Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity

MicroRNAs as Epigenetic Biomarkers of Pathogenetic Mechanisms of the Metabolic Syndrome Induced by Antiseizure Medications: Systematic Review

Antiseizure medication (ASM) induced metabolic syndrome (AIMetS) is a common adverse drug reaction (ADR) of pharmacotherapy for epilepsy and psychiatric disorders. However, the sensitivity and specificity of blood biomarkers may be insufficient due to the influence of combined pathology, concomitant diseases, and the peculiarities of the metabolism of ASMs in patients with epilepsy. Methods: The presented results of experimental and clinical studies of microRNAs (miRs) as epigenetic biomarkers of MetS and AIMetS, which were entered into the different databases, were analyzed for the last decade (2014-2024). Results: A systematic review demonstrated that miRs can act as promising epigenetic biomarkers of key AIMetS domains. However, the results of the review demonstrated the variable role of various miRs and their paralogs in the pathogenesis of AIMetS. Therefore, as part of this study, an miRs signature was proposed that allows us to assess the risk of developing and the severity of AIMetS as low risk, medium risk, and high risk. Conclusions: The mechanisms of development and biomarkers of AIMetS are an actual problem of epileptology, which is still far from being resolved. The development of panels (signatures) of epigenetic biomarkers of this widespread ADR may help to increase the safety of pharmacotherapy of epilepsy. However, to increase the sensitivity and specificity of circulating miRs in the blood as biomarkers of AIMetS, it is necessary to conduct "bridge" studies in order to replicate the results of preclinical and clinical studies into real clinical practice.

Transforming agents: The power of structural modifications in glioblastoma multiforme therapy

Glioblastoma (GBM) is a very deadly type of brain tumor with a poor prognosis and a short survival rate. Recent advancements in understanding GBM's molecular and genetic characteristics have led to the development of various therapeutic and diagnostic strategies. Key elements such as microRNAs, lncRNAs, exosomes, angiogenesis, and chromatin modifications are highlighted, alongside significant epigenetic alterations that impact therapy and diagnosis. Despite these advancements, molecular classifications have not improved patient outcomes due to intratumoral diversity complicating targeted therapies. In this article, it is tried to emphasize the potential of investigating the epigenetic landscape of GBM, particularly identifying patients with diffuse hypermethylation at gene promoters associated with better outcomes. Integrating epigenetic and genetic data has enhanced the identification of glioma subtypes with high diagnostic precision. The reversibility of epigenetic changes offers promising therapeutic prospects, as recent insights into the "epigenetic orchestra" suggest new avenues for innovative treatment modalities for this challenging cancer. In this review article, we focus on the roles of translational elements and their alterations in the context of GBM diagnosis and therapy.

BCyrius: An Upgraded Version of Cyrius for Accurate CYP2D6 Genotyping From Short-Read Sequencing Data

Pharmacogenomics is a field of personalized medicine that aims to tailor drug dosing based on the genetics of an individual. The polymorphic and complex CYP2D6 gene is important to analyze because of its role in the metabolism of approximately a quarter of all drugs. Several bioinformatic tools have been developed to genotype CYP2D6 from short-read sequencing data. Among these, Cyrius, a tool specifically designed for CYP2D6 genotyping, has demonstrated high performance across various datasets. However, Cyrius has not been updated in the past 3 years, during which dozens of new star alleles have been identified and some previously defined ones revised. In this work, we simulated all known CYP2D6 haplotypes to assess the ability of Cyrius to identify them. In that dataset, Cyrius was unable to call or misidentified 50 of 360 samples. Given the importance of providing an up-to-date tool, particularly in clinical settings, we present an upgraded version of the tool, named BCyrius, which includes all the missing star alleles as well as revisions to the previously listed ones. BCyrius successfully identified 100% of the currently defined minor star alleles, higher than Cyrius (85.6%) and the two other tested tools, Aldy and StellarPGx, which identified 92.2% and 87.8%, respectively. BCyrius also demonstrated slightly improved performance on a dataset of real biological samples, resulting in a higher call rate while maintaining similar accuracy with Cyrius. In addition to providing genotyping results, BCyrius also reports the predicted phenotype, along with information for each detected haplotype, including population frequencies.

Optimization of antidepressant treatment by pharmacogenomics: a case report

BACKGROUND

Few new psychiatric drugs have entered the market in recent decades; in contrast, the number of drugs carrying pharmacogenomic labels continues to increase. For the foreseeable future, the advancement of psychiatry and drug therapy may hinge on personalized treatment. Currently, antipsychotic or antidepressant choices rely heavily on the clinical experience of psychiatrists and potentially lengthy iterative trials. During these trials, the clinical response to treatment in acutely depressed patients can be assessed only after several weeks of exposure to the drug. Although pharmacogenomic testing has been used in clinical care for several years, most Chinese clinicians struggle to utilize the information accurately, resulting in expensive tests that provide little real benefit to patients. Here, we demonstrate how to combine the results of pharmacogenomic testing to develop an individualized treatment plan. Our goal is to find the optimal medication regimen and dosage for the patient in the shortest possible time, control symptoms as soon as possible, and predict adverse drug reactions. This approach aims to offer a practical therapeutic idea for clinical practice.

CASE PRESENTATION

We present the case of a 27-year-old female patient experiencing a relapse of depression. Despite previous attempts with empiric medication, her symptoms remained uncontrolled, leading to exacerbation and drug withdrawal reactions. Utilizing the results of pharmacogenetic testing, we crafted an individualized treatment plan, resulting in rapid remission without any adverse drug reactions.

