Pharmacogenomics and individualized drug therapy

Pharmacogenomics: A Genetic Approach to Drug Development and Therapy

The majority of the well-known pharmacogenomics research used in the medical sciences contributes to our understanding of medication interactions. It has a significant impact on treatment and drug development. The broad use of pharmacogenomics is required for the progress of therapy. The main focus is on how genes and an intricate gene system affect the body's reaction to medications. Novel biomarkers that help identify a patient group that is more or less likely to respond to a certain medication have been discovered as a result of recent developments in the field of clinical therapeutics. It aims to improve customized therapy by giving the appropriate drug at the right dose at the right time and making sure that the right prescriptions are issued. A combination of genetic, environmental, and patient variables that impact the pharmacokinetics and/or pharmacodynamics of medications results in interindividual variance in drug response. Drug development, illness susceptibility, and treatment efficacy are all impacted by pharmacogenomics. The purpose of this work is to give a review that might serve as a foundation for the creation of new pharmacogenomics applications, techniques, or strategies.

Enzalutamide: Understanding and Managing Drug Interactions to Improve Patient Safety and Drug Efficacy

Enzalutamide is an oral androgen receptor signaling inhibitor utilized in the treatment of men with prostate cancer. It is a moderate inducer of the cytochrome P450 (CYP) enzymes CYP2C9 and CYP2C19, and a strong inducer of CYP3A4. It was also shown to be a mild inhibitor of the efflux transporter P-glycoprotein in patients with prostate cancer. Enzalutamide is primarily metabolized by CYP3A4 and CYP2C8. The risk of enzalutamide drug interactions arises primarily when it is coadministered with other drugs that interact with these CYPs, including CYP3A4. In this review, we begin by providing an overview of enzalutamide including its dosing, use in special populations, pharmacokinetics, changes to its prescribing information, and potential for interaction with coadministered drugs. Enzalutamide interactions with drugs from a wide range of medication classes commonly prescribed to patients with prostate cancer are described, including oral androgen deprivation therapy, agents used to treat a range of cardiovascular diseases, antidiabetic drugs, antidepressants, anti-seizure medications, common urology medications, analgesics, proton pump inhibitors, immunosuppressants, and antigout drugs. Enzalutamide interactions with common vitamins and supplements are also briefly discussed. This review provides a resource for healthcare practitioners and patients that will help provide a basis for the understanding and management of enzalutamide drug-drug interactions to inform decision making, improve patient safety, and optimize drug efficacy.

The Use of Microdosing for In vivo Phenotyping of Cytochrome P450 Enzymes: Where Do We Stand? A Narrative Review

Cytochrome P450 (CYP) enzymes play a central role in the elimination of approximately 80% of all clinically used drugs. Differences in CYP enzyme activity between individuals can contribute to interindividual variability in exposure and, therefore, treatment outcome. In vivo CYP enzyme activity could be determined with phenotyping. Currently, (sub)therapeutic doses are used for in vivo phenotyping, which can lead to side effects. The use of microdoses (100 µg) for in vivo phenotyping for CYP enzymes could overcome the limitations associated with the use of (sub)therapeutic doses of substrates. The aim of this review is to provide a critical overview of the application of microdosing for in vivo phenotyping of CYP enzymes. A literature search was performed to find drug-drug interaction studies of CYP enzyme substrates that used microdoses of the respective substrates. A substrate was deemed sensitive to changes in CYP enzyme activity when the pharmacokinetics of the substrate significantly changed during inhibition and induction of the enzyme. On the basis of the currently available evidence, the use of microdosing for in vivo phenotyping for subtypes CYP1A2, CYP2C9, CYP2D6, and CYP2E1 is not recommended. Microdosing can be used for the in vivo phenotyping of CYP2C19 and CYP3A. The recommended microdose phenotyping test for CYP2C19 is measuring the omeprazole area-under-the-concentration-time curve over 24 h (AUC0-24) after administration of a single 100 µg dose. CYP3A activity could be best determined with a 0.1-75 µg dose of midazolam, and subsequently measuring AUC extrapolated to infinity (AUC∞) or clearance. Moreover, there are two metrics available for midazolam using a limited sampling strategy: AUC over 10 h (AUC0-10) and AUC from 2 to 4 h (AUC2-4).

Estimating the prevalence of potential and actionable drug-gene interactions in Irish primary care: A cross-sectional study

AIMS

Pharmacogenetics (PGx) is increasingly recognized as a strategy for medicines optimisation and prevention of adverse drug reactions. According to guidelines produced by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetic Working Group (DPWG), most medicines with drug-gene interactions (DGIs) are prescribed in primary care. This study aimed to estimate the prevalence of potential and actionable DGIs involving all medicines dispensed in Irish primary care.

METHODS

Dispensings of 46 drugs to General Medical Services (GMS) patients in the Health Service Executive Primary Care Reimbursement Service Irish pharmacy claims database from 01 January 2021 to 31 December 2021 were analysed to estimate the national prevalence of total dispensings and incidence of first-time dispensings of drugs with potential DGIs according to the CPIC and/or DPWG guidelines. Phenotype frequency data from the UK Biobank and the CPIC were used to estimate the incidence of actionable DGIs.

RESULTS

One in five dispensings (12 443 637 of 62 754 498, 19.8%) were medicines with potential DGIs, 1 878 255 of these dispensed for the first time. On application of phenotype frequencies and linked guideline based therapeutic recommendations, 2 349 055 potential DGIs (18.9%) required action, such as monitoring and guarding against maximum dose, drug or dose change. One in five (369 700, 19.7%) first-time dispensings required action, with 139 169 (7.4%) requiring a change in prescribing. Antidepressants, weak opioids and statins were most commonly identified as having actionable DGIs.

CONCLUSIONS

This study estimated a high prevalence of DGIs in primary care in Ireland, identifying the need and opportunity to optimize drug therapy through PGx testing.

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.

Pharmacogenomics of Drugs Used in β-Thalassemia and Sickle-Cell Disease: From Basic Research to Clinical Applications

In this short review we have presented and discussed studies on pharmacogenomics (also termed pharmacogenetics) of the drugs employed in the treatment of β-thalassemia or Sickle-cell disease (SCD). This field of investigation is relevant, since it is expected to help clinicians select the appropriate drug and the correct dosage for each patient. We first discussed the search for DNA polymorphisms associated with a high expression of γ-globin genes and identified this using GWAS studies and CRISPR-based gene editing approaches. We then presented validated DNA polymorphisms associated with a high HbF production (including, but not limited to the HBG2 XmnI polymorphism and those related to the BCL11A, MYB, KLF-1, and LYAR genes). The expression of microRNAs involved in the regulation of γ-globin genes was also presented in the context of pharmacomiRNomics. Then, the pharmacogenomics of validated fetal hemoglobin inducers (hydroxyurea, butyrate and butyrate analogues, thalidomide, and sirolimus), of iron chelators, and of analgesics in the pain management of SCD patients were considered. Finally, we discuss current clinical trials, as well as international research networks focusing on clinical issues related to pharmacogenomics in hematological diseases.

