Pharmacogenomics: translating functional genomics into rational therapeutics

3D spheroid HepaRG and fluorescent biphasic tracer for CYP3A4-mediated antibiotic interaction monitoring in sepsis

Cytochrome P450 3A4 (CYP3A4) is a crucial enzyme in the metabolism of xenobiotics, particularly in drug metabolism interactions (DDIs), making it a significant factor in clinical drug use. However, current assay techniques are both laborious and costly, making it difficult to construct a high-throughput monitoring method that can be used in conjunction with the clinic. This poses certain safety hazards for drug combination. Therefore, it is crucial to develop a synchronized monitoring method for the inhibition and induction of CYP3A4. In this study, we utilized 3D culture technology to develop a HepaRG cells spheroid model. The CYP450 and transporter expression, the albumin secretion, and urea synthesis capacity characteristics were analyzed. The NEN probe was utilized as a tracer molecule for CYP3A4. The fluorescence intensity of metabolites was characterized by laser confocal technique to determine the inhibition and expression of CYP3A4 in the HepaRG cell spheroid model by the antibiotics for sepsis. The results indicate that the HepaRG sphere model successfully possessed the physiological phenotype of the liver, which could be used for drug interaction monitoring. Through positive drug testing, NEN probe was able to achieve bidirectional characterization of CYP3A4 induction and inhibition. The monitoring method described in this paper was successfully applied to drug interaction monitoring of commonly used antibiotics in sepsis patients, which is a convenient and rapid monitoring method. The proposed method offers a new strategy for monitoring CYP3A4-mediated drug-drug interactions with a high-throughput assay, which will help to improve the safety of clinical drug combination.

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.

Development and Evaluation of Ontogeny Functions of the Major UDP-Glucuronosyltransferase Enzymes to Underwrite Physiologically Based Pharmacokinetic Modeling in Pediatric Populations

Uridine 5'-diphospho-glucuronosyltransferases (UGTs) demonstrate variable expression in the pediatric population. Thus, understanding of age-dependent maturation of UGTs is critical for accurate pediatric pharmacokinetics (PK) prediction of drugs that are susceptible for glucuronidation. Ontogeny functions of major UGTs have been previously developed and reported. However, those ontogeny functions are based on in vitro data (i.e., enzyme abundance, in vitro substrate activity, and so on) and therefore, may not translate to in vivo maturation of UGTs in the clinical setting. This report describes meta-analysis of the literature to develop and compare ontogeny functions for 8 primary UGTs (UGT1A1, UGT1A4, UGT1A6, UGT1A9, UGT2B7, UGT2B10, UGT2B15, and UGT2B17) based on published in vitro and in vivo studies. Once integrated with physiologically based pharmacokinetics modeling models, in vivo activity-based ontogeny functions demonstrated somewhat greater prediction accuracy (mean squared error, MSE: 0.05) compared to in vitro activity (MSE: 0.104) and in vitro abundance-based ontogeny functions (MSE: 0.129).

Aging precisely: Precision medicine through the lens of an older adult

Precision medicine presents an opportunity to use novel, data-driven strategies to improve patient care. The field of precision medicine has undergone many advancements over the past few years. It has moved beyond incorporation of individualized genetic risk into medical decision-making to include multiple other factors such as unique social, demographic, behavioral, and clinical characteristics. Geriatric medicine stands to benefit heavily from the integration of precision medicine into its standard practices. Older adults, compared with other populations, have high clinical and biological heterogeneity that can alter the risks and benefits of different approaches to patient care. These factors have not been routinely considered previously by geriatricians. Yet, geriatricians' ability to address older adults' baseline heterogeneity is increasingly recognized as a cornerstone of delivering quality care in a geriatric medical practice. Given the shared focus of individualized decision-making, precision medicine is a natural fit for geriatric medicine. This manuscript provides, via cases and discussion, examples that illustrate how precision medicine can improve the care of our older patients today. We will share specific and existing tools and evidence, and review the existing multilevel barriers to further incorporate and implement these tools into clinical practice. We propose methods to address these barriers and to help realize the full potential of precision medicine for the care of older adults. We conclude with a brief discussion of potential future directions of research of precision medicine in the care of older adults.

Causal machine learning for predicting treatment outcomes

Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of drugs. A key benefit of causal ML is that it allows for estimating individualized treatment effects, so that clinical decision-making can be personalized to individual patient profiles. Causal ML can be used in combination with both clinical trial data and real-world data, such as clinical registries and electronic health records, but caution is needed to avoid biased or incorrect predictions. In this Perspective, we discuss the benefits of causal ML (relative to traditional statistical or ML approaches) and outline the key components and steps. Finally, we provide recommendations for the reliable use of causal ML and effective translation into the clinic.

Pharmacogenomics in Clinical Practice for Older People

Older people are over-represented among individuals that experience adverse drug reactions (ADR) and adverse drug events (ADE). Furthermore, older people are over-represented among individuals that visit emergency departments and are hospitalized because of ADRs. Moreover, older people are overrepresented among those who suffer ADEs while hospitalized. Finally, older people are among those most likely to have an anaphylactic response to prescription medications. Therefore, older people are prime candidates for efforts aimed at optimizing pharmacotherapeutic outcomes. Pharmacogenomics is an approach of using genetic data to optimize pharmacotherapeutic outcomes. Over the last two decades, pharmacogenomics grew from research initiatives into the current environment of pharmacogenomics implementation. Specifically, implementing pharmacogenomics into clinical settings or within health care systems has proven beneficial in optimizing pharmacotherapeutic outcomes. Therefore, pharmacists focused on optimizing pharmacotherapeutic outcomes for older people should be aware of the approaches to and resources available for implementing pharmacogenomics. KEY WORDS: Drug labeling biomarkers, Genes, Older adults, Pharmacogenomics.

Impact of pharmacogenomic profiles on post-surgical pain following laparotomy for gynecologic pathology

OBJECTIVES

The aim of this prospective study was to compare perioperative opioid use in women by status of CYP2D6, a highly polymorphic pharmacogene relevant to opioid metabolism.

METHODS

Patients undergoing laparotomy were prospectively recruited and provided a preoperative saliva swab for a pharmacogenomic (PGx) gene panel. Postoperative opioid usage and pain scores were evaluated via chart review and a phone survey. Pharmacogenes known to be relevant to opioid metabolism were genotyped, and opioid metabolizing activity predicted by CYP2D6 genotyping. Patient and procedural factors were compared using Fisher's exact and Kruskal-Wallis tests.

RESULTS

The 96 enrolled patients were classified as ultra-rapid (N = 3, 3%), normal (58, 60%), intermediate (27, 28%), and poor (8, 8%) opioid metabolizers. There was no difference in surgical complexity across CYP2D6 categories (p = 0.61). Morphine Milligram Equivalents (MME) consumed during the first 24 h after peri-operative suite exit were significantly different between groups: ultrarapid metabolizers had the highest median MME (75, IQR 45-88) compared to the other three groups (normal metabolizers 23 [8-45], intermediate metabolizers 48 [20-63], poor metabolizers 31 [12-53], p = 0.03). Opioid requirements were clinically greater in ultrarapid metabolizers during the second 24 h and last 24 h but were statistically similar (p = 0.07). There was no difference in MME prescribed at discharge (p = 0.22) or patient satisfaction with pain control (p = 0.64) between groups.