CONCLUSION

Recognizing the complexity of antidepressant response, our patients aim to improve their understanding, as well as that of other healthcare providers, by undergoing pharmacogenomics testing. This enhances the credibility of their medication choices. While pharmacogenomics is just one aspect considered in selecting a treatment regimen for depression, it remains a valuable tool for increasing credibility and mitigating potential adverse events.

PharmFreq: a comprehensive atlas of ethnogeographic allelic variation in clinically important pharmacogenes

Genetic polymorphisms in drug metabolizing enzymes, drug transporters as well as in genes encoding the human major histocompatibility complex contribute to inter-individual differences in drug efficacy and safety. The extent, pattern and complexity of such pharmacogenetic variation differ drastically across human populations. Here, we present PharmFreq, a global repository of pharmacogenetic frequency information that aggregates frequency data of 658 allelic variants from over 10 million individuals collected from >1200 studies across 144 countries. Most investigations were conducted in East Asian and European populations, accounting for 29.4 and 26.6% of all studies, respectively. We find that the number of studies per country and aggregated cohort size correlated significantly with population size (R = 0.55, P= 3*10-9) and country gross domestic product (R = 0.43, P= 2*10-6) with overall population coverage varying between 5% in Estonia to < 0.001% in many countries in Sub-Saharan Africa and Asia. All frequency data are openly accessible via a web-based interactive dashboard at pharmfreq.com that facilitates the exploration, visualization and analysis of country- and population-specific data and their inferred phenotypic consequences. PharmFreq thus presents a comprehensive, freely available resource for pharmacogenetic variant frequencies that can inform about ethnogeographic pharmacogenomic diversity and reveal important inequities that help to focus future research efforts into underrepresented populations.

MALDI-TOF MS-based SNP assay used to determine the appropriate antidepression for Chinese patients

Medicine remains the preferred primary treatment for depression, although some patients show remarkable individual variations in achieving satisfactory clinical outcomes during medication. Genetic polymorphisms cause approximately 40 % of individual differences in treatment response. Therefore, this study aimed to develop a technique to identify single nucleotide polymorphisms (SNPs) associated with the metabolism, effectiveness, and side effects of antidepressant medications in Chinese patients. Bibliometrics was used to search literature related to "depression" and "SNP" in Web of Science. The obtained SNP information was screened using the PharmGKB database. By designing and optimizing primers and conducting a compound amplification system, a method was established based on MALDI-TOF MS to detect polymorphisms associated with the antidepressant drugs, including sertraline, fluoxetine, citalopram, escitalopram, venlafaxine, fluvoxamine, paroxetine, and mirtazapine. The accuracy and sensitivity of the established method were verified by Sanger sequencing. A total of 10,043 articles were screened from the database, and 46 SNPs with a mutation frequency of >1 % in Asian populations and annotated with relevant clinical drugs were extracted from the PharmGKB database. This method was compared with the results of Sanger sequencing, and the accuracy of the detection results was 100 %. The MALDI-TOF MS-based SNP assay developed in this study can be a fast, convenient and effective way for patients to find the right medication for themselves. Moreover, we found that this SNP assay holds the promise of being a potential reference tool for assessing individualised differences in drug efficacy, not only for screening the causes of poor antidepressant efficacy in patients after taking medication, but also for advising physicians to understand individualised differences in drug efficacy.

Physiological markers for immunotherapeutics: a review

Immunotherapy has been advanced through multiple approaches, including immunogenic cytokines, monoclonal antibodies, therapeutic vaccinations, adoptive cell transfer, stem cell transplantation, and oncolytic viruses. This review analyses various strategies in genomics, transcriptomics, single-cell techniques, computational analysis, big data, and imaging technologies for the identification of tumour microbiota and microenvironments. Immunotherapy is becoming acknowledged as a feasible cancer treatment method, facilitating innovative cancer medicines and personalized medicine techniques.

Revolutionizing Personalized Medicine: Synergy with Multi-Omics Data Generation, Main Hurdles, and Future Perspectives

The field of personalized medicine is undergoing a transformative shift through the integration of multi-omics data, which mainly encompasses genomics, transcriptomics, proteomics, and metabolomics. This synergy allows for a comprehensive understanding of individual health by analyzing genetic, molecular, and biochemical profiles. The generation and integration of multi-omics data enable more precise and tailored therapeutic strategies, improving the efficacy of treatments and reducing adverse effects. However, several challenges hinder the full realization of personalized medicine. Key hurdles include the complexity of data integration across different omics layers, the need for advanced computational tools, and the high cost of comprehensive data generation. Additionally, issues related to data privacy, standardization, and the need for robust validation in diverse populations remain significant obstacles. Looking ahead, the future of personalized medicine promises advancements in technology and methodologies that will address these challenges. Emerging innovations in data analytics, machine learning, and high-throughput sequencing are expected to enhance the integration of multi-omics data, making personalized medicine more accessible and effective. Collaborative efforts among researchers, clinicians, and industry stakeholders are crucial to overcoming these hurdles and fully harnessing the potential of multi-omics for individualized healthcare.

