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Molatefi R, Talebi S, Samei A, Roshanravan N, Manshouri S, Hashemi B, Ghobadi Dana V, Mosharkesh E, Bahar MA, Khajoei S, Seif F. Clues of HLAs, metabolic SNPs, and epigenetic factors in T cell-mediated drug hypersensitivity reactions. Heliyon 2024; 10:e33976. [PMID: 39100437 PMCID: PMC11296025 DOI: 10.1016/j.heliyon.2024.e33976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 07/01/2024] [Accepted: 07/01/2024] [Indexed: 08/06/2024] Open
Abstract
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.
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Affiliation(s)
- Rasol Molatefi
- Cancer Immunology and Immunotherapy Research Center, Ardabil University of Medical Sciences, Ardabil, Iran
| | - Sedighe Talebi
- Department of Traditional Medicine, School of Persian Medicine, Shahed University, Tehran, Iran
| | - Azam Samei
- Department of Laboratory Sciences, School of Allied Medical Sciences, Kashan University of Medical Sciences, Kashan, Iran
| | - Neda Roshanravan
- Cardiovascular Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Shirin Manshouri
- Rajaei Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Baran Hashemi
- Rajaei Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Vahid Ghobadi Dana
- Department of Immunology and Allergy, Academic Center for Education, Culture, and Research (ACECR), Tehran, Iran
| | - Erfan Mosharkesh
- Faculty of Veterinary Medicine, University of Tabriz, Tabriz, Iran
| | - Mohammad Ali Bahar
- Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Sholeh Khajoei
- Clinical Research Development Center, Imam Khomeini Hospital, Jiroft University of Medical Sciences, Jiroft, Iran
| | - Farhad Seif
- Department of Immunology and Allergy, Academic Center for Education, Culture, and Research (ACECR), Tehran, Iran
- Department of Photodynamic Therapy, Medical Laser Research Center, Academic Center for Education, Culture, and Research (ACECR), Tehran, Iran
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Ji Y, Zhao J, Gong J, Sedlazeck FJ, Fan S. Unveiling novel genetic variants in 370 challenging medically relevant genes using the long read sequencing data of 41 samples from 19 global populations. Mol Genet Genomics 2024; 299:65. [PMID: 38972030 DOI: 10.1007/s00438-024-02158-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 06/16/2024] [Indexed: 07/08/2024]
Abstract
BACKGROUND A large number of challenging medically relevant genes (CMRGs) are situated in complex or highly repetitive regions of the human genome, hindering comprehensive characterization of genetic variants using next-generation sequencing technologies. In this study, we employed long-read sequencing technology, extensively utilized in studying complex genomic regions, to characterize genetic alterations, including short variants (single nucleotide variants and short insertions and deletions) and copy number variations, in 370 CMRGs across 41 individuals from 19 global populations. RESULTS Our analysis revealed high levels of genetic variants in CMRGs, with 68.73% exhibiting copy number variations and 65.20% containing short variants that may disrupt protein function across individuals. Such variants can influence pharmacogenomics, genetic disease susceptibility, and other clinical outcomes. We observed significant differences in CMRG variation across populations, with individuals of African ancestry harboring the highest number of copy number variants and short variants compared to samples from other continents. Notably, 15.79% to 33.96% of short variants were exclusively detectable through long-read sequencing. While the T2T-CHM13 reference genome significantly improved the assembly of CMRG regions, thereby facilitating variant detection in these regions, some regions still lacked resolution. CONCLUSION Our results provide an important reference for future clinical and pharmacogenetic studies, highlighting the need for a comprehensive representation of global genetic diversity in the reference genome and improved variant calling techniques to fully resolve medically relevant genes.
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Affiliation(s)
- Yanfeng Ji
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China
| | - Junfan Zhao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China
| | - Jiao Gong
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
- Department of Computer Science, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
| | - Shaohua Fan
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China.
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De Mattia E, Milan N, Assaraf YG, Toffoli G, Cecchin E. Clinical Implementation of Rare and Novel DPYD Variants for Personalizing Fluoropyrimidine Treatment: Challenges and Opportunities. Int J Biol Sci 2024; 20:3742-3759. [PMID: 39113696 PMCID: PMC11302886 DOI: 10.7150/ijbs.97686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 06/11/2024] [Indexed: 08/10/2024] Open
Abstract
Fluoropyrimidines (FLs) [5-Fluorouracil, Capecitabine] are used in the treatment of several solid tumors. Dihydropyrimidine dehydrogenase (DPD) is the rate-limiting enzyme for FL detoxification, and its deficiency could lead to severe, life-threatening or fatal toxicity after FL administration. Testing with a pharmacogenetic panel of four deleterious variants in the dihydropyrimidine dehydrogenase gene (DPYD) (DPYD*2A, DPYD*13, c.2846A > T, c.1129-5923C > G) prior to FL treatment, is recommended by scientific consortia (e.g., CPIC, DPWG) and drug regulatory agencies (e.g., EMA). However, this panel identifies < 20% of patients at risk of severe FL-related toxicity. Cumulative recent evidence highlights the potential clinical value of rare (minor allele frequency < 1%) and novel DPYD genetic variants for identifying an additional fraction of DPD-deficient patients at increased risk of severe FL-related toxicity. In this review, we aimed to comprehensively describe the available evidence regarding the potential clinical predictive role of novel and rare DPYD variants as toxicity markers in FL-treated patients, and to discuss the challenges and opportunities in tailoring FL treatment based upon clinical application of such markers. Although we must overcome existing barriers to the clinical implementation, the available data support that comprehensive assessment of the DPYD sequence, including rare and novel genetic variants, may significantly enhance the pre-emptive identification of at-risk patients, compared to the current targeted approach.
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Affiliation(s)
- Elena De Mattia
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, via Franco Gallini n. 2, 33081 Aviano (PN), Italy
| | - Noemi Milan
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, via Franco Gallini n. 2, 33081 Aviano (PN), Italy
| | - Yehuda G. Assaraf
- The Fred Wyszkowski Cancer Research Laboratory, Faculty of Biology, Technion-Israel Institute of Technology, Haifa 3200003, Israel
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, via Franco Gallini n. 2, 33081 Aviano (PN), Italy
| | - Erika Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, via Franco Gallini n. 2, 33081 Aviano (PN), Italy
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van Westrhenen R, Ingelman-Sundberg M. Rare variants and clozapine: Reply. Eur Neuropsychopharmacol 2024; 84:16-17. [PMID: 38643694 DOI: 10.1016/j.euroneuro.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 03/12/2024] [Accepted: 03/15/2024] [Indexed: 04/23/2024]
Affiliation(s)
- Roos van Westrhenen
- Department of Psychiatry, Parnassia Psychiatric Institute, Overschiestraat 57, Amsterdam 1062 HN, the Netherlands; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; St. John's National Academy of Health Sciences, Bangalore, India.
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Odeh M, Sbitan L, Alzraikat N, Tanous H, Al-Diery T. Precision medicine in pharmacy: assessing pharmacogenomics competence among pharmacists and pharmacy students. J Pharm Policy Pract 2024; 17:2354879. [PMID: 38868176 PMCID: PMC11168213 DOI: 10.1080/20523211.2024.2354879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2024] Open
Abstract
Background Pharmacogenomics, a key component of precision medicine, aims to improve healthcare outcomes. As pharmacists play a pivotal role in this evolving field, an assessment of their preparedness to apply pharmacogenomics is imperative. Methods In this cross-sectional study, a validated questionnaire (Content Validity Ratio > 0.741, p < 0.05) that demonstrated reliability (Cronbach's alpha for all scales > 0.7) gathered data on demographics, knowledge, attitudes, barriers, and confidence in pharmacogenomics among pharmacists and pharmacy students in Jordan. Statistical analysis assessed associations and their strength within the collected data and variables. Results This study included 514 pharmacists and pharmacy students. Knowledge scores were moderate and correlated with academic level and pharmacy school attended. Most participants were open to providing pharmacogenomics testing and interpretation through pharmacy services, but the majority demonstrated concerns about potential misinterpretation of test results and the resulting patients' anxiety. Students cited limited accessibility, while pharmacists identified the lack of standardised guidelines as the main roadblock. Conclusion This study highlights the need for education to prepare pharmacists for their role in pharmacogenomics. Despite positive attitudes from pharmacists, addressing knowledge gaps, the low confidence in recommending pharmacogenomics tests, and concerns about implementation are essential.
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Affiliation(s)
- Mohanad Odeh
- Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmaceutical Sciences, The Hashemite University, Zarqa, Jordan
| | - Lana Sbitan
- Faculty of Medicine, The Hashemite University, Zarqa, Jordan
| | - Noor Alzraikat
- King Hussein Medical Center, Royal Medical Services, Amman, Jordan
| | - Haneen Tanous
- Princess Basma Teaching Hospital, Ministry of Health, Irbid, Jordan
| | - Tarik Al-Diery
- College of Pharmacy, QU Health, Qatar University, Doha, Qatar
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Zhou Y, Pirmann S, Lauschke VM. APF2: an improved ensemble method for pharmacogenomic variant effect prediction. THE PHARMACOGENOMICS JOURNAL 2024; 24:17. [PMID: 38802404 PMCID: PMC11129946 DOI: 10.1038/s41397-024-00338-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/26/2024] [Accepted: 05/15/2024] [Indexed: 05/29/2024]
Abstract
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.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet and University Hospital, Stockholm, Sweden
| | - Sebastian Pirmann
- Computational Oncology Group, Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz Information and Data Science School for Health, Karlsruhe/Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Center for Molecular Medicine, Karolinska Institutet and University Hospital, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tübingen, Tübingen, Germany.
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Ragia G, Pallikarou M, Manolopoulou Y, Vorvolakos T, Manolopoulos VG. Genetic diversity of cytochrome P450 in patients receiving psychiatric care in Greece: a step towards clinical implementation. Pharmacogenomics 2024:1-13. [PMID: 38884939 DOI: 10.1080/14622416.2024.2346072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 04/12/2024] [Indexed: 06/18/2024] Open
Abstract
Aim: We herein inferred the genetic diversity of CYP450 isoenzymes to predict the percentage of patients who need dose adjustment in drugs used in psychiatry. Materials & methods: Data of 784 Greek patients receiving psychiatric care who were genotyped for CYP2D6, CYP2C19, CYP1A2, CYP3A5 and CYP2C9 isoenzymes were inferred to gene-drug pairs according to the US FDA, Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group annotations and published literature. Results: Atypical metabolism was found for 36.8% of patients in CYP2D6, 49.2% in CYP2C19, 45% in CYP1A2, 16.7% in CYP3A5 and 41.8% in CYP2C9. Dosage adjustment need was estimated for 10.2% of venlafaxine, 10.0% of paroxetine, 6.4% of sertraline, 30.8% of citalopram, 52.1% of escitalopram, 18.2% of fluvoxamine, 54.1% of tricyclic antidepressants, 16.7% of zuclopenthixol, 10.6% of haloperidol and 13.3% of risperidone treated patients. Conclusion: Clinical psychiatric pharmacogenomic implementation holds promise to improve drug effectiveness and safety.