CONCLUSIONS

A positive association existed between increased CYP2D6 activity and in-hospital opioid requirements, especially in the first 24 h after surgery. This provides important information to further individualize opioid prescriptions for patients undergoing laparotomy for gynecologic pathology.

Cannabinoid-Induced Inhibition of Morphine Glucuronidation and the Potential for In Vivo Drug-Drug Interactions

Opioids are commonly prescribed for the treatment of chronic pain. Approximately 50% of adults who are prescribed opioids for pain co-use cannabis with their opioid treatment. Morphine is primarily metabolized by UDP-glucuronosyltransferase (UGT) 2B7 to an inactive metabolite, morphine-3-glucuronide (M3G), and an active metabolite, morphine-6-glucuronide (M6G). Previous studies have shown that major cannabis constituents including Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) inhibit major UGT enzymes. To examine whether cannabinoids or their major metabolites inhibit morphine glucuronidation by UGT2B7, in vitro assays and mechanistic static modeling were performed with these cannabinoids and their major metabolites including 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC), 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (11-COOH-THC), 7-hydroxy-cannabidiol (7-OH-CBD), and 7-carboxy-cannabidiol (7-COOH-CBD). In vitro assays with rUGT-overexpressing microsomes and human liver microsomes showed that THC and CBD and their metabolites inhibited UGT2B7-mediated morphine metabolism, with CBD and THC exhibiting the most potent Ki,u values (0.16 µM and 0.37 µM, respectively). Only 7-COOH-CBD exhibited no inhibitory activity against UGT2B7-mediated morphine metabolism. Static mechanistic modeling predicted an in vivo drug-drug interaction between morphine and THC after inhaled cannabis, and between THC, CBD, and 7-OH-CBD after oral consumption of cannabis. These data suggest that the co-use of these agents may lead to adverse drug events in humans.

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

Acceleration of infectious disease drug discovery and development using a humanized model of drug metabolism

A key step in drug discovery, common to many disease areas, is preclinical demonstration of efficacy in a mouse model of disease. However, this demonstration and its translation to the clinic can be impeded by mouse-specific pathways of drug metabolism. Here, we show that a mouse line extensively humanized for the cytochrome P450 gene superfamily ("8HUM") can circumvent these problems. The pharmacokinetics, metabolite profiles, and magnitude of drug-drug interactions of a test set of approved medicines were in much closer alignment with clinical observations than in wild-type mice. Infection with Mycobacterium tuberculosis, Leishmania donovani, and Trypanosoma cruzi was well tolerated in 8HUM, permitting efficacy assessment. During such assessments, mouse-specific metabolic liabilities were bypassed while the impact of clinically relevant active metabolites and DDI on efficacy were well captured. Removal of species differences in metabolism by replacement of wild-type mice with 8HUM therefore reduces compound attrition while improving clinical translation, accelerating drug discovery.

Mechanism Underlying Conflicting Drug-Drug Interaction Between Aprepitant and Voriconazole via Cytochrome P450 3A4-Mediated Metabolism

Background

Voriconazole is an antifungal drug for which therapeutic monitoring is recommended to prevent side effects. Temporary administration of the antiemetic drug fosaprepitant remarkably decreases the plasma concentration of voriconazole from the therapeutic range. The ratio of the major metabolite voriconazole N-oxide to voriconazole exceeded that at any other time for a patient who started chemotherapy during voriconazole therapy. We attributed this unpredictable result to cytochrome P450 3A4 induced by aprepitant that was converted from fosaprepitant in vivo.

Methods

Concentrations of voriconazole and voriconazole N-oxide were measured using liquid chromatography-mass spectrometry/mass spectrometry in primary human hepatocytes after incubation with aprepitant. Aprepitant suppressed voriconazole N-oxide formation within 24 h, followed by a continuous increase. Levels of drug-metabolizing cytochrome P450 mRNA were measured using real-time PCR in primary human hepatocytes incubated with aprepitant.

Results

Cytochrome P450 3A4 and 2C9 mRNA levels increased ~4- and 2-fold, respectively, over time. Cytochrome P450 3A4 induction was confirmed using reporter assays. We also assessed L-755446, a major metabolite of aprepitant that lacks a triazole ring. Both compounds dose-dependently increased reporter activity; however, induction by L-755446 was stronger than that by aprepitant.

Conclusion

These results indicate that aprepitant initially inhibited voriconazole metabolism via its triazole ring and increased cytochrome P450 3A4 induction following L-755446 formation. The decrease in plasma voriconazole concentration 7 days after fosaprepitant administration was mainly attributed to cytochrome P450 3A4 induction by L-755446.

Relevance of pharmacogenetics and pharmacogenomics in veterinary clinical practice: A review

The recent advances in high-throughput next-generation sequencing technologies have heralded the arrival of the Big Data era. As a result, the use of pharmacogenetics in drug discovery and individualized drug therapy has transformed the field of precision medicine. This paradigm shift in drug development programs has effectively reshaped the old drug development practices, which were primarily concerned with the physiological status of patients for drug development. Pharmacogenomics bridges the gap between pharmacodynamics and pharmacokinetics, advancing current diagnostic and treatment strategies and enabling personalized and targeted drug therapy. The primary goals of pharmacogenetic studies are to improve drug efficacy and minimize toxicities, to identify novel drug targets, to estimate drug dosage for personalized medicine, and to incorporate it as a routine diagnostic for disease susceptibility. Although pharmacogenetics has numerous applications in individualized drug therapy and drug development, it is in its infancy in veterinary medicine. The objective of this review is to present an overview of historical landmarks, current developments in various animal species, challenges and future perspectives of genomics in drug development and dosage optimization for individualized medicine in veterinary subjects.

PANCDR: precise medicine prediction using an adversarial network for cancer drug response

Pharmacogenomics aims to provide personalized therapy to patients based on their genetic variability. However, accurate prediction of cancer drug response (CDR) is challenging due to genetic heterogeneity. Since clinical data are limited, most studies predicting drug response use preclinical data to train models. However, such models might not be generalizable to external clinical data due to differences between the preclinical and clinical datasets. In this study, a Precision Medicine Prediction using an Adversarial Network for Cancer Drug Response (PANCDR) model is proposed. PANCDR consists of two sub-models, an adversarial model and a CDR prediction model. The adversarial model reduces the gap between the preclinical and clinical datasets, while the CDR prediction model extracts features and predicts responses. PANCDR was trained using both preclinical data and unlabeled clinical data. Subsequently, it was tested on external clinical data, including The Cancer Genome Atlas and brain tumor patients. PANCDR outperformed other machine learning models in predicting external test data. Our results demonstrate the robustness of PANCDR and its potential in precision medicine by recommending patient-specific drug candidates. The PANCDR codes and data are available at https://github.com/DMCB-GIST/PANCDR.