The 75-Year Anniversary of the Department of Physiology and Pharmacology at Karolinska Institutet-Examples of Recent Accomplishments and Future Perspectives

Karolinska Institutet is a medical university encompassing 21 departments distributed across three departmental or campus groups. Pharmacological research has a long and successful tradition at the institute with a multitude of seminal findings in the areas of neuronal control of vasodilatation, cardiovascular pharmacology, neuropsychopharmacology, receptor pharmacology, and pharmacogenomics that resulted in, among many other recognitions, two Nobel prizes in Physiology and Medicine, one in 1970 to Ulf von Euler for his discovery of the processes involved in storage, release, and inactivation of neurotransmitters and the other in 1982 to Sune Bergström and Bengt Samuelsson for their work on prostaglandins and the discovery of leukotrienes. Pharmacology at Karolinska Institutet has over the last decade been ranked globally among the top 10 according to the QS World University Ranking. With the Department of Physiology and Pharmacology now celebrating its 75-year anniversary, we wanted to take this as an opportunity to showcase recent research achievements and how they paved the way for current activities at the department. We emphasize examples from preclinical and clinical research where the dpartment's integrative environment and robust infrastructure have successfully facilitated the translation of findings into clinical applications and patient benefits. The close collaboration between preclinical scientists and clinical researchers across various disciplines, along with a strong network of partnerships within the department and beyond, positions us to continue leading world-class pharmacological research at the Department of Physiology and Pharmacology for decades to come. SIGNIFICANCE STATEMENT: Pharmacological research at Karolinska Institutet has a long and successful history. Given the 75-year anniversary of the Department of Physiology and Pharmacology, this perspective provides an overview of recent departmental achievements and future trajectories. For these developments, interdisciplinary and intersectoral collaborations and a clear focus on result translation are key elements to continue its legacy of world-leading pharmacological research.

Clues of HLAs, metabolic SNPs, and epigenetic factors in T cell-mediated drug hypersensitivity reactions

Drug hypersensitivities are common reactions due to immunologic responses. They are of utmost importance because they may generate severe and fatal outcomes. Some drugs may cause Adverse Drug Reactions (ADRs), such as drug hypersensitivity reactions (DHRs), which can occur due to the interaction of intact drugs or their metabolites with Human Leukocyte Antigens (HLAs) and T cell receptors (TCRs). This type develops over a period of 24-72 h after exposure and is classified as type IV of DHRs. Acute generalized exanthematic pustulosis (AGEP), Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN) and drug reaction with eosinophilia and systemic symptoms (DRESS) are types of Severe Cutaneous Adverse Reactions (SCARs). In this review, we aim to discuss the types of ADRs, the mechanisms involved in their development, and the role of immunogenetic factors, such as HLAs in type IV DHRs, single-nucleotide polymorphisms (SNPs), and some epigenetic modifications, e.g., DNA/histone methylation in a variety of genes and their promoters which may predispose subjects to DHRs. In conclusion, development of promising novel in vitro or in vivo diagnostic and prognostic markers is essential for identifying susceptible subjects or providing treatment protocols to work up patients with drug allergies as personalized medicine.

Impact of IL-6 and IL-10 genotypes on tacrolimus dose requirements in kidney transplant recipients: Monte Carlo analysis

Introduction: IL-6 and IL-10 may affect the activity of cytochrome P450 (CYP) 3A enzymes involved in tacrolimus (Tac) metabolism. Moreover, the effect of IL-6 and IL-10 on Tac pharmacokinetics may differ with respect to the genetic variations in their genes.Aim: To examine the influence of IL-6 and IL-10 gene polymorphisms on Tac dose requirements and exposure over a 5-year period following kidney transplantation. Univariate and standard multivariate linear regression and Monte Carlo analysis were performed to investigate potential covariates influencing Tac dose-adjusted trough concentration (C0/D) in various post-transplantation periods.Materials & methods: IL-6 (-174G > C), IL-10 (-1082G > A, -819C > T and -592C > A) genotype, Tac daily dose, C0, C0/D and intrapatient variability data were collected from 113 patients.Results: Multivariate regression analysis and accompanied Monte Carlo simulation underscore the importance of considering IL-6 -174G > C and IL-10 -1082G > A gene polymorphisms, alongside Tac metabolic phenotype and post-transplantation period, when tailoring Tac dosage regimen.Conclusion: This study provides valuable insights regarding the individualized adjustment of Tac treatment in various post-transplantation periods.

APF2: an improved ensemble method for pharmacogenomic variant effect prediction

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

Germline cis variant determines epigenetic regulation of the anti-cancer drug metabolism gene dihydropyrimidine dehydrogenase (DPYD)

Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome-edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.

Research progress and applications of epigenetic biomarkers in cancer

Epigenetic changes are heritable changes in gene expression without changes in the nucleotide sequence of genes. Epigenetic changes play an important role in the development of cancer and in the process of malignancy metastasis. Previous studies have shown that abnormal epigenetic changes can be used as biomarkers for disease status and disease prediction. The reversibility and controllability of epigenetic modification changes also provide new strategies for early disease prevention and treatment. In addition, corresponding drug development has also reached the clinical stage. In this paper, we will discuss the recent progress and application status of tumor epigenetic biomarkers from three perspectives: DNA methylation, non-coding RNA, and histone modification, in order to provide new opportunities for additional tumor research and applications.