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Affiliation(s)
- Georgia Ragia
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Dragana Campus, Alexandroupolis, 68100, Greece
- Individualised Medicine & Pharmacological Research Solutions (IMPReS) Center, Dragana Campus, Alexandroupolis, 68100, Greece
- DNALEX S.A., Leontaridou 2, Alexandroupolis, 68100, Greece
| | - Myria Pallikarou
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Dragana Campus, Alexandroupolis, 68100, Greece
- Individualised Medicine & Pharmacological Research Solutions (IMPReS) Center, Dragana Campus, Alexandroupolis, 68100, Greece
| | | | - Theofanis Vorvolakos
- Department of Psychiatry, Medical School, Academic General Hospital of Alexandroupolis, Democritus University of Thrace, Dragana Campus, Alexandroupolis, 68100, Greece
| | - Vangelis G Manolopoulos
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Dragana Campus, Alexandroupolis, 68100, Greece
- Individualised Medicine & Pharmacological Research Solutions (IMPReS) Center, Dragana Campus, Alexandroupolis, 68100, Greece
- Clinical Pharmacology Unit, Academic General Hospital of Alexandroupolis, Dragana Campus, Alexandroupolis, 68100, Greece
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Ingelman-Sundberg M, Pirmohamed M. Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment. J Intern Med 2024; 295:583-598. [PMID: 38343077 DOI: 10.1111/joim.13772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.
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Affiliation(s)
- Magnus Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Biomedicum 5B, Karolinska Institutet, Stockholm, Sweden
| | - Munir Pirmohamed
- Wolfson Centre for Personalised Medicine, Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
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Türkmen D, Bowden J, Masoli JAH, Melzer D, Pilling LC. SLCO1B1 Exome Sequencing and Statin Treatment Response in 64,000 UK Biobank Patients. Int J Mol Sci 2024; 25:4426. [PMID: 38674010 PMCID: PMC11050003 DOI: 10.3390/ijms25084426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/12/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
The solute carrier organic anion transporter family member 1B1 (SLCO1B1) encodes the organic anion-transporting polypeptide 1B1 (OATP1B1 protein) that transports statins to liver cells. Common genetic variants in SLCO1B1, such as *5, cause altered systemic exposure to statins and therefore affect statin outcomes, with potential pharmacogenetic applications; yet, evidence is inconclusive. We studied common and rare SLCO1B1 variants in up to 64,000 patients from UK Biobank prescribed simvastatin or atorvastatin, combining whole-exome sequencing data with up to 25-year routine clinical records. We studied 51 predicted gain/loss-of-function variants affecting OATP1B1. Both SLCO1B1*5 alone and the SLCO1B1*15 haplotype increased LDL during treatment (beta*5 = 0.08 mmol/L, p = 6 × 10-8; beta*15 = 0.03 mmol/L, p = 3 × 10-4), as did the likelihood of discontinuing statin prescriptions (hazard ratio*5 = 1.12, p = 0.04; HR*15 = 1.05, p = 0.04). SLCO1B1*15 and SLCO1B1*20 increased the risk of General Practice (GP)-diagnosed muscle symptoms (HR*15 = 1.22, p = 0.003; HR*20 = 1.25, p = 0.01). We estimated that genotype-guided prescribing could potentially prevent 18% and 10% of GP-diagnosed muscle symptoms experienced by statin patients, with *15 and *20, respectively. The remaining common variants were not individually significant. Rare variants in SLCO1B1 increased LDL in statin users by up to 1.05 mmol/L, but replication is needed. We conclude that genotype-guided treatment could reduce GP-diagnosed muscle symptoms in statin patients; incorporating further SLCO1B1 variants into clinical prediction scores could improve LDL control and decrease adverse events, including discontinuation.
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Affiliation(s)
- Deniz Türkmen
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
| | - Jack Bowden
- Exeter Diabetes Group (ExCEED), Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK;
- Department of Genetics, Novo Nordisk Research Centre Oxford, Innovation Building, Old Road Campus, Oxford OX3 7BN, UK
| | - Jane A. H. Masoli
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
- Department of Healthcare for Older People, Royal Devon University Healthcare NHS Foundation Trust, Exeter EX2 5DW, UK
| | - David Melzer
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
| | - Luke C. Pilling
- Epidemiology & Public Health Group, Department of Clinical & Biomedical Science, Faculty of Health & Life Sciences, University of Exeter, Exeter EX4 4QD, UK; (D.T.); (J.A.H.M.); (D.M.)
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Li P, Jiang Z, Liu T, Liu X, Qiao H, Yao X. Improving drug response prediction via integrating gene relationships with deep learning. Brief Bioinform 2024; 25:bbae153. [PMID: 38600666 PMCID: PMC11006795 DOI: 10.1093/bib/bbae153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 03/05/2024] [Accepted: 03/18/2024] [Indexed: 04/12/2024] Open
Abstract
Predicting the drug response of cancer cell lines is crucial for advancing personalized cancer treatment, yet remains challenging due to tumor heterogeneity and individual diversity. In this study, we present a deep learning-based framework named Deep neural network Integrating Prior Knowledge (DIPK) (DIPK), which adopts self-supervised techniques to integrate multiple valuable information, including gene interaction relationships, gene expression profiles and molecular topologies, to enhance prediction accuracy and robustness. We demonstrated the superior performance of DIPK compared to existing methods on both known and novel cells and drugs, underscoring the importance of gene interaction relationships in drug response prediction. In addition, DIPK extends its applicability to single-cell RNA sequencing data, showcasing its capability for single-cell-level response prediction and cell identification. Further, we assess the applicability of DIPK on clinical data. DIPK accurately predicted a higher response to paclitaxel in the pathological complete response (pCR) group compared to the residual disease group, affirming the better response of the pCR group to the chemotherapy compound. We believe that the integration of DIPK into clinical decision-making processes has the potential to enhance individualized treatment strategies for cancer patients.
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Affiliation(s)
- Pengyong Li
- School of Computer Science and Technology,Xidian University, 710126 Xi’an, Shaanxi, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, 519020 Macau, China
| | - Zhengxiang Jiang
- School of Electronic Engineering, Xidian University, 710126 Xi’an, Shaanxi, China
| | - Tianxiao Liu
- School of Computer Science and Technology,Xidian University, 710126 Xi’an, Shaanxi, China
| | - Xinyu Liu
- Beijing Laboratory of Biomedical Materials, Department of Geriatric Dentistry, Peking University School and Hospital of Stomatology, 100081 Beijing, China
| | - Hui Qiao
- Department of Oncology, Tai’an Municipal Hospital, 271021 Tai’an, Shandong, China
| | - Xiaojun Yao
- Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, 999078 Macao, China
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Goljan E, Abouelhoda M, Tahir A, ElKalioby M, Meyer B, Monies D. Large-scale next generation sequencing based analysis of SLCO1B1 pharmacogenetics variants in the Saudi population. Hum Genomics 2024; 18:30. [PMID: 38523294 PMCID: PMC10962151 DOI: 10.1186/s40246-024-00594-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/29/2024] [Indexed: 03/26/2024] Open
Abstract
BACKGROUND SLCO1B1 plays an important role in mediating hepatic clearance of many different drugs including statins, angiotensin-converting enzyme inhibitors, chemotherapeutic agents and antibiotics. Several variants in SLCO1B1 have been shown to have a clinically significant impact, in relation to efficacy of these medications. This study provides a comprehensive overview of SLCO1B1 variation in Saudi individuals, one of the largest Arab populations in the Middle East. METHODS The dataset of 11,889 (9,961 exomes and 1,928 pharmacogenetic gene panel) Saudi nationals, was used to determine the presence and frequencies of SLCO1B1 variants, as described by the Clinical Pharmacogenetic Implementation Consortium (CPIC). RESULTS We identified 141 previously described SNPs, of which rs2306283 (50%) and rs4149056 (28%), were the most common. In addition, we observed six alleles [*15 (24.7%) followed by *20 (8.04%), *14 (5.86%), *5 (3.84%), *31 (0.21%) and *9 (0.03%)] predicted to be clinically actionable. Allele diplotype to phenotype conversion revealed 41 OATP1B1 diplotypes. We estimated the burden of rare, and novel predicted deleterious variants, resulting from 17 such alterations. CONCLUSIONS The data we present, from one of the largest Arab cohorts studied to date, provides the most comprehensive overview of SLCO1B1 variants, and the subsequent OATP1B1 activity of this ethnic group, which thus far remains relatively underrepresented in available international genomic databases. We believe that the presented data provides a basis for further clinical investigations and the application of personalized statin drug therapy guidance in Arabs.
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Affiliation(s)
- Ewa Goljan
- Clinical Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, P.O. Box 3354, Riyadh, 11211, Saudi Arabia
| | - Mohammed Abouelhoda
- Computational Biosciences, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Asma Tahir
- Computational Biosciences, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Mohamed ElKalioby
- Computational Biosciences, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Brian Meyer
- Clinical Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, P.O. Box 3354, Riyadh, 11211, Saudi Arabia
| | - Dorota Monies
- Clinical Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, P.O. Box 3354, Riyadh, 11211, Saudi Arabia.
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12
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Kappel DB, Rees E, Fenner E, King A, Jansen J, Helthuis M, Owen MJ, O'Donovan MC, Walters JTR, Pardiñas AF. Rare variants in pharmacogenes influence clozapine metabolism in individuals with schizophrenia. Eur Neuropsychopharmacol 2024; 80:47-54. [PMID: 38310750 DOI: 10.1016/j.euroneuro.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 12/14/2023] [Accepted: 12/18/2023] [Indexed: 02/06/2024]
Abstract
Clozapine is the only licensed medication for treatment-resistant schizophrenia (TRS). Few predictors for variation in response to clozapine have been identified, but clozapine metabolism is known to influence therapeutic response and adverse side effects. Here, we expand on genome-wide studies of clozapine metabolism, previously focused on common genetic variation, by analysing whole-exome sequencing data from 2062 individuals with schizophrenia taking clozapine in the UK. We investigated whether rare genomic variation in genes and gene sets involved in the clozapine metabolism pathway influences plasma concentrations of clozapine metabolites, assessed through the longitudinal analysis of 6585 pharmacokinetic assays. We observed a statistically significant association between the burden of rare damaging coding variants (MAF ≤ 1 %) in gene sets broadly related to drug pharmacokinetics and lower clozapine (β = -0.054, SE = 0.019, P-value = 0.005) concentrations in plasma. We estimate that the effects in clozapine plasma concentrations of a single damaging allele in this gene set are akin to reducing the clozapine dose by about 35 mg/day. The gene-based analysis identified rare variants in CYP1A2, which encodes the enzyme responsible for converting clozapine to norclozapine, as having the strongest effects of any gene on clozapine metabolism (β = 0.324, SE = 0.124, P = 0.009). Our findings support the hypothesis that rare genetic variants in known drug-metabolising enzymes and transporters can markedly influence clozapine plasma concentrations; these results suggest that pharmacogenomic efforts trying to predict clozapine metabolism and personalise drug therapy could benefit from the inclusion of rare damaging variants in pharmacogenes beyond those already identified and catalogued as PGx star alleles.
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Affiliation(s)
- Djenifer B Kappel
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Elliott Rees
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Eilidh Fenner
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Adrian King
- Magna Laboratories Ltd., Ross-on-Wye, United Kingdom
| | - John Jansen
- Leyden Delta B.V., Nijmegen, The Netherlands
| | | | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Antonio F Pardiñas
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom.
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13
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Zhou Y, Lauschke VM. Next-generation sequencing in pharmacogenomics - fit for clinical decision support? Expert Rev Clin Pharmacol 2024; 17:213-223. [PMID: 38247431 DOI: 10.1080/17512433.2024.2307418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/16/2024] [Indexed: 01/23/2024]
Abstract
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.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
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14
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Tatarūnas V, Čiapienė I, Giedraitienė A. Precise Therapy Using the Selective Endogenous Encapsidation for Cellular Delivery Vector System. Pharmaceutics 2024; 16:292. [PMID: 38399346 PMCID: PMC10893373 DOI: 10.3390/pharmaceutics16020292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/13/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
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.
