Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2012;92:414-417. [PMID: 22992668 DOI: 10.1038/clpt.2012.96]

Pharmacogenetics of pediatric acute lymphoblastic leukemia in Uruguay: adverse events related to induction phase drugs

In Uruguay, the pediatric acute lymphoblastic leukemia (ALL) cure rate is 82.2%, similar to those reported in developed countries. However, many patients suffer adverse effects that could be attributed, in part, to genetic variability. This study aims to identify genetic variants related to drugs administered during the induction phase and analyze their contribution to adverse effects, considering individual genetic ancestry. Ten polymorphisms in five genes (ABCB1, CYP3A5, CEP72, ASNS, and GRIA1) related to prednisone, vincristine, and L-asparaginase were genotyped in 200 patients. Ancestry was determined using 45 ancestry informative markers (AIMs). The sample ancestry was 69.2% European, 20.1% Native American, and 10.7% African, but with high heterogeneity. Mucositis, Cushing syndrome, and neurotoxicity were the only adverse effects linked with genetic variants and ancestry. Mucositis was significantly associated with ASNS (rs3832526; 3R/3R vs. 2R carriers; OR: = 6.88 [1.88-25.14], p = 0.004) and CYP3A5 (non-expressors vs. expressors; OR: 4.55 [1.01-20.15], p = 0.049) genes. Regarding Cushing syndrome, patients with the TA genotype (rs1049674, ASNS) had a higher risk of developing Cushing syndrome than those with the TT genotype (OR: 2.60 [1.23-5.51], p = 0.012). Neurotoxicity was significantly associated with ABCB1 (rs9282564; TC vs. TT; OR: 4.25 [1.47-12.29], p = 0.007). Moreover, patients with <20% Native American ancestry had a lower risk of developing neurotoxicity than those with ≥20% (OR: 0.312 [0.120-0.812], p = 0.017). This study shows the importance of knowing individual genetics to improve the efficacy and safety of acute lymphoblastic leukemia.

Impact of CYP2C:TG Haplotype on CYP2C19 Substrates Clearance In Vivo, Protein Content, and In Vitro Activity

A novel haplotype composed of two non-coding variants, CYP2C18 NM_000772.3:c.*31T (rs2860840) and NM_000772.2:c.819+2182G (rs11188059), referred to as "CYP2C:TG," was recently associated with ultrarapid metabolism of various CYP2C19 substrates. As the underlying mechanism and clinical relevance of this effect remain uncertain, we analyzed existing in vivo and in vitro data to determine the magnitude of the CYP2C:TG haplotype effect. We assessed variability in pharmacokinetics of CYP2C19 substrates, including citalopram, sertraline, voriconazole, omeprazole, pantoprazole, and rabeprazole in 222 healthy volunteers receiving one of these six drugs. We also determined its impact on CYP2C8, CYP2C9, CYP2C18, and CYP2C19 protein abundance in 135 human liver tissue samples, and on CYP2C18/CYP2C19 activity in vitro using N-desmethyl atomoxetine formation. No effects were observed according to CYP2C:TG haplotype or to CYP2C19*1+TG alleles (i.e., CYP2C19 alleles containing the CYP2C:TG haplotype). In contrast, CYP2C19 intermediate (e.g., CYP2C19*1/*2) and poor metabolizers (e.g., CYP2C19*2/*2) showed significantly higher exposure in vivo, lower CYP2C19 protein abundance in human liver microsomes, and lower activity in vitro compared with normal, rapid (i.e., CYP2C19*1/*17), and ultrarapid metabolizers (i.e., CYP2C19*17/*17). Moreover, a tendency toward lower exposure was observed in ultrarapid metabolizers compared with rapid metabolizers and normal metabolizers. Furthermore, when the CYP2C19*17 allele was present, CYP2C18 protein abundance was increased suggesting that genetic variation in CYP2C19 may be relevant to the overall metabolism of certain drugs by regulating not only its expression levels, but also those of CYP2C18. Considering all available data, we conclude that there is insufficient evidence supporting clinical CYP2C:TG testing to inform drug therapy.

Repurposing Drugs: An Empowering Approach to Drug Discovery and Development

Drug discovery and development is a time-consuming and costly procedure that necessitates a substantial effort. Drug repurposing has been suggested as a method for developing medicines that takes less time than developing brand new medications and will be less expensive. Also known as drug repositioning or re-profiling, this strategy has been in use from the time of serendipitous drug discoveries to the modern computer aided drug designing and use of computational chemistry. In the light of the COVID-19 pandemic too, drug repurposing emerged as a ray of hope in the dearth of available medicines. Data availability by electronic recording, libraries, and improvements in computational techniques offer a vital substrate for systemic evaluation of repurposing candidates. In the not-too-distant future, it could be possible to create a global research archive for us to access, thus accelerating the process of drug development and repurposing. This review aims to present the evolution, benefits and drawbacks including current approaches, key players and the legal and regulatory hurdles in the field of drug repurposing. The vast quantities of available data secured in multiple drug databases, assisting in drug repurposing is also discussed.

Assessment of clinically actionable pharmacogenetic markers to stratify anti-seizure medications

Epilepsy treatment is challenging due to heterogeneous syndromes, different seizure types and higher inter-individual variability. Identification of genetic variants predicting drug efficacy, tolerability and risk of adverse-effects for anti-seizure medications (ASMs) is essential. Here, we assessed the clinical actionability of known genetic variants, based on their functional and clinical significance and estimated their diagnostic predictability. We performed a systematic PubMed search to identify articles with pharmacogenomic (PGx) information for forty known ASMs. Functional annotation of the identified genetic variants was performed using different in silico tools, and their clinical significance was assessed using the American College of Medical Genetics (ACMG) guidelines for variant pathogenicity, level of evidence (LOE) from PharmGKB and the United States-Food and drug administration (US- FDA) drug labelling with PGx information. Diagnostic predictability of the replicated genetic variants was evaluated by calculating their accuracy. A total of 270 articles were retrieved with PGx evidence associated with 19 ASMs including 178 variants across 93 genes, classifying 26 genetic variants as benign/ likely benign, fourteen as drug response markers and three as risk factors for drug response. Only seventeen of these were replicated, with accuracy (up to 95%) in predicting PGx outcomes specific to six ASMs. Eight out of seventeen variants have FDA-approved PGx drug labelling for clinical implementation. Therefore, the remaining nine variants promise for potential clinical actionability and can be improvised with additional experimental evidence for clinical utility.

Irinotecan-Induced Toxicity: A Pharmacogenetic Study Beyond UGT1A1

BACKGROUND AND OBJECTIVE

Side effects of irinotecan treatment can be dose limiting and may impair quality of life. In this study, we investigated the correlation between single nucleotide polymorphisms (SNPs) in genes encoding enzymes involved in the irinotecan metabolism and transport, outside UGT1A1, and irinotecan-related toxicity. We focused on carboxylesterases, which are involved in formation of the active metabolite SN-38 and on drug transporters.

METHODS

Patients who provided written informed consent at the Erasmus Medical Center Cancer Institute to the Code Geno study (local protocol: MEC02-1002) or the IRI28-study (NTR-6612) were enrolled in the study and were genotyped for 15 SNPs in the genes CES1, CES2, SLCO1B1, ABCB1, ABCC2, and ABCG2.

RESULTS

From 299 evaluable patients, 86 patients (28.8%) developed severe irinotecan-related toxicity. A significantly higher risk of toxicity was seen in ABCG2 c.421C>A variant allele carriers (P = 0.030, OR 1.88, 95% CI 1.06-3.34). Higher age was associated with all grade diarrhea (P = 0.041, OR 1.03, 95% CI 1.00-1.06). In addition, CES1 c.1165-41C>T and CES1 n.95346T>C variant allele carriers had a lower risk of all-grade thrombocytopenia (P = 0.024, OR 0.42, 95% CI 0.20-0.90 and P = 0.018, OR 0.23, 95% CI 0.08-0.79, respectively).

CONCLUSION

Our study indicates that ABCG2 and CES1 SNPs might be used as predictive markers for irinotecan-induced toxicity.