Germline cis variant determines epigenetic regulation of the anti-cancer drug metabolism gene dihydropyrimidine dehydrogenase (DPYD)

Enhancers are critical for regulating tissue-specific gene expression, and genetic variants within enhancer regions have been suggested to contribute to various cancer-related processes, including therapeutic resistance. However, the precise mechanisms remain elusive. Using a well-defined drug-gene pair, we identified an enhancer region for dihydropyrimidine dehydrogenase (DPD, DPYD gene) expression that is relevant to the metabolism of the anti-cancer drug 5-fluorouracil (5-FU). Using reporter systems, CRISPR genome edited cell models, and human liver specimens, we demonstrated in vitro and vivo that genotype status for the common germline variant (rs4294451; 27% global minor allele frequency) located within this novel enhancer controls DPYD transcription and alters resistance to 5-FU. The variant genotype increases recruitment of the transcription factor CEBPB to the enhancer and alters the level of direct interactions between the enhancer and DPYD promoter. Our data provide insight into the regulatory mechanisms controlling sensitivity and resistance to 5-FU.

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

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

Advancing Precision Medicine: A Review of Innovative In Silico Approaches for Drug Development, Clinical Pharmacology and Personalized Healthcare

The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient's uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the "five rights": the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug-drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come.

Precise Therapy Using the Selective Endogenous Encapsidation for Cellular Delivery Vector System

Interindividual variability in drug response is a major problem in the prescription of pharmacological treatments. The therapeutic effect of drugs can be influenced by human genes. Pharmacogenomic guidelines for individualization of treatment have been validated and used for conventional dosage forms. However, drugs can often target non-specific areas and produce both desired and undesired pharmacological effects. The use of nanoparticles, liposomes, or other available forms for drug formulation could help to overcome the latter problem. Virus-like particles based on retroviruses could be a potential envelope for safe and efficient drug formulations. Human endogenous retroviruses would make it possible to overcome the host immune response and deliver drugs to the desired target. PEG10 is a promising candidate that can bind to mRNA because it is secreted like an enveloped virus-like extracellular vesicle. PEG10 is a retrotransposon-derived gene that has been domesticated. Therefore, formulations with PEG10 may have a lower immunogenicity. The use of existing knowledge can lead to the development of suitable drug formulations for the precise treatment of individual diseases.

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward

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

Pharmacogenomic biomarker information on drug labels of the Spanish Agency of Medicines and Sanitary products: evaluation and comparison with other regulatory agencies

This work aimed to analyse the pharmacogenetic information in the Spanish Drug Regulatory Agency (AEMPS) Summary of Products Characteristics (SmPC), evaluating the presence of pharmacogenetic biomarkers, as well as the associated recommendations. A total of 55.4% of the 1891 drug labels reviewed included information on pharmacogenetic biomarker(s). Pharmacogenomic information appears most frequently in the "antineoplastic and immunomodulating agents", "nervous system", and "cardiovascular system" Anatomical Therapeutic Chemical groups. A total of 509 different pharmacogenetic biomarkers were found, of which CYP450 enzymes accounted for almost 34% of the total drug-biomarker associations evaluated. A total of 3679 drug-biomarker pairs were identified, 102 of which were at the 1A level (PharmGKB® classification system), and 33.33% of these drug-pharmacogenetic biomarker pairs were assigned to "actionable PGx", 12.75% to "informative PGx", 4.9% to "testing recommended", and 4.9% to "testing required". The rate of coincidence in the assigned PGx level of recommendation between the AEMPS and regulatory agencies included in the PharmGKB® Drug Label Annotations database (i.e., the FDA, EMA, SWISS Medic, PMDA, and HCSC) ranged from 45% to 65%, being 'actionable level' the most frequent. On the other hand, discrepancies between agencies did not exceed 35%. This study highlights the presence of relevant pharmacogenetic information on Spanish drug labels, which would help avoid interactions, toxicity, or lack of treatment efficacy.

A Bibliometric and Visual Analysis of Single Nucleotide Polymorphism Studies in Depression

BACKGROUND

Genetic polymorphism has been proven to have an important association with depression, which can influence the risk of developing depression, the efficacy of medications, and adverse effects via metabolic and neurological pathways. Nonetheless, aspects of the association between single nucleotide polymorphisms and depression have not been systematically investigated by bibliometric analysis.

OBJECTIVE

The aim of this study was to analyze the current status and trends of single nucleotide polymorphism research on depression through bibliometric and visual analysis.

METHODS

The Web of Science Core Collection was used to retrieve 10,043 articles that were published between 1998 and 2021. CiteSpace (6.1 R4) was used to perform collaborative network analysis, co-citation analysis, co-occurrence analysis, and citation burst detection.

RESULTS

The most productive and co-cited journals were the Journal of Affective Disorders and Biological Psychiatry, respectively, and an analysis of the references showed that the most recent research focused on the largest thematic cluster, "5-HT", reflecting the important research base in this area. "CYP2D6" has been in the spotlight since its emergence in 2009 and has become a research hotspot since its outbreak in 2019. However, "BDNF ", "COMT ", "older adults", "loci", and "DNA methylation" are also the new frontier of research, and some of them are currently in the process of exploration.

CONCLUSION

These findings offer a useful perspective on existing research and potential future approaches in the study of the association between single nucleotide polymorphisms and depression, which may assist researchers in selecting appropriate collaborators or journals.

Influencia de la farmacogenética en la diversidad de respuesta a las estatinas asociada a las reacciones adversas

Introducción

Las estatinas son unos de los medicamentos más prescritos en los países desarrollados por ser el tratamiento de elección para reducir los niveles de colesterol ayudando así a prevenir la enfermedad cardiovascular. Sin embargo, un gran número de pacientes sufre reacciones adversas, en especial miotoxicidad. Entre los factores que influyen en la diversidad de respuesta, la farmacogenética puede jugar un papel relevante especialmente en la prevención de los efectos adversos asociados a estos medicamentos.

