relationships for individual patients by delivering the right drug to the right patients at the right dose. To achieve this goal, it has become increasingly important to assess gene‐drug interactions (GDIs) in clinical settings. The US Food and Drug Administration (FDA) periodically updates the table of pharmacogenetic/genomic (PGx) biomarkers in drug labeling on their website. As described herein, an effort was made to categorize various PGx biomarkers covered by the FDA‐PGx table into certain groups. There were 2 major groups, oncology molecular targets (OMT) and drug‐metabolizing enzymes and transporters (DMETs), which constitute ~70% of all biomarkers (~33% and ~35%, respectively). These biomarkers were further classified whether their labeling languages could be actionable in clinical practice. For OMT biomarkers, ~70% of biomarkers are considered actionable in clinical practice as they are critical for the selection of appropriate drugs to individual patients. In contrast, ~30% of DMET biomarkers are considered actionable for the dose adjustments or alternative therapies in specific populations, such as CYP2C19 and CYP2D6 poor metabolizers. In addition, the GDI results related to some of the other OMT and DMET biomarkers are considered to provide valuable information to clinicians. However, clinical GDI results on the other DMET biomarkers can possibly be used more effectively for dose recommendation. As the labels of some drugs already recommend the precise doses in specific populations, it will be desirable to have clear language for dose recommendation of other (or new) drugs if appropriate.

Pharmacogenetics of common SNP affecting drug metabolizing enzymes: comparison of allele frequencies between European and Malaysian/Singaporean

Compared to Europe, data on genetic variation in genes transcribing drug metabolizing enzymes among Asian is limited due to ethnic diversity. Here we compare frequencies for clinically relevant single nucleotide polymorphism (SNP) commonly observed in drug metabolizing enzymes between European and Malaysian/Singaporean. Minor allele frequencies (MAF) for the indicated SNPs for European, South Asian and East Asian populations were obtained from the NCBI website (https://www.ncbi.nlm.nih.gov/snp). The SNP prevalence among Malaysian/Singaporean was characterized from gene association studies. Generally, some SNPs in CYP2D6 and CYP2C19 do not show good agreement between the two populations as to the MAF value obtained. CYP2D6*4 tends to be more common among European, whereas CYP2D6*10 is more common in Malays and Chinese among Singaporean. Regardless of different phenotype, MAF of CYP2D6*4 for Indians is similar to that seen by the European. Singaporeans show smaller MAF for CYP2C19*17 but higher CYP2C19*2 frequencies as opposed to European ones. Following growing attention to the contribution of CYP3A4/5, N-acetyltransferases (NAT2), thiopurine methyltransferase (TPMT) and uridine diphosphate glucuronosyltransferases (UGT)2B7 in predicting drug response across Europe, there are limited pharmacogenetics (PGx) studies examining the gene-drug interaction among Malaysian/Singaporean. To better understand the heterogeneity of the drug response, PGx studies for the abovementioned enzymes between ethnics in Malaysian/Singaporean should be identified.

Pharmacogenetics of common SNP affecting drug metabolizing enzymes: comparison of allele frequencies between European and Malaysian/Singaporean

Compared to Europe, data on genetic variation in genes transcribing drug metabolizing enzymes among Asian is limited due to ethnic diversity. Here we compare frequencies for clinically relevant single nucleotide polymorphism (SNP) commonly observed in drug metabolizing enzymes between European and Malaysian/Singaporean. Minor allele frequencies (MAF) for the indicated SNPs for European, South Asian and East Asian populations were obtained from the NCBI website (https://www.ncbi.nlm.nih.gov/snp). The SNP prevalence among Malaysian/Singaporean was characterized from gene association studies. Generally, some SNPs in CYP2D6 and CYP2C19 do not show good agreement between the two populations as to the MAF value obtained. CYP2D6*4 tends to be more common among European, whereas CYP2D6*10 is more common in Malays and Chinese among Singaporean. Regardless of different phenotype, MAF of CYP2D6*4 for Indians is similar to that seen by the European. Singaporeans show smaller MAF for CYP2C19*17 but higher CYP2C19*2 frequencies as opposed to European ones. Following growing attention to the contribution of CYP3A4/5, N-acetyltransferases (NAT2), thiopurine methyltransferase (TPMT) and uridine diphosphate glucuronosyltransferases (UGT)2B7 in predicting drug response across Europe, there are limited pharmacogenetics (PGx) studies examining the gene-drug interaction among Malaysian/Singaporean. To better understand the heterogeneity of the drug response, PGx studies for the abovementioned enzymes between ethnics in Malaysian/Singaporean should be identified.