Pharmacogenetic Guidelines for Psychotropic Drugs: Optimizing Prescriptions in Clinical Practice

The modalities for prescribing a psychotropic (dose and choice of molecule) are currently unsatisfactory, which can lead to a lack of efficacy of the treatment associated with prolonged exposure of the patient to the symptoms of his or her illness and the side effects of the molecule. In order to improve the quality of treatment prescription, a part of the current biomedical research is dedicated to the development of pharmacogenetic tools for individualized prescription. In this guideline, we will present the genes of interest with level 1 clinical recommendations according to PharmGKB for the two major families of psychotropics: antipsychotics and antidepressants. For antipsychotics, there are CYP2D6 and CYP3A4, and for antidepressants, CYP2B6, CYP2D6, and CYP2C19. The study will focus on describing the role of each gene, presenting the variants that cause functional changes, and discussing the implications for prescriptions in clinical practice.

Pharmacogenomics in clinical trials: an overview

With the trend towards promoting personalised medicine (PM), the application of pharmacogenetics and pharmacogenomics (PGx) is of growing importance. For the purposes of clinical trials, the inclusion of PGx is an additional tool that should be considered for improving our knowledge about the effectiveness and safety of new drugs. A search of available clinical trials containing pharmacogenetic and PGx information was conducted on ClinicalTrials.gov. The results show there has been an increase in the number of trials containing PGx information since the 2000 s, with particular relevance in the areas of Oncology (28.43%) and Mental Health (10.66%). Most of the clinical trials focus on treatment as their primary purpose. In those clinical trials entries where the specific genes considered for study are detailed, the most frequently explored genes are CYP2D6 (especially in Mental Health and Pain), CYP2C9 (in Hematology), CYP2C19 (in Cardiology and Mental Health) and ABCB1 and CYP3A5 (particularly prominent in Transplantation and Cardiology), among others. Researchers and clinicans should be trained in pharmacogenetics and PGx in order to be able to make a proper interpretation of this data, contributing to better prescribing decisions and an improvement in patients' care, which would lead to the performance of PM.

Astragaloside IV against Alzheimer's disease via microglia-mediated neuroinflammation using network pharmacology and experimental validation

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases in the world. The effective therapeutic methods and drugs are still not clear. Astragaloside IV (AS-IV), a triterpenoid saponin isolated from the root of Huangqi, has a beneficial effect in the treatment of AD. However, whether AS-IV alters microglia in the inflammation of AD is still ambiguous. In our study, 99 common targets were collected between AS-IV and AD. BCL2 apoptosis regulator (Bcl-2), pro-apoptotic BCL-2 protein BAX, epidermal growth factor receptor (EGFR), and receptor tyrosine phosphatase type C (PTPRC) were screened for inflammation and microglia in the above targets by network pharmacology. Interleukin-1β (IL-1β) and EGFR both interact with signal transducer and activator of transcription 3 (STAT3) by a protein interaction network, and IL-1β had a higher affinity for AS-IV based on molecular docking. Enrichment revealed targets involved in the regulation of neuronal cell bodies, growth factor receptor binding, EGFR tyrosine kinase inhibitor resistance., etc. Besides, AS-IV alleviated the reduced cell proliferation in amyloid-beta (Aβ)-treated microglial BV2 cells. AS-IV affected BV2 cell morphological changes and decreased cluster of differentiation 11b (CD11b) gene, IL-1β, and EGFR mRNA levels increment during lipopolysaccharide (LPS) injury in BV2 cell activation. Therefore, AS-IV may regulate microglial activation and inflammation via EGFR-dependent pathways in AD. EGFR and IL-1β are vital targets that may relate to each other to coregulate downstream molecular functions in the cure of AD. Our study provides a candidate drug and disease target for the treatment of neurodegenerative diseases in the clinic.

ShinyTPs: Curating Transformation Products from Text Mining Results

Transformation product (TP) information is essential to accurately evaluate the hazards compounds pose to human health and the environment. However, information about TPs is often limited, and existing data is often not fully Findable, Accessible, Interoperable, and Reusable (FAIR). FAIRifying existing TP knowledge is a relatively easy path toward improving access to data for identification workflows and for machine-learning-based algorithms. ShinyTPs was developed to curate existing transformation information derived from text-mined data within the PubChem database. The application (available as an R package) visualizes the text-mined chemical names to facilitate the user validation of the automatically extracted reactions. ShinyTPs was applied to a case study using 436 tentatively identified compounds to prioritize TP retrieval. This resulted in the extraction of 645 reactions (associated with 496 compounds), of which 319 were not previously available in PubChem. The curated reactions were added to the PubChem Transformations library, which was used as a TP suspect list for identification of TPs using the open-source workflow patRoon. In total, 72 compounds from the library were tentatively identified, 18% of which were curated using ShinyTPs, showing that the app can help support TP identification in non-target analysis workflows.

Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry

Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.

Effect of CYP2D6 pharmacogenetic phenotype and phenoconversion on serum concentrations of antidepressants and antipsychotics: a retrospective cohort study

BACKGROUND

Pharmacogenetics (PGx), especially in regard to CYP2D6, is gaining more importance in routine clinical settings. Including phenoconversion effects (PC) in result interpretation could maximize its potential benefits. However, studies on genetics of pharmacokinetic genes including the functional enzyme status are lacking.

AIM

The retrospective analyses of clinical routine data aimed to investigating how the CYP2D6 functional enzyme status affects serum concentrations and metabolite-to-parent ratios of seven common psychotropic drugs and allows an evaluation of the relevance of this information for patient care.

METHOD

Two patient cohorts (total n = 316; 44.2 ± 15.4 years) were investigated for the CYP2D6 functional enzyme status and its associations with drug exposure and metabolism of venlafaxine, amitriptyline, mirtazapine, sertraline, escitalopram, risperidone and quetiapine.

RESULTS

We found an increase in intermediate and poor metabolizers, as well as a decrease in normal metabolizers of CYP2D6 when including PC. Moreover, we found associations between amitriptyline exposure with the phenoconversion-corrected activity score of CYP2D6 (Spearman correlation; p = 0.03), and risperidone exposure with CYP2D6 functional enzyme status (Kruskal-Wallis test; p = 0.01), as well as between metabolite-to-parent ratio of venlafaxine and risperidone with CYP2D6 functional enzyme status (Kruskal-Wallis test; p < 0.001; p = 0.05).

CONCLUSION

The data stress the relevance of PC-informed PGx in psychopharmacological treatment and suggest that PC should be included in PGx result interpretation when PGx is implemented in routine clinical care, especially before initiating amitriptyline- or risperidone-treatment, to start with a dose adequate to the respective CYP2D6 functional enzyme status. Moreover, PGx and therapeutic drug monitoring should be used complementary but not alternatively.

Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism

The cytochrome P450 (CYP450) enzyme system is responsible for the metabolism of more than two-thirds of xenobiotics. This review summarizes reports of a series of in silico tools for CYP450 enzyme-drug interaction predictions, including the prediction of sites of metabolism (SOM) of a drug and the identification of inhibitor/substrates for CYP subtypes. We also evaluated four prediction tools to identify CYP inhibitors utilizing 52 of the most frequently prescribed drugs. ADMET Predictor and CYPlebrity demonstrated the best performance. We hope that this review provides guidance for choosing appropriate enzyme prediction tools from a variety of in silico platforms to meet individual needs. Such predictions are useful for medicinal chemists to prioritize their designed compounds for further drug discovery.

Utility of triazole antifungal therapeutic drug monitoring: Insights from the Society of Infectious Diseases Pharmacists: Endorsed by the Mycoses Study Group Education and Research Consortium

Triazole antifungals (i.e., fluconazole, itraconazole, voriconazole, posaconazole, and isavuconazole) are commonly used in clinical practice to prevent or treat invasive fungal infections. Most triazole antifungals require therapeutic drug monitoring (TDM) due to highly variable pharmacokinetics, known drug interactions, and established relationships between exposure and response. On behalf of the Society of Infectious Diseases Pharmacists (SIDP), this insight describes the pharmacokinetic principles and pharmacodynamic targets of commonly used triazole antifungals and provides the rationale for utility of TDM within each agent.