The potential impact of CYP and UGT drug-metabolizing enzymes on brain target site drug exposure

Drug metabolism is one of the critical determinants of drug disposition throughout the body. While traditionally associated with the liver, recent research has unveiled the presence and functional significance of drug-metabolizing enzymes (DMEs) within the brain. Specifically, cytochrome P-450 enzymes (CYPs) and UDP-glucuronosyltransferases (UGTs) enzymes have emerged as key players in drug biotransformation within the central nervous system (CNS). This comprehensive review explores the cellular and subcellular distribution of CYPs and UGTs within the CNS, emphasizing regional expression and contrasting profiles between the liver and brain, humans and rats. Moreover, we discuss the impact of species and sex differences on CYPs and UGTs within the CNS. This review also provides an overview of methodologies for identifying and quantifying enzyme activities in the brain. Additionally, we present factors influencing CYPs and UGTs activities in the brain, including genetic polymorphisms, physiological variables, pathophysiological conditions, and environmental factors. Examples of CYP- and UGT-mediated drug metabolism within the brain are presented at the end, illustrating the pivotal role of these enzymes in drug therapy and potential toxicity. In conclusion, this review enhances our understanding of drug metabolism's significance in the brain, with a specific focus on CYPs and UGTs. Insights into the expression, activity, and influential factors of these enzymes within the CNS have crucial implications for drug development, the design of safe drug treatment strategies, and the comprehension of drug actions within the CNS. To that end, CNS pharmacokinetic (PK) models can be improved to further advance drug development and personalized therapy.

G-quadruplex forming sequences in the genes coding for cytochrome P450 enzymes and their potential roles in drug metabolism

The majority of drugs are metabolized by cytochrome P450 (CYP) enzymes, primarily belonging to the CYP1, CYP2 and CYP3 families. Genetic variations are the main cause of inter-individual differences in drug response, which constitutes a major concern in pharmacotherapy. G-quadruplexes (G4s), are non-canonical DNA and RNA secondary structures formed by guanine-rich sequences. G4s have been implicated in cancer and gene regulation. In this study, we investigated putative G4-forming sequences (PQSs) in the CYP genes. Our findings reveal a high density of PQSs in the full genes of CYP family 2. Moreover, we observe an increased density of PQSs in the promoters of CYP family 1 genes compared to non-CYP450 genes. Importantly, stable PQSs were also identified in all studied CYP genes. Subsequently, we assessed the impact of the most frequently reported genetic mutations in the selected genes and the possible effect of these mutations on G4 formation as well as on the thermodynamic stability of predicted G4s. We found that 4 SNPs overlap G4 sequences and lead to mutated DNA and RNA G4 forming sequences in their context. Notably, the mutation in the CYP2C9 gene, which is associated with impaired (S)-warfarin metabolism in patients, alters a G4 sequence. We then demonstrated that at least 10 of the 13 chosen cytochrome P450 G4 candidates form G-quadruplex structures in vitro, using a combination of spectroscopic methods. In conclusion, our findings indicate the potential role of G-quadruplexes in the regulation of cytochrome genes, and emphasize the importance of G-quadruplexes in drug metabolism.

Drug-microbiota interactions: an emerging priority for precision medicine

Individual variability in drug response (IVDR) can be a major cause of adverse drug reactions (ADRs) and prolonged therapy, resulting in a substantial health and economic burden. Despite extensive research in pharmacogenomics regarding the impact of individual genetic background on pharmacokinetics (PK) and pharmacodynamics (PD), genetic diversity explains only a limited proportion of IVDR. The role of gut microbiota, also known as the second genome, and its metabolites in modulating therapeutic outcomes in human diseases have been highlighted by recent studies. Consequently, the burgeoning field of pharmacomicrobiomics aims to explore the correlation between microbiota variation and IVDR or ADRs. This review presents an up-to-date overview of the intricate interactions between gut microbiota and classical therapeutic agents for human systemic diseases, including cancer, cardiovascular diseases (CVDs), endocrine diseases, and others. We summarise how microbiota, directly and indirectly, modify the absorption, distribution, metabolism, and excretion (ADME) of drugs. Conversely, drugs can also modulate the composition and function of gut microbiota, leading to changes in microbial metabolism and immune response. We also discuss the practical challenges, strategies, and opportunities in this field, emphasizing the critical need to develop an innovative approach to multi-omics, integrate various data types, including human and microbiota genomic data, as well as translate lab data into clinical practice. To sum up, pharmacomicrobiomics represents a promising avenue to address IVDR and improve patient outcomes, and further research in this field is imperative to unlock its full potential for precision medicine.

Translating pharmacogenomic sequencing data into drug response predictions-How to interpret variants of unknown significance

The rapid development of sequencing technologies during the past 20 years has provided a variety of methods and tools to interrogate human genomic variations at the population level. Pharmacogenes are well known to be highly polymorphic and a plethora of pharmacogenomic variants has been identified in population sequencing data. However, so far only a small number of these variants have been functionally characterized regarding their impact on drug efficacy and toxicity and the significance of the vast majority remains unknown. It is therefore of high importance to develop tools and frameworks to accurately infer the effects of pharmacogenomic variants and, eventually, aggregate the effect of individual variations into personalized drug response predictions. To address this challenge, we here first describe the technological advances, including sequencing methods and accompanying bioinformatic processing pipelines that have enabled reliable variant identification. Subsequently, we highlight advances in computational algorithms for pharmacogenomic variant interpretation and discuss the added value of emerging strategies, such as machine learning and the integrative use of omics techniques that have the potential to further contribute to the refinement of personalized pharmacological response predictions. Lastly, we provide an overview of experimental and clinical approaches to validate in silico predictions. We conclude that the iterative feedback between computational predictions and experimental validations is likely to rapidly improve the accuracy of pharmacogenomic prediction models, which might soon allow for an incorporation of the entire pharmacogenetic profile into personalized response predictions.

Implementation of Pharmacogenetics in First-Line Care: Evaluation of Its Use by General Practitioners

Pharmacogenetics (PGx) can explain/predict drug therapy outcomes. There is, however, unclarity about the use and usefulness of PGx in primary care. In this study, we investigated PGx tests ordered by general practitioners (GPs) in 2021 at Dept. Clinical Chemistry, Erasmus MC, and analyzed the gene tests ordered, drugs/drug groups, reasons for testing and single-gene versus panel testing. Additionally, a survey was sent to 90 GPs asking about their experiences and barriers to implementing PGx. In total, 1206 patients and 6300 PGx tests were requested by GPs. CYP2C19 was requested most frequently (17%), and clopidogrel was the most commonly indicated drug (23%). Regarding drug groups, antidepressants (51%) were the main driver for requesting PGx, followed by antihypertensives (26%). Side effects (79%) and non-response (27%) were the main indicators. Panel testing was preferred over single-gene testing. The survey revealed knowledge on when and how to use PGx as one of the main barriers. In conclusion, PGx is currently used by GPs in clinical practice in the Netherlands. Side effects are the main reason for testing, which mostly involves antidepressants. Lack of knowledge is indicated as a major barrier, indicating the need for more education on PGx for GPs.

Functional evaluation of CYP2C19 and CYP3A4 gene polymorphism on ibuprofen metabolism

AIM

Ibuprofen is the most commonly used analgesic. CYP polymorphisms are mainly responsible for the differences in drug metabolism among individuals. Variations in the ability of populations to metabolize ibuprofen can lead to drug exposure events. The aim of this study was to evaluate the effects of CYP2C19 and CYP3A4 polymorphisms on ibuprofen metabolism in a Chinese population.

METHODS

First, 31 CYP2C19 and 12 CYP3A4 microsomal enzymes were identified using an insect expression system. Then, variants were evaluated using a mature incubation system. Moreover, ibuprofen metabolite content was determined via ultra-performance liquid chromatography-tandem mass spectrometry analysis. Finally, kinetic parameters of CYP2C19 and CYP3A4 genotypes were determined via Michaelis-Menten curve fitting.

RESULTS

Most variants exhibited significantly altered intrinsic clearance compared to the wild type. In the CYP2C19 metabolic pathway, seven variants exhibited no significant alterations in intrinsic clearance (CLint), six variants exhibited significantly high CLint (121-291%), and the remaining 15 variants exhibited substantially reduced CLint (1-71%). In the CYP3A4 metabolic pathway, CYP3A4*30 was not detected in the metabolite content due to the absence of activity, and 10 variants exhibited significantly reduced CLint.