Assessment of Substrate Status of Drugs Metabolized by Polymorphic Cytochrome P450 (CYP) 2 Enzymes: An Analysis of a Large-Scale Dataset

BACKGROUND

The analysis of substrates of polymorphic cytochrome P450 (CYP) enzymes is important information to enable drug-drug interactions (DDIs) analysis and the relevance of pharmacogenetics in this context in large datasets. Our aim was to compare different approaches to assess the substrate properties of drugs for certain polymorphic CYP2 enzymes.

METHODS

A standardized manual method and an automatic method were developed and compared to assess the substrate properties for the metabolism of drugs by CYP2D6, 2C9, and 2C19. The automatic method used a matching approach to three freely available resources. We applied the manual and automatic methods to a large real-world dataset deriving from a prospective multicenter study collecting adverse drug reactions in emergency departments in Germany (ADRED).

RESULTS

In total, 23,878 medication entries relating to 895 different drugs were analyzed in the real-world dataset. The manual method was able to assess 12.2% (n = 109) of drugs, and the automatic method between 12.1% (n = 109) and 88.9% (n = 796), depending on the resource used. The CYP substrate classifications demonstrated moderate to almost perfect agreements for CYP2D6 and CYP2C19 (Cohen's Kappa (κ) 0.48-0.90) and fair to moderate agreements for CYP2C9 (κ 0.20-0.48).

CONCLUSION

A closer look at different classifications between methods revealed that both methods are prone to error in different ways. While the automated method excels in time efficiency, completeness, and actuality, the manual method might be better able to identify CYP2 substrates with clinical relevance.

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors

Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essential to avoiding potentially harmful pharmacokinetic drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Despite the development of several CYP inhibitor prediction models, the primary approach for screening CYP inhibitors still relies on experimental methods. This might stem from the limitations of existing models, which only provide deterministic classification outcomes instead of precise inhibition intensity (e.g., IC50) and often suffer from inadequate prediction reliability. To address this challenge, we propose an uncertainty-guided regression model to accurately predict the IC50 values of anti-CYP3A4 activities. First, a comprehensive data set of CYP3A4 inhibitors was compiled, consisting of 27,045 compounds with classification labels, including 4395 compounds with explicit IC50 values. Second, by integrating the predictions of the classification model trained on a larger data set and introducing an evidential uncertainty method to rank prediction confidence, we obtained a high-precision and reliable regression model. Finally, we use the evidential uncertainty values as a trustworthy indicator to perform a virtual screening of an in-house compound set. The in vitro experiment results revealed that this new indicator significantly improved the hit ratio and reduced false positives among the top-ranked compounds. Specifically, among the top 20 compounds ranked with uncertainty, 15 compounds were identified as novel CYP3A4 inhibitors, and three of them exhibited activities less than 1 μM. In summary, our findings highlight the effectiveness of incorporating uncertainty in compound screening, providing a promising strategy for drug discovery and development.

The roles of CYP2C19 and CYP3A4 in the in vitro metabolism of β-eudesmol in human liver: Reaction phenotyping and enzyme kinetics

β-eudesmol is a major bioactive component of Atractylodes lancea (AL). AL has been developed as the capsule formulation of standardized AL extract for treating cholangiocarcinoma (CCA). However, the complex constituents of herbal products increase the risk of adverse drug interactions. β-eudesmol has demonstrated inhibitory effects on rCYP2C19 and rCYP3A4 in the previous research. This study aimed to identify the cytochrome P450 (CYP) isoforms responsible for the metabolism of β-eudesmol and determine the enzyme kinetic parameters and the metabolic stability of β-eudesmol metabolism in the microsomal system. Reaction phenotyping using human recombinant CYPs (rCYPs) and selective chemical inhibitors of CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 was performed, and enzyme kinetics and metabolic stability were investigated using human liver microsome (HLM). The results suggest that CYP2C19 and CYP3A4 play significant roles in β-eudesmol metabolism. The disappearance half-life (t1/2 ) and intrinsic clearance (CLint ) of β-eudesmol were 17.09 min and 0.20 mL/min·mg protein, respectively. Enzyme kinetic analysis revealed the Michaelis-Menten constant (Km ) and maximum velocity (Vmax ) of 16.76 μM and 3.35 nmol/min·mg protein, respectively. As a component of AL, β-eudesmol, as a substrate and inhibitor of CYP2C19 and CYP3A4, has a high potential for drug-drug interactions when AL is co-administered with other herbs or conventional medicines.

Pharmacogenetic Variation in Neanderthals and Denisovans and Implications for Human Health and Response to Medications

Modern humans carry both Neanderthal and Denisovan (archaic) genome elements that are part of the human gene pool and affect the life and health of living individuals. The impact of archaic DNA may be particularly evident in pharmacogenes-genes responsible for the processing of exogenous substances such as food, pollutants, and medications-as these can relate to changing environmental effects, and beneficial variants may have been retained as modern humans encountered new environments. However, the health implications and contribution of archaic ancestry in pharmacogenes of modern humans remain understudied. Here, we explore 11 key cytochrome P450 genes (CYP450) involved in 75% of all drug metabolizing reactions in three Neanderthal and one Denisovan individuals and examine archaic introgression in modern human populations. We infer the metabolizing efficiency of these 11 CYP450 genes in archaic individuals and find important predicted phenotypic differences relative to modern human variants. We identify several single nucleotide variants shared between archaic and modern humans in each gene, including some potentially function-altering mutations in archaic CYP450 genes, which may result in altered metabolism in living people carrying these variants. We also identified several variants in the archaic CYP450 genes that are novel and unique to archaic humans as well as one gene, CYP2B6, that shows evidence for a gene duplication found only in Neanderthals and modern Africans. Finally, we highlight CYP2A6, CYP2C9, and CYP2J2, genes which show evidence for archaic introgression into modern humans and posit evolutionary hypotheses that explain their allele frequencies in modern populations.