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Affiliation(s)
- Vacis Tatarūnas
- Institute of Cardiology, Lithuanian University of Health Sciences, Sukileliu 15, LT 50103 Kaunas, Lithuania; (V.T.); (I.Č.)
| | - Ieva Čiapienė
- Institute of Cardiology, Lithuanian University of Health Sciences, Sukileliu 15, LT 50103 Kaunas, Lithuania; (V.T.); (I.Č.)
| | - Agnė Giedraitienė
- Institute of Microbiology and Virology, Lithuanian University of Health Sciences, Eiveniu 4, LT 50161 Kaunas, Lithuania
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15
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Müller JP, Sarömba J, Ziegler P, Tremmel R, Rengelshausen J, Schaeffeler E, Just KS, Schwab M, Kraus T, Stingl JC. Nutrimetric Validation of Solanidine as Dietary-Derived CYP2D6 Activity Marker In Vivo. Clin Pharmacol Ther 2024; 115:309-317. [PMID: 37971251 DOI: 10.1002/cpt.3106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 11/01/2023] [Indexed: 11/19/2023]
Abstract
CYP2D6 is involved in the metabolism of many drugs. Its activity is affected by pharmacogenetic variability leading to highly polymorphic phenotypes between individuals, affecting safety and efficacy of drugs. Recently, solanidine, a steroidal alkaloid from potatoes, and its metabolites, has been identified as a dietary-derived activity marker for CYP2D6. The intraday variability in plasma within individuals has not been studied yet in healthy subjects. As part of a CYP phenotyping cocktail study with 20 healthy participants, plasma concentrations of solanidine, 4-OH-solanidine and 3,4-secosolanidine-3,4-dioic acid (SSDA) were determined using a sensitive liquid chromatography-mass spectrometry method in urine and in plasma at timepoints 0, 2.5, 5, 8, and 24 hours after intake of test substances. The participants were phenotyped for CYP2D6 with oral metoprolol (12.5 mg) with 15 plasma sampling points over 24 hours (DRKS00028922). Metabolic ratios (MRs) of metabolite to parent plasma concentrations were formed from single timepoints and the area under the curve (AUC). All participants were genotyped for CYP2D6. The intra-individual variability of the CYP2D6 metabolite SSDA was highly stable with a median SD of 11.62% over 24 hours. MR SSDA/solanidine was more variable (median SD 31.90%) but correlated significantly at all measured timepoints with AUC MR α-OH-metoprolol/metoprolol. The AUC MR SSDA/solanidine showed a significant linear relationship with the genetically predicted CYP2D6 activity score. This study substantiates the MR SSDA/solanidine as CYP2D6 activity marker. The high correlation with metoprolol MR indicates a valid prediction of the CYP2D6 phenotype at any timepoint during the study day.
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Affiliation(s)
- Julian Peter Müller
- Institute of Clinical Pharmacology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Jens Sarömba
- Institute of Clinical Pharmacology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Patrick Ziegler
- Institute for Occupational, Social and Environmental Medicine, University Hospital of RWTH Aachen, Aachen, Germany
| | - Roman Tremmel
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart and University of Tuebingen, Tuebingen, Germany
| | - Jens Rengelshausen
- Institute for Occupational, Social and Environmental Medicine, University Hospital of RWTH Aachen, Aachen, Germany
| | - Elke Schaeffeler
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart and University of Tuebingen, Tuebingen, Germany
| | - Katja S Just
- Institute of Clinical Pharmacology, University Hospital of RWTH Aachen, Aachen, Germany
| | - Matthias Schwab
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart and University of Tuebingen, Tuebingen, Germany
- Departments of Clinical Pharmacology, and Pharmacy and Biochemistry, University of Tuebingen, Tuebingen, Germany
| | - Thomas Kraus
- Institute for Occupational, Social and Environmental Medicine, University Hospital of RWTH Aachen, Aachen, Germany
| | - Julia C Stingl
- Institute of Clinical Pharmacology, University Hospital of RWTH Aachen, Aachen, Germany
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16
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Lauschke VM, Zhou Y, Ingelman-Sundberg M. Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward. Annu Rev Pharmacol Toxicol 2024; 64:33-51. [PMID: 37506333 DOI: 10.1146/annurev-pharmtox-051921-091209] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2023]
Abstract
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.
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Affiliation(s)
- Volker M Lauschke
- Dr. Margarete Fischer-Bosch Institute for Clinical Pharmacology, Stuttgart, Germany
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden;
- Tübingen University, Tübingen, Germany
| | - Yitian Zhou
- Dr. Margarete Fischer-Bosch Institute for Clinical Pharmacology, Stuttgart, Germany
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden;
- Tübingen University, Tübingen, Germany
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17
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Larrue R, Fellah S, Hennart B, Sabaouni N, Boukrout N, Van der Hauwaert C, Delage C, Cheok M, Perrais M, Cauffiez C, Allorge D, Pottier N. Integrating rare genetic variants into DPYD pharmacogenetic testing may help preventing fluoropyrimidine-induced toxicity. THE PHARMACOGENOMICS JOURNAL 2024; 24:1. [PMID: 38216550 PMCID: PMC10786722 DOI: 10.1038/s41397-023-00322-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 10/23/2023] [Accepted: 12/05/2023] [Indexed: 01/14/2024]
Abstract
Variability in genes involved in drug pharmacokinetics or drug response can be responsible for suboptimal treatment efficacy or predispose to adverse drug reactions. In addition to common genetic variations, large-scale sequencing studies have uncovered multiple rare genetic variants predicted to cause functional alterations in genes encoding proteins implicated in drug metabolism, transport and response. To understand the functional importance of rare genetic variants in DPYD, a pharmacogene whose alterations can cause severe toxicity in patients exposed to fluoropyrimidine-based regimens, massively parallel sequencing of the exonic regions and flanking splice junctions of the DPYD gene was performed in a series of nearly 3000 patients categorized according to pre-emptive DPD enzyme activity using the dihydrouracil/uracil ([UH2]/[U]) plasma ratio as a surrogate marker of DPD activity. Our results underscore the importance of integrating next-generation sequencing-based pharmacogenomic interpretation into clinical decision making to minimize fluoropyrimidine-based chemotherapy toxicity without altering treatment efficacy.
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Affiliation(s)
- Romain Larrue
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France.
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France.
| | - Sandy Fellah
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Benjamin Hennart
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Naoual Sabaouni
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Nihad Boukrout
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Cynthia Van der Hauwaert
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Clément Delage
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Meyling Cheok
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Michaël Perrais
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Christelle Cauffiez
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
| | - Delphine Allorge
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
| | - Nicolas Pottier
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277-CANTHER-Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France
- Service de Toxicologie et Génopathies, CHU Lille, F-59000, Lille, France
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18
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Ingelman-Sundberg M, Nebert DW, Lauschke VM. Emerging trends in pharmacogenomics: from common variant associations toward comprehensive genomic profiling. Hum Genomics 2023; 17:105. [PMID: 37996916 PMCID: PMC10668450 DOI: 10.1186/s40246-023-00554-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 11/14/2023] [Indexed: 11/25/2023] Open
Affiliation(s)
| | - Daniel W Nebert
- Department of Environmental and Public Health Sciences, Center for Environmental Genetics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Department of Pediatrics and Molecular & Developmental Biology, Cincinnati Children's Research Center, Cincinnati, OH, 45229, USA
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tübingen, Tübingen, Germany.
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19
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De Mattia E, Polesel J, Silvestri M, Roncato R, Scarabel L, Calza S, Spina M, Puglisi F, Toffoli G, Cecchin E. The burden of rare variants in DPYS gene is a novel predictor of the risk of developing severe fluoropyrimidine-related toxicity. Hum Genomics 2023; 17:99. [PMID: 37946254 PMCID: PMC10633914 DOI: 10.1186/s40246-023-00546-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 10/26/2023] [Indexed: 11/12/2023] Open
Abstract
BACKGROUND Despite a growing number of publications highlighting the potential impact on the therapy outcome, rare genetic variants (minor allele frequency < 1%) in genes associated to drug adsorption, distribution, metabolism, and elimination are poorly studied. Previously, rare germline DPYD missense variants were shown to identify a subset of fluoropyrimidine-treated patients at high risk for severe toxicity. Here, we investigate the impact of rare genetic variants in a panel of 54 other fluoropyrimidine-related genes on the risk of severe toxicity. METHODS The coding sequence and untranslated regions of 54 genes related to fluoropyrimidine pharmacokinetics/pharmacodynamics were analyzed by next-generation sequencing in 120 patients developing grade 3-5 toxicity (NCI-CTC vs3.0) and 104 matched controls. Sequence Kernel Association Test (SKAT) analysis was used to select genes with a burden of genetic variants significantly associated with risk of severe toxicity. The statistical association of common and rare genetic variants in selected genes was further investigated. The functional impact of genetic variants was assessed using two different in silico prediction tools (Predict2SNP; ADME Prediction Framework). RESULTS SKAT analysis highlighted DPYS and PPARD as genes with a genetic mutational burden significantly associated with risk of severe fluoropyrimidine-related toxicity (Bonferroni adjusted P = 0.024 and P = 0.039, respectively). Looking more closely at allele frequency, the burden of rare DPYS variants was significantly higher in patients with toxicity compared with controls (P = 0.047, Mann-Whitney test). Carrying at least one rare DPYS variant was associated with an approximately fourfold higher risk of severe cumulative (OR = 4.08, P = 0.030) and acute (OR = 4.21, P = 0.082) toxicity. The burden of PPARD rare genetic variants was not significantly related to toxicity. Some common variants with predictive value in DPYS and PPARD were also identified: DPYS rs143004875-T and PPARD rs2016520-T variants predicted an increased risk of severe cumulative (P = 0.002 and P = 0.001, respectively) and acute (P = 0.005 and P = 0.0001, respectively) toxicity. CONCLUSION This work demonstrated that the rare mutational burden of DPYS, a gene strictly cooperating with DPYD in the catabolic pathway of fluoropyrimidines, is a promising pharmacogenetic marker for precision dosing of fluoropyrimidines. Additionally, some common genetic polymorphisms in DPYS and PPARD were identified as promising predictive markers that warrant further investigation.
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Affiliation(s)
- Elena De Mattia
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
| | - Jerry Polesel
- Unit of Cancer Epidemiology, Centro Di Riferimento Oncologico Di Aviano (CRO) IRCCS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
| | - Marco Silvestri
- Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Via Giacomo Venezian 1, 20133, Milan, Italy
| | - Rossana Roncato
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
| | - Lucia Scarabel
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
| | - Stefano Calza
- Department of Molecular and Translational Medicine, University of Brescia, Viale Europa 11, 25123, Brescia, Italy
| | - Michele Spina
- Department of Medical Oncology, Centro di Riferimento Oncologico di Aviano (CRO), IRCSS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
| | - Fabio Puglisi
- Department of Medical Oncology, Centro di Riferimento Oncologico di Aviano (CRO), IRCSS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
- Department of Medicine, University of Udine, Via Delle Scienze, 206, 33100, Udine, UD, Italy
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy
| | - Erika Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Via Franco Gallini n. 2, 33081, Aviano, PN, Italy.
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20
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Park Y, Lauschke V. Towards more accurate pharmacogenomic variant effect predictions. Pharmacogenomics 2023; 24:841-844. [PMID: 37846582 DOI: 10.2217/pgs-2023-0187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2023] Open
Abstract
Tweetable abstract Accurate variant interpretation has become a key bottleneck for the translation of an individual's pharmacogenome into actionable recommendations. We recommend an integrated use of multiplexed assays, structure-based predictions and biobank data to develop more accurate effect predictors.
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Affiliation(s)
- Yoomi Park
- Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, South Korea
- Medical Research Center, Seoul National University College of Medicine, Seoul, South Korea
| | - Volker Lauschke
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
- University of Tübingen, Tübingen, Germany
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21
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Tremmel R, Zhou Y, Schwab M, Lauschke VM. Structural variation of the coding and non-coding human pharmacogenome. NPJ Genom Med 2023; 8:24. [PMID: 37684227 PMCID: PMC10491600 DOI: 10.1038/s41525-023-00371-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 08/29/2023] [Indexed: 09/10/2023] Open
Abstract
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.