CONCLUSION

To the best of our knowledge, this is the first study to assess the kinetic characteristics of 31 CYP2C19 and 12 CYP3A4 genotypes on ibuprofen metabolism. However, further studies are needed on poor metabolizers as they are more susceptible to drug exposure. Our findings suggest that the kinetic characteristics in combination with artificial intelligence to predict the toxicity of ibuprofen and reduce any adverse drug reactions.

Race, Ethnicity, and Pharmacogenomic Variation in the United States and the United Kingdom

The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.

Bortezomib Pharmacogenetic Biomarkers for the Treatment of Multiple Myeloma: Review and Future Perspectives

Multiple myeloma (MM) is a hematological neoplasm for which different chemotherapy treatments are used with several drugs in combination. One of the most frequently used drugs for the treatment of MM is the proteasome inhibitor bortezomib. Patients treated with bortezomib are at increased risk for thrombocytopenia, neutropenia, gastrointestinal toxicities, peripheral neuropathy, infection, and fatigue. This drug is almost entirely metabolized by cytochrome CYP450 isoenzymes and transported by the efflux pump P-glycoprotein. Genes encoding both enzymes and transporters involved in the bortezomib pharmacokinetic pathway are highly polymorphic. The response to bortezomib and the incidence of adverse drug reactions (ADRs) vary among patients, which could be due to interindividual variations in these possible pharmacogenetic biomarkers. In this review, we compiled all pharmacogenetic information relevant to the treatment of MM with bortezomib. In addition, we discuss possible future perspectives and the analysis of potential pharmacogenetic markers that could influence the incidence of ADR and the toxicity of bortezomib. It would be a milestone in the field of targeted therapy for MM to relate potential biomarkers to the various effects of bortezomib on patients.

Pharmaco-Omics in Psoriasis: Paving the Way towards Personalized Medicine

The emergence of high-throughput approaches has had a profound impact on personalized medicine, evolving the identification of inheritable variation to trajectory analyses of transient states and paving the way for the unveiling of response biomarkers. The utilization of the multi-layered pharmaco-omics data, including genomics, transcriptomics, proteomics, and relevant biological information, has facilitated the identification of key molecular biomarkers that can predict the response to therapy, thereby optimizing treatment regiments and providing the framework for a tailored treatment plan. Despite the availability of multiple therapeutic options for chronic diseases, the highly heterogeneous clinical response hinders the alleviation of disease signals and exacerbates the annual burden and cost of hospitalization and drug regimens. This review aimed to examine the current state of the pharmaco-omic approaches performed in psoriasis, a common inflammatory disease of the skin. We sought to identify central studies that investigate the inter-individual variability and explore the underlying molecular mechanisms of drug response progression via biological profiling in psoriatic patients administered with the extended therapeutic armamentarium of psoriasis, incorporating conventional therapies, small molecules, as well as biological drugs that inhibit central pathogenic cytokines involved in the disease pathogenesis.

Individualized interventions and precision health: Lessons learned from a systematic review and implications for analytics-driven geriatric research

Older adults are characterized by profound clinical heterogeneity. When designing and delivering interventions, there exist multiple approaches to account for heterogeneity. We present the results of a systematic review of data-driven, personalized interventions in older adults, which serves as a use case to distinguish the conceptual and methodologic differences between individualized intervention delivery and precision health-derived interventions. We define individualized interventions as those where all participants received the same parent intervention, modified on a case-by-case basis and using an evidence-based protocol, supplemented by clinical judgment as appropriate, while precision health-derived interventions are those that tailor care to individuals whereby the strategy for how to tailor care was determined through data-driven, precision health analytics. We discuss how their integration may offer new opportunities for analytics-based geriatric medicine that accommodates individual heterogeneity but allows for more flexible and resource-efficient population-level scaling.

Do genetics contribute to TNF inhibitor response prediction in Psoriatic Arthritis?

Psoriatic arthritis (PsA) is a heterogeneous chronic musculoskeletal disease, affecting up to 30% of people with psoriasis. Research into PsA pathogenesis has led to the development of targeted therapies, including Tumor Necrosis Factor inhibitors (TNF-i). Good response is only achieved by ~60% of patients leading to 'trial and error' drug management approaches, adverse reactions and increasing healthcare costs. Robust and well-validated biomarker identification, and subsequent development of sensitive and specific assays, would facilitate the implementation of a stratified approach into clinical care. This review will summarise potential genetic biomarkers for TNF-i (adalimumab, etanercept and infliximab) response that have been reported to date. It will also comment upon the importance of managing clinical confounders when understanding drug response prediction. Variants in multiple gene regions including TNF-A, FCGR2A, TNFAIP3, TNFR1/TNFR1A/TNFRSF1A, TRAIL-R1/TNFRSF10A, FCGR3A have been reported to correlate with TNF-i response at various levels of statistical significance in patients with PsA. However, results were often from heterogenous and underpowered cohorts and none are currently implemented into clinical practice. External validation of genetic biomarkers in large, well-documented cohorts is required, and assessment of the predictive value of combining multiple genetic biomarkers with clinical measures is essential to clinically embed pharmacogenomics into PsA drug management.

Pharmacogenomics in Asians: Differences and similarities with other human populations

INTRODUCTION

Various pharmacogenomic (PGx) variants differ widely in different ethnicities. and clinical outcomes associated with these variants may also be substantially varied. Literature was searched in different databases, i.e. PubMed, ScienceDirect, Web of Science, and PharmGKB, from inception to 30 June 2022 for this review.

AREAS COVERED

Certain PGx variants were distinctly varied in Asian populations compared to the other human populations, e.g. CYP2C19*2,*3,*17; CYP2C9*2,*3; CYP2D6*4,*5,*10,*41; UGT1A1*6,*28; HLA-B*15:02, HLA-B*15:21, HLA-B*58:01, and HLA-A*31:01. However, certain other variants do not vary greatly between Asian and other ethnicities, e.g. CYP3A5*3; ABCB1, and SLCO1B1*5. As evident in this review, the risk of major adverse cardiovascular events (MACE) was much stronger in Asian patients taking clopidogrel and who inherited the CYP2C19 loss-of-function alleles, e.g. CYP2C19*2 and*3, when compared to the western/Caucasian patients. Additionally, the risk of carbamazepine-induced severe cutaneous adverse drug reactions (SCARs) for the patients inheriting HLA-B*15:02 and HLA-B*15:21 alleles varied significantly between Asian and other ethnicities. In contrast, both Caucasian and Asian patients inheriting the SLCO1B1*5 variant possessed a similar magnitude of muscle toxicity, i.e. myopathy.

EXPERT OPINION

Asian countries should take measures toward expanding PGx research, as well as initiatives for the purposes of obtaining clinical benefits from this newly evolving and economically viable treatment model.

Pharmacogenetics of Anticancer Drugs: Clinical Response and Toxicity

Cancer is the most challenging disease for medical professionals to treat. The factors underlying the complicated situation include anticancer drug-associated toxicity, non-specific response, low therapeutic window, variable treatment outcomes, development of drug resistance, treatment complications, and cancer recurrence. The remarkable advancement in biomedical sciences and genetics, over the past few decades, however, is changing the dire situation. The discovery of gene polymorphism, gene expression, biomarkers, particular molecular targets and pathways, and drug-metabolizing enzymes have paved the way for the development and provision of targeted and individualized anticancer treatment. Pharmacogenetics is the study of genetic factors having the potential to affect clinical responses and pharmacokinetic and pharmacodynamic behaviors of drugs. This chapter emphasizes pharmacogenetics of anticancer drugs and its applications in improving treatment outcomes, selectivity, toxicity of the drugs, and discovering and developing personalized anticancer drugs and genetic methods for prediction of drug response and toxicity.

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

Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.

