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Samarasinghe SR, Lee SB, Corpas M, Fatumo S, Guchelaar HJ, Nagaraj SH. Mapping the Pharmacogenetic Landscape in a Ugandan Population: Implications for Personalized Medicine in an Underrepresented Population. Clin Pharmacol Ther 2024. [PMID: 38837390 DOI: 10.1002/cpt.3309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/27/2024] [Indexed: 06/07/2024]
Abstract
Africans are extremely underrepresented in global genomic research. African populations face high burdens of communicable and non-communicable diseases and experience widespread polypharmacy. As population-specific genetic studies are crucial to understanding unique genetic profiles and optimizing treatments to reduce medication-related complications in this diverse population, the present study aims to characterize the pharmacogenomics profile of a rural Ugandan population. We analyzed low-pass whole genome sequencing data from 1998 Ugandans to investigate 18 clinically actionable pharmacogenes in this population. We utilized PyPGx to identify star alleles (haplotype patterns) and compared allele frequencies across populations using the Pharmacogenomics Knowledgebase PharmGKB. Clinical interpretations of the identified alleles were conducted following established dosing guidelines. Over 99% of participants displayed actionable phenotypes across the 18 pharmacogenes, averaging 3.5 actionable genotypes per individual. Several variant alleles known to affect drug metabolism (i.e., CYP3A5*1, CYP2B6*9, CYP3A5*6, CYP2D6*17, CYP2D6*29, and TMPT*3C)-which are generally more prevalent in African individuals-were notably enriched in the Ugandan cohort, beyond reported frequencies in other African peoples. More than half of the cohort exhibited a predicted impaired drug response associated with CFTR, IFNL3, CYP2B6, and CYP2C19, and approximately 31% predicted altered CYP2D6 metabolism. Potentially impaired CYP2C9, SLCO1B1, TPMT, and DPYD metabolic phenotypes were also enriched in Ugandans compared with other African populations. Ugandans exhibit distinct allele profiles that could impact drug efficacy and safety. Our findings have important implications for pharmacogenomics in Uganda, particularly with respect to the treatment of prevalent communicable and non-communicable diseases, and they emphasize the potential of pharmacogenomics-guided therapies to optimize healthcare outcomes and precision medicine in Uganda.
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Affiliation(s)
- Sumudu Rangika Samarasinghe
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
| | | | - Manuel Corpas
- College of Liberal Arts and Sciences, University of Westminster, London, UK
| | - Segun Fatumo
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, Queensland, Australia
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Ahn SH, Park Y, Kim JH. Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants. Genes (Basel) 2024; 15:521. [PMID: 38674455 PMCID: PMC11050392 DOI: 10.3390/genes15040521] [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: 03/04/2024] [Revised: 04/18/2024] [Accepted: 04/19/2024] [Indexed: 04/28/2024] Open
Abstract
The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.
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Affiliation(s)
- Se Hwan Ahn
- Department of Biomedical Sciences, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 03080, Republic of Korea;
| | - Yoomi Park
- Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 03080, Republic of Korea;
- Medical Research Center, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Ju Han Kim
- Department of Biomedical Sciences, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 03080, Republic of Korea;
- Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 03080, Republic of Korea;
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3
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Gan P, Hajis MIB, Yumna M, Haruman J, Matoha HK, Wahyudi DT, Silalahi S, Oktariani DR, Dela F, Annisa T, Pitaloka TDA, Adhiwijaya PK, Pauzi RY, Hertanto R, Kumaheri MA, Sani L, Irwanto A, Pradipta A, Chomchopbun K, Gonzalez-Porta M. Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip. Front Pharmacol 2024; 15:1349203. [PMID: 38529185 PMCID: PMC10961362 DOI: 10.3389/fphar.2024.1349203] [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: 12/04/2023] [Accepted: 02/05/2024] [Indexed: 03/27/2024] Open
Abstract
Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.