Influence of genetic polymorphisms in glutathione-S-transferases gene in response to imatinib among Brazilian patients with chronic myeloid leukemia

Polymorphism in metabolizing enzymes can influence drug response as well as the risk for adverse drug reactions. Nevertheless, there are still few studies analyzing the consequence of polymorphisms for the Glutathione-S-transferases (GST) gene to drug response in chronic myeloid leukemia (CML). This study reports, the influence of GSTP1*B and GSTT1/GSTM1null polymorphisms in response to imatinib in CML patients in a Brazilian population. One hundred thirty-nine CML patients from the Clinical Hospital of Goiânia, Goiás, Brazil, treated with imatinib were enrolled in this study. Genotyping of GSTT1 and GSTM1 genes deletions were performed by qPCR and of GSTP1 gene was performed by RFLP-PCR. The frequency of GSTP1*1B, GSTT1 and GSTM1null polymorphisms were determined for all patients. The influence of each patient's genotypes was analyzed with the patient's response to imatinib treatment. Brazilian CML patients revealed GSTT1 and GSTM1 genes deletions. GSTT1 deletion was found in 19.3% of patients and GSTM1 deletion in 48.7% of patients with CML. GSTT1/GSTM1 deletion was found in 11.7% in Brazilian CML patients. The "G allele" of GSTP1*B, is associated with later cytogenetic response in imatinib therapy. While, the gene presence combined with GG genotype (GSTM1 present/GSTPI-GG) conferred a tend to a later cytogenetic response to patients. GSTP1*B and GSTT1/GSTM1null polymorphisms influence treatment response in CML. Brazilian CML patients presenting GSTP1 AA/AG genotypes alone and in combination with GSTT1 null reach the cytogenetic response faster, while patients presenting GSTP1-GG and GSTMI positive genotypes may take longer to achieve cytogenetic response. As a result, it allows a better prognosis, with the use of an alternative therapy, other than reducing treatment cost.

Sources of Interindividual Variability

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in others. A significant source of this variability in drug response is drug metabolism, where differences in presystemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, C_max, and/or C_min) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is recognized that both intrinsic factors (e.g., genetics, age, sex, and disease states) and extrinsic factors (e.g., diet , chemical exposures from the environment, and the microbiome) play a significant role. For drug-metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, upregulation and downregulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less predictable and time-dependent manner. Understanding the mechanistic basis for variability in drug disposition and response is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that will improve outcomes in maintaining health and treating disease.

Pharmacogenomics, How to Deal with Different Types of Variants in Next Generation Sequencing Data in the Personalized Medicine Area

Pharmacogenomics (PGx) is the knowledge of diverse drug responses and effects in people, based on their genomic profiles. Such information is considered as one of the main directions to reach personalized medicine in future clinical practices. Since the start of applying next generation sequencing (NGS) methods in drug related clinical investigations, many common medicines found their genetic data for the related metabolizing/shipping proteins in the human body. Yet, the employing of technology is accompanied by big obtained data, which most of them have no clear guidelines for consideration in routine treatment decisions for patients. This review article talks about different types of NGS derived PGx variants in clinical studies and try to display the current and newly developed approaches to deal with pharmacogenetic data with/without clear guidelines for considering in clinical settings.

Distinct Effects of Inflammation on Cytochrome P450 Regulation and Drug Metabolism: Lessons from Experimental Models and a Potential Role for Pharmacogenetics

Personalized medicine strives to optimize drug treatment for the individual patient by taking into account both genetic and non-genetic factors for drug response. Inflammation is one of the non-genetic factors that has been shown to greatly affect the metabolism of drugs—primarily through inhibition of cytochrome P450 (CYP450) drug-metabolizing enzymes—and hence contribute to the mismatch between the genotype predicted drug response and the actual phenotype, a phenomenon called phenoconversion. This review focuses on inflammation-induced drug metabolism alterations. In particular, we discuss the evidence assembled through human in-vitro models on the effect of inflammatory mediators on clinically relevant CYP450 isoform levels and their metabolizing capacity. We also present an overview of the current understanding of the mechanistic pathways via which inflammation in hepatocytes may modulate hepatic functions that are critical for drug metabolism. Furthermore, since large inter-individual variability in response to inflammation is observed in human in-vitro models and clinical studies, we evaluate the potential role of pharmacogenetic variability in the inflammatory signaling cascade and how this can modulate the outcome of inflammation on drug metabolism and response.