Association between SLCO1B1 genetic polymorphisms and bleeding risk in patients treated with edoxaban

Since SLCO1B1 encodes the uptake transporter OATP1B1, which can influence the pharmacokinetic and pharmacodynamic profiles of edoxaban, polymorphisms in SLCO1B1 may affect the edoxaban response. This study aimed to investigate the association between SLCO1B1 gene polymorphisms and the bleeding risk in patients receiving edoxaban. We genotyped 10 single-nucleotide polymorphisms (SNPs) from the SLCO1B1 gene in patients receiving edoxaban. We also analyzed rs3842 of ABCB1 as a confounder. The odds ratio (OR) and adjusted OR (AOR) were calculated from univariate and multivariable analysis, respectively. The area under the receiver operating characteristic curve (AUROC) was constructed for the discrimination of the model. A total of 159 patients receiving edoxaban were analyzed. Overdose and rs4149056 showed significant association with bleeding complications by around 11- and 5.5-fold, respectively. Additionally, patients with the rs4149057 variant allele (C) had a 3.9-fold increased bleeding risk compared with wild-type homozygote carriers (TT), whereas rs2306283 variant homozygote (GG) carriers had a 0.27-fold reduced bleeding risk compared with wild-type allele (A) carriers. Patients with the variant-type homozygote (CC) of ABCB1 rs3842 had a higher bleeding risk than T allele carriers (AOR = 5.3 and 5.9). The final models for multivariable analyses were acceptable based on the AUROC values (> 0.70). These findings may help predict bleeding risk in patients taking edoxaban and help personalize treatment.

Network pharmacology and molecular docking to explore the potential mechanism of urolithin A in combined allergic rhinitis and asthma syndrome

This research used network pharmacology, molecular docking, in vivo studies, and other techniques to investigate the biological activity and mechanism of action of urolithin A (UA) in treating combined allergic rhinitis and asthma syndrome (CARAS). Urolithin A and potential related targets of allergic rhinitis and asthma were searched from the public databases. Then, bioinformatics analyses were given to protein-protein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and molecular dynamic simulation were performed, aiming at predicting the binding of the active compound to the core target. Finally, in vivo experiment was conducted for further validation. A total of 45 common targets of allergic rhinitis and urolithin A and 62 common targets of asthma and urolithin A were identified, among which six common core targets were screened with Cytoscape. Molecular docking indicated that these core targets had good binding activity to urolithin A, which was further confirmed by molecular dynamics simulation. In the CARAS mouse model, urolithin A showed anti-inflammatory properties. The biological activity and regulatory network of UA on CARAS were revealed, and the anti-inflammatory effect of UA was clarified, which could be associated with the equilibrium of the immune system's Th1/Th2 cells.

Drug dosage modifications in 24 million in-patient prescriptions covering eight years: A Danish population-wide study of polypharmacy

Polypharmacy has generally been assessed by raw counts of different drugs administered concomitantly to the same patients; not with respect to the likelihood of dosage-adjustments. To address this aspect of polypharmacy, the objective of the present study was to identify co-medications associated with more frequent dosage adjustments. The data foundation was electronic health records from 3.2 million inpatient admissions at Danish hospitals (2008-2016). The likelihood of dosage-adjustments when two drugs were administered concomitantly were computed using Bayesian logistic regressions. We identified 3,993 co-medication pairs that associate significantly with dosage changes when administered together. Of these pairs, 2,412 (60%) did associate with readmission, mortality or longer stays, while 308 (8%) associated with reduced kidney function. In comparison to co-medications pairs that were previously classified as drug-drug interactions, pairs not classified as drug-drug interactions had higher odds ratios of dosage modifications than drug pairs with an established interaction. Drug pairs not corresponding to known drug-drug interactions while still being associated significantly with dosage changes were prescribed to fewer patients and mentioned more rarely together in the literature. We hypothesize that some of these pairs could be associated with yet to be discovered interactions as they may be harder to identify in smaller-scale studies.

Advances in the understanding of acetaminophen toxicity mechanisms: a clinical toxicology perspective

INTRODUCTION

Acetaminophen (paracetamol) is a commonly used analgesic and antipyretic agent, which is safe in therapeutic doses. Acetaminophen poisoning due to self-harm or repeated supratherapeutic ingestion is a common cause of acute liver injury. Acetylcysteine has been a mainstay of treatment for acetaminophen poisoning for decades and is efficacious if administered early. However, treatment failures occur if administered late, in 'massive' overdoses or in high-risk patients.

AREAS COVERED

This review provides an overview of the mechanisms of toxicity of acetaminophen poisoning (metabolic and oxidative phase) and how this relates to the assessment and treatment of the acetaminophen poisoned patient. The review focuses on how these advances offer further insight into the utility of novel biomarkers and the role of proposed adjunct treatments.

EXPERT OPINION

Advances in our understanding of acetaminophen toxicity have allowed the development of novel biomarkers and a better understanding of how adjunct treatments may prevent acetaminophen toxicity. Newly proposed adjunct treatments like fomepizole are being increasingly used without robust clinical trials. Novel biomarkers (not yet clinically available) may provide better assessment of these newly proposed adjunct treatments, particularly in clinical trials. These advances in our understanding of acetaminophen toxicity and liver injury hold promise for improved diagnosis and treatment.

Case report: application of pharmacogenetics in the personalized treatment of an elderly patient with a major depressive episode

Background

Pharmacogenetic analyses can predict interpersonal differences in response to psychopharmacotherapy, which greatly facilitates the selection of the most effective medication at optimal doses. By personalizing therapy in this way, we can minimize adverse drug reactions (ADR) and prevent polypharmacy. Most psychotropic medications are metabolized by the cytochrome P450 enzymes CYP2D6, CYP2C19, and CYPA3A4, which influence drug metabolism and concentration, affecting both efficacy and the occurrence of ADR. The relationships between genetic variations and enzymatic activity allow pharmacogenetic analysis to provide important data for optimal drug selection. The following case report illustrates the impact of pharmacogenetic analysis on the course of pharmacologic treatment in an elderly patient with a major depressive episode.

Methods

We present a case of a 79-year-old patient treated for severe depression with psychotic symptoms. We collected data on treatment selection and response to treatment before and after pharmacogenetic analysis. For pharmacogenetic analysis, common functional variants in CYP1A2, CYP3A4, CYP2B6, CYP2C19, and CYP2D6 were genotyped, and corresponding evidence-based treatment recommendations were prepared.

Results

The patient suffered from lack of efficacy and serious ADR of several medications, resulting in worsening depression and treatment resistance over the course of several months of treatment. Pharmacogenetic analysis provided important insights into the patient's pharmacokinetic phenotype and allowed us to personalize treatment and achieve remission of the depressive episode.

Conclusion

In the case presented, we have shown how consideration of pharmacogenetic characteristics in an individual patient can improve treatment outcome and patient well-being. Knowledge of the patient's pharmacogenetic characteristics helped us to personalize treatment, resulting in complete remission of psychopathology. Due to the complexity of psychiatric disorders, the efficacy of combinations of different medications, which are often required in individual patients, cannot be clearly explained. Therefore, it is of great importance to conduct further pharmacokinetic and pharmacogenetic studies to better assess gene-drug interactions in psychopharmacotherapy.

A pilot pharmacogenetic study of calcium channel blocker treatment of bipolar mania

Common genetic variants located in calcium channel genes are important markers of genetic susceptibility for bipolar disorder (BD). Previous clinical trials with Calcium Channel Blocker (CCB) medication improved mood stability for some BD patients. We hypothesize that manic patients who carried calcium channel risk variants would differentially benefit from treatment with CCBs. In this pilot study, 50 BD patients (Chinese: 39; US: 11) who were hospitalized for manic episodes were given add-on CCB treatment. We determined genotypes for each patient. There was a significant decrease in the Young Mania Rating Scale (YMRS) after add-on medication treatment. Of note, two intronic variants of the Calcium Voltage-Gated Channel Subunit Alpha1 B (CACNA1B) were associated with treatment outcomes for manic patients: rs2739258 and rs2739260. BD rs2739258/rs2739260 AG-allele carriers had a better treatment response with add-on CCB than those carrying the AA or GG genotypes by survival analysis. Although these findings did not pass multiple testing correction, this study suggests that single-nucleotide polymorphisms (SNPs) residing in calcium channel genes could be predictors for response to add-on CCB treatment of bipolar mania patients, and that calcium channel genes may be involved in treatment responses for BD.