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Affiliation(s)
- Pamela Gan
- Nalagenetics Pte Ltd., Singapore, Singapore
| | | | | | | | | | | | | | | | - Fitria Dela
- PT Genomik Solidaritas Indonesia, Jakarta, Indonesia
| | - Tazkia Annisa
- PT Genomik Solidaritas Indonesia, Jakarta, Indonesia
| | | | | | | | | | | | | | | | - Ariel Pradipta
- PT Genomik Solidaritas Indonesia, Jakarta, Indonesia
- Department Biochemistry and Molecular Biology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
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Zhou Q, Ghezelji M, Hari A, Ford MKB, Holley C, Mirabello L, Chanock S, Sahinalp SC, Numanagić I. Geny: A Genotyping Tool for Allelic Decomposition of Killer Cell Immunoglobulin-Like Receptor Genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.582413. [PMID: 38529502 PMCID: PMC10962708 DOI: 10.1101/2024.02.27.582413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Accurate genotyping of Killer cell Immunoglobulin-like Receptor (KIR) genes plays a pivotal role in enhancing our understanding of innate immune responses, disease correlations, and the advancement of personalized medicine. However, due to the high variability of the KIR region and high level of sequence similarity among different KIR genes, the currently available genotyping methods are unable to accurately infer copy numbers, genotypes and haplotypes of individual KIR genes from next-generation sequencing data. Here we introduce Geny, a new computational tool for precise genotyping of KIR genes. Geny utilizes available KIR haplotype databases and proposes a novel combination of expectation-maximization filtering schemes and integer linear programming-based combinatorial optimization models to resolve ambiguous reads, provide accurate copy number estimation and estimate the haplotype of each copy for the genes within the KIR region. We evaluated Geny on a large set of simulated short-read datasets covering the known validated KIR region assemblies and a set of Illumina short-read samples sequenced from 25 validated samples from the Human Pangenome Reference Consortium collection and showed that it outperforms the existing genotyping tools in terms of accuracy, precision and recall. We envision Geny becoming a valuable resource for understanding immune system response and consequently advancing the field of patient-centric medicine.
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Twesigomwe D, Drögemöller BI, Wright GEB, Adebamowo C, Agongo G, Boua PR, Matshaba M, Paximadis M, Ramsay M, Simo G, Simuunza MC, Tiemessen CT, Lombard Z, Hazelhurst S. Characterization of CYP2B6 and CYP2A6 Pharmacogenetic Variation in Sub-Saharan African Populations. Clin Pharmacol Ther 2024; 115:576-594. [PMID: 38049200 DOI: 10.1002/cpt.3124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 11/16/2023] [Indexed: 12/06/2023]
Abstract
Genetic variation in CYP2B6 and CYP2A6 is known to impact interindividual response to antiretrovirals, nicotine, and bupropion, among other drugs. However, the full catalogue of clinically relevant pharmacogenetic variants in these genes is yet to be established, especially across African populations. This study therefore aimed to characterize the star allele (haplotype) distribution in CYP2B6 and CYP2A6 across diverse and understudied sub-Saharan African (SSA) populations. We called star alleles from 961 high-depth full genomes using StellarPGx, Aldy, and PyPGx. In addition, we performed CYP2B6 and CYP2A6 star allele frequency comparisons between SSA and other global biogeographical groups represented in the new 1000 Genomes Project high-coverage dataset (n = 2,000). This study presents frequency information for star alleles in CYP2B6 (e.g., *6 and *18; frequency of 21-47% and 2-19%, respectively) and CYP2A6 (e.g., *4, *9, and *17; frequency of 0-6%, 3-10%, and 6-20%, respectively), and predicted phenotypes (for CYP2B6), across various African populations. In addition, 50 potentially novel African-ancestry star alleles were computationally predicted by StellarPGx in CYP2B6 and CYP2A6 combined. For each of these genes, over 4% of the study participants had predicted novel star alleles. Three novel star alleles in CYP2A6 (*54, *55, and *56) and CYP2B6 apiece, and several suballeles were further validated via targeted Single-Molecule Real-Time resequencing. Our findings are important for informing the design of comprehensive pharmacogenetic testing platforms, and are highly relevant for personalized medicine strategies, especially relating to antiretroviral medication and smoking cessation treatment in Africa and the African diaspora. More broadly, this study highlights the importance of sampling diverse African ethnolinguistic groups for accurate characterization of the pharmacogene variation landscape across the continent.