Hydrocodone, Oxycodone, and Morphine Metabolism and Drug-Drug Interactions

Awareness of drug interactions involving opioids is critical for patient treatment as they are common therapeutics used in numerous care settings, including both chronic and disease-related pain. Not only do opioids have narrow therapeutic indexes and are extensively used, but they have the potential to cause severe toxicity. Opioids are the classical pain treatment for patients who suffer from moderate to severe pain. More importantly, opioids are often prescribed in combination with multiple other drugs, especially in patient populations who typically are prescribed a large drug regimen. This review focuses on the current knowledge of common opioid drug-drug interactions (DDIs), focusing specifically on hydrocodone, oxycodone, and morphine DDIs. The DDIs covered in this review include pharmacokinetic DDI arising from enzyme inhibition or induction, primarily due to inhibition of cytochrome p450 enzymes (CYPs). However, opioids such as morphine are metabolized by uridine-5'-diphosphoglucuronosyltransferases (UGTs), principally UGT2B7, and glucuronidation is another important pathway for opioid-drug interactions. This review also covers several pharmacodynamic DDI studies as well as the basics of CYP and UGT metabolism, including detailed opioid metabolism and the potential involvement of metabolizing enzyme gene variation in DDI. Based upon the current literature, further studies are needed to fully investigate and describe the DDI potential with opioids in pain and related disease settings to improve clinical outcomes for patients. SIGNIFICANCE STATEMENT: A review of the literature focusing on drug-drug interactions involving opioids is important because they can be toxic and potentially lethal, occurring through pharmacodynamic interactions as well as pharmacokinetic interactions occurring through inhibition or induction of drug metabolism.

Insight into Risk Factors, Pharmacogenetics/Genomics, and Management of Adverse Drug Reactions in Elderly: A Narrative Review

The European Medicine Agency (EMA) has defined Adverse Drug Reactions (ADRs) as "a noxious and unintended response to a medicine", not including poisoning, accidental, or intentional overdoses. The ADR occurrence differs based on the approach adopted for defining and detecting them, the characteristics of the population under study, and the research setting. ADRs have a significant impact on morbidity and mortality, particularly among older adults, and represent a financial burden for health services. Between 30% and 60% of ADRs might be predictable and preventable, emerging as a result of inappropriate prescription, drug chemistry inherent toxicity, cell-specific drug toxicity, age- and sex-related anomalies in drug absorption, distribution, metabolism, and elimination (ADME), and drug-drug interactions (DDIs) in combination therapies or when a patient is treated with different drugs for concomitant disorders. This is particularly important in chronic diseases which require long-term treatments. Rapid developments in pharmacogenetics/genomics have improved the understanding of ADRs accompanied by more accurate prescriptions and reduction in unnecessary costs. To alleviate the burden of ADRs, especially in the elderly, interventions focused on pharmaceutical principles, such as medication review and reconciliation, should be integrated into a broader assessment of patients' characteristics, needs, and health priorities. Digital health interventions could offer valuable solutions to assist healthcare professionals in identifying inappropriate prescriptions and promoting patient adherence to pharmacotherapies.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Pharmacokinetics of obese adults: Not only an increase in weight

Obesity is a pathophysiological state defined by a body mass index > 30 kg/m2 and characterized by an adipose tissue accumulation leading to an important weight increased. Several pathologies named comorbidities such as cardiovascular disease, type 2 diabetes and cancer make obesity the fifth cause of death in the world. Physiological changes impact the four main phases of pharmacokinetics of some drugs and leads to an inappropriate drug-dose. For absorption, the gastrointestinal transit is accelerated, and the gastric empty time is shortened, that can reduce the solubilization and absorption of some oral drugs. The drug distribution is probably the most impacted by the obesity-related changes because the fat mass (FM) increases at the expense of the lean body weight (LBW), leading to an important increase of the volume of distribution for lipophilic drugs and a low or moderately increase of this parameter for hydrophilic drugs. This modification of the distribution may require drug-dose adjustments. By various mechanisms, the metabolism and elimination of drugs are impacted by obesity and should be considered as similar or lower than that non-obese patients. To better understand the necessary drug-dose adjustments in obese patients, a narrative review of the literature was conducted to highlight the main elements to consider in the therapeutic management of adult obese patients.

Desipramine induces eryptosis in human erythrocytes, an effect blunted by nitric oxide donor sodium nitroprusside and N-acetyl-L-cysteine but enhanced by Calcium depletion

Background: Desipramine a representative of tricyclic antidepressants (TCAs) promotes recovery of depressed patients by inhibition of reuptake of neurotransmitters serotonin (SER) and norepinephrine (NE) in the presynaptic membrane by directly blocking their respective transporters SERT and NET.Aims: To study the effect of desipramine on programmed erythrocyte death (eryptosis) and explore the underlying mechanisms.Methods: Phosphatidylserine (PS) exposure on the cell surface as marker of cell death was estimated from annexin-V-binding, cell volume from forward scatter in flow cytometry. Hemolysis was determined photometrically, and intracellular glutathione [GSH]i from high performance liquid chromatography.Results: Desipramine dose-dependently significantly enhanced the percentage of annexin-V-binding cells and didn´t impact glutathione (GSH) synthesis. Desipramine-induced eryptosis was significantly reversed by pre-treatment of erythrocytes with either nitric oxide (NO) donor sodium nitroprusside (SNP) or N-acetyl-L-cysteine (NAC). The highest inhibitory effect was obtained by using both inhibitors together. Calcium (Ca2+) depletion aggravated desipramine-induced eryptosis. Changing the order of treatment, i.e. desipramine first followed by inhibitors, could not influence the inhibitory effect of SNP or NAC.Conclusion: Antidepressants-caused intoxication can be treated by SNP and NAC, respectively. B) Patients with chronic hypocalcemia should not be treated with tricyclic anti-depressants or their dose should be noticeably reduced.

Pharmacogenomic panel testing provides insight and enhances medication management in people with HIV

OBJECTIVE

Our study aimed to assess the impact of pharmacogenomic panel testing in people with HIV (PWH).

DESIGN

Prospective, observational intervention assessment.

METHODS

One hundred PWH were provided a comprehensive pharmacogenomic panel during routine care visits within the HIV specialty clinic of a large academic medical center. The panel determined the presence of specific genetic variants that could predict response or toxicity to commonly prescribed antiretroviral therapy (ART) and non-ART medications. An HIV specialty pharmacist reviewed the results with participants and the care team. The pharmacist (1) recommended clinically actionable interventions based on the participants' current drug therapy, (2) assessed for genetic explanations for prior medication failures, adverse effects, or intolerances, and (3) advised on potential future clinically actionable care interventions based on individual genetic phenotypes.

RESULTS

Ninety-six participants (median age 53 years, 74% white, 84% men, 89% viral load <50 copies/ml) completed panel testing, yielding 682 clinically relevant pharmacogenomic results (133 major, 549 mild-moderate). Ninety participants (89 on ART) completed follow-up visits with 65 (72%) receiving clinical recommendations based on current medication profiles. Of the 105 clinical recommendations, 70% advised additional monitoring for efficacy or toxicity, and 10% advised alteration of drug therapy. Panel results offered explanation for prior ART inefficacy in one participant and ART intolerance in 29%. Genetic explanation for non-ART toxicity was seen in 21% of participants, with genetic contributors to inefficacy of non-ART therapy identified in 39% of participants.

CONCLUSION

Preliminary data in a small cohort of PWH demonstrates benefit of routine pharmacogenomic panel testing.

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.