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Potential active compounds and common mechanisms of Evodia rutaecarpa for Alzheimer's disease comorbid pain by network pharmacology analysis

Evodia rutaecarpa (Evodia) is a Chinese herbal medicine with analgesic and anti-neurodegenerative properties. However, whether Evodia compounds can be applied for the comorbid pain of Alzheimer's disease (AD) and the underlying mechanisms remain unclear. Herein, 137 common targets of Evodia between AD and pain were predicted from drug and disease target databases. Subsequently, protein-protein interaction (PPI) network, protein function module construction, and bioinformatics analyses were used to analyze the potential relationship among targets, pathways, and diseases. Evodia could simultaneously treat AD comorbid pain through multi-target, multi-component, and multi-pathway mechanisms, and inflammation was an important common phenotype of AD and pain. The relationship between important transcription factors such as RELA, NF-κB1, SP1, STAT3, and JUN on IL-17, TNF, and MAPK signaling pathways might be potential mechanisms of Evodia. Additionally, 10 candidate compounds were predicted, and evodiamine might be the effective active ingredient of Evodia in treating AD or pain. In summary, this study provided a reference for subsequent research and a novel understanding and direction for the clinical use of evodiamine to treat AD patients with comorbid pain.

Association between genetic polymorphisms in fibrinogen genes and bleeding risk in patients treated with direct oral anticoagulants

Introduction

This study aimed to investigate the association between polymorphisms in fibrinogen genes and bleeding risk in patients receiving direct oral anticoagulants (DOACs).

Method

Patients treated with DOACs from June 2018 to December 2021 were enrolled in the study. Genotyping was done for rs2070011, rs6050, and rs2070022 in fibrinogen alpha chain (FGA); rs1800788, rs4220, and rs4463047 in fibrinogen beta chain (FGB); and rs2066865 and rs1800792 in fibrinogen gamma chain (FGG), along with F2 rs5896 and F10 rs5960. Multivariable logistic regression analysis was performed to investigate the risk factors for bleeding and to develop a risk scoring system.

Results

A total of 468 patients were included in the analysis, 14 of whom experienced major bleeding and 36 experienced clinically relevant non-major bleeding. In the multivariable analysis, overdose, anaemia, F2 rs5896, and FGG rs1800792 were found to be significantly associated with bleeding risk. Specifically, patients with the TT genotype of F2 rs5896 and the CC genotype of FGG rs1800792 had 2.1 times (95% confidence interval [CI] 1.1-3.9) and 2.7 times (95% CI 1.2-5.9) higher bleeding risk than the C allele and T allele carriers, respectively. Based on the risk scoring system, patients with 0, 1, 2, 3, 4, and 5 points were predicted to have 5.2%, 10.8%, 22.4%, 32.3%, 42.3%, and 61.8% of bleeding risk, respectively.

Conclusion

To our knowledge, this is the first study to investigate the effects of polymorphisms in fibrinogen genes on DOAC response. After validation, these results will be useful for personalised DOAC therapy.

Towards Evidence-Based Implementation of Pharmacogenomics in Southern Africa: Comorbidities and Polypharmacy Profiles across Diseases

Pharmacogenomics may improve patient care by guiding drug selection and dosing; however, this requires prior knowledge of the pharmacogenomics of drugs commonly used in a specific setting. The aim of this study was to identify a preliminary set of pharmacogenetic variants important in Southern Africa. We describe comorbidities in 3997 patients from Malawi, South Africa, and Zimbabwe. These patient cohorts were included in pharmacogenomic studies of anticoagulation, dyslipidemia, hypertension, HIV and breast cancer. The 20 topmost prescribed drugs in this population were identified. Using the literature, a list of pharmacogenes vital in the response to the top 20 drugs was constructed leading to drug-gene pairs potentially informative in translation of pharmacogenomics. The most reported morbidity was hypertension (58.4%), making antihypertensives the most prescribed drugs, particularly amlodipine. Dyslipidemia occurred in 31.5% of the participants, and statins were the most frequently prescribed as cholesterol-lowering drugs. HIV was reported in 20.3% of the study participants, with lamivudine/stavudine/efavirenz being the most prescribed antiretroviral combination. Based on these data, pharmacogenes of immediate interest in Southern African populations include ABCB1, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLC22A1, SLCO1B1 and UGT1A1. Variants in these genes are a good starting point for pharmacogenomic translation programs in Southern Africa.

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.

Identifying biomarkers of treatment response to ciclosporin in atopic dermatitis through multiomic predictive modelling: DERMATOMICS study protocol

INTRODUCTION

There is a need to optimise the management of atopic dermatitis (AD), improving the efficacy of treatments and reducing the toxicity associated with them. Although the efficacy of ciclosporine (CsA) in the treatment of AD has been thoroughly documented in the literature, the optimal dose has not been yet established. The use of multiomic predictive models of treatment response could optimise CsA therapy in AD.

METHODS AND ANALYSIS

The study is a low-intervention phase 4 trial to optimise the treatment of patients with moderate-severe AD requiring systemic treatment. The primary objectives are to identify biomarkers that could allow for the selection of responders and non-responders to first-line treatment with CsA and to develop a response prediction model to optimise the CsA dose and treatment regimen in responding patients based on these biomarkers. The study is divided into two cohorts: the first comprised of patients starting treatment with CsA (cohort 1), and the second, of patients already receiving or who have received CsA therapy (cohort 2).

ETHICS AND DISSEMINATION

The study activities began following authorisation by the Spanish Regulatory Agency (AEMPS) and the Clinical Research Ethics Committee of La Paz University Hospital approval. Trial results will be submitted for publication in an open access peer-reviewed medical speciality-specific publication.Trial registration of this study can be located at the EU Clinical Trials Register, available from https://euclinicaltrials.eu/search-for-clinical-trials/?lang=en. Our clinical trial was registered in the website before the enrolment of the first patient complying with European regulations. EU Clinical Trials Register is a primary registry according the WHO. Once our trial was included in a primary and official registry, in order to extend the accessibility to our research, we also registered it retrospectively in clinicaltrials.gov; however, this is not mandatory as per our regulation.

TRIAL REGISTRATION NUMBER

NCT05692843.

Pilot Study: Personalized Medicine in Endoscopy, Can Pharmacogenomics Predict Response to Conscious Sedation?

BACKGROUND

Adequate response to moderate (conscious) sedation varies significantly between individuals. Polymorphisms in genes encoding drug metabolizing enzymes can lead to inter-individual variability in drug efficacy, potentially influencing sedation requirements during endoscopic procedures.

OBJECTIVES

The aim of this study was to assess the potential role of inter-individual variation in inherited polymorphisms of drug-metabolizing enzymes, cytochrome P450 (CYP450), specifically CYP3A4 and CYP3A5, in sedation requirements for outpatient endoscopic procedures.

METHODS

A retrospective analysis of sedation requirements and pharmacogenomics data in 106 unique patients who received outpatient esophagogastroduodenoscopy (EGD), colonoscopy, or both between December 2011 and February 2019 was conducted. Patients were divided into two groups based on their sedation requirements during endoscopy (high vs. normal sedation).

RESULTS

Patients with reduced a CYP2C19 metabolism (poor + intermediate metabolizers) (odds ratio [OR] = 0.38, 95% confidence interval [CI]: 0.16-0.91, p = 0.03), poor CYP3A5 metabolism (OR = 0.25, 95% CI: 0.095-0.65, p = 0.0046), and poor UGT1A1 (OR = 2.76, 95% CI: 1.07-7.13, p = 0.08) had higher odds of requiring normal sedation compared to those with CYP2C19 increased metabolism, CYP3A5 intermediate metabolism, and UGT1A1 intermediate metabolism.