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Affiliation(s)
- David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Britt I Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Galen E B Wright
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre and Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
- Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Clement Adebamowo
- Institute for Human Virology, Abuja, Nigeria
- Division of Cancer Epidemiology, Department of Epidemiology and Public Health, and the Marlene and Stewart Greenebaum Comprehensive Cancer Centre, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Godfred Agongo
- Navrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana
- Department of Biochemistry and Forensic Sciences, School of Chemical and Biochemical Sciences, C.K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana
| | - Palwendé R Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Clinical Research Unit of Nanoro, Institut de Recherche en Sciences de la Santé, Nanoro, Burkina Faso
| | - Mogomotsi Matshaba
- Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana
- Retrovirology, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Maria Paximadis
- Centre for HIV and STIs, National Institute for Communicable Diseases, National Health Laboratory Services and Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Molecular and Cell Biology, University of the Witwatersrand, Johannesburg, South Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Gustave Simo
- Molecular Parasitology and Entomology Unit, Department of Biochemistry, Faculty of Science, University of Dschang, Dschang, Cameroon
| | - Martin C Simuunza
- Department of Disease Control, School of Veterinary Medicine, University of Zambia, Lusaka, Zambia
| | - Caroline T Tiemessen
- Centre for HIV and STIs, National Institute for Communicable Diseases, National Health Laboratory Services and Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Zané Lombard
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
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6
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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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7
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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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8
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Ji Y, Shaaban S. Interrogating Pharmacogenetics Using Next-Generation Sequencing. J Appl Lab Med 2024; 9:50-60. [PMID: 38167765 DOI: 10.1093/jalm/jfad097] [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: 08/18/2023] [Accepted: 10/18/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Pharmacogenetics or pharmacogenomics (PGx) is the study of the role of inherited or acquired sequence change in drug response. With the rapid evolution of molecular techniques, bioinformatic tools, and increased throughput of functional genomic studies, the discovery of PGx associations and clinical implementation of PGx test results have now moved beyond a handful variants in single pharmacogenes and multi-gene panels that interrogate a few pharmacogenes to whole-exome and whole-genome scales. Although some laboratories have adopted next-generation sequencing (NGS) as a testing platform for PGx and other molecular tests, most clinical laboratories that offer PGx tests still use targeted genotyping approaches. CONTENT This article discusses primarily the technical considerations for clinical laboratories to develop NGS-based PGx tests including whole-genome and whole-exome sequencing analyses and highlights the challenges and opportunities in test design, content selection, bioinformatic pipeline for PGx allele and diplotype assignment, rare variant classification, reporting, and briefly touches a few additional areas that are important for successful clinical implementation of PGx results. SUMMARY The accelerated speed of technology development associated with continuous cost reduction and enhanced ability to interrogate complex genome regions makes it inevitable for most, if not all, clinical laboratories to transition PGx testing to an NGS-based platform in the near future. It is important for laboratories and relevant professional societies to recognize both the potential and limitations of NGS-based PGx profiling, and to work together to develop a standard and consistent practice to maximize the variant or allele detection rate and utility of PGx testing.
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Affiliation(s)
- Yuan Ji
- Department of Pathology, University of Utah, Salt Lake City, UT, United States
- Molecular Genetics and Genomics, ARUP Laboratories, Salt Lake City, UT, United States
| | - Sherin Shaaban
- Department of Pathology, University of Utah, Salt Lake City, UT, United States
- Molecular Genetics and Genomics, ARUP Laboratories, Salt Lake City, UT, United States
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9
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Turner AJ, Nofziger C, Ramey BE, Ly RC, Bousman CA, Agúndez JAG, Sangkuhl K, Whirl-Carrillo M, Vanoni S, Dunnenberger HM, Ruano G, Kennedy MA, Phillips MS, Hachad H, Klein TE, Moyer AM, Gaedigk A. PharmVar Tutorial on CYP2D6 Structural Variation Testing and Recommendations on Reporting. Clin Pharmacol Ther 2023; 114:1220-1237. [PMID: 37669183 PMCID: PMC10840842 DOI: 10.1002/cpt.3044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 08/23/2023] [Indexed: 09/07/2023]
Abstract
The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus and a comprehensive summary of structural variation. CYP2D6 contributes to the metabolism of numerous drugs and, thus, genetic variation in its gene impacts drug efficacy and safety. To accurately predict a patient's CYP2D6 phenotype, testing must include structural variants including gene deletions, duplications, hybrid genes, and combinations thereof. This tutorial offers a comprehensive overview of CYP2D6 structural variation, terms, and definitions, a review of methods suitable for their detection and characterization, and practical examples to address the lack of standards to describe CYP2D6 structural variants or any other pharmacogene. This PharmVar tutorial offers practical guidance on how to detect the many, often complex, structural variants, as well as recommends terms and definitions for clinical and research reporting. Uniform reporting is not only essential for electronic health record-keeping but also for accurate translation of a patient's genotype into phenotype which is typically utilized to guide drug therapy.