Identification of SNPs associated with methotrexate treatment outcomes in patients with early rheumatoid arthritis

Methotrexate is one of the cornerstones of rheumatoid arthritis (RA) therapy. Genetic factors or single nucleotide polymorphisms (SNPs) are responsible for 15%–30% of the variation in drug response. Identification of clinically effective SNP biomarkers for predicting methotrexate (MTX) sensitivity has been a challenge. The aim of this study was to explore the association between the disease related outcome of MTX treatment and 23 SNPs in 8 genes of the MTX pathway, as well as one pro-inflammatory related gene in RA patients naïve to MTX. Categorical outcomes such as Disease Activity Score (DAS)-based European Alliance of Associations for Rheumatology (EULAR) non-response at 4 months, The American College of Rheumatology and EULAR (ACR/EULAR) non-remission at 6 months, and failure to sustain MTX monotherapy from 12 to 24 months were assessed, together with continuous outcomes of disease activity, joint pain and fatigue. We found that the SNPs rs1801394 in the MTRR gene, rs408626 in DHFR gene, and rs2259571 in AIF-1 gene were significantly associated with disease activity relevant continuous outcomes. Additionally, SNP rs1801133 in the MTHFR gene was identified to be associated with improved fatigue. Moreover, associations with p values at uncorrected significance level were found in SNPs and different categorical outcomes: 1) rs1476413 in the MTHFR gene and rs3784864 in ABCC1 gene are associated with ACR/EULAR non-remission; 2) rs1801133 in the MTHFR gene is associated with EULAR response; 3) rs246240 in the ABCC1 gene, rs2259571 in the AIF-1 gene, rs2274808 in the SLC19A1 gene and rs1476413 in the MTHFR gene are associated with failure to MTX monotherapy after 12–24 months. The results suggest that SNPs in genes associated with MTX activity may be used to predict MTX relevant-clinical outcomes in patients with RA.

Pharmacogenomics of Methotrexate Pathway in Rheumatoid Arthritis Patients: Approach toward Personalized Medicine

Background: Methotrexate (MTX) is one of the most common medications used for rheumatoid arthritis (RA) treatment. Single-nucleotide polymorphisms (SNPs) could potentially predict variability in therapeutic outcomes. Aim: This study aims to assess the impact of SNPs in genes encoding for the MTX pathway for predicting clinical and therapeutic responses to MTX in a cohort of Egyptian patients with RA. Subjects and Methods: Data from 107 Egyptian RA patients (aged 44.4 ± 11.4 years) treated with MTX monotherapy, for a duration of 3.7 ± 3.3 years, were collected. Genotypes of 10 SNPs from four different genes were analyzed using the allelic discrimination PCR technique. Results: The ATIC rs3821353 G/T (p = 0.034) and the C/T and C/C of SLC19A1 rs7279445 (p = 0.0018) were associated with a non-response to MTX, while DHFR rs10072026 C/T and C/C were associated with a good response (p < 0.001). Carriers of the ATIC rs382135 3 G (p = 0.001) and ATIC rs4673990 G (p < 0.001) alleles were more likely to develop RA, while the SLC19A1 rs11702425 T (p < 0.001) and GGH rs12681874 T (p = 0.003) allele carriers were more likely to be protected against RA. Carriers of the ATIC rs4673990 A/G genotype (p < 0.001) were at risk of developing RA, while carriers of the following genotypes were mostly protected against RA: ATIC rs3821353 T/T (p < 0.001), ATIC rs3821353 G/G (p = 0.004), SLC19A1 rs11702425 T/T (p = 0.001), SLC19A1 rs11702425 C/T (p = 0.003), GGH rs12681874 C/T (p = 0.004) and GGH rs12681874 T/T (0.002). Conclusion: The genotyping of genes involved in the MTX pathway may be helpful to predict which RA patients will/will not benefit from MTX, and thus, may help to apply a personalized medicine approach in RA.

Physiologically based pharmacokinetic modelling to predict the pharmacokinetics of metoprolol in different CYP2D6 genotypes

Metoprolol, a selective β₁-adrenoreceptor blocking agent used in the treatment of hypertension, angina, and heart failure, is primarily metabolized by the CYP2D6 enzyme, which catalyzes α-hydroxylation and O-desmethylation. As CYP2D6 is genetically highly polymorphic and the enzymatic activity differs greatly depending on the presence of the mutant allele(s), the pharmacokinetic profile of metoprolol is highly variable depending on the genotype of CYP2D6. The aim of study was to develop the physiologically based pharmacokinetic (PBPK) model of metoprolol related to CYP2D6 genetic polymorphism for personalized therapy with metoprolol. For PBPK modelling, our previous pharmacogenomic data were used. To obtain kinetic parameters (K_m, V_max, and CL_int) of each genotype, the recombinant CYP enzyme of each genotype was incubated with metoprolol and metabolic rates were assayed. Based on these data, the PBPK model of metoprolol was developed and validated in different CYP2D6 genotypes using PK-Sim^® software. As a result, the input values for various parameters for the PBPK model were presented and the PBPK model successfully described the pharmacokinetics of metoprolol in each genotype group. The simulated values were within the acceptance criterion (99.998% confidence intervals) compared with observed values. The PBPK model developed in this study can be used for personalized pharmacotherapy with metoprolol in individuals of various races, ages, and CYP2D6 genotypes.

An Updated Review of Genetic Associations With Severe Adverse Drug Reactions: Translation and Implementation of Pharmacogenomic Testing in Clinical Practice

Adverse drug reactions (ADR) remain the major problems in healthcare. Most severe ADR are unpredictable, dose-independent and termed as type B idiosyncratic reactions. Recent pharmacogenomic studies have demonstrated the strong associations between severe ADR and genetic markers, including specific HLA alleles (e.g., HLA-B*15:02/HLA-B*57:01/HLA-A*31:01 for carbamazepine-induced severe cutaneous adverse drug reactions [SCAR], HLA-B*58:01 for allopurinol-SCAR, HLA-B*57:01 for abacavir-hypersensitivity, HLA-B*13:01 for dapsone/co-trimoxazole-induced SCAR, and HLA-A*33:01 for terbinafine-induced liver injury), drug metabolism enzymes (such as CYP2C9*3 for phenytoin-induced SCAR and missense variant of TPMT/NUDT15 for thiopurine-induced leukopenia), drug transporters (e.g., SLCO1B1 polymorphism for statin-induced myopathy), and T cell receptors (Sulfanilamide binding into the CDR3/Vα of the TCR 1.3). This mini review article aims to summarize the current knowledge of pharmacogenomics of severe ADR, and the potentially clinical use of these genetic markers for avoidance of ADR.

Comparison of Quenching Efficiencies in Long Triple-Labeled and Double-Labeled TaqMan Oligodeoxynucleotide Probes

Although triple labeling of molecular beacons has been documented to improve quenching efficiencies and studies generally assume similar benefits at long TaqMan probes, a limited number of works have studied this issue in TaqMan probes. We therefore prepared a series of long triple-labeled oligodeoxynucleotide probes with 6-carboxyfluorescein as a fluorophore at the 5'-end and BlackBerry (BBQ-650) or azaphthalocyanine quenchers at the 3'-end and in the intrastrand position and systematically compared their quenching efficiencies with those of the corresponding double-labeled probes including important control probes. A model polymerase chain reaction (PCR) assay enabled the determination of the quenching efficiencies of static and Förster resonance energy transfer (FRET) quenching in the target probes. The type of probe had no effect on the static quenching ability. Importantly, FRET quenching of double-labeled probes with a quencher at the 3'-end showed a statistically insignificant difference from the control probe without any quencher, indicating the need to shift the quencher closer to the fluorophore in long probes. Shortening the distance between the fluorophore and the quencher played a key role in FRET quenching, whereas the introduction of an additional quencher only slightly improved the quenching efficiency. BBQ-labeled probes had lower quenching efficiencies than azaphthalocyanine probes. The methodologies and relationships described above seem, however, to be universal and applicable to any quencher.