Epigenetic Mechanisms Contribute to Intraindividual Variations of Drug Metabolism Mediated by Cytochrome P450 Enzymes

Significant interindividual and intraindividual variations on cytochrome P450 (CYP)-mediated drug metabolism exist in the general population globally. Genetic polymorphisms are one of the major contribution factors for interindividual variations, but epigenetic mechanisms mainly contribute to intraindividual variations, including DNA methylation, histone modifications, microRNAs, and long non-coding RNAs. The current review provides analysis of advanced knowledge in the last decade on contributions of epigenetic mechanisms to intraindividual variations on CYP-mediated drug metabolism in several situations, including (1) ontogeny, the developmental changes of CYP expression in individuals from neonates to adults; (2) increased activities of CYP enzymes induced by drug treatment; (3) increased activities of CYP enzymes in adult ages induced by drug treatment at neonate ages; and (4) decreased activities of CYP enzymes in individuals with drug-induced liver injury (DILI). Furthermore, current challenges, knowledge gaps, and future perspective of the epigenetic mechanisms in development of CYP pharmacoepigenetics are discussed. In conclusion, epigenetic mechanisms have been proven to contribute to intraindividual variations of drug metabolism mediated by CYP enzymes in age development, drug induction, and DILI conditions. The knowledge has helped understanding how intraindividual variation are generated. Future studies are needed to develop CYP-based pharmacoepigenetics to guide clinical applications for precision medicine with improved therapeutic efficacy and reduced risk of adverse drug reactions and toxicity. SIGNIFICANCE STATEMENT: Understanding epigenetic mechanisms in contribution to intraindividual variations of CYP-mediated drug metabolism may help to develop CYP-based pharmacoepigenetics for precision medicine to improve therapeutic efficacy and reduce adverse drug reactions and toxicity for drugs metabolized by CYP enzymes.

Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance

Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.

Rationally Engineered CYP3A4 Fluorogenic Substrates for Functional Imaging Analysis and Drug-Drug Interaction Studies

Cytochrome P450 3A4 (CYP3A4) is a key xenobiotic-metabolizing enzyme-mediated drug metabolism and drug-drug interaction (DDI). Herein, an effective strategy was used to rationally construct a practical two-photon fluorogenic substrate for hCYP3A4. Following two-round structure-based substrate discovery and optimization, we have successfully constructed a hCYP3A4 fluorogenic substrate (F8) with desirable features, including high binding affinity, rapid response, excellent isoform specificity, and low cytotoxicity. Under physiological conditions, F8 is readily metabolized by hCYP3A4 to form a brightly fluorescent product (4-OH F8) that can be easily detected by various fluorescence devices. The practicality of F8 for real-time sensing and functional imaging of hCYP3A4 has been examined in tissue preparations, living cells, and organ slices. F8 also demonstrates good performance for high-throughput screening of hCYP3A4 inhibitors and assessing DDI potentials in vivo. Collectively, this study develops an advanced molecular tool for sensing CYP3A4 activities in biological systems, which strongly facilitates CYP3A4-associated fundamental and applied research studies.

Cannabinoids and Multiple Sclerosis: A Critical Analysis of Therapeutic Potentials and Safety Concerns

Multiple sclerosis (MS) is a complicated condition in which the immune system attacks myelinated axons in the central nervous system (CNS), destroying both myelin and axons to varying degrees. Several environmental, genetic, and epigenetic factors influence the risk of developing the disease and how well it responds to treatment. Cannabinoids have recently sparked renewed interest in their therapeutic applications, with growing evidence for their role in symptom control in MS. Cannabinoids exert their roles through the endogenous cannabinoid (ECB) system, with some reports shedding light on the molecular biology of this system and lending credence to some anecdotal medical claims. The double nature of cannabinoids, which cause both positive and negative effects, comes from their actions on the same receptor. Several mechanisms have been adopted to evade this effect. However, there are still numerous limitations to using cannabinoids to treat MS patients. In this review, we will explore and discuss the molecular effect of cannabinoids on the ECB system, the various factors that affect the response to cannabinoids in the body, including the role of gene polymorphism and its relation to dosage, assessing the positive over the adverse effects of cannabinoids in MS, and finally, exploring the possible functional mechanism of cannabinoids in MS and the current and future progress of cannabinoid therapeutics.

Unusual Biotransformation Reactions of Drugs and Drug Candidates

Detailed assessment of the fate of drugs in nonclinical test species and humans is essential to ensure the safety and efficacy of medicines in patients. In this context, biotransformation of drugs and drug candidates has been an area of keen interest over many decades in the pharmaceutical industry as well as academia. Although many of the enzymes and biotransformation pathways involved in the metabolism of xenobiotics and more specifically drugs have been well characterized, each drug molecule is unique and constitutes specific challenges for the biotransformation scientist. In this mini-review written for the special issue on the occasion of the 50th Anniversary celebration of Drug Metabolism and Disposition and to celebrate contributions of F. Peter Guengerich, one of the pioneers of the drug metabolism field, recently reported "unusual" biotransformation reactions are presented. Scientific and technological advances in the "toolbox" of the biotransformation scientists are summarized. As the pharmaceutical industry continues to explore therapeutic modalities different from the traditional small molecule drugs, the new challenges confronting the biotransformation scientist as well as future opportunities are discussed. SIGNIFICANCE STATEMENT: For the biotransformation scientists, it is essential to share and be aware of unexpected biotransformation reactions so that they can increase their confidence in predicting metabolites of drugs in humans to ensure the safety and efficacy of these metabolites before the medicines reach large numbers of patients. The purpose of this review is to highlight recent observations of "unusual" metabolites so that the scientists working in the area of drug metabolism can strengthen their readiness in expecting the unexpected.

Inhibition of human UDP-glucuronosyltransferase enzyme by ripretinib: Implications for drug-drug interactions

Ripretinib, a tyrosine kinase inhibitor (TKI), is the first FDA approved fourth-line therapy for adults with advanced gastrointestinal stromal tumor (GIST). Studies have shown that several TKIs for treating GIST were potent inhibitors of human UDP- glucosyltransferase (UGTs) enzymes. However, whether ripretinib affects the activity of UGTs remains unclear. The aim of this study was to investigate the effects of ripretinib on major UGT isoforms, as well as to evaluate its potential drug-drug interactions (DDIs) risk caused by the inhibition of UGTs activities. The inhibitory effects and inhibition modes of ripretinib on UGTs were systematically evaluated using high-performance liquid chromatography (HPLC) and enzyme kinetic studies, respectively. Our data showed that ripretinib exhibited potent inhibition against UGT1A1, UGT1A3, UGT1A4, UGT1A7 and UGT1A8. Enzyme kinetic studies indicated that ripretinib was not only a competitive inhibitor of UGT1A1, UGT1A4 and UGT1A7, but also a noncompetitive inhibitor of UGT1A3, as well as a mixed inhibitor of UGT1A8. The prediction results of in vitro-in vivo extrapolation (IVIVE) demonstrated that ripretinib might bring the potential risk of DDIs when combined with substrates of UGT1A1, UGT1A3, UGT1A4, UGT1A7 or UGT1A8. Therefore, special attention should be paid when ripretinib is used in conjunction with other drugs metabolized by UGTs to avoid risk of DDIs in clinic.