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Affiliation(s)
- Amy J Turner
- Department of Pediatrics, Children’s Research Institute, The Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- RPRD Diagnostics LLC, Wauwatosa, Wisconsin, USA
| | | | | | - Reynold C Ly
- Department of Medical and Molecular Genetics, Division of Diagnostic Genomics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Chad A Bousman
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
| | - José AG Agúndez
- University of Extremadura, Cáceres, Spain
- Institute of Molecular Pathology Biomarkers, Cáceres, Spain
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | | | | | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University Health System, Evanston, Illinois, USA
| | - Gualberto Ruano
- Institute of Living, Hartford Hospital (Hartford CT) and Department of Psychiatry, University of Connecticut School of Medicine (Farmington CT), USA
| | - Martin A Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | | | - Houda Hachad
- Houda Hachad, Department of Clinical Operations, AccessDx Laboratories, Houston, Texas, USA
| | - Teri E Klein
- Departments of Biomedical Data Science and Medicine (BMIR), Stanford University, Stanford, California, USA
| | - Ann M Moyer
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Andrea Gaedigk
- Children’s Mercy Research Institute (CMRI), Kansas City, Missouri, USA
- School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
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Deserranno K, Tilleman L, Rubben K, Deforce D, Van Nieuwerburgh F. Targeted haplotyping in pharmacogenomics using Oxford Nanopore Technologies' adaptive sampling. Front Pharmacol 2023; 14:1286764. [PMID: 38026945 PMCID: PMC10679755 DOI: 10.3389/fphar.2023.1286764] [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: 08/31/2023] [Accepted: 10/30/2023] [Indexed: 12/01/2023] Open
Abstract
Pharmacogenomics (PGx) studies the impact of interindividual genomic variation on drug response, allowing the opportunity to tailor the dosing regimen for each patient. Current targeted PGx testing platforms are mainly based on microarray, polymerase chain reaction, or short-read sequencing. Despite demonstrating great value for the identification of single nucleotide variants (SNVs) and insertion/deletions (INDELs), these assays do not permit identification of large structural variants, nor do they allow unambiguous haplotype phasing for star-allele assignment. Here, we used Oxford Nanopore Technologies' adaptive sampling to enrich a panel of 1,036 genes with well-documented PGx relevance extracted from the Pharmacogenomics Knowledge Base (PharmGKB). By evaluating concordance with existing truth sets, we demonstrate accurate variant and star-allele calling for five Genome in a Bottle reference samples. We show that up to three samples can be multiplexed on one PromethION flow cell without a significant drop in variant calling performance, resulting in 99.35% and 99.84% recall and precision for the targeted variants, respectively. This work advances the use of nanopore sequencing in clinical PGx settings.
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Affiliation(s)
| | | | | | | | - Filip Van Nieuwerburgh
- Laboratory of Pharmaceutical Biotechnology, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
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11
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Huebner T, Steffens M, Scholl C. Current status of the analytical validation of next generation sequencing applications for pharmacogenetic profiling. Mol Biol Rep 2023; 50:9587-9599. [PMID: 37787843 PMCID: PMC10635985 DOI: 10.1007/s11033-023-08748-z] [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: 06/05/2023] [Accepted: 08/08/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND Analytical validity is a prerequisite to use a next generation sequencing (NGS)-based application as an in vitro diagnostic test or a companion diagnostic in clinical practice. Currently, in the United States and the European Union, the intended use of such NGS-based tests does not refer to guided drug therapy on the basis of pharmacogenetic profiling of drug metabolizing enzymes, although the value of pharmacogenetic testing has been reported. However, in research, a large variety of NGS-based tests are used and have been confirmed to be at least comparable to array-based testing. METHODS AND RESULTS A systematic evaluation was performed screening and assessing published literature on analytical validation of NGS applications for pharmacogenetic profiling of CYP2C9, CYP2C19, CYP2D6, VKORC1 and/or UGT1A1. Although NGS applications are also increasingly used for implementation assessments in clinical practice, we show in the present systematic literature evaluation that published information on the current status of analytical validation of NGS applications targeting drug metabolizing enzymes is scarce. Furthermore, a comprehensive performance evaluation of whole exome and whole genome sequencing with the intended use for pharmacogenetic profiling has not been published so far. CONCLUSIONS A standard in reporting on analytical validation of NGS-based tests is not in place yet. Therefore, many relevant performance criteria are not addressed in published literature. For an appropriate analytical validation of an NGS-based qualitative test for pharmacogenetic profiling at least accuracy, precision, limit of detection and specificity should be addressed to facilitate the implementation of such tests in clinical use.