Overcome Drug Resistance in Cholangiocarcinoma: New Insight Into Mechanisms and Refining the Preclinical Experiment Models

Cholangiocarcinoma (CCA) is an aggressive tumor characterized by a poor prognosis. Therapeutic options are limited in patients with advanced stage of CCA, as a result of the intrinsic or acquired resistance to currently available chemotherapeutic agents, and the lack of new drugs entering into clinical application. The challenge in translating basic research to the clinical setting, caused by preclinical models not being able to recapitulate the tumor characteristics of the patient, seems to be an important reason for the lack of effective and specific therapies for CCA. So, there seems to be two ways to improve patient outcomes. The first one is developing the combination therapies based on a better understanding of the mechanisms contributing to the resistance to currently available chemotherapeutic agents. The second one is developing novel preclinical experimental models that better recapitulate the genetic and histopathological features of the primary tumor, facilitating the screening of new drugs for CCA patients. In this review, we discussed the evidence implicating the mechanisms underlying treatment resistance to currently investigated drugs, and the development of preclinical experiment models for CCA.

Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review

Conventional medicines optimisation interventions in people with multimorbidity and polypharmacy are complex and yet limited; a more holistic and integrated approach to healthcare delivery is required. Pharmacogenetics has potential as a component of medicines optimisation. Studies involving multi-medicine pharmacogenetics in adults with multimorbidity or polypharmacy, reporting on outcomes derived from relevant core outcome sets, were included in this systematic review. Narrative synthesis was undertaken to summarise the data; meta-analysis was inappropriate due to study heterogeneity. Fifteen studies of diverse design and variable quality were included. A small, randomised study involving pharmacist-led medicines optimisation, including pharmacogenetics, suggests this approach could have significant benefits for patients and health systems. However, due to study design heterogeneity and the quality of the included studies, it is difficult to draw generalisable conclusions. Further pragmatic, robust pharmacogenetics studies in diverse, real-world patient populations, are required to establish the benefit of multi-medicine pharmacogenetic screening on patient outcomes.

Pharmacist assessment of drug-gene interactions and drug-induced phenoconversion in major depressive disorder: a case report

BACKGROUND

Response to antidepressant therapy is highly variable among individuals. Pharmacogenomic (PGx) testing presents an opportunity to guide drug selection while optimizing therapy outcomes and/or decreasing the risk for toxicity.

CASE PRESENTATION

A patient with multiple comorbidities, including severe major depressive disorder (MDD), experienced adverse drug events and undesirable response to multiple antidepressant medications (i.e., bupropion, escitalopram, and venlafaxine). A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions as well as other clinical factors to provide recommendations for antidepressant therapy optimization.

CONCLUSION

This case highlights the importance of PGx testing and the key role of pharmacists in identifying and mitigating drug-related problems and optimizing drug therapy in patients with MDD.

KCNQ1 rs2237895 polymorphism is associated with the therapeutic response to sulfonylureas in Iranian type 2 diabetes mellitus patients

Background and Aims

Sulfonylureas are the most secondary prescribed oral anti-diabetic drug. Understanding its genetic role in pharmacodynamics can elucidate a considerable knowledge about personalized treatment in type 2 diabetes patients. This study aimed to assess the impact of KCNQ1 variants on sulfonylureas response among type 2 diabetes Iranian patients.

Methods and Results

100 patients were recruited who were under sulfonylureas therapy for six months. 50 responder and 50 non-responder patients were selected. KCNQ1 variants were determined by the RFLP method, and their role in treatment response was assessed retrospectively. Patients with rs2237895 CC and AC genotypes demonstrated a significant decrement in FBS and HbA1c after treatment over patients with AA genotypes (All P < 0.001). Compared to the A allele, the odds ratio for treatment success between carriers with rs2237895 C allele was 4.22-fold (P < 0.001). Patients with rs2237892 CT heterozygous genotype exhibit a higher reduction rate in HbA1c and FBS than CC homozygotes (P=0.064 and P=0.079, respectively). The rs2237892 T allele carriers showed an odds ratio equals to 2.83-fold over C allele carriers in the responder group compared to the non-responder group (p=0.081).

Conclusion

Findings suggest that the KCNQ1 rs2237895 polymorphism is associated with the sulfonylureas response on Iranian type 2 diabetes patients.

Frequencies of CYP2B6∗4,∗5, and ∗6 Alleles within an Iranian Population (Mazandaran)

Background

The human CYP2B subfamily consists of one functional gene (CYP2B6) and one pseudogene (CYP2B7P). Cytochrome P450 2B6 (CYP2B6) is a highly polymorphic enzyme that shows marked interindividual and interethnic variations. Currently, 38 alleles have been described, and some of the allelic variants have been associated with low enzyme activity. The aim of this study was to investigate the frequencies of CYP2B6^∗4, CYP2B6^∗5, and CYP2B6^∗6 alleles in the Mazani ethnic group among Iranian Population.

Methods

The study was conducted in 289 unrelated healthy volunteers. DNA was extracted from peripheral blood and analyzed by the PCR-RFLP protocol. The PCR product was digested with restriction enzymes and then separated using agarose gel electrophoresis.

Results

The frequency of CYP2B6^∗4, CYP2B6^∗5, and CYP2B6^∗6 in this study was 34.60%, 7.26%, and 34.54%, respectively.

Conclusion

The frequency of the CYP2B6^∗4 allele in the Mazani ethnic group was much higher (34.60%) than other population. The frequency of CYP2B6^∗6 (34.54%) also was higher than its frequency in other previously reported population. But the frequency of CYP2B6^∗5 in this study was lower than expected. These results will be useful in understanding the ethnic diversity in Iranian population and offer a preliminary basis for more rational use of drugs that are substrates for CYP2B6 in this population.

Cytochrome P450 Enzymes and Drug Metabolism in Humans

Human cytochrome P450 (CYP) enzymes, as membrane-bound hemoproteins, play important roles in the detoxification of drugs, cellular metabolism, and homeostasis. In humans, almost 80% of oxidative metabolism and approximately 50% of the overall elimination of common clinical drugs can be attributed to one or more of the various CYPs, from the CYP families 1–3. In addition to the basic metabolic effects for elimination, CYPs are also capable of affecting drug responses by influencing drug action, safety, bioavailability, and drug resistance through metabolism, in both metabolic organs and local sites of action. Structures of CYPs have recently provided new insights into both understanding the mechanisms of drug metabolism and exploiting CYPs as drug targets. Genetic polymorphisms and epigenetic changes in CYP genes and environmental factors may be responsible for interethnic and interindividual variations in the therapeutic efficacy of drugs. In this review, we summarize and highlight the structural knowledge about CYPs and the major CYPs in drug metabolism. Additionally, genetic and epigenetic factors, as well as several intrinsic and extrinsic factors that contribute to interindividual variation in drug response are also reviewed, to reveal the multifarious and important roles of CYP-mediated metabolism and elimination in drug therapy.

Comprehensive Parent-Metabolite PBPK/PD Modeling Insights into Nicotine Replacement Therapy Strategies

Background

Nicotine, the pharmacologically active substance in both tobacco and many electronic cigarette (e-cigarette) liquids, is responsible for the addiction that sustains cigarette smoking. With 8 million deaths worldwide annually, smoking remains one of the major causes of disability and premature death. However, nicotine also plays an important role in smoking cessation strategies.

Objectives

The aim of this study was to develop a comprehensive, whole-body, physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model of nicotine and its major metabolite cotinine, covering various routes of nicotine administration, and to simulate nicotine brain tissue concentrations after the use of combustible cigarettes, e-cigarettes, nicotine gums, and nicotine patches.