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Affiliation(s)
- Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University Tübingen, Tübingen, Germany
| | - Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Matthias Schwab
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University Tübingen, Tübingen, Germany
- Departments of Clinical Pharmacology and Pharmacy and Biochemistry, University Tübingen, Tübingen, Germany
| | - Volker M Lauschke
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University Tübingen, Tübingen, Germany.
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
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22
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Sandhu AK, Naderi E, Wijninga MJ, Liemburg EJ, Cath D, Bruggeman R, Alizadeh BZ. Pharmacogenetics of Long-Term Outcomes of Schizophrenia Spectrum Disorders: The Functional Role of CYP2D6 and CYP2C19. J Pers Med 2023; 13:1354. [PMID: 37763122 PMCID: PMC10532576 DOI: 10.3390/jpm13091354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/25/2023] [Accepted: 08/27/2023] [Indexed: 09/29/2023] Open
Abstract
Schizophrenia spectrum disorders (SSD) are complex mental disorders, and while treatment with antipsychotics is important, many patients do not respond or develop serious side effects. Genetic variation has been shown to play a considerable role in determining an individual's response to antipsychotic medication. However, previous pharmacogenetic (PGx) studies have been limited by small sample sizes, lack of consensus regarding relevant genetic variants, and cross-sectional designs. The current study aimed to investigate the association between PGx variants and long-term clinical outcomes in 691 patients of European ancestry with SSD. Using evidence from the literature on candidate genes involved in antipsychotic pharmacodynamics, we created a polygenic risk score (PRS) to investigate its association with clinical outcomes. We also created PRS using core variants of psychotropic drug metabolism enzymes CYP2D6 and CYP2C19. Furthermore, the CYP2D6 and CYP2C19 functional activity scores were calculated to determine the relationship between metabolism and clinical outcomes. We found no association for PGx PRSs and clinical outcomes; however, an association was found with CYP2D6 activity scores by the traditional method. Higher CYP2D6 metabolism was associated with high positive and high cognitive impairment groups relative to low symptom severity groups. These findings highlight the need to test PGx efficacy with different symptom domains. More evidence is needed before pharmacogenetic variation can contribute to personalized treatment plans.
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Affiliation(s)
- Amrit K. Sandhu
- Department of Epidemiology, University Medical Centre Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Elnaz Naderi
- Department of Epidemiology, University Medical Centre Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
- Centre for Statistical Genetics, Gertude H. Sergiesky Centre, Department of Neurology, Columbia University Medical Centre, New York, NY 10032, USA
| | - Morenika J. Wijninga
- Department of Epidemiology, University Medical Centre Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Edith J. Liemburg
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | | | - Danielle Cath
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
- GGZ Drenthe, Department of Specialist Trainings, 9704 LA Assen, The Netherlands
| | - Richard Bruggeman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
| | - Behrooz Z. Alizadeh
- Department of Epidemiology, University Medical Centre Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
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23
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Suominen L, Sjöstedt N, Vellonen KS, Gynther M, Auriola S, Kidron H. In vitro identification of decreased function phenotype ABCG2 variants. Eur J Pharm Sci 2023; 188:106527. [PMID: 37451410 DOI: 10.1016/j.ejps.2023.106527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/09/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023]
Abstract
Reduced activity of efflux transporter ABCG2, caused e.g., by inhibition or decreased function genetic variants, can increase drug absorption and plasma levels. ABCG2 has one clinically significant single nucleotide variant Q141K (c.421C>A), which leads to decreased protein levels and transport activity. In addition to Q141K, ABCG2 has over 500 rare (<1% minor allele frequency) nonsynonymous variants, but their functionality remains unknown. We studied the transport activity and abundance of 30 rare ABCG2 variants. The variants were transiently expressed in HEK293 cells. Transport activity and protein abundance were measured from inside-out crude membrane vesicles. Results were normalised to the reference ABCG2, while Q141K was used to categorise variants into decreased and normal function phenotypes based on their apparent transport activity. Fourteen variants (G80E, D128V, T434M, Q437R, C438R, C438W, C438Y, L479S, P480L, S486N, T512N, S519P, G553D and K647E) had similar or lower apparent transport activity than Q141K and thus were categorised as having a decreased function phenotype. Protein abundance could not explain all of the observed changes in transport activity: Only six variants (D128V, Q437R, C438R, S519P, G553D, and K647E) had similar or lower abundance compared to Q141K. The decreased function variants may increase systemic drug exposure and therefore cause interindividual variability in pharmacokinetics. In the future, in vitro phenotype classification may help to design personalised drug treatments.
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Affiliation(s)
- Laura Suominen
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki FI-00014, Finland
| | - Noora Sjöstedt
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki FI-00014, Finland
| | | | - Mikko Gynther
- School of Pharmacy, University of Eastern Finland, Kuopio FI-70210, Finland
| | - Seppo Auriola
- School of Pharmacy, University of Eastern Finland, Kuopio FI-70210, Finland
| | - Heidi Kidron
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Helsinki FI-00014, Finland.
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24
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Sinha K, Ghosh N, Sil PC. A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies. Chem Res Toxicol 2023; 36:1174-1205. [PMID: 37561655 DOI: 10.1021/acs.chemrestox.2c00375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Drug toxicity prediction is an important step in ensuring patient safety during drug design studies. While traditional preclinical studies have historically relied on animal models to evaluate toxicity, recent advances in deep-learning approaches have shown great promise in advancing drug safety science and reducing animal use in preclinical studies. However, deep-learning-based approaches also face challenges in handling large biological data sets, model interpretability, and regulatory acceptance. In this review, we provide an overview of recent developments in deep-learning-based approaches for predicting drug toxicity, highlighting their potential advantages over traditional methods and the need to address their limitations. Deep-learning models have demonstrated excellent performance in predicting toxicity outcomes from various data sources such as chemical structures, genomic data, and high-throughput screening assays. The potential of deep learning for automated feature engineering is also discussed. This review emphasizes the need to address ethical concerns related to the use of deep learning in drug toxicity studies, including the reduction of animal use and ensuring regulatory acceptance. Furthermore, emerging applications of deep learning in drug toxicity prediction, such as predicting drug-drug interactions and toxicity in rare subpopulations, are highlighted. The integration of deep-learning-based approaches with traditional methods is discussed as a way to develop more reliable and efficient predictive models for drug safety assessment, paving the way for safer and more effective drug discovery and development. Overall, this review highlights the critical role of deep learning in predictive toxicology and drug safety evaluation, emphasizing the need for continued research and development in this rapidly evolving field. By addressing the limitations of traditional methods, leveraging the potential of deep learning for automated feature engineering, and addressing ethical concerns, deep-learning-based approaches have the potential to revolutionize drug toxicity prediction and improve patient safety in drug discovery and development.
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Affiliation(s)
- Krishnendu Sinha
- Department of Zoology, Jhargram Raj College, Jhargram 721507, West Bengal, India
| | - Nabanita Ghosh
- Department of Zoology, Maulana Azad College, Kolkata 700013, West Bengal, India
| | - Parames C Sil
- Division of Molecular Medicine, Bose Institute, Kolkata 700054, West Bengal, India
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25
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de Jong LM, Boussallami S, Sánchez-López E, Giera M, Tushuizen ME, Hoekstra M, Hawinkels LJAC, Rissmann R, Swen JJ, Manson ML. The impact of CYP2C19 genotype on phenoconversion by concomitant medication. Front Pharmacol 2023; 14:1201906. [PMID: 37361233 PMCID: PMC10285291 DOI: 10.3389/fphar.2023.1201906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 05/19/2023] [Indexed: 06/28/2023] Open
Abstract
Introduction: Pharmacogenetics-informed drug prescribing is increasingly applied in clinical practice. Typically, drug metabolizing phenotypes are determined based on genetic test results, whereupon dosage or drugs are adjusted. Drug-drug-interactions (DDIs) caused by concomitant medication can however cause mismatches between predicted and observed phenotypes (phenoconversion). Here we investigated the impact of CYP2C19 genotype on the outcome of CYP2C19-dependent DDIs in human liver microsomes. Methods: Liver samples from 40 patients were included, and genotyped for CYP2C19*2, *3 and *17 variants. S-mephenytoin metabolism in microsomal fractions was used as proxy for CYP2C19 activity, and concordance between genotype-predicted and observed CYP2C19 phenotype was examined. Individual microsomes were subsequently co-exposed to fluvoxamine, voriconazole, omeprazole or pantoprazole to simulate DDIs. Results: Maximal CYP2C19 activity (Vmax) in genotype-predicted intermediate metabolizers (IMs; *1/*2 or *2/*17), rapid metabolizers (RMs; *1/*17) and ultrarapid metabolizers (UMs; *17/*17) was not different from Vmax of predicted normal metabolizers (NMs; *1/*1). Conversely, CYP2C19*2/*2 genotyped-donors exhibited Vmax rates ∼9% of NMs, confirming the genotype-predicted poor metabolizer (PM) phenotype. Categorizing CYP2C19 activity, we found a 40% concordance between genetically-predicted CYP2C19 phenotypes and measured phenotypes, indicating substantial phenoconversion. Eight patients (20%) exhibited CYP2C19 IM/PM phenotypes that were not predicted by their CYP2C19 genotype, of which six could be linked to the presence of diabetes or liver disease. In subsequent DDI experiments, CYP2C19 activity was inhibited by omeprazole (-37% ± 8%), voriconazole (-59% ± 4%) and fluvoxamine (-85% ± 2%), but not by pantoprazole (-2 ± 4%). The strength of CYP2C19 inhibitors remained unaffected by CYP2C19 genotype, as similar percental declines in CYP2C19 activity and comparable metabolism-dependent inhibitory constants (Kinact/KI) of omeprazole were observed between CYP2C19 genotypes. However, the consequences of CYP2C19 inhibitor-mediated phenoconversion were different between CYP2C19 genotypes. In example, voriconazole converted 50% of *1/*1 donors to a IM/PM phenotype, but only 14% of *1/*17 donors. Fluvoxamine converted all donors to phenotypic IMs/PMs, but *1/*17 (14%) were less likely to become PMs than *1/*1 (50%) or *1/*2 and *2/*17 (57%). Conclusion: This study suggests that the differential outcome of CYP2C19-mediated DDIs between genotypes are primarily dictated by basal CYP2C19 activity, that may in part be predicted by CYP2C19 genotype but likely also depends on disease-related factors.