Is it really safe to replace decabromodiphenyl ether (BDE209) with decabromodiphenyl ethane (DBDPE)?: A perspective from hepatotoxicity

In this paper, the hepatocytotoxicity and aryl hydrocarbon receptor (AHR) activity of decabromodiphenyl ethane (DBDPE), decabromodiphenyl ether (BDE209) and other 18 analogues were evaluated in vitro using human normal liver cell L02. These dioxin-like compounds showed differential hepatocytotoxicity (EC₅₀  = 0.38-17.87 mg/L) and AHR activity (EROD activity = 4.53-46.35 U/μg). In silico study indicated the distance of π-π bonds between the benzene ring of compounds and residue Phe234 of AHR played a key role in the binding of AHR, and the substituents on the benzene ring also influenced the activity. Combining molecular biology and bioomics, the comprehensive investigations on the hepatotoxic mechanisms have demonstrated the AHR signaling pathway was the key mediation mechanism for the hepatotoxicity of DBDPE/BDE209. The cytochrome P450s (CYP2 family) mediated formation of reactive oxygenated intermediates might be the dominant toxic mechanism, which could produce oxidative stress or cause genotoxicity. Although the experimental toxicity of DBDPE was smaller relative to BDE209, the health risk of DBDPE may be much greater than we expected, due to the high potential to form a variety of dioxin-like intermediates by microbial oxidation of ethyl group. Therefore, whether it is really safe to replace BDE209 with DBDPE is a debatable question, and more ecotoxicological and health data are needed to clarify this issue.

Friend or foe? The dual role of triptolide in the liver, kidney, and heart

Triptolide, a controversial natural compound due to its significant pharmacological activities and multiorgan toxicity, has gained much attention since it was isolated from the traditional Chinese herb Tripterygium wilfordii Hook F. However, in addition to its severe toxicity, triptolide also presents powerful therapeutic potency in the same organs, such as the liver, kidney, and heart, which corresponds to the Chinese medicine theory of You Gu Wu Yun (anti-fire with fire) and deeply interested us. To determine the possible mechanisms involved in the dual role of triptolide, we reviewed related articles about the application of triptolide in both physiological and pathological conditions. Inflammation and oxidative stress are the two main ways triptolide exerts different roles, and the cross-talk between NF-κB and Nrf2 may be one of the mechanisms responsible for the dual role of triptolide and may represent the scientific connotation of You Gu Wu Yun. For the first time, we present a review of the dual role of triptolide in the same organ and propose the possible scientific connotation of the Chinese medicine theory of You Gu Wu Yun, hoping to promote the safe and efficient use of triptolide and other controversial medicines.

Drugging the microbiome: targeting small microbiome molecules

The human microbiome represents a large and diverse collection of microbes that plays an integral role in human physiology and pathophysiology through interactions with the host and within the microbial community. While early work exploring links between microbiome signatures and diseases states has been associative, emerging evidence demonstrates the metabolic products of the human microbiome have more proximal causal effects on disease phenotypes. The therapeutic implications of this shift are profound as manipulation of the microbiome by the administration of live biotherapeutics, ongoing, can now be pursued alongside research efforts toward describing inhibitors of key microbiome enzymes involved in the biosynthesis of metabolites implicated in various disease states and processing of host-derived metabolites. With growing interest in 'drugging the microbiome', we review few notable microbial metabolites for which traditional drug-development campaigns have yielded compounds with therapeutic promise.

Comprehensive in vitro and in silico assessments of metabolic capabilities of 24 genomic variants of CYP2C19 using two different substrates

Introduction: Most hepatically cleared drugs are metabolized by cytochromes P450 (CYPs), and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provide curated clinical references for CYPs to apply individual genome data for optimized drug therapy. However, incorporating novel pharmacogenetic variants into guidelines takes considerable time. Methods: We comprehensively assessed the drug metabolizing capabilities of CYP2C19 variants discovered through population sequencing of two substrates, S-mephenytoin and omeprazole. Results: Based on established functional assays, 75% (18/24) of the variants not yet described in Pharmacogene Variation (PharmVar) had significantly altered drug metabolizing capabilities. Of them, seven variants with inappreciable protein expression were evaluated as protein damaging by all three in silico prediction algorithms, Sorting intolerant from tolerant (SIFT), Polymorphism Phenotyping v2 (PolyPhen-2), and Combined annotation dependent depletion (CADD). The five variants with decreased metabolic capability (<50%) of wild type for either substrates were evaluated as protein damaging by all three in silico prediction algorithms, except CADD exact score of NM_000769.4:c.593T>C that was 19.68 (<20.0). In the crystal structure of the five polymorphic proteins, each altered residue of all those proteins was observed to affect the key structures of drug binding specificity. We also identified polymorphic proteins indicating different tendencies of metabolic capability between the two substrates (5/24). Discussion: Therefore, we propose a methodology that combines in silico prediction algorithms and functional assays on polymorphic CYPs with multiple substrates to evaluate the changes in the metabolism of all possible genomic variants in CYP genes. The approach would reinforce existing guidelines and provide information for prescribing appropriate medicines for individual patients.

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.

Cytochrome P450 Transcriptional Regulation by Testis-Specific Y-Encoded-Like Protein: Identification of Novel Upstream Transcription Factors

Cytochrome P450s (CYPs) display significant inter-individual variation in expression, much of which remains unexplained by known CYP single-nucleotide polymorphisms (SNPs). Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators for several drug-metabolizing CYPs including CYP3A4 However, transcription factors (TFs) that might influence CYP expression through an effect on TSPYL expression are unknown. Therefore, we studied regulators of TSPYL expression in hepatic cell lines and their possible SNP-dependent variation. Specifically, we identified candidate TFs that might influence TSPYL expression using the ENCODE ChIPseq database. Subsequently, the expression of TSPYL1/2/4 as well as that of selected CYP targets for TSPYL regulation were assayed in hepatic cell lines before and after knockdown of TFs that might influence CYP expression through TSPYL-dependent mechanisms. Those results were confirmed by studies of TF binding to TSPYL1/2/4 gene promoter regions. In hepatic cell lines, knockdown of the REST and ZBTB7A TFs resulted in decreased TSPYL1 and TSPYL4 expression and increased CYP3A4 expression, changes reversed by TSPYL1/4 overexpression. Potential binding sites for REST and ZBTB7A on the promoters of TSPYL1 and TSPYL4 were confirmed by chromatin immunoprecipitation. Finally, common SNP variants in upstream binding sites on the TSPYL1/4 promoters were identified and luciferase reporter constructs confirmed SNP-dependent modulation of TSPYL1/4 gene transcription. In summary, we identified REST and ZBTB7A as regulators of the expression of TSPYL genes which themselves can contribute to regulation of CYP expression and-potentially-of drug metabolism. SNP-dependent modulation of TSPYL transcription may contribute to individual variation in both CYP expression and-downstream-drug response phenotypes. SIGNIFICANCE STATEMENT: Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators of cytochrome P450 (CYP) gene expression. Here, we report that variation in TSPYL expression as a result of the effects of genetically regulated TSPYL transcription factors is an additional factor that could result in downstream variation in CYP expression and potentially, as a result, variation in drug biotransformation.