Methods

A parent–metabolite, PBPK/PD model of nicotine for a non-smoking and a smoking population was developed using 91 plasma and brain tissue concentration–time profiles and 11 heart rate profiles. Among others, cytochrome P450 (CYP) 2A6 and 2B6 enzymes were implemented, including kinetics for CYP2A6 poor metabolizers.

Results

The model is able to precisely describe and predict both nicotine plasma and brain tissue concentrations, cotinine plasma concentrations, and heart rate profiles. 100% of the predicted area under the concentration–time curve (AUC) and maximum concentration (C_max) values meet the twofold acceptance criterion with overall geometric mean fold errors of 1.12 and 1.15, respectively. The administration of combustible cigarettes, e-cigarettes, nicotine patches, and nicotine gums was successfully implemented in the model and used to identify differences in steady-state nicotine brain tissue concentration patterns.

Conclusions

Our PBPK/PD model may be helpful in further investigations of nicotine dependence and smoking cessation strategies. As the model represents the first nicotine PBPK/PD model predicting nicotine concentration and heart rate profiles after the use of e-cigarettes, it could also contribute to a better understanding of the recent increase in youth e-cigarette use.

Electronic supplementary material

The online version of this article (10.1007/s40262-020-00880-4) contains supplementary material, which is available to authorized users.

Variability of Pharmacogenomics Information in Drug Labels Approved by Different Agencies and Its Ethical Implications

AIMS

The aim of this study was to determine if there are discrepancies among various agency-approved labels for the same active ingredient and where the labels approved by the Turkish Medicines and Medical Devices Agency (TMMDA) stand regarding the inclusion of PGx and discuss these ethical implications.

BACKGROUND

The efficacy and safety of drugs can be improved by rational prescription and personalization of medicine for each patient. Pharmacogenomics information (PGx) in drug labels (DL) is one of the important tools for the personalization of medications because genetic differences may affect both drug efficacy and safety. Providing adequate PGx to patients has ethical implications.

OBJECTIVE

To evaluate PGx in the DLs approved by TMMDA and other national agencies provided by the Pharmacogenomics Knowledgebase.

METHODS

DL annotations from the Pharmacogenomics Knowledgebase and DLs approved by the TMMDA were analyzed according to information and action levels, which are "testing required", "testing recommended", "actionable", and "informative".

RESULTS

There are 381 drugs listed in PharmGKB drug label annotations with pharmacogenomics information and 278 of these have biomarkers. A total of 242 (63.5%) drugs are approved and available in Turkey. Of these, 207 (85.5%) contain the same information as in or similar to that in the labels approved by the other agencies. The presence and level of information varied among the DLs approved by different agencies. The inconsistencies may have an important effect on the efficacy and the safety of drugs.

CONCLUSION

These findings suggest a need for the standardization of PGx information globally because it may not only affect the efficacy and safety of medications but also essential ethical rules regarding patient rights by violating not sufficiently sharing all available information.

Efficacy of computational predictions of the functional effect of idiosyncratic pharmacogenetic variants

Background

Pharmacogenetic variation is important to drug responses through diverse and complex mechanisms. Predictions of the functional impact of missense pharmacogenetic variants primarily rely on the degree of sequence conservation between species as a primary discriminator. However, idiosyncratic or off-target drug-variant interactions sometimes involve effects that are peripheral or accessory to the central systems in which a gene functions. Given the importance of sequence conservation to functional prediction tools-these idiosyncratic pharmacogenetic variants may violate the assumptions of predictive software commonly used to infer their effect.

Methods

Here we exhaustively assess the effectiveness of eleven missense mutation functional inference tools on all known pharmacogenetic missense variants contained in the Pharmacogenomics Knowledgebase (PharmGKB) repository. We categorize PharmGKB entries into sub-classes to catalog likely off-target interactions, such that we may compare predictions across different variant annotations.

Results

As previously demonstrated, functional inference tools perform variably across the complete set of PharmGKB variants, with large numbers of variants incorrectly classified as 'benign'. However, we find substantial differences amongst PharmGKB variant sub-classes, particularly in variants known to cause off-target, type B adverse drug reactions, that are largely unrelated to the main pharmacological action of the drug. Specifically, variants associated with off-target effects (hence referred to as off-target variants) were most often incorrectly classified as 'benign'. These results highlight the importance of understanding the underlying mechanism of pharmacogenetic variants and how variants associated with off-target effects will ultimately require new predictive algorithms.

Conclusion

In this work we demonstrate that functional inference tools perform poorly on pharmacogenetic variants, particularly on subsets enriched for variants causing off-target, type B adverse drug reactions. We describe how to identify variants associated with off-target effects within PharmGKB in order to generate a training set of variants that is needed to develop new algorithms specifically for this class of variant. Development of such tools will lead to more accurate functional predictions and pave the way for the increased wide-spread adoption of pharmacogenetics in clinical practice.

The Central Role of Cytochrome P450 in Xenobiotic Metabolism-A Brief Review on a Fascinating Enzyme Family

Human Cytochrome P450 (CYP) enzymes constitute a superfamily of membrane-bound hemoproteins that are responsible for the metabolism of a wide variety of clinically, physiologically, and toxicologically important compounds. These heme-thiolate monooxygenases play a pivotal role in the detoxification of xenobiotics, participating in the metabolism of many structurally diverge compounds. This short-review is intended to provide a summary on the major roles of CYPs in Phase I xenobiotic metabolism. The manuscript is focused on eight main topics that include the most relevant aspects of past and current CYP research. Initially, (I) a general overview of the main aspects of absorption, distribution, metabolism, and excretion (ADME) of xenobiotics are presented. This is followed by (II) a background overview on major achievements in the past of the CYP research field. (III) Classification and nomenclature of CYPs is briefly reviewed, followed by (IV) a summary description on CYP's location and function in mammals. Subsequently, (V) the physiological relevance of CYP as the cornerstone of Phase I xenobiotic metabolism is highlighted, followed by (VI) reviewing both genetic determinants and (VI) nongenetic factors in CYP function and activity. The last topic of the review (VIII) is focused on the current challenges of the CYP research field.

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.

Vaccines are not one size fits all, just like medications: rotavirus vaccine study

The current global coronavirus disease 2019 pandemic has shown us once again how important vaccination is in controlling and preventing the spread of deadly diseases. Vaccinations are one of the most tried and tested public health measures aimed at the prevention and eventual eradication of various diseases. Many debilitating diseases like polio have been eradicated in countries like India due to effective vaccination strategies. Just like with any other public health initiative, there do exist various challenges for vaccination. Efficacy and correlate of protection studies are crucial in determining which vaccine works best. The rotavirus vaccine (ROTAVAC; Bharat Biotech International Ltd., Hyderabad, India) is one such example where efficacy seen in one geographical and ethnic population is not replicated elsewhere. This has prompted various researchers and pharmaceutical companies to think about customizing vaccines to the individual needs of a particular geographic and ethnic group. In this brief communication, we look at the rotavirus vaccination story and see how it laid down the idea for customized vaccination development and what the future of vaccine development looks like.