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Affiliation(s)
- Laura M. de Jong
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, Netherlands
| | - Soukayna Boussallami
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, Netherlands
| | - Elena Sánchez-López
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands
| | - Maarten E. Tushuizen
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, Netherlands
| | - Menno Hoekstra
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, Netherlands
| | - Lukas J. A. C. Hawinkels
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, Netherlands
| | - Robert Rissmann
- Centre for Human Drug Research, Leiden, Netherlands
- Division of BioTherapeutics, Leiden Academic Centre for Drug Research, Leiden, Netherlands
- Department of Dermatology, Leiden University Medical Center, Leiden, Netherlands
| | - Jesse J. Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Martijn L. Manson
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden, Netherlands
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26
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Atiq MA, Peterson SE, Langman LJ, Baudhuin LM, Black JL, Moyer AM. Determination of the Duplicated CYP2D6 Allele Using Real-Time PCR Signal: An Alternative Approach. J Pers Med 2023; 13:883. [PMID: 37373874 DOI: 10.3390/jpm13060883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 05/17/2023] [Accepted: 05/20/2023] [Indexed: 06/29/2023] Open
Abstract
CYP2D6 duplication has important pharmacogenomic implications. Reflex testing with long-range PCR (LR-PCR) can resolve the genotype when a duplication and alleles with differing activity scores are detected. We evaluated whether visual inspection of plots from real-time-PCR-based targeted genotyping with copy number variation (CNV) detection could reliably determine the duplicated CYP2D6 allele. Six reviewers evaluated QuantStudio OpenArray CYP2D6 genotyping results and the TaqMan Genotyper plots for seventy-three well-characterized cases with three copies of CYP2D6 and two different alleles. Reviewers blinded to the final genotype visually assessed the plots to determine the duplicated allele or opt for reflex sequencing. Reviewers achieved 100% accuracy for cases with three CYP2D6 copies that they opted to report. Reviewers did not request reflex sequencing in 49-67 (67-92%) cases (and correctly identified the duplicated allele in each case); all remaining cases (6-24) were marked by at least one reviewer for reflex sequencing. In most cases with three copies of CYP2D6, the duplicated allele can be determined using a combination of targeted genotyping using real-time PCR with CNV detection without need for reflex sequencing. In ambiguous cases and those with >3 copies, LR-PCR and Sanger sequencing may still be necessary for determination of the duplicated allele.
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Affiliation(s)
- Mazen A Atiq
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Sandra E Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Loralie J Langman
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Linnea M Baudhuin
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - John L Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN 55905, USA
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27
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Maslarinou A, Manolopoulos VG, Ragia G. Pharmacogenomic-guided dosing of fluoropyrimidines beyond DPYD: time for a polygenic algorithm? Front Pharmacol 2023; 14:1184523. [PMID: 37256234 PMCID: PMC10226670 DOI: 10.3389/fphar.2023.1184523] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 04/19/2023] [Indexed: 06/01/2023] Open
Abstract
Fluoropyrimidines are chemotherapeutic agents widely used for the treatment of various solid tumors. Commonly prescribed FPs include 5-fluorouracil (5-FU) and its oral prodrugs capecitabine (CAP) and tegafur. Bioconversion of 5-FU prodrugs to 5-FU and subsequent metabolic activation of 5-FU are required for the formation of fluorodeoxyuridine triphosphate (FdUTP) and fluorouridine triphosphate, the active nucleotides through which 5-FU exerts its antimetabolite actions. A significant proportion of FP-treated patients develop severe or life-threatening, even fatal, toxicity. It is well known that FP-induced toxicity is governed by genetic factors, with dihydropyrimidine dehydrogenase (DPYD), the rate limiting enzyme in 5-FU catabolism, being currently the cornerstone of FP pharmacogenomics. DPYD-based dosing guidelines exist to guide FP chemotherapy suggesting significant dose reductions in DPYD defective patients. Accumulated evidence shows that additional variations in other genes implicated in FP pharmacokinetics and pharmacodynamics increase risk for FP toxicity, therefore taking into account more gene variations in FP dosing guidelines holds promise to improve FP pharmacotherapy. In this review we describe the current knowledge on pharmacogenomics of FP-related genes, beyond DPYD, focusing on FP toxicity risk and genetic effects on FP dose reductions. We propose that in the future, FP dosing guidelines may be expanded to include a broader ethnicity-based genetic panel as well as gene*gene and gender*gene interactions towards safer FP prescription.
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Affiliation(s)
- Anthi Maslarinou
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Individualised Medicine and Pharmacological Research Solutions Center, Alexandroupolis, Greece
| | - Vangelis G. Manolopoulos
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Individualised Medicine and Pharmacological Research Solutions Center, Alexandroupolis, Greece
- Clinical Pharmacology Unit, Academic General Hospital of Alexandroupolis, Alexandroupolis, Greece
| | - Georgia Ragia
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, Greece
- Individualised Medicine and Pharmacological Research Solutions Center, Alexandroupolis, Greece
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28
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Bertholim-Nasciben L, Scliar MO, Debortoli G, Thiruvahindrapuram B, Scherer SW, Duarte YAO, Zatz M, Suarez-Kurtz G, Parra EJ, Naslavsky MS. Characterization of pharmacogenomic variants in a Brazilian admixed cohort of elderly individuals based on whole-genome sequencing data. Front Pharmacol 2023; 14:1178715. [PMID: 37234706 PMCID: PMC10206227 DOI: 10.3389/fphar.2023.1178715] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 04/10/2023] [Indexed: 05/28/2023] Open
Abstract
Introduction: Research in the field of pharmacogenomics (PGx) aims to identify genetic variants that modulate response to drugs, through alterations in their pharmacokinetics (PK) or pharmacodynamics (PD). The distribution of PGx variants differs considerably among populations, and whole-genome sequencing (WGS) plays a major role as a comprehensive approach to detect both common and rare variants. This study evaluated the frequency of PGx markers in the context of the Brazilian population, using data from a population-based admixed cohort from Sao Paulo, Brazil, which includes variants from WGS of 1,171 unrelated, elderly individuals. Methods: The Stargazer tool was used to call star alleles and structural variants (SVs) from 38 pharmacogenes. Clinically relevant variants were investigated, and the predicted drug response phenotype was analyzed in combination with the medication record to assess individuals potentially at high-risk of gene-drug interaction. Results: In total, 352 unique star alleles or haplotypes were observed, of which 255 and 199 had a frequency < 0.05 and < 0.01, respectively. For star alleles with frequency > 5% (n = 97), decreased, loss-of-function and unknown function accounted for 13.4%, 8.2% and 27.8% of alleles or haplotypes, respectively. Structural variants (SVs) were identified in 35 genes for at least one individual, and occurred with frequencies >5% for CYP2D6, CYP2A6, GSTM1, and UGT2B17. Overall 98.0% of the individuals carried at least one high risk genotype-predicted phenotype in pharmacogenes with PharmGKB level of evidence 1A for drug interaction. The Electronic Health Record (EHR) Priority Result Notation and the cohort medication registry were combined to assess high-risk gene-drug interactions. In general, 42.0% of the cohort used at least one PharmGKB evidence level 1A drug, and 18.9% of individuals who used PharmGKB evidence level 1A drugs had a genotype-predicted phenotype of high-risk gene-drug interaction. Conclusion: This study described the applicability of next-generation sequencing (NGS) techniques for translating PGx variants into clinically relevant phenotypes on a large scale in the Brazilian population and explores the feasibility of systematic adoption of PGx testing in Brazil.
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Affiliation(s)
- Luciana Bertholim-Nasciben
- School of Public Health, University of São Paulo, São Paulo, Brazil
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Marilia O. Scliar
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Guilherme Debortoli
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | | | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Yeda A. O. Duarte
- Medical-Surgical Nursing Department, School of Nursing, University of São Paulo, São Paulo, Brazil
| | - Mayana Zatz
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Guilherme Suarez-Kurtz
- Divisão de Pesquisa Clínica e Desenvolvimento Tecnológico, Instituto Nacional de Câncer, Rio de Janeiro, Brazil
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | - Michel S. Naslavsky
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
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29
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Nunez-Torres R, Pita G, Peña-Chilet M, López-López D, Zamora J, Roldán G, Herráez B, Álvarez N, Alonso MR, Dopazo J, Gonzalez-Neira A. A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact. Pharmaceutics 2023; 15:pharmaceutics15041286. [PMID: 37111771 PMCID: PMC10140932 DOI: 10.3390/pharmaceutics15041286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/03/2023] [Accepted: 04/16/2023] [Indexed: 04/29/2023] Open
Abstract
The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.
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Affiliation(s)
- Rocio Nunez-Torres
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Guillermo Pita
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - María Peña-Chilet
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centre for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, 41013 Sevilla, Spain
- Computational Systems Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Seville, Spain
| | - Daniel López-López
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centre for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, 41013 Sevilla, Spain
- Computational Systems Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Seville, Spain
| | - Jorge Zamora
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Gema Roldán
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
| | - Belén Herráez
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Nuria Álvarez
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - María Rosario Alonso
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Joaquín Dopazo
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centre for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, 41013 Sevilla, Spain
- Computational Systems Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Seville, Spain
- Functional Genomics Node, FPS/ELIXIR-ES, Hospital Virgen del Rocío, 41013 Sevilla, Spain
| | - Anna Gonzalez-Neira
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
- Centre for Biomedical Network Research on Rare Diseases (CIBERER-U706), ISCIII, 28029 Madrid, Spain
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30
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Khor CC, Winter S, Sutiman N, Mürdter TE, Chen S, Lim JSL, Li Z, Li J, Sim KS, Ganchev B, Eccles D, Eccles B, Tapper W, Zgheib NK, Tfayli A, Ng RCH, Yap YS, Lim E, Wong M, Wong NS, Ang PCS, Dent R, Tremmel R, Klein K, Schaeffeler E, Zhou Y, Lauschke VM, Eichelbaum M, Schwab M, Brauch HB, Chowbay B, Schroth W. Cross-Ancestry Genome-Wide Association Study Defines the Extended CYP2D6 Locus as the Principal Genetic Determinant of Endoxifen Plasma Concentrations. Clin Pharmacol Ther 2023; 113:712-723. [PMID: 36629403 DOI: 10.1002/cpt.2846] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 12/23/2022] [Indexed: 01/12/2023]
Abstract
The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (n = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (n = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (n = 287, n = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (ρ = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (n = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R2 ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.
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Affiliation(s)
- Chiea Chuen Khor
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore.,Singapore Eye Research Institute, Singapore, Singapore.,Clinical Pharmacology, SingHealth, Singapore, Singapore
| | - Stefan Winter
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
| | - Natalia Sutiman
- Clinical Pharmacology Laboratory, Division of Cellular and Molecular Research, National Cancer Centre, Singapore, Singapore
| | - Thomas E Mürdter
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
| | - Sylvia Chen
- Clinical Pharmacology Laboratory, Division of Cellular and Molecular Research, National Cancer Centre, Singapore, Singapore
| | - Joanne Siok Liu Lim
- Clinical Pharmacology Laboratory, Division of Cellular and Molecular Research, National Cancer Centre, Singapore, Singapore
| | - Zheng Li
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Jingmei Li
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Kar Seng Sim
- Division of Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Boian Ganchev
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
| | - Diana Eccles
- Faculty of Medicine, Cancer Sciences Academic Unit and University of Southampton Clinical Trials Unit, University of Southampton, Southampton, UK.,University Hospital Southampton National Health Service Foundation Trust, Southampton, UK
| | - Bryony Eccles
- Faculty of Medicine, Cancer Sciences Academic Unit and University of Southampton Clinical Trials Unit, University of Southampton, Southampton, UK.,University Hospital Southampton National Health Service Foundation Trust, Southampton, UK
| | - William Tapper
- Faculty of Medicine, Cancer Sciences Academic Unit and University of Southampton Clinical Trials Unit, University of Southampton, Southampton, UK.,University Hospital Southampton National Health Service Foundation Trust, Southampton, UK
| | - Nathalie K Zgheib
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Arafat Tfayli
- Hematology-Oncology Division, Department of Internal Medicine, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | | | - Yoon Sim Yap
- Division of Medical Oncology, National Cancer Centre, Singapore, Singapore
| | - Elaine Lim
- Division of Medical Oncology, National Cancer Centre, Singapore, Singapore
| | - Mabel Wong
- Division of Medical Oncology, National Cancer Centre, Singapore, Singapore
| | - Nan Soon Wong
- OncoCare Cancer Centre, Mount Elizabeth Novena Medical Centre, Singapore, Singapore
| | - Peter Cher Siang Ang
- OncoCare Cancer Centre, Mount Elizabeth Novena Medical Centre, Singapore, Singapore
| | - Rebecca Dent
- Division of Medical Oncology, National Cancer Centre, Singapore, Singapore
| | - Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
| | - Kathrin Klein
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
| | - Elke Schaeffeler
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany.,Image-Guided and Functionally Instructed Tumor Therapies Cluster of Excellence (iFIT), University of Tübingen, Tübingen, Germany
| | - Yitian Zhou
- Department of Laboratory Medicine, Karolinska Institute, Stockholm, Sweden
| | - Volker M Lauschke
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany.,Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden
| | - Michel Eichelbaum
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
| | - Matthias Schwab
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,Image-Guided and Functionally Instructed Tumor Therapies Cluster of Excellence (iFIT), University of Tübingen, Tübingen, Germany.,Department of Clinical Pharmacology, University of Tübingen, Tübingen, Germany.,Department of Biochemistry and Pharmacy, University of Tübingen, Tübingen, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center, Partner Site Tübingen, Tübingen, Germany
| | - Hiltrud B Brauch
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany.,Image-Guided and Functionally Instructed Tumor Therapies Cluster of Excellence (iFIT), University of Tübingen, Tübingen, Germany.,German Cancer Consortium (DKTK), German Cancer Research Center, Partner Site Tübingen, Tübingen, Germany
| | - Balram Chowbay
- Clinical Pharmacology, SingHealth, Singapore, Singapore.,Clinical Pharmacology Laboratory, Division of Cellular and Molecular Research, National Cancer Centre, Singapore, Singapore.,Centre for Clinician-Scientist Development, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Werner Schroth
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.,University Tübingen, Tübingen, Germany
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Abstract
Inter-individual variability in drug response, be it efficacy or safety, is common and likely to become an increasing problem globally given the growing elderly population requiring treatment. Reasons for this inter-individual variability include genomic factors, an area of study called pharmacogenomics. With genotyping technologies now widely available and decreasing in cost, implementing pharmacogenomics into clinical practice - widely regarded as one of the initial steps in mainstreaming genomic medicine - is currently a focus in many countries worldwide. However, major challenges of implementation lie at the point of delivery into health-care systems, including the modification of current clinical pathways coupled with a massive knowledge gap in pharmacogenomics in the health-care workforce. Pharmacogenomics can also be used in a broader sense for drug discovery and development, with increasing evidence suggesting that genomically defined targets have an increased success rate during clinical development.
