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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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2
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Sivadas A, Sahana S, Jolly B, Bhoyar RC, Jain A, Sharma D, Imran M, Senthivel V, Divakar MK, Mishra A, Mukhopadhyay A, Gibson G, Narayan KV, Sivasubbu S, Scaria V, Kurpad AV. Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population. BMJ Open Diabetes Res Care 2024; 12:e003769. [PMID: 38471670 PMCID: PMC10936492 DOI: 10.1136/bmjdrc-2023-003769] [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: 09/12/2023] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
INTRODUCTION Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants. RESEARCH DESIGN AND METHODS We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test. RESULTS Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs). CONCLUSIONS Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.
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Affiliation(s)
- Ambily Sivadas
- St John's Research Institute, Bangalore, Karnataka, India
| | - S Sahana
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Bani Jolly
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Rahul C Bhoyar
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
| | - Abhinav Jain
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Disha Sharma
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
| | - Mohamed Imran
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Vigneshwar Senthivel
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Mohit Kumar Divakar
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Anushree Mishra
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
| | | | - Greg Gibson
- Georgia Institute of Technology, Atlanta, Georgia, USA
| | | | - Sridhar Sivasubbu
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
| | - Vinod Scaria
- CSIR Institute of Genomics and Integrative Biology, New Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, India
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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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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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Kanji CR, Mbavha BT, Masimirembwa C, Thelingwani RS. Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry. PLoS One 2023; 18:e0292131. [PMID: 37788265 PMCID: PMC10547200 DOI: 10.1371/journal.pone.0292131] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/13/2023] [Indexed: 10/05/2023] Open
Abstract
Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.
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Affiliation(s)
- Comfort Ropafadzo Kanji
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
- Department of Clinical Pharmacology, University of Zimbabwe (UZ), Harare, Zimbabwe
| | - Bianza Tinotenda Mbavha
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
| | - Collen Masimirembwa
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
| | - Roslyn Stella Thelingwani
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
- CradleOmics, Harare, Zimbabwe
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Twesigomwe D, Drögemöller BI, Wright GE, Adebamowo C, Agongo G, Boua PR, Matshaba M, Paximadis M, Ramsay M, Simo G, Simuunza MC, Tiemessen CT, Lombard Z, Hazelhurst S. Characterization of CYP2D6 Pharmacogenetic Variation in Sub-Saharan African Populations. Clin Pharmacol Ther 2023; 113:643-659. [PMID: 36111505 PMCID: PMC9957841 DOI: 10.1002/cpt.2749] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 09/11/2022] [Indexed: 11/07/2022]
Abstract
Cytochrome P450 2D6 (CYP2D6) is a key enzyme in drug response owing to its involvement in the metabolism of ~ 25% of clinically prescribed medications. The encoding CYP2D6 gene is highly polymorphic, and many pharmacogenetics studies have been performed worldwide to investigate the distribution of CYP2D6 star alleles (haplotypes); however, African populations have been relatively understudied to date. In this study, the distributions of CYP2D6 star alleles and predicted drug metabolizer phenotypes-derived from activity scores-were examined across multiple sub-Saharan African populations based on bioinformatics analysis of 961 high-depth whole genome sequences. This was followed by characterization of novel star alleles and suballeles in a subset of the participants via targeted high-fidelity Single-Molecule Real-Time resequencing (Pacific Biosciences). This study revealed varying frequencies of known CYP2D6 alleles and predicted phenotypes across different African ethnolinguistic groups. Twenty-seven novel CYP2D6 star alleles were predicted computationally and two of them were further validated. This study highlights the importance of studying variation in key pharmacogenes such as CYP2D6 in the African context to better understand population-specific allele frequencies. This will aid in the development of better genotyping panels and star allele detection approaches with a view toward supporting effective implementation of precision medicine strategies in Africa and across the African diaspora.