Total Value of Ownership and Overall Equipment Effectiveness analysis to evaluate the impact of automation on time and costs of therapeutic drug monitoring

Total Value of Ownership (TVO) and Overall Equipment Effectiveness (OEE) analysis are novel tools capable of monitoring and analyzing industrial processes by assessing the efficiency of the entire instrumental equipment and calculating instrument capacity utilization. Such integrated analysis, measuring quality indicators of the testing process, could also provide new perspectives and methodologies for the workflow organization of clinical laboratories. In this study, TVO and OEE were employed for the evaluation of two different configurations of a therapeutic drug monitoring sector, comparing the results obtained for immunosuppressant (ISD) and anti-epileptic drugs (AED) analysis as well as checking their quantitative performance in terms of limit of quantification, accuracy and precision. TVO analysis was performed for ISDs, including the Total Direct Labor Time, Total Cycle Time and Turnaround Time as well as cost of testing. Instruments' performance and workload were assessed using OEE indicator, studying Availability, Performance and Quality factors. Total Cycle Time for a batch was 3.55 h, decreasing of 1.5 h in the new setting where personnel are engaged for 0.98 h, 25% of total testing time. The calculated cost per sample was 6.60 euro. Availability values were significantly higher for automated sample-handling system and ISDs analysis by LC-MS. Higher Performance values were obtained for LC-MS system for AED and other TDM. Quality values were >0.94 for all instruments. TVO and OEE proved to be applicable to clinical laboratory environment, quantifying benefits and costs of newly developed semi-automated therapeutic drug monitoring sector. This novel approach based on an integrated analysis may help activity planning and quality improvement and could be used in the future for benchmarking progress as a product/process comparison tool in other laboratory fields.

Drug-Metabolizing Cytochrome P450 Enzymes Have Multifarious Influences on Treatment Outcomes

Drug metabolism is a critical process for the removal of unwanted substances from the body. In humans, approximately 80% of oxidative metabolism and almost 50% of the overall elimination of commonly used drugs can be attributed to one or more of various cytochrome P450 (CYP) enzymes from CYP families 1-3. In addition to the basic metabolic effects for elimination, CYP enzymes in vivo are capable of affecting the treatment outcomes in many cases. Drug-metabolizing CYP enzymes are mainly expressed in the liver and intestine, the two principal drug oxidation and elimination organs, where they can significantly influence the drug action, safety, and bioavailability by mediating phase I metabolism and first-pass metabolism. Furthermore, CYP-mediated local drug metabolism in the sites of action may also have the potential to impact drug response, according to the literature in recent years. This article underlines the ability of CYP enzymes to influence treatment outcomes by discussing CYP-mediated diversified drug metabolism in primary metabolic sites (liver and intestine) and typical action sites (brain and tumors) according to their expression levels and metabolic activity. Moreover, intrinsic and extrinsic factors of personal differential CYP phenotypes that contribute to interindividual variation of treatment outcomes are also reviewed to introduce the multifarious pivotal role of CYP-mediated metabolism and clearance in drug therapy.

Characterization of cytochrome P450 (CYP) 2D6 drugs as substrates of human organic cation transporters and multidrug and toxin extrusion proteins

BACKGROUND AND PURPOSE

The metabolic activity of cytochrome P450 (CYP) 2D6 is highly variable and CYP2D6 genotypes insufficiently explain the extensive and intermediate metabolic phenotypes, limiting the prediction of drug response plus adverse drug reactions. Since CYP2D6 prototypic substrates are positively charged, the aim of this study was to evaluate the organic cation transporters (OCTs) and multidrug and toxin extrusion proteins (MATEs) as potential contributors to the variability of CYP2D6 hydroxylation of debrisoquine, dextromethorphan, diphenhydramine, perhexiline and sparteine.

EXPERIMENTAL APPROACH

OCT1/SLC22A1-, OCT2/SLC22A2-, OCT3/SLC22A3-, MATE1/SLC47A1-, and MATE2K/SLC47A2-overexpressing cell lines were used to investigate the transport of the selected drugs. Individuals from a study cohort, well defined with respect to CYP2D6 genotype and sparteine pharmacokinetics, were genotyped for the common OCT1 variants rs12208357 (OCT1-R61C), rs34130495 (OCT1-G401S), rs202220802 (OCT1-Met420del), rs34059508 (OCT1-G465R), OCT2 variant rs316019 (OCT2-A270S) and MATE1 variant rs2289669. Sparteine pharmacokinetics was stratified according to CYP2D6 and OCT1, OCT2 or MATE1 genotype.

KEY RESULTS

OCTs and MATE1 transport sparteine and debrisoquine with high affinity in vitro, but OCT- and MATE1-dependent transport of dextromethorphan, diphenhydramine and perhexiline was not detected. Sparteine and debrisoquine transport depends on OCT1 genotype; however, sparteine pharmacokinetics is independent from OCT1 genotype.

CONCLUSIONS AND IMPLICATIONS

Some drugs that are substrates of CYP2D6 are also substrates of OCTs and MATE1, suggesting overlapping specificities. Variability in sparteine hydroxylation in extensive and intermediate metabolizers cannot be explained by OCT1 genetic variants indicating presence of other factors. Dose-dependent toxicities of dextromethorphan, diphenhydramine and perhexiline appear to be independent from OCTs and MATEs.

Expression and Possible Molecular Mechanisms of microRNA-205-5p in Patients With Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent malignancy worldwide, with high incidence and poor survival rates. Increased expression of microRNA-205-5p (miR-205-5p) may influence the outcomes of HNSCC, but the identities of miR-205-5p target genes and the potential signaling pathways related to HNSCC remain unclear. RT-qPCR was used to detect the expression levels of miR-205-5p in the plasma of patients with HNSCC. We also performed a meta-analysis using data from relevant literature, and the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases to evaluate the expression level of miR-205-5p in HNSCC. Next, we predicted the potential miR-205-5p target genes in HNSCC. We also used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for enrichment analyses adapted to investigate the dynamics and possible mechanisms of miR-205-5p in HNSCC. Lastly, we predicted the potential miR-205-5p target genes by evaluating their expression level and using Spearman analysis. Expression of miR-205-5p was higher in HNSCC tissues compared to normal unafflicted tissue samples (P < 0.05), and the corresponding summary receiver operating characteristic (sROC) was 0.82.The pooled sensitivity, specificity, PLR, NLR, and DOR values were 0.78 (95% CI: 0.75-0.81), 0.67 (95% CI: 0.60-0.73), 2.34 (95% CI: 1.45-3.76), 0.34 (95% CI: 0.19-0.60), and 8.16 (95% CI: 4.01-16.64), respectively. Based on GO and KEGG analyses, we found that miR-205-5p was correlated with the progression of HNSCC through association with signaling pathways, including the drug metabolism-cytochrome P450 pathway. Analysis of the target genes revealed that flavin-containing monooxygenase isoform 2 (FMO2) and alcohol dehydrogenase 1B (ADH1B) may be important targets of miR-205-5p. In summary, miR-205-5p may have a significant role in the prognosis of HNSCC and may serve as a potential biomarker in HNSCC.

Drug-Drug Interactions Involving Intestinal and Hepatic CYP1A Enzymes

Cytochrome P450 (CYP) 1A enzymes are considerably expressed in the human intestine and liver and involved in the biotransformation of about 10% of marketed drugs. Despite this doubtless clinical relevance, CYP1A1 and CYP1A2 are still somewhat underestimated in terms of unwanted side effects and drug–drug interactions of their respective substrates. In contrast to this, many frequently prescribed drugs that are subjected to extensive CYP1A-mediated metabolism show a narrow therapeutic index and serious adverse drug reactions. Consequently, those drugs are vulnerable to any kind of inhibition or induction in the expression and function of CYP1A. However, available in vitro data are not necessarily predictive for the occurrence of clinically relevant drug–drug interactions. Thus, this review aims to provide an up-to-date summary on the expression, regulation, function, and drug–drug interactions of CYP1A enzymes in humans.

Development of a Pharmacogenetic Lab-on-Chip Assay Based on the In-Check Technology to Screen for Genetic Variations Associated to Adverse Drug Reactions to Common Chemotherapeutic Agents

BACKGROUND

Antineoplastic agents represent the most common class of drugs causing Adverse Drug Reactions (ADRs). Mutant alleles of genes coding for drug-metabolizing enzymes are the best studied individual risk factors for these ADRs. Although the correlation between genetic polymorphisms and ADRs is well-known, pharmacogenetic tests are limited to centralized laboratories with expensive or dedicated instrumentation used by specialized personnel. Nowadays, DNA chips have overcome the major limitations in terms of sensibility, specificity or small molecular detection, allowing the simultaneous detection of several genetic polymorphisms with time and costs-effective advantages. In this work, we describe the design of a novel silicon-based lab-on-chip assay able to perform low-density and high-resolution multi-assay analysis (amplification and hybridization reactions) on the In-Check platform.