Contenido

Revisión de los conocimientos actuales sobre la influencia de la farmacogenética en la aparición y prevención de las reacciones adversas asociadas a estatinas, así como del beneficio clínico del test farmacogenético anticipado.

Resumen

Variaciones genéticas en SLCO1B1 (rs4149056) para todas las estatinas; en ABCG2 (rs2231142) para rosuvastatina; o en CYP2C9 (rs1799853 y rs1057910) para fluvastatina están asociadas a un incremento de las reacciones adversas de tipo muscular y a una baja adherencia al tratamiento. Además, diversos fármacos inhibidores de estos transportadores y enzimas de biotransformación incrementan la exposición sistémica de las estatinas favoreciendo la aparición de las reacciones adversas.

Perspectiva

La implementación clínica del análisis anticipado de este panel de farmacogenética evitaría en gran parte la aparición de reacciones adversas. Además, la estandarización en la identificación de los efectos adversos, en la metodología e interpretación del genotipo, permitirá obtener resultados más concluyentes sobre la asociación entre las variantes genéticas del SLCO1B1, ABCG y CYP2C9 y la aparición de reacciones adversas y establecer recomendaciones para alcanzar tratamientos más personalizados para cada estatina.

Influence of pharmacogenetics on the diversity of response to statins associated with adverse drug reactions

Background

Statins are one of the most prescribed medications in developed countries as the treatment of choice for reducing cholesterol and preventing cardiovascular diseases. However, a large proportion of patients experience adverse drug reactions, especially myotoxicity. Among the factors that influence the diversity of response, pharmacogenetics emerges as a relevant factor of influence in inter-individual differences in response to statins and can be useful in the prevention of adverse drug effects.

Content

A systematic review was performed of current knowledge of the influence of pharmacogenetics on the occurrence and prevention of statin-associated adverse reactions and clinical benefits of preemptive pharmacogenetics testing.

Summary

Genetic variants SLCO1B1 (rs4149056) for all statins; ABCG2 (rs2231142) for rosuvastatin; or CYP2C9 (rs1799853 and rs1057910) for fluvastatin are associated with an increase in muscle-related adverse effects and poor treatment adherence. Besides, various inhibitors of these transporters and biotransformation enzymes increase the systemic exposure of statins, thereby favoring the occurrence of adverse drug reactions.

Outlook

The clinical preemptive testing of this pharmacogenetic panel would largely prevent the incidence of adverse drug reactions. Standardized methods should be used for the identification of adverse effects and the performance and interpretation of genotyping test results. Standardization would allow to obtain more conclusive results about the association between SLCO1B1, ABCG and CYP2C9 variants and the occurrence of adverse drug reactions. As a result, more personalized recommendations could be established for each statin.

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.

Structural variation of the coding and non-coding human pharmacogenome

Genetic variants in drug targets and genes encoding factors involved in drug absorption, distribution, metabolism and excretion (ADME) can have pronounced impacts on drug pharmacokinetics, response, and toxicity. While the landscape of genetic variability at the level of single nucleotide variants (SNVs) has been extensively studied in these pharmacogenetic loci, their structural variation is only poorly understood. Thus, we systematically analyzed the genetic structural variability across 908 pharmacogenes (344 ADME genes and 564 drug targets) based on publicly available whole genome sequencing data from 10,847 unrelated individuals. Overall, we extracted 14,984 distinct structural variants (SVs) ranging in size from 50 bp to 106 Mb. Each individual harbored on average 10.3 and 1.5 SVs with putative functional effects that affected the coding regions of ADME genes and drug targets, respectively. In addition, by cross-referencing pharmacogenomic SVs with experimentally determined binding data of 224 transcription factors across 130 cell types, we identified 1276 non-coding SVs that overlapped with gene regulatory elements. Based on these data, we estimate that non-coding structural variants account for 22% of the genetically encoded pharmacogenomic variability. Combined, these analyses provide the first comprehensive map of structural variability across pharmacogenes, derive estimates for the functional impact of non-coding SVs and incentivize the incorporation of structural genomic data into personalized drug response predictions.

Impact of individual factors on DNA methylation of drug metabolism genes: A systematic review

Individual differences in drug response have always existed in clinical treatment. Many non-genetic factors show non-negligible impacts on personalized medicine. Emerging studies have demonstrated epigenetic could connect non-genetic factors and individual treatment differences. We used systematic retrieval methods and reviewed studies that showed individual factors' impact on DNA methylation of drug metabolism genes. In total, 68 studies were included, and half (n = 36) were cohort studies. Six aspects of individual factors were summarized from the perspective of personalized medicine: parental exposure, environmental pollutants exposure, obesity and diet, drugs, gender and others. The most research (n = 11) focused on ABCG1 methylation. The majority of studies showed non-genetic factors could result in a significant DNA methylation alteration in drug metabolism genes, which subsequently affects the pharmacokinetic processes. However, the underlying mechanism remained unknown. Finally, some viewpoints were presented for future research.