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.

Ontogeny of CYP3A and UGT activity in preterm piglets: a translational model for drug metabolism in preterm newborns

Despite considerable progress in understanding drug metabolism in the human pediatric population, data remains scarce in preterm neonates. Improving our knowledge of the ADME properties in this vulnerable age group is of utmost importance to avoid suboptimal dosing, which may lead to adverse drug reactions. The juvenile (mini)pig is a representative model for hepatic drug metabolism in human neonates and infants, especially phase I reactions. However, the effect of prematurity on the onset of hepatic phase I and phase II enzyme activity has yet to be investigated in this animal model. Therefore, the aim of this study was to assess the ontogeny of CYP3A and UGT enzyme activity in the liver of preterm (gestational day 105-107) and term-born (gestational day 115-117) domestic piglets. In addition, the ontogeny pattern between the preterm and term group was compared to examine whether postconceptional or postnatal age affects the onset of enzyme activity. The following age groups were included: preterm postnatal day (PND) 0 (n = 10), PND 5 (n = 10), PND 11 (n = 8), PND 26 (n = 10) and term PND 0 (n = 10), PND 5 (n = 10), PND 11 (n = 8), PND 19 (n = 18) and PND 26 (n = 10). Liver microsomes were extracted, and the metabolism of CYP3A and UGT-specific substrates assessed enzyme activity. Preterm CYP3A activity was only detectable at PND 26, whereas term CYP3A activity showed a gradual postnatal increase from PND 11 onwards. UGT activity gradually increased between PND 0 and PND 26 in preterm and term-born piglets, albeit, being systematically lower in the preterm group. Thus, postconceptional age is suggested as the main driver affecting porcine CYP3A and UGT enzyme ontogeny. These data are a valuable step forward in the characterization of the preterm piglet as a translational model for hepatic drug metabolism in the preterm human neonate.

Effects of CYP3A43 Expression on Cell Proliferation and Migration of Lung Adenocarcinoma and Its Clinical Significance

The cytochrome P450s (CYP450s) include key oxidative enzymes involved in the metabolism of various carcinogens and anticancer drugs. Bioinformatic studies have demonstrated the association of CYP3A43 with liver cancer and ovarian cancer. However, the biological function of CYP3A43 in tumor progression remains unclear. To further reveal the role of CYP3A43 in tumor progression, we first analyzed the data from the UALCAN database and found that CYP3A43 was negatively correlated to the cancer staging and lymph node metastasis of lung adenocarcinoma (LUAD). We established stable CYP3A43-knockdown LUAD H1299 cell line and found that its knockdown enhanced cell proliferation, colony formation, and migration in vitro, and promoted the growth of tumor xenograft in vivo. Interestingly, when CYP3A43 was ectopically-expressed in the LUAD cell lines, decreased cell proliferation and ERK1/2 phosphorylation level were observed. Lastly, we also identified CYP3A43 co-expressed genes in LUAD from LinkedOmics database followed by GO and KEGG analyses. In conclusion, our results indicate the unprecedented role of CYP3A43 in the suppression of LUAD and provide new possibilities for targeted therapy of this life-threatening disease.

Tacrolimus pharmacokinetics in pediatric nephrotic syndrome: A combination of population pharmacokinetic modelling and machine learning approaches to improve individual prediction

Background and Aim: Tacrolimus (TAC) is a first-line immunosuppressant for the treatment of refractory nephrotic syndrome (RNS), but the pharmacokinetics of TAC varies widely among individuals, and there is still no accurate model to predict the pharmacokinetics of TAC in RNS. Therefore, this study aimed to combine population pharmacokinetic (PPK) model and machine learning algorithms to develop a simple and accurate prediction model for TAC.

Methods: 139 children with RNS from August 2013 to December 2018 were included, and blood samples of TAC trough and partial peak concentrations were collected. The blood concentration of TAC was determined by enzyme immunoassay; CYP3A5 was genotyped by polymerase chain reaction-restriction fragment length polymorphism method; MYH9, LAMB2, ACTN4 and other genotypes were determined by MALDI-TOF MS method; PPK model was established by nonlinear mixed-effects method. Based on this, six machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Extra-Trees, Gradient Boosting Decision Tree (GBDT), Adaptive boosting (AdaBoost) and Lasso, were used to establish the machine learning model of TAC clearance.

Results: A one-compartment model of first-order absorption and elimination adequately described the pharmacokinetics of TAC. Age, co-administration of Wuzhi capsules, CYP3A5 *3/*3 genotype and CTLA4 rs4553808 genotype were significantly affecting the clearance of TAC. Among the six machine learning models, the Lasso algorithm model performed the best (R2 = 0.42).

Conclusion: For the first time, a clearance prediction model of TAC in pediatric patients with RNS was established using PPK combined with machine learning, by which the individual clearance of TAC can be predicted more accurately, and the initial dose of administration can be optimized to achieve the goal of individualized treatment.

A unified GCNN model for predicting CYP450 inhibitors by using graph convolutional neural networks with attention mechanism

Undesirable drug-drug interactions (DDIs) may lead to serious adverse side effects when more than two drugs are administered to a patient simultaneously. One of the most common DDIs is caused by unexpected inhibition of a specific human cytochrome P450 (CYP450), which plays a dominant role in the metabolism of the co-administered drugs. Therefore, a unified and reliable method for predicting the potential inhibitors of CYP450 family is extremely important in drug development. In this work, graph convolutional neural network (GCN) with attention mechanism and 1-D convolutional neural network (CNN) were used to extract the features of CYP ligands and the binding sites of CYP450 respectively, which were then combined to establish a unified GCN-CNN (GCNN) model for predicting the inhibitors of 5 dominant CYP isoforms, i.e., 1A2, 2C9, 2C19, 2D6, and 3A4. Overall, the established GCNN model showed good performances on the test samples and achieved better performances than the recently proposed iCYP-MFE model by using the same datasets. Based on the heat-map analysis of the resulting molecular graphs, the key structural determinants of the CYP inhibitors were further explored.

Potential of UK and US newspapers for shaping patients' knowledge and perceptions about antidiabetic medicines: a content analysis

Background

Information about how newspapers portray antidiabetic medicines to readers is lacking. This study investigated the reporting on antidiabetic medicines in the most widely circulated newspapers published in the United Kingdom (UK) and the United States (US) over a 10-year period.