CONCLUSION

Information about inter-individual variation in (CYP450) genes may be useful for determining the sedation requirements for outpatient endoscopic procedures. We found that patients with reduced CYP2C19 metabolism, poor CYP3A5 metabolism, and poor UGT1A1 metabolism were more likely to require normal sedation requirements during outpatient endoscopic procedures.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Liquid Chromatography-Tandem Mass Spectrometry Method for Detection and Quantification of Meloxicam and 5'-Carboxymeloxicam in Oral Fluid Samples

A sensitive, selective and particularly fast method of liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated for the determination of meloxicam and its main metabolite, 5'-carboxymeloxicam, in oral fluid samples. Meloxicam and its major metabolite were separated using a Shim-Pack XR-ODS 75 L × 2.0 column and C18 pre-column at 40 °C using a mixture of methanol and 10 mM ammonium acetate (80:20, v/v) with an injection flow rate of 0.3 mL/min. The total time of the analytical run was 5 min. Sixteen volunteers had oral fluid samples collected sequentially before and after taking a meloxicam tablet (15 mg) for up to 96 h. With the concentrations obtained, the pharmacokinetic parameters were determined using the Phoenix WinNonlin software. The parameters evaluated for meloxicam and 5'-carboxymeloxicam in the oral fluid samples showed linearity, accuracy, precision, medium-quality control (MQC-78.12 ng/mL), high-quality control (HQC-156.25 ng/mL), lower limits of quantification (LLOQ-0.6103 ng/mL), low-quality control (LQC-2.44 ng/mL), stability and dilution. Prostaglandin E₂ (PGE₂) was also detected and quantified in the oral fluid samples, demonstrating the possibility of a pharmacokinetic/pharmacodynamic (PK/PD) study with this methodology. All the parameters evaluated in the validation of the methodology in the oral fluid samples proved to be stable and within the possible variations in each of the described parameters. Through the data presented, the possibility of a PK/PD study was demonstrated, detecting and quantifying meloxicam, its main metabolite and PGE₂ in oral fluid samples using LC-MS/MS.

PopTradeOff: A database for exploring population-specificity of adaptive evolution, disease susceptibility, and drug responsiveness

The influence of adaptive evolution on disease susceptibility has drawn attention; however, the extent of the influence, whether favored mutations also influence drug responses, and whether the associations between the three are population-specific remain unknown. Using a reported deep learning network to integrate seven statistical tests for detecting selection signals, we predicted favored mutations in the genomes of 17 human populations and integrated these favored mutations with reported GWAS sites and drug response-related variants into the database PopTradeOff (http://www.gaemons.net/PopFMIntro). The database also contains genome annotation information on the SNP, sequence, gene, and pathway levels. The preliminary data analyses suggest that substantial associations exist between adaptive evolution, disease susceptibility, and drug responses and that the associations are highly population-specific. The database may be valuable for disease studies, drug development, and personalized medicine.

Mining of molecular insights of CYP2A6 and its variants complex with coumarin (CYP2A6*-coumarin) using molecular dynamics simulation

CYP2A6 is a very important enzyme that plays a crucial role in nicotine compounds and is responsible for the metabolism of more than 3% drugs of total metabolized drugs by the CYP family and reported as one of very important pharmacogenes. CYP2A6 is highly polymorphic in nature and reported with more than 40 variants, most of these variants are SNPs originated and population specific. It has been well observed and reported that the presence of these population-specific non-synonymous SNPs in CYP2A6 alters the rate of drug metabolism and as a functional consequence, drugs produce an abnormal response. Though genomics and pharmacogenomics studies are there, very less is known about the structural effects of these SNPs on molecular-interaction and folding of CYP2A6. To fill the knowledge gap, SNPs based four variants, i.e., CYP2A6*2, CYP2A6*18, CYP2A6*21, and CYP2A6*35, which are frequently reported in the South Asian population, were considered for the study. Coumarin (DB04665), a well reported drug, is considered as a model substance, and the effect of all four variants on 'CYP2A6*-coumarin' complex was studied. MD simulation-based analysis (at 200 ns) was performed and comparative analysis with respect to wild type 'CYP2A6-coumarin' complex was done. Though observation didn't find any global effect on complete complex but found some crucial minor-local alteration in interaction and folding process. It is assumed that the change due to SNPs in the single amino acid did not bring global change in physiochemical properties of CYP2A6* but caused local-trivial changes which are very crucial for its metabolic activity.Communicated by Ramaswamy H. Sarma.

Pharmacogenomics of response to statin treatment and susceptibility to statin-induced adverse drug reactions in Asians: a scoping review

Background

Statins are the most widely used lipid-lowering agents for patients with hyperlipidemia. However, interindividual variations in efficacy and risk of adverse drug reactions to statin treatment have been widely reported. Ethnicity is well known to be one of the contributing factors to this variation, particularly among Asians.

Objectives

To identify genetic variants associated with statin treatment responses among Asian populations with a focus on four commonly prescribed statins: atorvastatin, rosuvastatin, simvastatin, and pravastatin.

Methods

A literature search was conducted in Medline and Embase databases. Studies published from 2008 to 2021 were included. The title and abstract of each article were screened by two reviewers and verified by another two reviewers. Data charted include information on authors, year of study, study population, statin studied, gene studied, study findings, and data of significant statistical value.

Results

A total of 35 articles were included from the 1,939 original studies related to treatment efficacy and 5 articles out of the 284 original studies related to adverse effects. Genetic variants in transmembrane transporters, cytochrome P450 isoenzymes, and apolipoproteins are the most extensively studied among Asian populations, with a main focus on ethnic Chinese. However, Asia consists of genetically different populations, and the results of this review indicated that there is a paucity of studies on other ethnic groups within Asia.

Conclusions

Considering the ethnicity of patients could provide a potential value to personalized medicine in statin therapy.

Pharmacogenomics in practice: a review and implementation guide

Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests' reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.

MBROLE3: improved functional enrichment of chemical compounds for metabolomics data analysis

MBROLE (Metabolites Biological Role) facilitates the biological interpretation of metabolomics experiments. It performs enrichment analysis of a set of chemical compounds through statistical analysis of annotations from several databases. The original MBROLE server was released in 2011 and, since then, different groups worldwide have used it to analyze metabolomics experiments from a variety of organisms. Here we present the latest version of the system, MBROLE3, accessible at http://csbg.cnb.csic.es/mbrole3. This new version contains updated annotations from previously included databases as well as a wide variety of new functional annotations, such as additional pathway databases and Gene Ontology terms. Of special relevance is the inclusion of a new category of annotations, 'indirect annotations', extracted from the scientific literature and from curated chemical-protein associations. The latter allows to analyze enriched annotations of the proteins known to interact with the set of chemical compounds of interest. Results are provided in the form of interactive tables, formatted data to download, and graphical plots.

Genetic variations that influence paclitaxel pharmacokinetics and intracellular effects that may contribute to chemotherapy-induced neuropathy: A narrative review

Taxanes, particularly paclitaxel and docetaxel, are chemotherapeutic agents commonly used to treat breast cancers. A frequent side effect is chemotherapy-induced peripheral neuropathy (CIPN) that occurs in up to 70% of all treated patients and impacts the quality of life during and after treatment. CIPN presents as glove and stocking sensory deficits and diminished motor and autonomic function. Nerves with longer axons are at higher risk of developing CIPN. The causes of CIPN are multifactorial and poorly understood, limiting treatment options. Pathophysiologic mechanisms can include: (i) disruptions of mitochondrial and intracellular microtubule functions, (ii) disruption of axon morphology, and (iii) activation of microglial and other immune cell responses, among others. Recent work has explored the contribution of genetic variation and selected epigenetic changes in response to taxanes for any insights into their relation to pathophysiologic mechanisms of CIPN20, with the hope of identifying predictive and targetable biomarkers. Although promising, many genetic studies of CIPN are inconsistent making it difficult to develop reliable biomarkers of CIPN. The aims of this narrative review are to benchmark available evidence and identify gaps in the understanding of the role genetic variation has in influencing paclitaxel's pharmacokinetics and cellular membrane transport potentially related to the development of CIPN.