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Affiliation(s)
- David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
| | - Britt I. Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health SciencesUniversity of ManitobaWinnipegManitobaCanada
| | - Galen E.B. Wright
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg Health Sciences Centre and Max Rady College of MedicineUniversity of ManitobaWinnipegManitobaCanada
- Department of Pharmacology and Therapeutics, Rady Faculty of Health SciencesUniversity of ManitobaWinnipegManitobaCanada
| | - Clement Adebamowo
- Institute for Human VirologyAbujaNigeria
- Division of Cancer Epidemiology, Department of Epidemiology and Public Health, and the Marlene and Stewart Greenebaum Comprehensive Cancer CentreUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Godfred Agongo
- Navrongo Health Research CentreGhana Health ServiceNavrongoGhana
- C.K. Tedam University of Technology and Applied SciencesNavrongoGhana
| | - Palwendé R. Boua
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
- Clinical Research Unit of NanoroInstitut de Recherche en Sciences de la SantéNanoroBurkina Faso
| | - Mogomotsi Matshaba
- Botswana‐Baylor Children's Clinical Centre of ExcellenceGaboroneBotswana
- RetrovirologyDepartment of Pediatrics, Baylor College of MedicineHoustonTexasUSA
| | - Maria Paximadis
- Centre for HIV and STIs, National Institute for Communicable Diseases, National Health Laboratory Services and Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
- School of Molecular and Cell BiologyUniversity of the WitwatersrandJohannesburgSouth Africa
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
| | - Gustave Simo
- Molecular Parasitology and Entomology Unit, Department of Biochemistry, Faculty of ScienceUniversity of DschangDschangCameroon
| | - Martin C. Simuunza
- Department of Disease Control, School of Veterinary MedicineUniversity of ZambiaLusakaZambia
| | - Caroline T. Tiemessen
- Centre for HIV and STIs, National Institute for Communicable Diseases, National Health Laboratory Services and Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
| | - Zané Lombard
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa
- School of Electrical and Information EngineeringUniversity of the WitwatersrandJohannesburgSouth Africa
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Hong DZ, Ong TCC, Timbadia DP, Tan HTA, Kwa ED, Chong WQ, Goh BC, Loh WS, Loh KS, Tan EC, Tay JK. Systematic Review and Meta-Analysis of the Influence of Genetic Variation on Ototoxicity in Platinum-Based Chemotherapy. Otolaryngol Head Neck Surg 2023; 168:1324-1337. [PMID: 36802061 DOI: 10.1002/ohn.222] [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: 05/03/2022] [Revised: 11/04/2022] [Accepted: 11/19/2022] [Indexed: 02/19/2023]
Abstract
OBJECTIVE The objective of this meta-analysis is to evaluate the impact of genetic polymorphisms on platinum-based chemotherapy (PBC)-induced ototoxicity. DATA SOURCES Systematic searches of PubMed, Embase, Cochrane, and Web of Science were conducted from the inception of the databases to May 31, 2022. Abstracts and presentations from conferences were also reviewed. REVIEW METHODS Four investigators independently extracted data in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Differences in the prevalence of PBC-induced ototoxicity between reference and variant (i) genotypes and (ii) alleles were analyzed. The overall effect size was presented using the random-effects model as an odds ratio (OR) with a 95% confidence interval (CI). RESULTS From 32 included articles, 59 single nucleotide polymorphisms on 28 genes were identified, with 4406 total unique participants. For allele frequency analysis, the A allele in ACYP2 rs1872328 was positively associated with ototoxicity (OR: 2.61; 95% CI: 1.06-6.43; n = 2518). Upon limiting to cisplatin use only, the T allele of COMT rs4646316 and COMT rs9332377 revealed significant results. For genotype frequency analysis, the CT/TT genotype in ERCC2 rs1799793 demonstrated an otoprotective effect (OR: 0.50; 95% CI: 0.27-0.94; n = 176). Excluding studies using carboplatin or concomitant radiotherapy revealed significant effects with COMT rs4646316, GSTP1 rs1965, and XPC rs2228001. Major sources of variations between studies include differences in patient demographics, ototoxicity grading systems, and treatment protocols. CONCLUSION Our meta-analysis presents polymorphisms that exert ototoxic or otoprotective effects in patients undergoing PBC. Importantly, several of these alleles are observed at high frequencies globally, highlighting the potential for polygenic screening and cumulative risk evaluation for personalized care.