Methods

The Nexis UK database was used to identify and select relevant articles. Systematic content analysis of the articles which met the inclusion criteria (articles of any format that contained reference to antidiabetic medicines) within the highest circulated newspapers in the UK and US between 2009 and 2018 was conducted. Inter-rater reliability of coding was established using a 10% sample of the identified articles.

Results

A total of 560 (369 UK and 191 US) relevant newspaper articles were retrieved. In the UK, the number of relevant articles showed a slightly increasing trend over the study period, while in the US, article numbers declined over the study period. Safety/risk of antidiabetic medicines was the most frequent theme covered by the articles (34.6%). Over one-third of the newspaper articles were written from a clinical perspective (37.7%). Insulin was the most commonly discussed class of antidiabetic medicine (23.1%). Control of blood sugar levels (53.1%) and side effects/toxicity (92.7%) were the most frequently reported benefit and risk of antidiabetic medicines, respectively. The most frequently reported organ systems harmed by antidiabetic medicines were the cardiovascular, endocrine and gastrointestinal systems. The UK newspapers were more likely to report the benefits of antidiabetic medicines (p = 0.005), while the US articles were more likely to report on harms/risks (p = 0.001). The majority of relevant articles (91.8%) were judged as having a balanced judgement, while 8.2% of the articles were rated as exaggerated.

Conclusions

This study has revealed that antidiabetic medicines are indeed reported on by UK and US newspapers. As media portrayal has the potential to negatively or positively influence patients’ views of their medication for diabetes, healthcare professionals should check on patients’ beliefs and knowledge about their medication and proactively provide objective and balanced information (including promotion of medication adherence).

Sulfation of 12-hydroxy-nevirapine by human SULTs and the effects of genetic polymorphisms of SULT1A1 and SULT2A1

Nevirapine (NVP) is an effective drug for the treatment of HIV infections, but its use is limited by a high incidence of severe skin rash and liver injury. 12-Hydroxynevirapine (12-OH-NVP) is the major metabolite of nevirapine. There is strong evidence that the sulfate of 12-OH-NVP is responsible for the skin rash. While several cytosolic sulfotransferases (SULTs) have been shown to be capable of sulfating 12-OH-NVP, the exact mechanism of sulfation in vivo is unclear. The current study aimed to clarify human SULT(s) and human organs that are capable of sulfating 12-OH-NVP and investigate the metabolic sulfation of 12-OH-NVP using cultured HepG2 human hepatoma cells. Enzymatic assays revealed that of the thirteen human SULTs, SULT1A1 and SULT2A1 displayed strong 12-OH-NVP-sulfating activity. 1-Phenyl-1-hexanol (PHHX), which applied topically prevents the skin rash in rats, inhibited 12-OH-NVP sulfation by SULT1A1 and SULT2A1, implying the involvement of these two enzymes in the sulfation of 12-OH-NVP in vivo. Among five human organ cytosols analyzed, liver cytosol displayed the strongest 12-OH-NVP-sulfating activity, while a low but significant activity was detected with skin cytosol. Cultured HepG2 cells were shown to be capable of sulfating 12-OH-NVP. The effects of genetic polymorphisms of SULT1A1 and SULT2A1 genes on the sulfation of 12-OH-NVP by SULT1A1 and SULT2A1 allozymes were investigated. Two SULT1A1 allozymes, Arg37Asp and Met223Val, showed no detectable 12-OH-NVP-sulfating activity, while a SULT2A1 allozyme, Met57Thr, displayed significantly higher 12-OH-NVP-sulfating activity compared with the wild-type enzyme. Collectively, these results contribute to a better understanding of the involvement of sulfation in NVP-induced skin rash and provide clues to the possible role of SULT genetic polymorphisms in the risk of this adverse reaction.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

A review of the genetic determinants of praziquantel resistance in Schistosoma mansoni: Is praziquantel and intestinal schistosomiasis a perfect match?

Schistosomiasis is a neglected tropical disease (NTD) caused by parasitic trematodes belonging to the Schistosoma genus. The mainstay of schistosomiasis control is the delivery of a single dose of praziquantel (PZQ) through mass drug administration (MDA) programs. These programs have been successful in reducing the prevalence and intensity of infections. Due to the success of MDA programs, the disease has recently been targeted for elimination as a public health problem in some endemic settings. The new World Health Organization (WHO) treatment guidelines aim to provide equitable access to PZQ for individuals above two years old in targeted areas. The scale up of MDA programs may heighten the drug selection pressures on Schistosoma parasites, which could lead to the emergence of PZQ resistant schistosomes. The reliance on a single drug to treat a disease of this magnitude is worrying should drug resistance develop. Therefore, there is a need to detect and track resistant schistosomes to counteract the threat of drug resistance to the WHO 2030 NTD roadmap targets. Until recently, drug resistance studies have been hindered by the lack of molecular markers associated with PZQ resistance. This review discusses recent significant advances in understanding the molecular basis of PZQ action in S. mansoni and proposes additional genetic determinants associated with PZQ resistance. PZQ resistance will also be analyzed in the context of alternative factors that may decrease efficacy within endemic field settings, and the most recent treatment guidelines recommended by the WHO.

Pharmacogenetics of Praziquantel Metabolism: Evaluating the Cytochrome P450 Genes of Zimbabwean Patients During a Schistosomiasis Treatment

Schistosomiasis is a parasitic disease infecting over 236 million people annually, with the majority affected residing on the African continent. Control of this disease is reliant on the drug praziquantel (PZQ), with treatment success dependent on an individual reaching PZQ concentrations lethal to schistosomes. Despite the complete reliance on PZQ to treat schistosomiasis in Africa, the characterization of the pharmacogenetics associated with PZQ metabolism in African populations has been sparse. We aimed to characterize genetic variation in the drug-metabolising cytochrome P450 enzymes (CYPs) and determine the association between each variant and the efficacy of PZQ treatment in Zimbabwean patients exposed to Schistosoma haematobium infection. Genomic DNA from blood samples of 114 case-control Zimbabweans infected with schistosomes were sequenced using the CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 genes as targets. Bioinformatic tools were used to identify and predict functional effects of detected single nucleotide polymorphisms (SNPs). A random forest (RF) model was then used to assess SNPs most predictive of PZQ efficacy, with a misclassification rate of 29%. SNPs were detected across all six genes, with 70 SNPs identified and multiple functional changes to the CYP enzymes predicted. Only four SNPs were significantly associated with PZQ efficacy using χ² tests, with rs951840747 (OR: 3.61, p = 0.01) in the CYP1A2 gene having the highest odds of an individual possessing this SNP clearing infection, and rs6976017 (OR: 2.19, p = 0.045) of CYP3A5 determined to be the most predictive of PZQ efficacy via the RF. Only the rs28371702 (CC) genotype (OR: 2.36, p = 0.024) of CYP2D6 was significantly associated with an unsuccessful PZQ treatment. This study adds to the genomic characterization of the diverse populations in Africa and identifies variants relevant to other pharmacogenetic studies crucial for the development and usage of drugs in these populations.