Pharmacogenetics of pain management in Zimbabwean patients with sickle cell disease

Background: Pain is a common cause of hospitalization in sickle cell disease (SCD) patients. Failure to effectively control pain remains a challenge in patient care. Materials & methods: The authors conducted a cross-sectional study to determine the effect of CYP2D6 and UGT2B7 polymorphisms on pain management in 106 Zimbabwean SCD patients. Participant information was collected on a questionnaire. Genotyping was conducted using the GenoPharm® pharmacogenomics open array panel containing CYP2D6 and UGT genetic variants implicated in opioid response. Results: The reduced function alleles CYP2D6*17 and *29 had high frequencies of 15.9% and 12.9%, respectively. UGT2B7 rs73823859 showed a statistically significant correlation with pain levels (p = 0.0454). Conclusion: This study demonstrated the role of UGT2B7 polymorphism in SCD patient pain management.

How to Run the Pharmacogenomics Clinical Annotation Tool (PharmCAT)

Pharmacogenomics (PGx) investigates the genetic influence on drug response and is an integral part of precision medicine. While PGx testing is becoming more common in clinical practice and may be reimbursed by Medicare/Medicaid and commercial insurance, interpreting PGx testing results for clinical decision support is still a challenge. The Pharmacogenomics Clinical Annotation Tool (PharmCAT) has been designed to tackle the need for transparent, automatic interpretations of patient genetic data. PharmCAT incorporates a patient's genotypes, annotates PGx information (allele, genotype, and phenotype), and generates a report with PGx guideline recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and/or the Dutch Pharmacogenetics Working Group (DPWG). PharmCAT has introduced new features in the last 2 years, including a variant call format (VCF) Preprocessor, the inclusion of DPWG guidelines, and functionalities for PGx research. For example, researchers can use the VCF Preprocessor to prepare biobank-scale data for PharmCAT. In addition, PharmCAT enables the assessment of novel partial and combination alleles that are composed of known PGx variants and can call CYP2D6 genotypes based on single and deletions in the input VCF file. This tutorial provides materials and detailed step-by-step instructions for how to use PharmCAT in a versatile way that can be tailored to users' individual needs.

OregonFluor enables quantitative intracellular paired agent imaging to assess drug target availability in live cells and tissues

Non-destructive fluorophore diffusion across cell membranes to provide an unbiased fluorescence intensity readout is critical for quantitative imaging applications in live cells and tissues. Commercially available small-molecule fluorophores have been engineered for biological compatibility, imparting high water solubility by modifying rhodamine and cyanine dye scaffolds with multiple sulfonate groups. The resulting net negative charge, however, often renders these fluorophores cell-membrane-impermeant. Here we report the design and development of our biologically compatible, water-soluble and cell-membrane-permeable fluorophores, termed OregonFluor (ORFluor). By adapting previously established ratiometric imaging methodology using bio-affinity agents, it is now possible to use small-molecule ORFluor-labelled therapeutic inhibitors to quantitatively visualize their intracellular distribution and protein target-specific binding, providing a chemical toolkit for quantifying drug target availability in live cells and tissues.

The Prevalence and Features of Medications With Actionable Pharmacogenomic Biomarkers Prescribed to Kidney Transplant Recipients

BACKGROUND

Genetic variants are associated with pharmacokinetic and pharmacodynamic changes, leading to variability in drug effects and safety profiles in the clinical response. The role of genetic variants in kidney transplant recipients (KTRs) has not been extensively studied. Here, we explored the potential of incorporating pharmacogenomic (PGx) gene biomarkers into prescription practices for KTRs.

METHODS

This study analyzed 490 KTRs participating in the Taiwan Precision Medicine Initiative program and used medications with actionable PGx biomarkers. The analysis included prescriptions issued between January 2000 and December 2021 with 206 CPIC-recommended level A or B gene-drug pairs, encompassing 363 single or combination drug products.

RESULTS

All KTRs had the potential to receive at least one prescription that could be adjusted based on their genetic profiles after the day of surgery. The top 5 medications prescribed within the first 3 months after transplantation were mycophenolic acid, tacrolimus, pantoprazole, labetalol, and tramadol. These findings highlight the significant potential of PGx-guided prescriptions for KTRs. Additionally, some drug-gene pairs, such as tramadol/CYP2D6, pantoprazole/CYP2C19, and atorvastatin/SLCO1B1, were considered high-quality evidence by the Clinical Pharmacogenetics Implementation Consortium and were included in the Food and Drug Administration's drug labels, indicating that they have the potential for clinical application.

CONCLUSIONS

Overall, this study demonstrated the potential of incorporating PGx gene biomarkers into prescribing practices for KTRs, which could improve personalized pharmacotherapy for these patients.

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.

Toxicity prediction using target, interactome, and pathway profiles as descriptors

In silico methods are essential to the safety evaluation of chemicals. Computational risk assessment offers several approaches, with data science and knowledge-based methods becoming an increasingly important sub-group. One of the substantial attributes of data science is that it allows using existing data to find correlations, build strong hypotheses, and create new, valuable knowledge that may help to reduce the number of resource intensive experiments. In choosing a suitable method for toxicity prediction, the available data and desired toxicity endpoint are two essential factors to consider. The complexity of the endpoint can impact the success rate of the in silico models. For highly complex endpoints such as hepatotoxicity, it can be beneficial to decipher the toxic event from a more systemic point of view. We propose a data science-based modelling pipeline that uses compounds` connections to tissue-specific biological targets, interactome, and biological pathways as descriptors of compounds. Models trained on different combinations of the collected, compound-target, compound-interactor, and compound-pathway profiles, were used to predict the hepatotoxicity of drug-like compounds. Several tree-based models were trained, utilizing separate and combined target, interactome and pathway level variables. The model using combined descriptors of all levels and the random forest algorithm was further optimized. Descriptor importance for model performance was addressed and examined for a biological explanation to define which targets or pathways can have a crucial role in toxicity. Descriptors connected to cytochromes P450 enzymes, heme degradation and biological oxidation received high weights. Furthermore, the involvement of other, less discussed processes in connection with toxicity, such as the involvement of RHO GTPase effectors in hepatotoxicity, were marked as fundamental. The optimized combined model using only the selected descriptors yielded the best performance with an accuracy of 0.766. The same dataset using classical Morgan fingerprints for compound representation yielded models with similar performance measures, as well as the combination of systems biology-based descriptors and Morgan fingerprints. Consequently, adding the structural information of compounds did not enhance the predictive value of the models. The developed systems biology-based pipeline comprises a valuable tool in predicting toxicity, while providing novel insights about the possible mechanisms of the unwanted events.

Investigation of effective components and action mechanism of Yiguanjian in treatment of liver fibrosis based on network pharmacology

BACKGROUND

Traditional Chinese medicine compounds are characterized by the comprehensive adjustment of multiple components and show unique advantages in the prevention and treatment of liver fibrosis. Yiguanjian (YGJ) is a famous prescription for nourishing Yin to soothe the liver, which can improve the symptoms of liver fibrosis, and understanding its anti-liver fibrosis mechanism can promote its development and use.

AIM

To explore the mechanism of YGJ in the treatment of liver fibrosis through network pharmacology and to experi-mentally validate the initial results obtained.

METHODS

Components of YGJ and potentially targeted proteins were downloaded from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The targets of liver fibrosis were accessed from GeneCard and OMIM databases. STRING database was utilized to construct a protein-protein interaction (PPI) network based on the components of YGJ and the targets of liver fibrosis. The PPI network was subjected to random walk with restart (RWR) to obtain key genes, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed based on the DAVID database. For animal experimental validation, eighteen SD rats were randomly assigned to a normal group, a model group, and a YGJ group. The rats in the model group and YGJ group were intraperitoneally injected with 50% CCl₄ olive oil solution for 6 wk to induce liver fibrosis, and rats in the normal group were intraperitoneally injected with the same amount of olive oil solution. Then, the rats of the YGJ group were given YGJ decoction (6.67 g/kg) daily for 4 weeks. Meanwhile, rats in the other groups were given distilled water. Blood and liver samples were collected, and the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the serum of rats were detected with an automated analyzer. Pathological changes in liver tissue were observed by hematoxylin-eosin (HE) and Masson staining. Western blot and qRT-PCR were used to detect the expression of key proteins and genes in the liver.