Individual variation in unfractionated heparin dosing after pediatric cardiac surgery

We aimed to identify attributing factors to the interindividual variabilities of the infusion rates in unfractionated heparin therapy. We included patients who required unfractionated heparin therapy to achieve the target APTT after cardiac surgery between May 2014 and February 2018. Fifty-nine patients were included, of whom 8 underwent Blalock-Taussig shunt; 27, Glenn procedure; 19, Fontan procedure; 3, mechanical valve replacement; and 2, Rastelli procedure. Previously reported variables that influenced the response to unfractionated heparin treatment were initially compared, which included age; weight; sex; type of surgery; platelet count; fibrinogen, antithrombin III, total protein, albumin, alanine transaminase, and creatinine levels; and use of fresh frozen plasma. The type of surgical procedure was found to be significantly associated with the differences in heparin infusion rate (P = 0.00073). Subsequently, the variance explained by these factors was estimated through a selection based on the minimum Akaike information criterion value; models constructed by various combinations of the surgery types were compared. The model including the Blalock-Taussig shunt, Glenn procedure, and mechanical valve replacement showed the highest summed variance explained (29.1%). More than 70% of the interindividual variability in initial heparin maintenance dosing was unexplained.

Pharmacogenetic-Pharmacokinetic Interactions in Drug Marketing Authorization Applications via the European Medicines Agency Between 2014 and 2017

This study aimed to determine to which extent data on potential pharmacogenetic-pharmacokinetic (PG-PK) interactions are provided to, and assessed by, the European Medicines Agency (EMA) in novel drug marketing authorization applications (MAAs), and whether regulatory assessment of PG-PK interactions is adequate or could be optimized. For this purpose, we retrospectively analyzed MAAs of small molecule drugs assessed by the EMA between January 2014 and December 2017. As per two key requirements in the EMA's guideline, we analyzed cases where (i) a single functionally polymorphic drug metabolizing enzyme (DME) metabolizes > 25% of the drug, or (ii) the drug's PK shows high interindividual variability not explained by other factors than PG. Results showed that, of 113 drugs analyzed, 53 (47%) had ≥ 1 functionally polymorphic DME accounting for > 25% of the drug's metabolism, yielding 55 gene-drug pairs. For 36 of 53 (68%) of the products, CYP3A4 was the major DME. Compliance with European Union (EU) guidance on PG-PK issues in drug development was notably different for CYP3A4 substrates vs. non-CYP3A4 substrates. Adequate PG-PK data were provided during registration in 89% (16/18) of cases concerning non-CYP3A4 substrates, compared with 32% (12/37) of cases concerning CYP3A4 substrates. Concluding, PG-PK interactions related to non-CYP3A4 substrate drugs were, in general, addressed adequately in EU MAAs. PG-PK information on CYP3A4 substrates was available less frequently, despite some available evidence on the functional relevance of CYP3A4 polymorphisms. A more harmonized approach toward assessment of PG-PK issues in EU MAAs seems warranted, and a discussion on the relevance of CYP3A4 polymorphisms, such as CYP3A4*22, is recommended.

Human variability in isoform-specific UDP-glucuronosyltransferases: markers of acute and chronic exposure, polymorphisms and uncertainty factors

UDP-glucuronosyltransferases (UGTs) are involved in phase II conjugation reactions of xenobiotics and differences in their isoform activities result in interindividual kinetic differences of UGT probe substrates. Here, extensive literature searches were performed to identify probe substrates (14) for various UGT isoforms (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT2B7 and UGT2B15) and frequencies of human polymorphisms. Chemical-specific pharmacokinetic data were collected in a database to quantify interindividual differences in markers of acute (Cmax) and chronic (area under the curve, clearance) exposure. Using this database, UGT-related uncertainty factors were derived and compared to the default factor (i.e. 3.16) allowing for interindividual differences in kinetics. Overall, results show that pharmacokinetic data are predominantly available for Caucasian populations and scarce for other populations of different geographical ancestry. Furthermore, the relationships between UGT polymorphisms and pharmacokinetic parameters are rarely addressed in the included studies. The data show that UGT-related uncertainty factors were mostly below the default toxicokinetic uncertainty factor of 3.16, with the exception of five probe substrates (1-OH-midazolam, ezetimibe, raltegravir, SN38 and trifluoperazine), with three of these substrates being metabolised by the polymorphic isoform 1A1. Data gaps and future work to integrate UGT-related variability distributions with in vitro data to develop quantitative in vitro-in vivo extrapolations in chemical risk assessment are discussed.