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Affiliation(s)
- Daniel Z Hong
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
| | - Thaned C C Ong
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
| | - Dhayan P Timbadia
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
| | - Hui T A Tan
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
| | - Eunice D Kwa
- Department of Otolaryngology-Head and Neck Surgery, National University Hospital, Singapore, Singapore
| | - Wan Q Chong
- Department of Haematology-Oncology, National University Hospital, Singapore, Singapore
| | - Boon C Goh
- Department of Haematology-Oncology, National University Hospital, Singapore, Singapore
| | - Woei S Loh
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
- Department of Otolaryngology-Head and Neck Surgery, National University Hospital, Singapore, Singapore
| | - Kwok S Loh
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
- Department of Otolaryngology-Head and Neck Surgery, National University Hospital, Singapore, Singapore
| | - Ene C Tan
- KK Research Centre, KK Women's and Children's Hospital, Singapore, Singapore
| | - Joshua K Tay
- Department of Otolaryngology-Head and Neck Surgery, National University of Singapore, Singapore, Singapore
- Department of Otolaryngology-Head and Neck Surgery, National University Hospital, Singapore, Singapore
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Shivaram S, Gao H, Qin S, Liu D, Weinshilboum RM, Wang L. Cytochrome P450 Transcriptional Regulation by Testis-Specific Y-Encoded-Like Protein: Identification of Novel Upstream Transcription Factors. Drug Metab Dispos 2023; 51:1-7. [PMID: 36153008 PMCID: PMC9832376 DOI: 10.1124/dmd.122.000945] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 01/14/2023] Open
Abstract
Cytochrome P450s (CYPs) display significant inter-individual variation in expression, much of which remains unexplained by known CYP single-nucleotide polymorphisms (SNPs). Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators for several drug-metabolizing CYPs including CYP3A4 However, transcription factors (TFs) that might influence CYP expression through an effect on TSPYL expression are unknown. Therefore, we studied regulators of TSPYL expression in hepatic cell lines and their possible SNP-dependent variation. Specifically, we identified candidate TFs that might influence TSPYL expression using the ENCODE ChIPseq database. Subsequently, the expression of TSPYL1/2/4 as well as that of selected CYP targets for TSPYL regulation were assayed in hepatic cell lines before and after knockdown of TFs that might influence CYP expression through TSPYL-dependent mechanisms. Those results were confirmed by studies of TF binding to TSPYL1/2/4 gene promoter regions. In hepatic cell lines, knockdown of the REST and ZBTB7A TFs resulted in decreased TSPYL1 and TSPYL4 expression and increased CYP3A4 expression, changes reversed by TSPYL1/4 overexpression. Potential binding sites for REST and ZBTB7A on the promoters of TSPYL1 and TSPYL4 were confirmed by chromatin immunoprecipitation. Finally, common SNP variants in upstream binding sites on the TSPYL1/4 promoters were identified and luciferase reporter constructs confirmed SNP-dependent modulation of TSPYL1/4 gene transcription. In summary, we identified REST and ZBTB7A as regulators of the expression of TSPYL genes which themselves can contribute to regulation of CYP expression and-potentially-of drug metabolism. SNP-dependent modulation of TSPYL transcription may contribute to individual variation in both CYP expression and-downstream-drug response phenotypes. SIGNIFICANCE STATEMENT: Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators of cytochrome P450 (CYP) gene expression. Here, we report that variation in TSPYL expression as a result of the effects of genetically regulated TSPYL transcription factors is an additional factor that could result in downstream variation in CYP expression and potentially, as a result, variation in drug biotransformation.