METHODS

The novel lab-on-chip was used to screen 17 allelic variants of three genes associated with adverse reactions to common chemotherapeutic agents: DPYD (Dihydropyrimidine dehydrogenase), MTHFR (5,10-Methylenetetrahydrofolate reductase) and TPMT (Thiopurine S-methyltransferase).

RESULTS

Inter- and intra assay variability were performed to assess the specificity and sensibility of the chip. Linear regression was used to assess the optimal hybridization temperature set at 52 °C (R2 ≈ 0.97). Limit of detection was 50 nM.

CONCLUSIONS

The high performance in terms of sensibility and specificity of this lab-on-chip supports its further translation to clinical diagnostics, where it may effectively promote precision medicine.

Treatment Response Biomarkers in Anxiety Disorders: From Neuroimaging to Neuronally-Derived Extracellular Vesicles and Beyond

Multiple and diverse psychotherapeutic or psychopharmacologic treatments effectively reduce symptoms for many patients with anxiety disorders, but the trajectory and magnitude of response vary considerably. This heterogeneity of treatment response has invigorated the search for biomarkers of treatment response in anxiety disorders, across the lifespan. In this review, we summarize evidence for biomarkers of treatment response in children, adolescents and adults with generalized, separation and social anxiety disorders as well as panic disorder. We then discuss the relationship between these biomarkers of treatment response and the pathophysiology of anxiety disorders. Finally, we provide context for treatment response biomarkers of the future, including neuronally-derived extracellular vesicles in anxiety disorders and discuss challenges that must be overcome prior to the debut of treatment response biomarkers in the clinic. A number of promising treatment response biomarkers have been identified, although there is an urgent need to replicate findings and to identify which biomarkers might guide clinicians in selecting from available treatments rather than just simply identifying patients who may be less likely to respond to a given intervention.

Pharmacogenomic Biomarkers and Their Applications in Psychiatry

Realizing the promise of precision medicine in psychiatry is a laudable and beneficial endeavor, since it should markedly reduce morbidity and mortality and, in effect, alleviate the economic and social burden of psychiatric disorders. This review aims to summarize important issues on pharmacogenomics in psychiatry that have laid the foundation towards personalized pharmacotherapy and, in a broader sense, precision medicine. We present major pharmacogenomic biomarkers and their applications in a variety of psychiatric disorders, such as depression, attention-deficit/hyperactivity disorder (ADHD), narcolepsy, schizophrenia, and bipolar disorder. In addition, we extend the scope into epilepsy, since antiepileptic drugs are widely used to treat psychiatric disorders, although epilepsy is conventionally considered to be a neurological disorder.

A Review of the Important Role of CYP2D6 in Pharmacogenomics

Cytochrome P450 2D6 (CYP2D6) is a critical pharmacogene involved in the metabolism of ~20% of commonly used drugs across a broad spectrum of medical disciplines including psychiatry, pain management, oncology and cardiology. Nevertheless, CYP2D6 is highly polymorphic with single-nucleotide polymorphisms, small insertions/deletions and larger structural variants including multiplications, deletions, tandem arrangements, and hybridisations with non-functional CYP2D7 pseudogenes. The frequency of these variants differs across populations, and they significantly influence the drug-metabolising enzymatic function of CYP2D6. Importantly, altered CYP2D6 function has been associated with both adverse drug reactions and reduced drug efficacy, and there is growing recognition of the clinical and economic burdens associated with suboptimal drug utilisation. To date, pharmacogenomic clinical guidelines for at least 48 CYP2D6-substrate drugs have been developed by prominent pharmacogenomics societies, which contain therapeutic recommendations based on CYP2D6-predicted categories of metaboliser phenotype. Novel algorithms to interpret CYP2D6 function from sequencing data that consider structural variants, and machine learning approaches to characterise the functional impact of novel variants, are being developed. However, CYP2D6 genotyping is yet to be implemented broadly into clinical practice, and so further effort and initiatives are required to overcome the implementation challenges and deliver the potential benefits to the bedside.

Genotype by environment interaction for gene expression in Drosophila melanogaster

The genetics of phenotypic responses to changing environments remains elusive. Using whole-genome quantitative gene expression as a model, here we study how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed in different environments (25 °C and 18 °C). We find a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increases at 18 °C relative to 25 °C for most genes that have a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments are shared and have similar effects, analysis of the environment-specific eQTLs reveals enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks are highly conserved across environments. Genes with higher network connectivity are under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

Repurposing Drugs for COVID-19: Pharmacokinetics and Pharmacogenomics of Chloroquine and Hydroxychloroquine

Background

A new coronavirus SARS-CoV-2 has been identified as the etiological agent of the severe acute respiratory syndrome, COVID-19, the source and cause of the 2019–20 coronavirus pandemic. Hydroxychloroquine and chloroquine have gathered extraordinary attention as therapeutic candidates against SARS-CoV-2 infections. While there is growing scientific data on the therapeutic effect, there is also concern for toxicity of the medications. The therapy of COVID-19 by hydroxychloroquine and chloroquine is off-label. Studies to analyze the personalized effect and safety are lacking.

Methods

A review of the literature was performed using Medline/PubMed/Embase database. A variety of keywords were employed in keyword/title/abstract searches. The electronic search was followed by extensive hand searching using reference lists from the identified articles.

Results

A total of 126 results were obtained after screening all sources. Mechanisms underlying variability in drug concentrations and therapeutic response with chloroquine and hydroxychloroquine in mediating beneficial and adverse effects of chloroquine and hydroxychloroquine were reviewed and analyzed. Pharmacogenomic studies from various disease states were evaluated to elucidate the role of genetic variation in drug response and toxicity.

Conclusion

Knowledge of the pharmacokinetics and pharmacogenomics of chloroquine and hydroxychloroquine is necessary for effective and safe dosing and to avoid treatment failure and severe complications.

Tri-Allelic Haplotypes Determine and Differentiate Functionally Normal Allele CYP2D6*2 and Impaired Allele CYP2D6*41

CYP2D6 metabolizes 20-25% of all clinically used drugs and its complex genetic polymorphism is a major determinant of drug safety and efficacy. We investigated the basis for the functional difference between the two common alleles *2 (g.2851C>T + g.4181G>C, normal function) and *41 (additional intronic g.2989G>A, reduced function). A recently reported far-distant enhancer polymorphism rs5758550A/G linked to *2 has been suggested to play a decisive role. Genotyping of two white cohorts confirmed strong linkage of rs5758550G to *2, whereas no influence was found on metabolic ratio of sparteine or hepatic expression. Genomic plasmid constructs carrying individual variants or combinations thereof were expressed in COS1 and Huh7 cells. Both g.2851C>T(R296C) and g.2989G>A reduced enzyme activity and protein levels similarly by ~ 50-65% compared to reference (*1), whereas the double variant had only ~ 20% activity. Although the unexpected loss of function caused by g.2851C>T was compensated by g.4181G>C (mimicking the EM-phenotype of *2), the additional loss of function due to intronic g.2989G>A in the triple variant was not compensated (mimicking the IM-phenotype of *41). We also confirmed increased erroneous splicing in carriers of g.2989G>A but not of g.2851C>T as a likely explanation for the impaired function of *41. In conclusion, our data demonstrate g.2989G>A as causal variant of impaired allele CYP2D6*41 whereas triple-haplotypes have to be considered to explain the functional difference between *2 and *41. These data are important for genotyping strategies and clinical implementation of CYP2D6 pharmacogenetics.