Functional characterization of the chlorzoxazone 6-hydroxylation activity of human cytochrome P450 2E1 allelic variants in Han Chinese

BACKGROUNDS

Cytochrome P450 (P450) 2E1 is one of the primary enzymes responsible for the metabolism of xenobiotics, such as drugs and environmental carcinogens. The genetic polymorphisms of the CYP2E1 gene in promoter and coding regions have been identified previously in the Han Chinese population from four different geographic areas of Mainland China.

METHODS

To investigate whether genetic variants identified in the CYP2E1 coding region affect enzyme function, the enzymes of four single nucleotide polymorphism (SNP) variants in the coding region (novel c.1009C>T, causing p.Arg337X, where X represents the translational stop codon; c.227G>A, causing p.Arg76His; c.517G>A, yielding p.Gly173Ser; and c.1263C>T, presenting the highest allele frequency), two novel alleles (c.[227G>A;1263C>T] and c.[517G>A;1263C>T]), and the wild-type CYP2E1 were heterologously expressed in COS-7 cells and functionally characterized in terms of expression level and chlorzoxazone 6-hydroxylation activity. The impact of the CYP2E1 variant sequence on enzyme activity was predicted with three programs: Polyphen 2, PROVEAN and SIFT.

RESULTS

The prematurely terminated p.Arg337X variant enzyme was undetectable by western blotting and inactive toward chlorzoxazone 6-hydroxylation. The c.1263C>T and c.[517G>A;1263C>T] variant enzymes exhibited properties similar to those of the wild-type CYP2E1. The CYP2E1 variants c.227G>A and c.[227G>A;1263C>T] displayed significantly reduced enzyme activity relative to that of the wild-type enzyme (decreased by 42.8% and 32.8%, respectively; P < 0.01). The chlorzoxazone 6-hydroxylation activity of the c.517G>A transfectant was increased by 31% compared with the wild-type CYP2E1 enzyme (P < 0.01). Positive correlations were observed between the protein content and enzyme activity for CYP2E1 (P = 0.0005, r 2 = 0.8833). The characterization of enzyme function allelic variants in vitro was consistent with the potentially deleterious effect of the amino acid changes as determined by prediction tools.

CONCLUSIONS

These findings indicate that the genetic polymorphisms of CYP2E1, i.e., c.1009C>T (p.Arg337X), c.227G>A (p.Arg76His), and c.517G>A (p.Gly173Ser), could influence the metabolism of CYP2E1 substrates, such as chlorzoxazone.

Relationship between plasma exposure of zolpidem and CYP2D6 genotype in healthy Korean subjects

Zolpidem, a widely prescribed hypnotic agent, is extensively metabolized by cytochrome P450 (CYP) 3A4, and CYP2C9, CYP1A2 and CYP2D6 are also involved in the metabolism of zolpidem. The aim of the study was to investigate the effects of CYP2D6 genotypes on the exposure of zolpidem. The healthy male volunteers were divided into three different genotype groups (CYP2D6*wt/*wt [*wt = *1 or *2], CYP2D6*wt/*10, and CYP2D6*10/*10). Each subject received a single oral dose of zolpidem 5 mg with or without a steady-state concentration of clarithromycin (a potent inhibitor of CYP3A4), and plasma concentrations of zolpidem were measured up to 12 h after zolpidem dosing by using liquid chromatography-tandem mass spectrometry method. When zolpidem was administered alone, the exposure of zolpidem (the total areas under the curve and the mean peak plasma concentrations) was not significantly different among three different genotype groups. Even with the steady-state concentration of clarithromycin, a potent CYP3A4 inhibitor, there were no significant differences in the exposure of zolpidem in relation to CYP2D6 genotypes.

Brazilian cohort and genes encoding for drug-metabolizing enzymes and drug transporters

Background & aim: Genetic variability in drug absorption, distribution, metabolism and excretion (ADME) genes contributes to the high heterogeneity of drug responses. The present study investigated polymorphisms of ADME genes frequencies and compared the findings with populations from other continents, available in the 1000 Genome Project (1 KGP) and the Exome Aggregation Consortium (ExAC) databases. Methodology & results: We conducted a study of 100 patients in Brazil and a total of 2003 SNPs were evaluated by targeted next-generation sequencing in 148 genes, including Phase I enzymes (n = 50), Phase II enzymes (n = 38) and drug transporters (n = 60). Overall, the distribution of minor allele frequency (MAF) suggests that the distribution of 2003 SNPs is similar between Brazilian cohort, 1 KGP and ExAC; however, we found moderate SNP allele-frequency divergence between Brazilian cohort and both 1000 KGP and ExAC. These differences were observed in several relevant genes including CYP3A4, NAT2 and SLCO1B1. Conclusion: We concluded that the Brazilian population needs clinical assessment of drug treatment based on individual genotype rather than ethnicity.