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32
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Dheyaa Aziz N, Abbood SH, Al-Mayali AH, Hadi NR. ASSOCIATION OF SOLUTE CARRIER ORGANIC ANION TRANSPORTER 1B1 GENE POLYMORPHISM WITH RESPONSE TO ATORVASTATIN AND ASSOCIATED MYOPATHY IN IRAQI DYSLIPIDEMIA PATIENTS. POLSKI MERKURIUSZ LEKARSKI : ORGAN POLSKIEGO TOWARZYSTWA LEKARSKIEGO 2023; 51:496-503. [PMID: 38069850 DOI: 10.36740/merkur202305108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
OBJECTIVE Aim: The study aims to investigate the effect of solute carriers organic anions transporters 1B1 (SLCO1B1) gene polymorphisms rs4149056, rs2306283, rs55901008, and rs729559745 in a sample of patients with dyslipidemia, and relate it to atorvastatin response and associated myopathy. PATIENTS AND METHODS Materials and Methods: A cross sectional enrolled 200 patients both males and females of Arabic race, Iraqi nationality aged between 30-65 years. The patients were divided into two groups: Group 1 (Atorvastatin responders and tolerant), Group 2 (Atorvastatin non responder and intolerant). Blood samples collected from the patients for biochemical studies and analyzed statistically by Student T-test and Chi-square, and DNA extracted for polymerase chains reactions (PCR). RESULTS Results: The results showed insignificant association P≥0.05 between the demographic characteristics of the study population with different genotypes, and significant difference P<0.05 in the biochemical parameters regarding (T-cholesterol, triglycerides, low density lipoproteins, and Creatine kinase-MM) when comparing the two groups. Odds ratio (OR) with confidence intervals CI (95%) used to evaluate the risk association to develop myopathy and poor response to atorvastatin therapy show relevant association for CC and CT genotype of rs4149056, while rs2306283 GG genotype show low association, also rs55901008 show low association for CC genotype, and moderate association for rs72559745 genotypes GG, AG. CONCLUSION Conclusions: The mutant allele's genotypes of rs4149056, rs55901008, and rs72559745, and the wild allele genotype of rs2306283 show significant association with the development of poor response to atorvastatin and elevated the level of CK-MM plasma concentration.
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Affiliation(s)
- Noor Dheyaa Aziz
- DEPARTMENT OF CLINICAL PHARMACY, COLLEGE OF PHARMACY, UNIVERSITY OF KERBALA, KERBALA, IRAQ
| | - Sameer H Abbood
- DEPARTMENT OF PHARMACOLOGY AND THERAPEUTICS, SCHOOL OF MEDICINE, KUFA UNIVERSITY, KUFA, IRAQ
| | - Ahmed H Al-Mayali
- DEPARTMENT OF INTERNAL MEDICINE, COLLEGE OF MEDICINE, UNIVERSITY OF KERBALA, KERBALA, IRAQ
| | - Najah Rayish Hadi
- DEPARTMENT OF PHARMACOLOGY & THERAPEUTICS, FACULTY OF MEDICINE, UNIVERSITY OF KUFA, KUFA, IRAQ
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33
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Parada-Márquez JF, Maldonado-Rodriguez ND, Triana-Fonseca P, Contreras-Bravo NC, Calderón-Ospina CA, Restrepo CM, Morel A, Ortega-Recalde OJ, Silgado-Guzmán DF, Angulo-Aguado M, Fonseca-Mendoza DJ. Pharmacogenomic profile of actionable molecular variants related to drugs commonly used in anesthesia: WES analysis reveals new mutations. Front Pharmacol 2023; 14:1047854. [PMID: 37021041 PMCID: PMC10069477 DOI: 10.3389/fphar.2023.1047854] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 03/06/2023] [Indexed: 04/07/2023] Open
Abstract
Background: Genetic interindividual variability is associated with adverse drug reactions (ADRs) and affects the response to common drugs used in anesthesia. Despite their importance, these variants remain largely underexplored in Latin-American countries. This study describes rare and common variants found in genes related to metabolism of analgesic and anaesthetic drug in the Colombian population. Methods: We conducted a study that included 625 Colombian healthy individuals. We generated a subset of 14 genes implicated in metabolic pathways of common medications used in anesthesia and assessed them by whole-exome sequencing (WES). Variants were filtered using two pipelines: A) novel or rare (minor allele frequency-MAF <1%) variants including missense, loss-of-function (LoF, e.g., frameshift, nonsense), and splice site variants with potential deleterious effect and B) clinically validated variants described in the PharmGKB (categories 1, 2 and 3) and/or ClinVar databases. For rare and novel missense variants, we applied an optimized prediction framework (OPF) to assess the functional impact of pharmacogenetic variants. Allelic, genotypic frequencies and Hardy-Weinberg equilibrium were calculated. We compare our allelic frequencies with these from populations described in the gnomAD database. Results: Our study identified 148 molecular variants potentially related to variability in the therapeutic response to 14 drugs commonly used in anesthesiology. 83.1% of them correspond to rare and novel missense variants classified as pathogenic according to the pharmacogenetic optimized prediction framework, 5.4% were loss-of-function (LoF), 2.7% led to potential splicing alterations and 8.8% were assigned as actionable or informative pharmacogenetic variants. Novel variants were confirmed by Sanger sequencing. Allelic frequency comparison showed that the Colombian population has a unique pharmacogenomic profile for anesthesia drugs with some allele frequencies different from other populations. Conclusion: Our results demonstrated high allelic heterogeneity among the analyzed sampled, enriched by rare (91.2%) variants in pharmacogenes related to common drugs used in anesthesia. The clinical implications of these results highlight the importance of implementation of next-generation sequencing data into pharmacogenomic approaches and personalized medicine.
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Affiliation(s)
| | | | - Paula Triana-Fonseca
- Department of Molecular Diagnosis, Genética Molecular de Colombia SAS, Bogotá, Colombia
| | - Nora Constanza Contreras-Bravo
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
| | - Carlos Alberto Calderón-Ospina
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
| | - Carlos M. Restrepo
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
| | - Adrien Morel
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
| | - Oscar Javier Ortega-Recalde
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
| | | | - Mariana Angulo-Aguado
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
- *Correspondence: Mariana Angulo-Aguado, ; Dora Janeth Fonseca-Mendoza,
| | - Dora Janeth Fonseca-Mendoza
- School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Universidad Del Rosario, Bogotá, Colombia
- *Correspondence: Mariana Angulo-Aguado, ; Dora Janeth Fonseca-Mendoza,
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34
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Zhou Y, Lauschke VM. Challenges Related to the Use of Next-Generation Sequencing for the Optimization of Drug Therapy. Handb Exp Pharmacol 2023; 280:237-260. [PMID: 35792943 DOI: 10.1007/164_2022_596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Over the last decade, next-generation sequencing (NGS) methods have become increasingly used in various areas of human genomics. In routine clinical care, their use is already implemented in oncology to profile the mutational landscape of a tumor, as well as in rare disease diagnostics. However, its utilization in pharmacogenomics is largely lacking behind. Recent population-scale genome data has revealed that human pharmacogenes carry a plethora of rare genetic variations that are not interrogated by conventional array-based profiling methods and it is estimated that these variants could explain around 30% of the genetically encoded functional pharmacogenetic variability.To interpret the impact of such variants on drug response a multitude of computational tools have been developed, but, while there have been major advancements, it remains to be shown whether their accuracy is sufficient to improve personalized pharmacogenetic recommendations in robust trials. In addition, conventional short-read sequencing methods face difficulties in the interrogation of complex pharmacogenes and high NGS test costs require stringent evaluations of cost-effectiveness to decide about reimbursement by national healthcare programs. Here, we illustrate current challenges and discuss future directions toward the clinical implementation of NGS to inform genotype-guided decision-making.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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35
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Bai H, Zhang X, Bush WS. Pharmacogenomic and Statistical Analysis. Methods Mol Biol 2023; 2629:305-330. [PMID: 36929083 DOI: 10.1007/978-1-0716-2986-4_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.
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Affiliation(s)
- Haimeng Bai
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Xueyi Zhang
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
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36
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Jukic M, Milosavljević F, Molden E, Ingelman-Sundberg M. Pharmacogenomics in treatment of depression and psychosis: an update. Trends Pharmacol Sci 2022; 43:1055-1069. [PMID: 36307251 DOI: 10.1016/j.tips.2022.09.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 11/11/2022]
Abstract
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.
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Affiliation(s)
- Marin Jukic
- Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Filip Milosavljević
- Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway; Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Magnus Ingelman-Sundberg
- Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
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37
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Zhou Y, Lauschke VM. The genetic landscape of major drug metabolizing cytochrome P450 genes-an updated analysis of population-scale sequencing data. THE PHARMACOGENOMICS JOURNAL 2022; 22:284-293. [PMID: 36068297 PMCID: PMC9674520 DOI: 10.1038/s41397-022-00288-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/05/2022] [Accepted: 08/19/2022] [Indexed: 06/15/2023]
Abstract
Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77, Stockholm, Sweden.
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
- University of Tuebingen, Tuebingen, Germany.