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Affiliation(s)
- Suganti Shivaram
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Huanyao Gao
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Sisi Qin
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Duan Liu
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Richard M Weinshilboum
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
| | - Liewei Wang
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Therapeutics, Mayo Clinic, Rochester, Minnesota
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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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10
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Zhou Y, Koutsilieri S, Eliasson E, Lauschke VM. A paradigm shift in pharmacogenomics: From candidate polymorphisms to comprehensive sequencing. Basic Clin Pharmacol Toxicol 2022; 131:452-464. [PMID: 35971800 PMCID: PMC9805052 DOI: 10.1111/bcpt.13779] [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: 06/05/2022] [Revised: 07/28/2022] [Accepted: 08/09/2022] [Indexed: 01/09/2023]
Abstract
Genetic factors have long been recognized as important determinants of interindividual variability in drug efficacy and toxicity. However, despite the increasing number of established gene-drug associations, candidate polymorphisms can only explain a fraction of the genetically encoded functional variability in drug disposition. Advancements in genetic profiling methods now allow to analyse the landscape of human pharmacogenetic variations comprehensively, which opens new opportunities to identify novel factors that could explain the "missing heritability." Here, we provide an updated overview of the landscape of pharmacogenomic variability based on recent analyses of population-scale sequencing projects. We then summarize the current state-of-the-art how the functional consequences of variants with unknown effects can be quantitatively estimated while discussing challenges and peculiarities that are specific to pharmacogenes. In the last sections, we discuss the importance of considering ethnogeographic diversity to provide equitable benefits of pharmacogenomics and summarize current roadblocks for the implementation of sequencing-based guidance of clinical decision-making. Based on the current state of the field, we conclude that testing is likely to gradually shift from the interrogation of selected candidate polymorphisms to comprehensive sequencing, which allows to consider the full spectrum of pharmacogenomic variations for a true personalization of genomic prescribing.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden,Department of Laboratory MedicineKarolinska InstitutetStockholmSweden
| | | | - Erik Eliasson
- Department of Laboratory MedicineKarolinska InstitutetStockholmSweden
| | - Volker M. Lauschke
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden,Dr Margarete Fischer‐Bosch Institute of Clinical PharmacologyStuttgartGermany,University of TübingenTübingenGermany
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11
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Keogh M, Fragala MS, Peter AP, Lorenz RA, Goldberg SE, Shaman JA. Early Insights From a Pharmacogenomic-Enriched Comprehensive Medication Management Program Implementation in an Adult Employee Population. J Occup Environ Med 2022; 64:e818-e822. [PMID: 36155954 PMCID: PMC9722373 DOI: 10.1097/jom.0000000000002705] [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] [Indexed: 02/04/2023]
Abstract
OBJECTIVES The aims of the study are to assess adoption of a pharmacogenomic-enriched comprehensive medication management program in a self-insured employer setting and to better understand medication risks that affect employees. METHODS Employees were identified to be at high risk of medication mismanagement and were subsequently provided with a program and process to improve their health. DNA testing, a clinical decision support system, and pharmacists were used to identify medication safety and effectiveness issues and to recommend appropriate changes. RESULTS A total of 10.6% of the invited employees enrolled in the program. Actionable recommendations were suggested by pharmacists for 85.8% of employees who completed the program, averaging 5.2 recommendations per person. CONCLUSIONS Implementation of a PGx + CMM program in a self-insured employer setting is feasible, detects risks in prescription regimens, and offers opportunities to improve medication management and reduce the burden of healthcare expenses.