The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy

Pharmacotherapy for neuropsychiatric disorders, such as anxiety and depression, has been characterized by significant inter-individual variability in drug response and the development of side effects. Pharmacogenetics, as a key part of personalized medicine, aims to optimize therapy according to a patient's individual genetic signature by targeting genetic variations involved in pharmacokinetic or pharmacodynamic processes. Pharmacokinetic variability refers to variations in a drug's absorption, distribution, metabolism, and elimination, whereas pharmacodynamic variability results from variable interactions of an active drug with its target molecules. Pharmacogenetic research on depression and anxiety has focused on genetic polymorphisms affecting metabolizing cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes, P-glycoprotein ATP-binding cassette (ABC) transporters, and monoamine and γ-aminobutyric acid (GABA) metabolic enzymes, transporters, and receptors. Recent pharmacogenetic studies have revealed that more efficient and safer treatments with antidepressants and anxiolytics could be achieved through genotype-guided decisions. However, because pharmacogenetics cannot explain all observed heritable variations in drug response, an emerging field of pharmacoepigenetics investigates how epigenetic mechanisms, which modify gene expression without altering the genetic code, might influence individual responses to drugs. By understanding the epi(genetic) variability of a patient's response to pharmacotherapy, clinicians could select more effective drugs while minimizing the likelihood of adverse reactions and therefore improve the quality of treatment.

Pharmacogenetic allele variant frequencies: An analysis of the VA's Million Veteran Program (MVP) as a representation of the diversity in US population

We present allele frequencies of pharmacogenomics relevant variants across multiple ancestry in a sample representative of the US population. We analyzed 658,582 individuals with genotype data and extracted pharmacogenomics relevant single nucleotide variant (SNV) alleles, human leukocyte antigens (HLA) 4-digit alleles and an important copy number variant (CNV), the full deletion/duplication of CYP2D6. We compiled distinct allele frequency tables for European, African American, Hispanic, and Asian ancestry individuals. In addition, we compiled allele frequencies based on local ancestry reconstruction in the African-American (2-way deconvolution) and Hispanic (3-way deconvolution) cohorts.

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

DNA methylation of the TPMT gene and azathioprine pharmacokinetics in children with very early onset inflammatory bowel disease

BACKGROUND

Thiopurine methyltransferase (TPMT) is a crucial enzyme for azathioprine biotransformation and its activity is higher in very early onset inflammatory bowel disease (VEO-IBD) patients than in adolescents with IBD (aIBD).

AIMS

The aims of this pharmacoepigenetic study were to evaluate differences in peripheral blood DNA methylation of the TPMT gene and in azathioprine pharmacokinetics in patients with VEO-IBD compared to aIBD.

METHODS

The association of age with whole genome DNA methylation profile was evaluated in a pilot group of patients and confirmed by a meta-analysis on 3 cohorts of patients available on the public functional genomics data repository. Effects of candidate CpG sites in the TPMT gene were validated in a larger cohort using pyrosequencing. TPMT activity and azathioprine metabolites (TGN) were measured in patients' erythrocytes by HPLC and associated with patients' age group and TPMT DNA methylation.

RESULTS

Whole genome DNA methylation pilot analysis, combined with the meta-analysis revealed cg22736354, located on TPMT downstream neighboring region, as the only statistically significant CpG whose methylation increases with age, resulting lower in VEO-IBD patients compared to aIBD (median 9.6% vs 12%, p = 0.029). Pyrosequencing confirmed lower cg22736354 methylation in VEO-IBD patients (median 4.0% vs 6.0%, p = 4.6 ×10-5). No differences in TPMT promoter methylation were found. Reduced cg22736354 methylation was associated with lower TGN concentrations (rho = 0.31, p = 0.01) in patients with VEO-IBD and aIBD.

CONCLUSION

Methylation of cg22736354 in TPMT gene neighborhood is lower in patients with VEO-IBD and is associated with reduced azathioprine inactivation and increased TGN concentrations.

Pharmacogenomics in treatment of depression and psychosis: an update

Genetic factors can, to a certain extent, successfully predict the therapeutic effects, metabolism, and adverse reactions of drugs. This research field, pharmacogenomics, is well developed in oncology and is currently expanding in psychiatry. Here, we summarize the latest development in pharmacogenomic psychiatry, where results of several recent large studies indicate a true benefit and cost-effectiveness of pre-emptive genotyping for more successful psychotherapy. However, it is apparent that we still lack knowledge of many additional heritable genetic factors of importance for explanation of the interindividual differences in response to psychiatric drugs. Thus, more effort to further develop pharmacogenomic psychiatry should be invested to achieve a broader clinical implementation.

Drug-Drug-Gene Interactions in Cardiovascular Medicine

Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean

Metabolome is the end point of the genome-environment interplay, and enables an important holistic overview of individual adaptability and host responses to environmental, ecological, as well as endogenous changes such as disease. Pharmacometabolomics is the application of metabolome knowledge to decipher the mechanisms of interindividual and intraindividual variations in drug efficacy and safety. Pharmacometabolomics also contributes to prediction of drug treatment outcomes on the basis of baseline (predose) and postdose metabotypes through mathematical modeling. Thus, pharmacometabolomics is a strong asset for a diverse community of stakeholders interested in theory and practice of evidence-based and precision/personalized medicine: academic researchers, public health scholars, health professionals, pharmaceutical, diagnostics, and biotechnology industries, among others. In this expert review, we discuss pharmacometabolomics in four contexts: (1) an interdisciplinary omics tool and field to map the mechanisms and scale of interindividual variability in drug effects, (2) discovery and development of translational biomarkers, (3) advance digital biomarkers, and (4) empower drug repurposing, a field that is increasingly proving useful in the current era of Covid-19. As the applications of pharmacometabolomics are growing rapidly in the current postgenome era, next-generation proteomics and metabolomics follow the example of next-generation sequencing analyses. Pharmacometabolomics can also empower data reliability and reproducibility through multiomics integration strategies, which use each data layer to correct, connect with, and inform each other. Finally, we underscore here that contextual data remain crucial for precision medicine and drug development that stand the test of time and clinical relevance.