Variant discovery using next-generation sequencing and its future role in pharmacogenetics

Next-generation sequencing (NGS) has enabled the discovery of a multitude of novel and mostly rare variants in pharmacogenes that may alter a patient’s therapeutic response to drugs. In addition to single nucleotide variants, structural variation affecting the number of copies of whole genes or parts of genes can be detected. While current guidelines concerning clinical implementation mostly act upon well-documented, common single nucleotide variants to guide dosing or drug selection, in silico and large-scale functional assessment of rare variant effects on protein function are at the forefront of pharmacogenetic research to facilitate their clinical integration. Here, we discuss the role of NGS in variant discovery, paving the way for more comprehensive genotype-guided pharmacotherapy that can translate to improved clinical care.

Considerations for Determining Direct Versus Indirect Functional Effects of Solubilizing Excipients on Drug Transporters for Enhancing Bioavailability

Excipients used in drug formulations at clinically safe levels have been considered to be pharmacologically inert; however, numerous studies have suggested that many solubilizing agents may modulate drug transporter activities and intestinal absorption. Here, the reported interactions between various solubilizing excipients and drug transporters are evaluated to consider various potential underlying mechanisms. This forms the basis for debate in the field in regard to whether or not the effects are based on "direct" interactions or "indirect" consequences arising from the role of the excipients. For example, an increase in apparent drug solubility can give rise to saturation of transporters according to Michaelis-Menten kinetics. This is also drawing the attention of regulatory agencies as they seek to understand the role of formulation additives. The continued application of excipients as a tool in solubility enhancement is crucial in the drug development process, creating a need for additional data to verify the proposed mechanism behind these changes. A literature review is provided here with some guidance on other factors that should be considered to delineate the effects that arise from direct physiological interactions or indirect effects. The results of such studies may aid the rational design of bioavailability-enhancing formulations.

Identification of new probe substrates for human CYP20A1

CYP20A1 is a well-conserved member of the human cytochrome P450 enzyme family for which no endogenous or xenobiotic substrate is known. We have recently shown that this enzyme has moderate activity towards two proluciferin probe substrates. In order to facilitate the search for physiological substrates we have tested nine additional proluciferins in this study and identified three such probe substrates that give much higher product yields. Using one of these probes, we demonstrate inhibition of CYP20A1 activity by 1-benzylimidazole, ketoconazole and letrozole. Finally, we show that the combination of two common single nucleotide polymorphisms (SNPs) ofCYP20A1leads to an enzyme (CYP20A1Leu97Phe346) with reduced activity.

The effect of CYP2D6 variation on antipsychotic-induced hyperprolactinaemia: a systematic review and meta-analysis

Hyperprolactinemia is a known adverse drug reaction to antipsychotic treatment. Antipsychotic blood levels are influenced by cytochrome P450 enzymes, primarily CYP2D6. Variation in CYP450 genes may affect the risk of antipsychotic-induced hyperprolactinemia. We undertook a systematic review and meta-analysis to assess whether CYP2D6 functional genetic variants are associated with antipsychotic-induced hyperprolactinemia. The systematic review identified 16 relevant papers, seven of which were suitable for the meta-analysis (n = 303 participants including 134 extreme metabolisers). Participants were classified into four phenotype groups as poor, intermediate, extensive, and ultra-rapid metabolisers. A random effects meta-analysis was used and Cohen's d calculated as the effect size for each primary study. We found no significant differences in prolactin levels between CYP2D6 metabolic groups. Current evidence does not support using CYP2D6 genotyping to reduce risk of antipsychotic-induced hyperprolactinemia. However, statistical power is limited. Future studies with larger samples and including a range of prolactin-elevating drugs are needed.

Research advances in the association of drug-induced liver injury with polymorphisms in human leukocyte antigen

Drug-induced liver injury is an important adverse drug reaction. Due to the lack of specificity in clinical symptoms and pathological features, there are still no reliable diagnostic biomarkers, so drug-induced liver injury is a diagnosis of exclusion. The article reviews the relevant advances in the association between novel human leukocyte antigen gene polymorphisms and drug-induced liver injury in order to identify potential biomarkers and provide a new method for the prediction and diagnosis of drug-induced liver injury. Henceforth, while studying the association between them, it will also need that the large sample and prospective studies to gain supporting evidence to implement translational application, so as to improve the safety and effectiveness of medication and achieve individualized treatment.