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12
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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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13
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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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14
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Maruf AA, Bousman CA. Approaches and hurdles of implementing pharmacogenetic testing in the psychiatric clinic. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2022; 1:e26. [PMID: 38868642 PMCID: PMC11114389 DOI: 10.1002/pcn5.26] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/07/2022] [Accepted: 06/01/2022] [Indexed: 06/14/2024]
Abstract
Pharmacogenetic (PGx) testing has emerged as a tool for predicting a person's ability to process and react to drugs. Despite the growing evidence-base, enthusiasm, and successful efforts to implement PGx testing in psychiatry, a consensus on how best to implement PGx testing into practice has not been established and numerous hurdles to widespread adoption remain to be overcome. In this article, we summarize the most used approaches and commonly encountered hurdles when implementing PGx testing into routine psychiatric care. We also highlight effective strategies that have been used to overcome hurdles. These strategies include the development of user-friendly clinical workflows for test ordering, use, and communication of results, establishment of test standardization and reimbursement policies, and development of tailored curriculums for educating health-care providers and the public. Although knowledge and awareness of these approaches and strategies to overcome hurdles alone may not be sufficient for successful implementation, they are necessary to ensure the effective spread, scale, and sustainability of PGx testing in psychiatry and other areas of medicine.
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Affiliation(s)
- Abdullah Al Maruf
- Rady Faculty of Health Sciences, College of PharmacyUniversity of ManitobaWinnipegManitobaCanada
- Children's Hospital Research Institute of ManitobaWinnipegManitobaCanada
- Centre on AgingUniversity of ManitobaWinnipegManitobaCanada
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Departments of Psychiatry and Physiology & PharmacologyUniversity of CalgaryCalgaryAlbertaCanada
| | - Chad A. Bousman
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Departments of Psychiatry and Physiology & PharmacologyUniversity of CalgaryCalgaryAlbertaCanada
- Department of Medical GeneticsUniversity of CalgaryCalgaryAlbertaCanada
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Alberta Children's Hospital Research InstituteUniversity of CalgaryCalgaryAlbertaCanada
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15
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Wang L, Scherer SE, Bielinski SJ, Muzny DM, Jones LA, Black JL, Moyer AM, Giri J, Sharp RR, Matey ET, Wright JA, Oyen LJ, Nicholson WT, Wiepert M, Sullard T, Curry TB, Vitek CRR, McAllister TM, Sauver JL, Caraballo PJ, Lazaridis KN, Venner E, Qin X, Hu J, Kovar CL, Korchina V, Walker K, Doddapaneni H, Wu TJ, Raj R, Denson S, Liu W, Chandanavelli G, Zhang L, Wang Q, Kalra D, Karow MB, Harris KJ, Sicotte H, Peterson SE, Barthel AE, Moore BE, Skierka JM, Kluge ML, Kotzer KE, Kloke K, Vander Pol JM, Marker H, Sutton JA, Kekic A, Ebenhoh A, Bierle DM, Schuh MJ, Grilli C, Erickson S, Umbreit A, Ward L, Crosby S, Nelson EA, Levey S, Elliott M, Peters SG, Pereira N, Frye M, Shamoun F, Goetz MP, Kullo IJ, Wermers R, Anderson JA, Formea CM, El Melik RM, Zeuli JD, Herges JR, Krieger CA, Hoel RW, Taraba JL, Thomas SR, Absah I, Bernard ME, Fink SR, Gossard A, Grubbs PL, Jacobson TM, Takahashi P, Zehe SC, Buckles S, Bumgardner M, Gallagher C, Fee-Schroeder K, Nicholas NR, Powers ML, Ragab AK, Richardson DM, Stai A, Wilson J, Pacyna JE, Olson JE, Sutton EJ, Beck AT, Horrow C, Kalari KR, Larson NB, Liu H, Wang L, Lopes GS, Borah BJ, Freimuth RR, Zhu Y, Jacobson DJ, Hathcock MA, Armasu SM, McGree ME, Jiang R, Koep TH, Ross JL, Hilden M, Bosse K, Ramey B, Searcy I, Boerwinkle E, Gibbs RA, Weinshilboum RM. Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study. Genet Med 2022; 24:1062-1072. [PMID: 35331649 PMCID: PMC9272414 DOI: 10.1016/j.gim.2022.01.022] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 12/12/2022] Open
Abstract
PURPOSE The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
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Affiliation(s)
- Liewei Wang
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN
| | - Steven E. Scherer
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Donna M. Muzny
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Leila A. Jones
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - John Logan Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Ann M. Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Wayne T. Nicholson
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | - Mathieu Wiepert
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Terri Sullard
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Timothy B. Curry
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Jennifer L. Sauver
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Pedro J. Caraballo
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Konstantinos N. Lazaridis
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Eric Venner
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Xiang Qin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Jianhong Hu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Christie L. Kovar
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Viktoriya Korchina
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Kimberly Walker
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | | | - Tsung-Jung Wu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Ritika Raj
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Shawn Denson
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Wen Liu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Gauthami Chandanavelli