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38
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Budhwani KI, Patel ZH, Guenter RE, Charania AA. A hitchhiker's guide to cancer models. Trends Biotechnol 2022; 40:1361-1373. [PMID: 35534320 PMCID: PMC9588514 DOI: 10.1016/j.tibtech.2022.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 03/31/2022] [Accepted: 04/08/2022] [Indexed: 01/21/2023]
Abstract
Cancer is a complex and uniquely personal disease. More than 1.7 million people in the United States are diagnosed with cancer every year. As the burden of cancer grows, so does the need for new, more effective therapeutics and for predictive tools to identify optimal, personalized treatment options for every patient. Cancer models that recapitulate various aspects of the disease are fundamental to making advances along the continuum of cancer treatment from benchside discoveries to bedside delivery. In this review, we use a thought experiment as a vehicle to arrive at four broad categories of cancer models and explore the strengths, weaknesses, opportunities, and threats for each category in advancing our understanding of the disease and improving treatment strategies.
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Affiliation(s)
- Karim I Budhwani
- CerFlux, Inc., Birmingham, AL, USA; Department of Radiation Oncology, Heersink School of Medicine, University of Alabama at Birmingham (UAB), Birmingham, AL, USA; Department of Physics, Coe College, Cedar Rapids, IA, USA.
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39
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Bafiti V, Katsila T. Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:542-551. [PMID: 36149303 DOI: 10.1089/omi.2022.0097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
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.
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Affiliation(s)
- Vivi Bafiti
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
| | - Theodora Katsila
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece
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40
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Shiraishi Y, Okada A, Chiba K, Kawachi A, Omori I, Mateos RN, Iida N, Yamauchi H, Kosaki K, Yoshimi A. Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data. Nat Commun 2022; 13:5357. [PMID: 36175409 PMCID: PMC9522810 DOI: 10.1038/s41467-022-32887-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 08/23/2022] [Indexed: 12/01/2022] Open
Abstract
Many disease-associated genomic variants disrupt gene function through abnormal splicing. With the advancement of genomic medicine, identifying disease-associated splicing associated variants has become more important than ever. Most bioinformatics approaches to detect splicing associated variants require both genome and transcriptomic data. However, there are not many datasets where both of them are available. In this study, we develop a methodology to detect genomic variants that cause splicing changes (more specifically, intron retention), using transcriptome sequencing data alone. After evaluating its sensitivity and precision, we apply it to 230,988 transcriptome sequencing data from the publicly available repository and identified 27,049 intron retention associated variants (IRAVs). In addition, by exploring positional relationships with variants registered in existing disease databases, we extract 3,000 putative disease-associated IRAVs, which range from cancer drivers to variants linked with autosomal recessive disorders. The in-silico screening framework demonstrates the possibility of near-automatically acquiring medical knowledge, making the most of massively accumulated publicly available sequencing data. Collections of IRAVs identified in this study are available through IRAVDB (https://iravdb.io/). This paper proposed a novel in-silico framework for automatically screening disease-related variants and applied it to over 200,000 transcriptomes, providing an example to acquire medically relevant knowledge from publicly available sequence data.
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Affiliation(s)
- Yuichi Shiraishi
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan.
| | - Ai Okada
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Kenichi Chiba
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Asuka Kawachi
- Cancer RNA Research Unit, National Cancer Center Research Institute, Tokyo, Japan
| | - Ikuko Omori
- Cancer RNA Research Unit, National Cancer Center Research Institute, Tokyo, Japan
| | - Raúl Nicolás Mateos
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Naoko Iida
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Hirofumi Yamauchi
- Cancer RNA Research Unit, National Cancer Center Research Institute, Tokyo, Japan
| | - Kenjiro Kosaki
- Center for Medical Genetics, Keio University School of Medicine, Tokyo, Japan
| | - Akihide Yoshimi
- Cancer RNA Research Unit, National Cancer Center Research Institute, Tokyo, Japan
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41
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Cao P, Guo W, Wang J, Wu S, Huang Y, Wang Y, Liu Y, Zhang Y. Population pharmacokinetic study of pemetrexed in chinese primary advanced non-small cell lung carcinoma patients. Front Pharmacol 2022; 13:954242. [PMID: 36105185 PMCID: PMC9466465 DOI: 10.3389/fphar.2022.954242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/29/2022] [Indexed: 11/13/2022] Open
Abstract
The purposes of this study were to identify physiological and genetic factors that contributed to variability of pemetrexed (PEM) exposure and to optimize the dosing regimens for Chinese non-small cell lung carcinoma patients. A prospective population pharmacokinetics (PPK) research was performed in this population. The PEM concentrations of 192 plasma samples from 116 in-hospital patients were detected. All patients were genotyped for polymorphisms. The PPK model of PEM was developed. The pharmacokinetic behavior of PEM was described by a two-compartment model with first-order elimination. The population typical values were as follows: clearance (CL) 8.29 L/h, intercompartmental clearance (Q) 0.10 L/h, central volume of distribution (V1) 18.94 L and peripheral volume of distribution (V2) 5.12 L. Creatinine clearance (CrCl) was identified as a covariate to CL, and ERCC1 (rs3212986) and CYP3A5 (rs776746) gene polymorphisms as covariates to Q. By using empirical body surface area (BSA)-based dosing strategy, PEM exposure decreased with the elevation of CrCl. Contrarily, CrCl-based dosing strategy exhibited a satisfactory efficacy of achieving the target PEM exposure. BSA-based dosing regimen in current clinic practice is not suitable to achieve the target exposure in PEM chemotherapy of Chinese NSCLC patients. Alternatively, renal function-based dosing strategy is suggested.
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Affiliation(s)
- Peng Cao
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan, China
| | - Wei Guo
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan, China
| | - Jun Wang
- Department of Clinical Pharmacy, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sanlan Wu
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan, China
| | - Yifei Huang
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan, China
| | - Yang Wang
- Department of Clinical Pharmacy, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- *Correspondence: Yang Wang, ; Yani Liu, ; Yu Zhang,
| | - Yani Liu
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan, China
- *Correspondence: Yang Wang, ; Yani Liu, ; Yu Zhang,
| | - Yu Zhang
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan, China
- *Correspondence: Yang Wang, ; Yani Liu, ; Yu Zhang,
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42
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Zhou Y, Tremmel R, Schaeffeler E, Schwab M, Lauschke VM. Challenges and opportunities associated with rare-variant pharmacogenomics. Trends Pharmacol Sci 2022; 43:852-865. [PMID: 36008164 DOI: 10.1016/j.tips.2022.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/15/2022] [Accepted: 07/29/2022] [Indexed: 12/26/2022]
Abstract
Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany
| | - Elke Schaeffeler
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany; Cluster of Excellence iFIT (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany
| | - Matthias Schwab
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; Cluster of Excellence iFIT (EXC2180) Image-Guided and Functionally Instructed Tumor Therapies, University of Tübingen, Tübingen, Germany; Department of Clinical Pharmacology, and Department of Biochemistry and Pharmacy, University of Tübingen, Tübingen, Germany
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, 171 77 Stockholm, Sweden; Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; University of Tübingen, Tübingen, Germany.
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43
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Daly AK. Pharmacogenetics of the cytochromes P450: Selected pharmacological and toxicological aspects. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2022; 95:49-72. [PMID: 35953163 DOI: 10.1016/bs.apha.2022.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
With the availability of detailed genomic data on all 57 human cytochrome P450 genes, it is clear that there is substantial variability in gene product activity with functionally significant polymorphisms reported across almost all isoforms. This article is concerned mainly with 13 P450 isoforms of particular relevance to xenobiotic metabolism. After brief review of the extent of polymorphism in each, the relevance of selected P450 isoforms to both adverse drug reaction and disease susceptibility is considered in detail. Bleeding due to warfarin and other coumarin anticoagulants is considered as an example of a type A reaction with idiosyncratic adverse drug reactions affecting the liver and skin as type B. It is clear that CYP2C9 variants contribute significantly to warfarin dose requirement and also risk of bleeding, with a minor contribution from CYP4F2. In the case of idiosyncratic adverse drug reactions, CYP2B6 variants appear relevant to both liver and skin reactions to several drugs with CYP2C9 variants also relevant to phenytoin-related skin rash. The relevance of P450 genotype to disease susceptibility is also considered but detailed genetic studies now suggest that CYP2A6 is the only P450 relevant to risk of lung cancer with alleles associated with low or absent activity clearly protective against disease. Other cytochrome P450 genotypes are generally not predictors for risk of cancer or other complex disease development.
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Affiliation(s)
- Ann K Daly
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom.
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44
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Ingelman-Sundberg M. Cytochrome P450 polymorphism: From evolution to clinical use. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2022; 95:393-416. [PMID: 35953162 DOI: 10.1016/bs.apha.2022.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
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.
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Affiliation(s)
- Magnus Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institute, Stockholm, Sweden.
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45
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Silgado-Guzmán DF, Angulo-Aguado M, Morel A, Niño-Orrego MJ, Ruiz-Torres DA, Contreras Bravo NC, Restrepo CM, Ortega-Recalde O, Fonseca-Mendoza DJ. Characterization of ADME Gene Variation in Colombian Population by Exome Sequencing. Front Pharmacol 2022; 13:931531. [PMID: 35846994 PMCID: PMC9280300 DOI: 10.3389/fphar.2022.931531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/08/2022] [Indexed: 11/18/2022] Open
Abstract
In genes related to drug pharmacokinetics, molecular variations determine interindividual variability in the therapeutic efficacy and adverse drug reactions. The assessment of single-nucleotide variants (SNVs) is used with growing frequency in pharmacogenetic practice, and recently, high-throughput genomic analyses obtained through next-generation sequencing (NGS) have been recognized as powerful tools to identify common, rare and novel variants. These genetic profiles remain underexplored in Latin-American populations, including Colombia. In this study, we investigated the variability of 35 genes included in the ADME core panel (absorption, distribution, metabolism, and excretion) by whole-exome sequencing (WES) of 509 unrelated Colombian individuals with no previous reports of adverse drug reactions. Rare variants were filtered according to the minor allele frequencies (MAF) <1% and potential deleterious consequences. The functional impact of novel and rare missense variants was assessed using an optimized framework for pharmacogenetic variants. Bioinformatic analyses included the identification of clinically validated variants described in PharmGKB and ClinVar databases. Ancestry from WES data was inferred using the R package EthSEQ v2.1.4. Allelic frequencies were compared to other populations reported in the public gnomAD database. Our analysis revealed that rare missense pharmacogenetic variants were 2.1 times more frequent than common variants with 121 variants predicted as potentially deleterious. Rare loss of function (LoF) variants were identified in 65.7% of evaluated genes. Regarding variants with clinical pharmacogenetic effect, our study revealed 89 sequence variations in 28 genes represented by missense (62%), synonymous (22.5%), splice site (11.2%), and indels (3.4%). In this group, ABCB1, ABCC2, CY2B6, CYP2D6, DPYD, NAT2, SLC22A1, and UGTB2B7, are the most polymorphic genes. NAT2, CYP2B6 and DPYD metabolizer phenotypes demonstrated the highest variability. Ancestry analysis indicated admixture in 73% of the population. Allelic frequencies exhibit significant differences with other Latin-American populations, highlighting the importance of pharmacogenomic studies in populations of different ethnicities. Altogether, our data revealed that rare variants are an important source of variability in pharmacogenes involved in the pharmacokinetics of drugs and likely account for the unexplained interindividual variability in drug response. These findings provide evidence of the utility of WES for pharmacogenomic testing and into clinical practice.