RESULTS

A total of 52 components and 186 potential targets of YGJ were obtained, and 1080 targets of liver fibrosis were screened. The top 10 genes with the high-affinity scores to the drug targets were STAT6, SRC, MAPK3, STX1A, EP300, STAT3, PLG, CTNNB1, CDKN1B, and CANX. The top 50 genes were mainly enriched in response to PI3K- Akt signaling pathway and FoxO signaling pathway, etc. In CCl4-induced liver fibrosis rats, YGJ decoction could significantly improve liver lesions and reduce fibrosis. YGJ decoction could reduce α-SMA expression, promote the expression of phosphorylated STAT6, increase the protein expression of PPAR-γ and CD163 and the mRNA expression of Arg-1, CD206, and CD163, and inhibit the gene expression of IL-6.

CONCLUSION

The therapeutic effect of YGJ decoction for liver fibrosis involves multiple components and multiple pathways, including the STAT6/PPAR-γ pathway.

The Wu-Shi-Cha formula protects against ulcerative colitis by orchestrating immunity and microbiota homeostasis

ETHNOPHARMACOLOGICAL RELEVANCE

Ulcerative colitis (UC) has become a healthy burden worldwide due to its insidious onset and repetitive relapse, with a rather complex etiology, including inappropriate immune response, dysbiosis, genetic susceptibility, and unhealthy diets. The Wu-Shi-Cha (WSC) formula is a widely utilized drug to protect against gastrointestinal disorders.

AIM OF THE STUDY

The study aspired to dissect the pertinent mechanisms of the WSC to treat UC.

MATERIALS AND METHODS

Network pharmacology and weighted gene co-expression network analysis (WGCNA) were performed to predict the targets of WSC in the context of UC and colorectal cancer. Dextran sodium sulfate (DSS) was used to construct murine models of experimental colitis, and the WSC was given to colitis mice for 14 days. Feces and colon samples were subjected to 16S rRNA gene sequencing combined with liquid chromatography-mass spectrometry (LC-MS) and biochemical experiments, respectively.

RESULTS

Network pharmacology analysis predicted that the WSC formula could orchestrate inflammation, infection, and tumorigenesis, and WGCNA based on The Cancer Genome Atlas (TCGA) database showed a potent anti-neoplastic effect of the WSC therapy for colorectal cancer. The WSC therapy rescued bursts of pro-inflammatory cytokines and colonic epithelial collapse in DSS-induced colitis mice. Moreover, the high dose of WSC treatment facilitated the alternative activation of peritoneal macrophages (Mφs) and these Mφs were conducive to the survival of intestinal stem cells (ISCs), and the disturbed homeostasis of gut microbiota was re-established after WSC treatment, as evidenced by the decreased colonization of pathological taxa in the fecal samples.

CONCLUSION

The WSC formula suppresses inflammation and re-establishes the homeostasis of gut microbiota, thereby ameliorating colitis progression.

Genetic control of RNA editing in neurodegenerative disease

A-to-I RNA editing diversifies human transcriptome to confer its functional effects on the downstream genes or regulations, potentially involving in neurodegenerative pathogenesis. Its variabilities are attributed to multiple regulators, including the key factor of genetic variants. To comprehensively investigate the potentials of neurodegenerative disease-susceptibility variants from the view of A-to-I RNA editing, we analyzed matched genetic and transcriptomic data of 1596 samples across nine brain tissues and whole blood from two large consortiums, Accelerating Medicines Partnership-Alzheimer's Disease and Parkinson's Progression Markers Initiative. The large-scale and genome-wide identification of 95 198 RNA editing quantitative trait loci revealed the preferred genetic effects on adjacent editing events. Furthermore, to explore the underlying mechanisms of the genetic controls of A-to-I RNA editing, several top RNA-binding proteins were pointed out, such as EIF4A3, U2AF2, NOP58, FBL, NOP56 and DHX9, since their regulations on multiple RNA-editing events were probably interfered by these genetic variants. Moreover, these variants may also contribute to the variability of other molecular phenotypes associated with RNA editing, including the functions of 3 proteins, expressions of 277 genes and splicing of 449 events. All the analyses results shown in NeuroEdQTL (https://relab.xidian.edu.cn/NeuroEdQTL/) constituted a unique resource for the understanding of neurodegenerative pathogenesis from genotypes to phenotypes related to A-to-I RNA editing.

S. B, Chatterjee M, Prabhash K, Sreekanthreddy P, Rishi KD, Goswami HM, Veldore VH. An absolute approach to using whole exome DNA and RNA workflow for cancer biomarker testing

Introduction

The concept of personalized medicine in cancer has emerged rapidly with the advancement of genome sequencing and the identification of clinically relevant variants that contribute to disease prognosis and facilitates targeted therapy options. In this study, we propose to validate a whole exome-based tumor molecular profiling for DNA and RNA from formalin-fixed paraffin-embedded (FFPE) tumor tissue.

Methods

The study included 166 patients across 17 different cancer types. The scope of this study includes the identification of single-nucleotide variants (SNVs), insertions/deletions (INDELS), copy number alterations (CNAs), gene fusions, tumor mutational burden (TMB), and microsatellite instability (MSI). The assay yielded a mean read depth of 200×, with &gt;80% of on-target reads and a mean uniformity of &gt;90%. Clinical maturation of whole exome sequencing (WES) (DNA and RNA)- based assay was achieved by analytical and clinical validations for all the types of genomic alterations in multiple cancers. We here demonstrate a limit of detection (LOD) of 5% for SNVs and 10% for INDELS with 97.5% specificity, 100% sensitivity, and 100% reproducibility.

Results

The results were &gt;98% concordant with other orthogonal techniques and appeared to be more robust and comprehensive in detecting all the clinically relevant alterations. Our study demonstrates the clinical utility of the exome-based approach of comprehensive genomic profiling (CGP) for cancer patients at diagnosis and disease progression.

Discussion

The assay provides a consolidated picture of tumor heterogeneity and prognostic and predictive biomarkers, thus helping in precision oncology practice. The primary intended use of WES (DNA+RNA) assay would be for patients with rare cancers as well as for patients with unknown primary tumors, and this category constitutes nearly 20–30% of all cancers. The WES approach may also help us understand the clonal evolution during disease progression to precisely plan the treatment in advanced stage disease.

Polypharmacy and precision medicine

Precision medicine is an approach to maximise the effectiveness of disease treatment and prevention and minimise harm from medications by considering relevant demographic, clinical, genomic and environmental factors in making treatment decisions. Precision medicine is complex, even for decisions about single drugs for single diseases, as it requires expert consideration of multiple measurable factors that affect pharmacokinetics and pharmacodynamics, and many patient-specific variables. Given the increasing number of patients with multiple conditions and medications, there is a need to apply lessons learned from precision medicine in monotherapy and single disease management to optimise polypharmacy. However, precision medicine for optimisation of polypharmacy is particularly challenging because of the vast number of interacting factors that influence drug use and response. In this narrative review, we aim to provide and apply the latest research findings to achieve precision medicine in the context of polypharmacy. Specifically, this review aims to (1) summarise challenges in achieving precision medicine specific to polypharmacy; (2) synthesise the current approaches to precision medicine in polypharmacy; (3) provide a summary of the literature in the field of prediction of unknown drug-drug interactions (DDI) and (4) propose a novel approach to provide precision medicine for patients with polypharmacy. For our proposed model to be implemented in routine clinical practice, a comprehensive intervention bundle needs to be integrated into the electronic medical record using bioinformatic approaches on a wide range of data to predict the effects of polypharmacy regimens on an individual. In addition, clinicians need to be trained to interpret the results of data from sources including pharmacogenomic testing, DDI prediction and physiological-pharmacokinetic-pharmacodynamic modelling to inform their medication reviews. Future studies are needed to evaluate the efficacy of this model and to test generalisability so that it can be implemented at scale, aiming to improve outcomes in people with polypharmacy.