Considerations of biomarker application for cancer continuum in the era of precision medicine

Purpose of the review

The goal of this review is to highlight emerging biomarker research by the key phases of the cancer continuum and outline the methodological considerations for biomarker application.

Recent findings

While biomarkers have an established role in targeted therapy and to some extent, disease monitoring, their role in early detection and survivorship remains to be elucidated. With the advent of omics technology, the discovery of biomarkers has been accelerated exponentially, therefore careful consideration to ensure an unbiased study design and robust validity is crucial.

Summary

The rigor of biomarker research holds the key to the success of precision health care. The potential clinical utility and the feasibility of implementation should be central to future biomarker research study design.

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

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

Atraumatic osteonecrosis of the humeral head: pathophysiology and current concepts of evaluation and treatment

The humeral head is considered the second most common site for osteonecrosis to occur after the femoral head. As seen in the femoral head, the circulatory implications characteristic of this condition are attributable to the interaction between a genetic predisposition and the exposure to certain risk factors. There is no consensus regarding the pathogenesis of osteonecrosis, yet the final common pathway results in disrupted blood supply, increased intraosseous pressure, and bone death. Disease staging using radiography and magnetic resonance imaging is predictive of disease progression and can help the orthopedic surgeon to guide treatment. Although there is a myriad of treatment modalities, there is a lack of high-quality evidence to conclude what is the most appropriate treatment option for each stage of humeral head osteonecrosis. Nonoperative treatment is the preferred option in early-stage disease, and it may prevent disease progression. Nonetheless, in some cases, disease progression occurs despite nonoperative measures, and surgical treatment is required. The purpose of this article is to provide an updated review of the available evidence on risk factors, diagnosis, and treatment of atraumatic humeral head osteonecrosis.

CYP2C19 and CYP2D6 Genotypes and Metabolizer Status Distribution in a Bulgarian Psychiatric Cohort

CYP2D6 and CYP2C19 are enzymes of essential significance for the pharmacokinetics of a multitude of commonly used antidepressants, antipsychotics, antiemetics, β-blockers, opioids, antiestrogen, antacids, etc. Polymorphisms in the respective genes are well established as resulting in functional differences, which in turn can impact safety and efficacy. Importantly, the prevalence of genetic CYP2D6 and CYP2C19 variability differs drastically between populations. Drawing on the limited information concerning genotype frequencies in Bulgaria, we here analyzed 742 Bulgarian psychiatric patients predominantly diagnosed with depression and/or anxiety. Specifically, we analyzed frequencies of CYPC19*2, *4 and *17, as well as of CYP2D6*2, *3, *4, *5, *6, *10 and *41. In total, 571 out of 742 patients (77%) carried at least one variant which impacts metabolizer status. Overall, 48.6% of the studied individuals were classified as non-normal metabolizers of CYP2D6 with most exhibiting reduced function (38.2% intermediate metabolizers and 6.6% poor metabolizers). In contrast, for CYP2C19, the majority of non-normal metabolizers showed increased functionality (28.9% rapid and 5.5% ultrarapid metabolizers), while reduced activity metabolizer status accounted for 25.6% (23.8% intermediate and 1.8% poor metabolizers). These results provide an important resource to assess the genetically encoded functional variability of CYP2D6 and CYP2C19 which may have significant implications for precision medicine in Bulgarian psychiatry practice.

Cytochrome P450 polymorphism: From evolution to clinical use

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

Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum

India confines more than 17% of the world’s population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population.

The clinically relevant CYP2C8*3 and CYP2C9*2 haplotype is inherited from Neandertals

Genetic variation in genes encoding cytochrome P450 enzymes influences the metabolism of drugs and endogenous compounds. The locus containing the cytochrome genes CYP2C8 and CYP2C9 on chromosome 10 exhibits linkage disequilibrium between the CYP2C8*3 and CYP2C9*2 alleles, forming a haplotype of ~300 kilobases. This haplotype is associated with altered metabolism of several drugs, most notably reduced metabolism of warfarin and phenytoin, leading to toxicity at otherwise therapeutic doses. Here we show that this haplotype is inherited from Neandertals.

Population pharmacogenomics: an update on ethnogeographic differences and opportunities for precision public health

Both safety and efficacy of medical treatment can vary depending on the ethnogeographic background of the patient. One of the reasons underlying this variability is differences in pharmacogenetic polymorphisms in genes involved in drug disposition, as well as in drug targets. Knowledge and appreciation of these differences is thus essential to optimize population-stratified care. Here, we provide an extensive updated analysis of population pharmacogenomics in ten pharmacokinetic genes (CYP2D6, CYP2C19, DPYD, TPMT, NUDT15 and SLC22A1), drug targets (CFTR) and genes involved in drug hypersensitivity (HLA-A, HLA-B) or drug-induced acute hemolytic anemia (G6PD). Combined, polymorphisms in the analyzed genes affect the pharmacology, efficacy or safety of 141 different drugs and therapeutic regimens. The data reveal pronounced differences in the genetic landscape, complexity and variant frequencies between ethnogeographic groups. Reduced function alleles of CYP2D6, SLC22A1 and CFTR were most prevalent in individuals of European descent, whereas DPYD and TPMT deficiencies were most common in Sub-Saharan Africa. Oceanian populations showed the highest frequencies of CYP2C19 loss-of-function alleles while their inferred CYP2D6 activity was among the highest worldwide. Frequencies of HLA-B*15:02 and HLA-B*58:01 were highest across Asia, which has important implications for the risk of severe cutaneous adverse reactions upon treatment with carbamazepine and allopurinol. G6PD deficiencies were most frequent in Africa, the Middle East and Southeast Asia with pronounced differences in variant composition. These variability data provide an important resource to inform cost-effectiveness modeling and guide population-specific genotyping strategies with the goal of optimizing the implementation of precision public health.