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Affiliation(s)
| | - Mariana Angulo-Aguado
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Adrien Morel
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - María José Niño-Orrego
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Daniel-Armando Ruiz-Torres
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Nora Constanza Contreras Bravo
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Carlos Martin Restrepo
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Oscar Ortega-Recalde
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
- *Correspondence: Oscar Ortega-Recalde, ; Dora Janeth Fonseca-Mendoza,
| | - Dora Janeth Fonseca-Mendoza
- Center for Research in Genetics and Genomics—CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
- *Correspondence: Oscar Ortega-Recalde, ; Dora Janeth Fonseca-Mendoza,
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46
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van Vugt-Lussenburg BMA, Capinha L, Reinen J, Rooseboom M, Kranendonk M, Onderwater RCA, Jennings P. " Commandeuring" Xenobiotic Metabolism: Advances in Understanding Xenobiotic Metabolism. Chem Res Toxicol 2022; 35:1184-1201. [PMID: 35768066 PMCID: PMC9297329 DOI: 10.1021/acs.chemrestox.2c00067] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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The understanding
of how exogenous chemicals (xenobiotics) are
metabolized, distributed, and eliminated is critical to determine
the impact of the chemical and its metabolites to the (human) organism.
This is part of the research and educational discipline ADMET (absorption,
distribution, metabolism, elimination, and toxicity). Here, we review
the work of Jan Commandeur and colleagues who have not only made a
significant impact in understanding of phase I and phase II metabolism
of several important compounds but also contributed greatly to the
development of experimental techniques for the study of xenobiotic
metabolism. Jan Commandeur’s work has covered a broad area
of research, such as the development of online screening methodologies,
the use of a combination of enzyme mutagenesis and molecular modeling
for structure–activity relationship (SAR) studies, and the
development of novel probe substrates. This work is the bedrock of
current activities and brings the field closer to personalized (cohort-based)
pharmacology, toxicology, and hazard/risk assessment.
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Affiliation(s)
| | - Liliana Capinha
- Division of Computational and Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMs), Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Jelle Reinen
- Charles River Den Bosch, Hambakenwetering 7, 5203 DL Hertogenbosch, The Netherlands
| | - Martijn Rooseboom
- Shell Global Solutions International B.V., 1030 BN The Hague, The Netherlands
| | - Michel Kranendonk
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School/Faculty of Medical Sciences, Universidade NOVA de Lisboa, Campo dos Mártires da Pátria 130, 1169-056 Lisboa, Portugal
| | | | - Paul Jennings
- Division of Computational and Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMs), Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
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47
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Wilma K, Noora S, Riikka M, Liina J, Kati-Sisko V, Mikko N, Mikko N, Seppo A, Heidi K. Functional in vitro characterization of SLCO1B1 variants and simulation of the clinical pharmacokinetic impact of impaired OATP1B1 function. Eur J Pharm Sci 2022; 176:106246. [PMID: 35752377 DOI: 10.1016/j.ejps.2022.106246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 06/09/2022] [Accepted: 06/20/2022] [Indexed: 12/01/2022]
Abstract
Organic Anion Transporting Polypeptide 1B1 is important to the hepatic elimination and distribution of many drugs. If OATP1B1 function is decreased, it can increase plasma exposure of e.g. several statins leading to increased risk of muscle toxicity. First, we examined the impact of three naturally occurring rare variants and the frequent SLCO1B1 c.388A>G variant on in vitro transport activity with cellular uptake assay using two substrates: 2', 7'-dichlorofluorescein (DCF) and rosuvastatin. Secondly, LC-MS/MS based quantitative targeted absolute proteomics measured the OATP1B1 protein abundance in crude membrane fractions of HEK293 cells over-expressing these SNVs. Additionally, we simulated the effect of impaired OATP1B1 function on rosuvastatin pharmacokinetics to estimate the need for genotype-guided dosing. R57Q impaired DCF and rosuvastatin transport significantly yet did not change protein expression considerably, while N130D and N151S did not alter activity but increased protein expression. R253Q did not change protein expression but reduced DCF uptake and increased rosuvastatin Km. Based on pharmacokinetics simulations, doses of 30 mg (with 50% OATP1B1 function) and 20 mg (with 0% OATP1B1 function) result in plasma exposure similar to 40 mg dose (with 100% OATP1B1 function). Therefore dose reductions might be considered to avoid increased plasma exposure caused by function-impairing OATP1B1 genetic variants, such as R57Q.
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Affiliation(s)
- Kiander Wilma
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5E, 00014, Helsinki, Finland
| | - Sjöstedt Noora
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5E, 00014, Helsinki, Finland
| | - Manninen Riikka
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5E, 00014, Helsinki, Finland
| | - Jaakkonen Liina
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5E, 00014, Helsinki, Finland
| | | | - Neuvonen Mikko
- Department of Clinical Pharmacology, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Niemi Mikko
- Department of Clinical Pharmacology, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Individualized Drug Therapy Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Department of Clinical Pharmacology, HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
| | - Auriola Seppo
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Kidron Heidi
- Division of Pharmaceutical Biosciences, Faculty of Pharmacy, University of Helsinki, Viikinkaari 5E, 00014, Helsinki, Finland.
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48
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Campbell C, McCormack M, Patel S, Stapleton C, Bobbili D, Krause R, Depondt C, Sills GJ, Koeleman BP, Striano P, Zara F, Sander JW, Lerche H, Kunz WS, Stefansson K, Stefansson H, Doherty CP, Heinzen EL, Scheffer IE, Goldstein DB, O'Brien T, Cotter D, Berkovic SF, Sisodiya SM, Delanty N, Cavalleri GL. A pharmacogenomic assessment of psychiatric adverse drug reactions to levetiracetam. Epilepsia 2022; 63:1563-1570. [PMID: 35298028 PMCID: PMC9321556 DOI: 10.1111/epi.17228] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/14/2022] [Accepted: 03/14/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Levetiracetam (LEV) is an effective antiseizure medicine, but 10%-20% of people treated with LEV report psychiatric side-effects, and up to 1% may have psychotic episodes. Pharmacogenomic predictors of these adverse drug reactions (ADRs) have yet to be identified. We sought to determine the contribution of both common and rare genetic variation to psychiatric and behavioral ADRs associated with LEV. METHODS This case-control study compared cases of LEV-associated behavioral disorder (n = 149) or psychotic reaction (n = 37) to LEV-exposed people with no history of psychiatric ADRs (n = 920). All samples were of European ancestry. We performed genome-wide association study (GWAS) analysis comparing those with LEV ADRs to controls. We estimated the polygenic risk scores (PRS) for schizophrenia and compared cases with LEV-associated psychotic reaction to controls. Rare variant burden analysis was performed using exome sequence data of cases with psychotic reactions (n = 18) and controls (n = 122). RESULTS Univariate GWAS found no significant associations with either LEV-associated behavioural disorder or LEV-psychotic reaction. PRS analysis showed that cases of LEV-associated psychotic reaction had an increased PRS for schizophrenia relative to contr ols (p = .0097, estimate = .4886). The rare-variant analysis found no evidence of an increased burden of rare genetic variants in people who had experienced LEV-associated psychotic reaction relative to controls. SIGNIFICANCE The polygenic burden for schizophrenia is a risk factor for LEV-associated psychotic reaction. To assess the clinical utility of PRS as a predictor, it should be tested in an independent and ideally prospective cohort. Larger sample sizes are required for the identification of significant univariate common genetic signals or rare genetic signals associated with psychiatric LEV ADRs.
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Affiliation(s)
- Ciarán Campbell
- FutureNeuro Research Centre, RCSI Dublin, Dublin, Ireland.,Department of Pharmacy and Biomolecular Science, RCSI Dublin, Dublin, Ireland
| | - Mark McCormack
- Department of Pharmacy and Biomolecular Science, RCSI Dublin, Dublin, Ireland
| | - Sonn Patel
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Caragh Stapleton
- Department of Pharmacy and Biomolecular Science, RCSI Dublin, Dublin, Ireland
| | - Dheeraj Bobbili
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Roland Krause
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Chantal Depondt
- Laboratory of Experimental Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Graeme J Sills
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Bobby P Koeleman
- Division of Neurosciences, Universitair Medisch Centrum Utrecht, Utrecht, The Netherlands.,Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
| | - Pasquale Striano
- Paediatric Neurology and Muscular Diseases Unit, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genova, Italy
| | - Federico Zara
- Paediatric Neurology and Muscular Diseases Unit, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genova, Italy.,IRCSS, "G. Gaslini" Institute, Genova, Italy
| | - Josemir W Sander
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands.,Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Bucks, UK
| | - Holger Lerche
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Wolfram S Kunz
- Department of Epileptology, University of Bonn, Bonn, Germany
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Colin P Doherty
- FutureNeuro Research Centre, RCSI Dublin, Dublin, Ireland.,Department of Neurology, Beaumont Hospital, Dublin, Ireland
| | - Erin L Heinzen
- School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ingrid E Scheffer
- Royal Children's Hospital, University of Melbourne, Melbourne, Victoria, Australia.,Florey Institute and Murdoch Children's Research Institute, Melbourne, Victoria, Australia.,Department of Medicine (Neurology), Epilepsy Research Centre, Austin Health, University of Melbourne, Heidelberg, Victoria, Australia
| | - David B Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Terence O'Brien
- Department of Neuroscience, Monash University, Melbourne, Victoria, Australia
| | - David Cotter
- FutureNeuro Research Centre, RCSI Dublin, Dublin, Ireland.,Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Samuel F Berkovic
- Department of Medicine (Neurology), Epilepsy Research Centre, Austin Health, University of Melbourne, Heidelberg, Victoria, Australia
| | | | - Sanjay M Sisodiya
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Bucks, UK
| | - Norman Delanty
- FutureNeuro Research Centre, RCSI Dublin, Dublin, Ireland.,Department of Pharmacy and Biomolecular Science, RCSI Dublin, Dublin, Ireland.,Department of Neurology, Beaumont Hospital, Dublin, Ireland
| | - Gianpiero L Cavalleri
- FutureNeuro Research Centre, RCSI Dublin, Dublin, Ireland.,Department of Pharmacy and Biomolecular Science, RCSI Dublin, Dublin, Ireland
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49
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Ingelman-Sundberg M. The missing heritability in pharmacogenomics: role of NFIB and other factors. Pharmacogenomics 2022; 23:453-455. [PMID: 35546341 DOI: 10.2217/pgs-2022-0054] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Magnus Ingelman-Sundberg
- Department of Physiology & Pharmacology, Section of Pharmacogenetics, Biomedicum 5B, Karolinska Institutet, SE-171 77 Stockholm, Sweden
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50
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Jayanti RP, Long NP, Phat NK, Cho YS, Shin JG. Semi-Automated Therapeutic Drug Monitoring as a Pillar toward Personalized Medicine for Tuberculosis Management. Pharmaceutics 2022; 14:pharmaceutics14050990. [PMID: 35631576 PMCID: PMC9147223 DOI: 10.3390/pharmaceutics14050990] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 04/26/2022] [Accepted: 05/02/2022] [Indexed: 12/10/2022] Open
Abstract
Standard tuberculosis (TB) management has failed to control the growing number of drug-resistant TB cases worldwide. Therefore, innovative approaches are required to eradicate TB. Model-informed precision dosing and therapeutic drug monitoring (TDM) have become promising tools for adjusting anti-TB drug doses corresponding with individual pharmacokinetic profiles. These are crucial to improving the treatment outcome of the patients, particularly for those with complex comorbidity and a high risk of treatment failure. Despite the actual benefits of TDM at the bedside, conventional TDM encounters several hurdles related to laborious, time-consuming, and costly processes. Herein, we review the current practice of TDM and discuss the main obstacles that impede it from successful clinical implementation. Moreover, we propose a semi-automated TDM approach to further enhance precision medicine for TB management.
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Affiliation(s)
- Rannissa Puspita Jayanti
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Nguyen Phuoc Long
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Nguyen Ky Phat
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Yong-Soon Cho
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
| | - Jae-Gook Shin
- Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan 47392, Korea; (R.P.J.); (N.P.L.); (N.K.P.); (Y.-S.C.)
- Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan 47392, Korea
- Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan 47392, Korea
- Correspondence: ; Tel.: +82-51-890-6709; Fax: +82-51-893-1232
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