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Lan Zhang
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Qiaoyan Wang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Divya Kalra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mary Beth Karow
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Hugues Sicotte
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Sandra E. Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Amy E. Barthel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Brenda E. Moore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Michelle L. Kluge
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Katrina E. Kotzer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Karen Kloke
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Heather Marker
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joseph A. Sutton
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | | | | | - Dennis M. Bierle
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | - Audrey Umbreit
- Department of Pharmacy, Mayo Clinic Health System, Mankato, MN
| | - Leah Ward
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | - Sheena Crosby
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | | | - Sharon Levey
- Department of Clinical Genomics, Mayo Clinic, Scottsdale, AZ
| | - Michelle Elliott
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Steve G. Peters
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Naveen Pereira
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Mark Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - Fadi Shamoun
- Department of Cardiovascular Medicine Mayo Clinic, Phoenix, AZ
| | - Matthew P. Goetz
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, MN
| | | | - Robert Wermers
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | | | - Scott R. Thomas
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Imad Absah
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Stephanie R. Fink
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Andrea Gossard
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Paul Takahashi
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Susan Buckles
- Department of Public Affairs, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Melody L. Powers
- Biospecimens Accessioning and Processing Laboratory, Mayo Clinic, Rochester, MN
| | - Ahmed K. Ragab
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | - Anthony Stai
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Jaymi Wilson
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joel E. Pacyna
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Janet E. Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Erica J. Sutton
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Annika T. Beck
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Caroline Horrow
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Krishna R. Kalari
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Nicholas B. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Hongfang Liu
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Liwei Wang
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Guilherme S. Lopes
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Bijan J. Borah
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ye Zhu
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Debra J. Jacobson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Matthew A. Hathcock
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Sebastian M. Armasu
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Michaela E. McGree
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ruoxiang Jiang
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | - Eric Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX,School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX,Corresponding Authors (), ()
| | - Richard M. Weinshilboum
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN,Corresponding Authors (), ()
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16
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Auwerx C, Sadler MC, Reymond A, Kutalik Z. From pharmacogenetics to pharmaco-omics: Milestones and future directions. HGG ADVANCES 2022; 3:100100. [PMID: 35373152 PMCID: PMC8971318 DOI: 10.1016/j.xhgg.2022.100100] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Marie C. Sadler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
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17
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Field MA. Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs. Front Med (Lausanne) 2022; 9:806696. [PMID: 35463004 PMCID: PMC9024231 DOI: 10.3389/fmed.2022.806696] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 03/21/2022] [Indexed: 11/13/2022] Open
Abstract
Precision medicine programs to identify clinically relevant genetic variation have been revolutionized by access to increasingly affordable high-throughput sequencing technologies. A decade of continual drops in per-base sequencing costs means it is now feasible to sequence an individual patient genome and interrogate all classes of genetic variation for < $1,000 USD. However, while advances in these technologies have greatly simplified the ability to obtain patient sequence information, the timely analysis and interpretation of variant information remains a challenge for the rollout of large-scale precision medicine programs. This review will examine the challenges and potential solutions that exist in identifying predictive genetic biomarkers and pharmacogenetic variants in a patient and discuss the larger bioinformatic challenges likely to emerge in the future. It will examine how both software and hardware development are aiming to overcome issues in short read mapping, variant detection and variant interpretation. It will discuss the current state of the art for genetic disease and the remaining challenges to overcome for complex disease. Success across all types of disease will require novel statistical models and software in order to ensure precision medicine programs realize their full potential now and into the future.