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Affiliation(s)
- Tatjana Huebner
- Research Division, Federal Institute for Drugs and Medical Devices (BfArM), Kurt-Georg-Kiesinger-Allee 3, Bonn, 53175, Germany.
| | - Michael Steffens
- Research Division, Federal Institute for Drugs and Medical Devices (BfArM), Kurt-Georg-Kiesinger-Allee 3, Bonn, 53175, Germany
| | - Catharina Scholl
- Research Division, Federal Institute for Drugs and Medical Devices (BfArM), Kurt-Georg-Kiesinger-Allee 3, Bonn, 53175, Germany
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Tremmel R, Pirmann S, Zhou Y, Lauschke VM. Translating pharmacogenomic sequencing data into drug response predictions-How to interpret variants of unknown significance. Br J Clin Pharmacol 2023. [PMID: 37759374 DOI: 10.1111/bcp.15915] [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: 09/07/2023] [Revised: 09/20/2023] [Accepted: 09/22/2023] [Indexed: 09/29/2023] Open
Abstract
The rapid development of sequencing technologies during the past 20 years has provided a variety of methods and tools to interrogate human genomic variations at the population level. Pharmacogenes are well known to be highly polymorphic and a plethora of pharmacogenomic variants has been identified in population sequencing data. However, so far only a small number of these variants have been functionally characterized regarding their impact on drug efficacy and toxicity and the significance of the vast majority remains unknown. It is therefore of high importance to develop tools and frameworks to accurately infer the effects of pharmacogenomic variants and, eventually, aggregate the effect of individual variations into personalized drug response predictions. To address this challenge, we here first describe the technological advances, including sequencing methods and accompanying bioinformatic processing pipelines that have enabled reliable variant identification. Subsequently, we highlight advances in computational algorithms for pharmacogenomic variant interpretation and discuss the added value of emerging strategies, such as machine learning and the integrative use of omics techniques that have the potential to further contribute to the refinement of personalized pharmacological response predictions. Lastly, we provide an overview of experimental and clinical approaches to validate in silico predictions. We conclude that the iterative feedback between computational predictions and experimental validations is likely to rapidly improve the accuracy of pharmacogenomic prediction models, which might soon allow for an incorporation of the entire pharmacogenetic profile into personalized response predictions.
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Affiliation(s)
- Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - 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
| | - Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
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Samarasinghe SR, Hoy W, Jadhao S, McMorran BJ, Guchelaar HJ, Nagaraj SH. The pharmacogenomic landscape of an Indigenous Australian population. Front Pharmacol 2023; 14:1180640. [PMID: 37284308 PMCID: PMC10241071 DOI: 10.3389/fphar.2023.1180640] [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: 03/06/2023] [Accepted: 04/07/2023] [Indexed: 06/08/2023] Open
Abstract
Background: Population genomic studies of individuals of Indigenous ancestry have been extremely limited comprising <0.5% of participants in international genetic databases and genome-wide association studies, contributing to a "genomic gap" that limits their access to personalised medicine. While Indigenous Australians face a high burden of chronic disease and associated medication exposure, corresponding genomic and drug safety datasets are sorely lacking. Methods: To address this, we conducted a pharmacogenomic study of almost 500 individuals from a founder Indigenous Tiwi population. Whole genome sequencing was performed using short-read Illumina Novaseq6000 technology. We characterised the pharmacogenomics (PGx) landscape of this population by analysing sequencing results and associated pharmacological treatment data. Results: We observed that every individual in the cohort carry at least one actionable genotype and 77% of them carry at least three clinically actionable genotypes across 19 pharmacogenes. Overall, 41% of the Tiwi cohort were predicted to exhibit impaired CYP2D6 metabolism, with this frequency being much higher than that for other global populations. Over half of the population predicted an impaired CYP2C9, CYP2C19, and CYP2B6 metabolism with implications for the processing of commonly used analgesics, statins, anticoagulants, antiretrovirals, antidepressants, and antipsychotics. Moreover, we identified 31 potentially actionable novel variants within Very Important Pharmacogenes (VIPs), five of which were common among the Tiwi. We further detected important clinical implications for the drugs involved with cancer pharmacogenomics such as thiopurines and tamoxifen, immunosuppressants like tacrolimus and certain antivirals used in the hepatitis C treatment due to potential differences in their metabolic processing. Conclusion: The pharmacogenomic profiles generated in our study demonstrate the utility of pre-emptive PGx testing and have the potential to help guide the development and application of precision therapeutic strategies tailored to Tiwi Indigenous patients. Our research provides valuable insights on pre-emptive PGx testing and the feasibility of its use in ancestrally diverse populations, emphasizing the need for increased diversity and inclusivity in PGx investigations.
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Affiliation(s)
| | - Wendy Hoy
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Sudhir Jadhao
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Brendan J McMorran
- John Curtin School of Medical Research, College of Health and Medicine, Australian National University, Canberra, ACT, Australia
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, QLD, Australia
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