Novel and replicated clinical and genetic risk factors for toxicity from high-dose methotrexate in pediatric acute lymphoblastic leukemia

STUDY OBJECTIVE

Methotrexate (MTX) is a key component of treatment for high-risk pediatric acute lymphoblastic leukemia (ALL) but may cause acute kidney injury and prolonged hospitalization due to delayed clearance. The purpose of this study is to identify clinical and genetic factors that may predict which children are at risk for creatinine increase and prolonged MTX clearance.

DESIGN

We conducted a single-center, retrospective cohort study of pediatric patients with ALL who received 4000-5000 mg/m2 of MTX. Measurements We performed germline genotyping to determine genetic ancestry and allele status for 49 single nucleotide polymorphisms (SNPs) identified from the literature as related to MTX disposition. Bayesian hierarchical ordinal regression models for creatinine increase and for prolonged MTX clearance were developed.

MAIN RESULTS

Hispanic ethnicity, body mass index (BMI) < 3%, BMI between 85%-95%, and Native American genetic ancestry were found to be associated with an increased risk for creatinine elevation. Older age, Black race, and use of the intensive monitoring protocol were associated with a decreased risk for creatinine elevation. Older age, B- compared to T-ALL, and the minor alleles of rs2838958/SLC19A1 and rs7317112/ABCC4 were associated with an increased risk for delayed clearance. Black race, MTX dose reduction, and the minor allele of rs2306283/SLCO1B1 were found to be associated with a decreased risk for delayed clearance.

CONCLUSIONS

These predictors of MTX toxicities may allow for more precise individualized toxicity risk prediction.

A retrospective analysis of preemptive pharmacogenomic testing in 22,918 individuals from China

BACKGROUND

Pharmacogenomics (PGx) examines the influence of genetic variation on drug responses. With more and more Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines published, PGx is gradually shifting from the reactive testing of single gene toward the preemptive testing of multiple genes. But the profile of PGx genes, especially for the intra-country diversity, is not well understood in China.

METHODS

We retrospectively collected preemptive PGx testing data of 22,918 participants from 20 provinces of China, analyzed frequencies of alleles, genotypes and phenotypes of pharmacogenes, predicted drug responses for each participant, and performed comparisons between different provinces.

RESULTS AND CONCLUSION

After analyzing 15 pharmacogenes from CPIC guidelines of 31 drugs, we found that 99.97% of individuals may have an atypical response to at least one drug; the participants carry actionable genotypes leading to atypical dosage recommendation for a median of eight drugs. Over 99% of the participants were recommended a decreased warfarin dose based on genetic factors. There were 20 drugs with high-risk ratios from 0.18% to 58.25%, in which clopidogrel showed the highest high-risk ratio. In addition, the high-risk ratio of rasburicase in GUANGDONG (risk ratio (RR) = 13.17, 95%CI:4.06-33.22, p < 0.001) and GUANGXI (RR = 23.44, 95%CI:8.83-52.85, p < 0.001) were significantly higher than that in all provinces. Furthermore, the diversity we observed among 20 provinces suggests that preemptive PGx testing in different geographical regions in China may need to pay more attention to specific genes. These results emphasize the importance of preemptive PGx testing and provide essential evidence for promoting clinical implementation in China.

CYP2D6 and CYP2C8 pharmacogenetics and pharmacological interactions to predict imatinib plasmatic exposure in GIST patients

AIMS

Patients on treatment with oral fixed dose imatinib are frequently under- or overexposed to the drug. We investigated the association between the gene activity score (GAS) of imatinib-metabolizing cytochromes (CYP3A4, CYP3A5, CYP2D6, CYP2C9, CYP2C19, CYP2C8) and imatinib and nor-imatinib exposure. We also investigated the impact of concurrent drug-drug-interactions (DDIs) on the association between GAS and imatinib exposure.

METHODS

Serial plasma samples were collected from 33 GIST patients treated with imatinib 400 mg daily within a prospective clinical trial. Imatinib and nor-imatinib C_trough were quantified by liquid chromatography with tandem mass spectrometry (LC-MS/MS). Genetic polymorphisms with a functional impact on imatinib-metabolizing cytochromes were identified and a GAS was calculated for each gene. A DDI-adjusted GAS was also generated.

RESULTS

Imatinib and nor-imatinib C_trough were measured in 161 plasma samples. CYP2D6 GAS and metabolizer status based on genotype were associated with imatinib and (imatinib + nor-imatinib) C_trough . CYP2D6 poor and intermediate metabolizers were predicted to have a lower nor-imatinib/imatinib metabolic ratio than normal metabolizers (0.197 and 0.193 vs. 0.247, P = .0205), whereas CYP2C8*3 carriers had a higher ratio than CYP2C8*1/*1 patients (0.263 vs. 0.201, P = .0220). CYP2C9 metabolizer status was inversely related to the metabolic ratio with an effect probably driven by the linkage disequilibrium between CYP2C9*2 and CYP2C8*3. The CYP2D6 DDI-adjusted GAS was still predictive of imatinib exposure.

CONCLUSIONS

These findings highlight that CYP2D6 plays a major role in imatinib pharmacokinetics, but other players (i.e., CYP2C8) may influence imatinib exposure. These findings could drive the selection of patients more susceptible to imatinib under- or overexposure who could be candidates for personalized treatment and intensified monitoring strategies.

Polygenic Pharmacogenomic Markers as Predictors of Toxicity Phenotypes in the Treatment of Acute Lymphoblastic Leukemia: A Single-Center Study

PURPOSE

Acute lymphoblastic leukemia (ALL) is the most prevalent cause of childhood cancer and requires a long course of therapy consisting of three primary phases with interval intensification blocks. Although these phases are necessary to achieve remission, the primary chemotherapeutic agents have potentially serious toxicities, which may lead to delays or discontinuations of therapy. The purpose of this study was to perform a comprehensive pharmacogenomic evaluation of common antileukemic agents and develop a polygenic toxicity risk score predictive of the most common toxicities observed during ALL treatment.

METHODS

This cross-sectional study included 75 patients with pediatric ALL treated between 2012 and 2020 at the University of Florida. Toxicity data were collected within 100 days of initiation of therapy using CTCAE v4.0 for toxicity grading. For pharmacogenomic evaluation, single-nucleotide polymorphisms (SNPs) and genes were selected from previous reports or PharmGKB database. 116 unique SNPs were evaluated for incidence of various toxicities. A multivariable multi-SNP modeling for up to 3-SNP combination was performed to develop a polygenic toxicity risk score of prognostic value.

RESULTS

We identified several SNPs predictive of toxicity phenotypes in univariate analysis. Further multivariable SNP-SNP combination analysis suggest that susceptibility to chemotherapy-induced toxicities is likely multigenic in nature. For 3-SNPscore models, patients with high scores experienced increased risk of GI (P = 2.07E-05, 3 SNPs: TYMS-rs151264360/FPGS-rs1544105/GSTM1-GSTM5-rs3754446), neurologic (P = .0005, 3 SNPs: DCTD-rs6829021/SLC28A3-rs17343066/CTPS1-rs12067645), endocrine (P = 4.77E-08, 3 SNPs: AKR1C3-rs1937840/TYMS-rs2853539/CTH-rs648743), and heme toxicities (P = .053, 3 SNPs: CYP3A5-rs776746/ABCB1-rs4148737/CTPS1-rs12067645).

CONCLUSION

Our results imply that instead of a single-SNP approach, SNP-SNP combinations in multiple genes in drug pathways increases the robustness of prediction of toxicity. These results further provide promising SNP models that can help establish clinically relevant biomarkers allowing for greater individualization of cancer therapy to maximize efficacy and minimize toxicity for each patient.