Effects of ABCB1 DNA methylation in donors on tacrolimus blood concentrations in recipients following liver transplantation

Aims

To investigate the effects of ABCB1 DNA methylation in donors on individual differences in tacrolimus blood concentrations following liver transplantation.

Methods

Twenty‐three donor liver samples carrying the CYP3A5*3/*3 genotype were classified into 2 groups based on their initial tacrolimus blood concentrations (C₀ >10 μg/L or <5 μg/L) following liver transplantation. ABCB1 mRNA levels in liver tissues and HepG2 cells were determined by quantitative reverse transcriptase polymerase chain reaction. DNA methylation status in liver tissues and HepG2 cells was determined using Illumina 850 methylation chip sequencing technology and pyrosequencing. 5‐Aza‐2dC was used to reverse methylation in HepG2 cells. Intracellular tacrolimus concentrations were determined by liquid mass spectrometry.

Results

Genome‐wide methylation sequencing and pyrosequencing analyses showed that the methylation levels of 3 ABCB1 CpG sites (cg12501229, cg00634941 and cg05496710) were significantly different between groups with different tacrolimus concentration/dose (C₀/D) ratios. ABCB1 mRNA expression in donor livers was found to be positively correlated with tacrolimus C₀/D ratio (R = .458, P < .05). After treatment with 5‐Aza‐2‐Dc, the methylation levels of the ABCB1 CpG sites in HepG2 cells significantly decreased, and this was confirmed by pyrosequencing; there was also a significant increase in ABCB1 transcription, which induced a decrease in intracellular tacrolimus concentrations.

Conclusion

ABCB1 CpG site methylation affects tacrolimus metabolism in humans by regulating ABCB1 expression. Therefore, ABCB1 DNA methylation in donor livers might be an important epigenetic factor that affects tacrolimus blood concentrations following liver transplantation.

From pharmacogenetics to pharmaco-omics: Milestones and future directions

The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.

The p53-Driven Anticancer Effect of Ribes fasciculatum Extract on AGS Gastric Cancer Cells

Cancer metastasis is directly related to the survival rate of cancer patients. Although cancer metastasis proceeds by the movement of cancer cells, it is fundamentally caused by its resistance to anoikis, a mechanism of apoptosis caused by the loss of adhesion of cancer cells. Therefore, it was found that inhibiting cancer migration and reducing anoikis resistance are important for cancer suppression, and natural compounds can effectively control it. Among them, Ribes fasciculatum, which has been used as a medicinal plant, was confirmed to have anticancer potential, and experiments were conducted to prove various anticancer effects by extracting Ribes fasciculatum (RFE). Through various experiments, it was observed that RFE induces apoptosis of AGS gastric cancer cells, arrests the cell cycle, induces oxidative stress, and reduces mobility. It was also demonstrated that anoikis resistance was attenuated through the downregulation of proteins, such as epidermal growth factor receptor (EGFR). Moreover, the anticancer effect of RFE depends upon the increase in p53 expression, suggesting that RFE is suitable for the development of p53-targeted anticancer materials. Moreover, through xenotransplantation, it was found that the anticancer effect of RFE confirmed in vitro was continued in vivo.

The Gene-Drug Duality: Exploring the Pharmacogenomics of Indigenous Populations

While pharmacogenomic studies have facilitated the rapid expansion of personalized medicine, the benefits of these findings have not been evenly distributed. Genomic datasets pertaining to Indigenous populations are sorely lacking, leaving members of these communities at a higher risk of adverse drug reactions (ADRs), and associated negative outcomes. Australia has one of the largest Indigenous populations in the world. Pharmacogenomic studies of these diverse Indigenous Australian populations have been hampered by a paucity of data. In this article, we discuss the history of pharmacogenomics and highlight the inequalities that must be addressed to ensure equal access to pharmacogenomic-based healthcare. We also review efforts to conduct the pharmacogenomic profiling of chronic diseases among Australian Indigenous populations and survey the impact of the lack of drug safety-related information on potential ADRs among individuals in these communities.

Rare genetic variability in human drug target genes modulates drug response and can guide precision medicine

Interindividual variability in drug response constitutes a major concern in pharmacotherapy. While polymorphisms in genes involved in drug disposition have been extensively studied, drug target variability remains underappreciated. By mapping the genomic variability of all human drug target genes onto high-resolution crystal structures of drug target complexes, we identified 1094 variants localized within 6 Å of drug-binding pockets and directly affecting their geometry, topology, or physicochemical properties. We experimentally show that binding site variants affect pharmacodynamics with marked drug- and variant-specific differences. In addition, we demonstrate that a common BCHE variant confers resistance to tacrine and rivastigmine, which can be overcome by the use of derivatives based on squaric acid scaffolds or tryptophan conjugation. These findings underscore the importance of genetic drug target variability and demonstrate that integration of genomic data and structural information can inform personalized drug selection and genetically guided drug development to overcome resistance.