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Affiliation(s)
- Matt A. Field
- Centre for Tropical Bioinformatics and Molecular Biology, College of Public Health, Medical and Veterinary Science, James Cook University, Cairns, QLD, Australia
- Immunogenomics Lab, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
- Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia
- *Correspondence: Matt A. Field
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18
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Identification of pharmacogenetic variants from large scale next generation sequencing data in the Saudi population. PLoS One 2022; 17:e0263137. [PMID: 35089958 PMCID: PMC8797234 DOI: 10.1371/journal.pone.0263137] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 01/12/2022] [Indexed: 11/19/2022] Open
Abstract
It is well documented that drug responses are related to Absorption, Distribution, Metabolism, and Excretion (ADME) characteristics of individual patients. Several studies have identified genetic variability in pharmacogenes, that are either directly responsible for or are associated with ADME, giving rise to individualized treatments. Our objective was to provide a comprehensive overview of pharmacogenetic variation in the Saudi population. We mined next generation sequencing (NGS) data from 11,889 unrelated Saudi nationals, to determine the presence and frequencies of known functional SNP variants in 8 clinically relevant pharmacogenes (CYP2C9, CYP2C19, CYP3A5, CYP4F2, VKORC1, DPYD, TPMT and NUDT15), recommended by the Clinical Pharmacogenetics Implementation Consortium (CPIC), and collectively identified 82 such star alleles. Functionally significant pharmacogenetic variants were prevalent especially in CYP genes (excluding CYP3A5), with 10-44.4% of variants predicted to be inactive or to have decreased activity. In CYP3A5, inactive alleles (87.5%) were the most common. Only 1.8%, 0.7% and 0.7% of NUDT15, TPMT and DPYD variants respectively, were predicted to affect gene activity. In contrast, VKORC1 was found functionally, to be highly polymorphic with 53.7% of Saudi individuals harboring variants predicted to result in decreased activity and 31.3% having variants leading to increased metabolic activity. Furthermore, among the 8 pharmacogenes studied, we detected six rare variants with an aggregated frequency of 1.1%, that among several other ethnicities, were uniquely found in Saudi population. Similarly, within our cohort, the 8 pharmacogenes yielded forty-six novel variants predicted to be deleterious. Based upon our findings, 99.2% of individuals from the Saudi population carry at least one actionable pharmacogenetic variant.
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Johnson D, Wilke MA, Lyle SM, Kowalec K, Jorgensen A, Wright GE, Drögemöller BI. A systematic review and analysis of the use of polygenic scores in pharmacogenomics. Clin Pharmacol Ther 2021; 111:919-930. [PMID: 34953075 DOI: 10.1002/cpt.2520] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 12/18/2021] [Indexed: 11/09/2022]
Abstract
Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.
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Affiliation(s)
- Danielle Johnson
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - MacKenzie Ap Wilke
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sarah M Lyle
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Kaarina Kowalec
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Andrea Jorgensen
- Department of Health Data Science, University of Liverpool, Liverpool, UK
| | - Galen Eb Wright
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre and Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Britt I Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.,CancerCare Manitoba Research Institute, Winnipeg, MB, Canada.,Children's Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
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20
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Bharti N, Banerjee R, Achalere A, Kasibhatla SM, Joshi R. Genetic diversity of 'Very Important Pharmacogenes' in two South-Asian populations. PeerJ 2021; 9:e12294. [PMID: 34824904 PMCID: PMC8590392 DOI: 10.7717/peerj.12294] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 09/21/2021] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVES Reliable identification of population-specific variants is important for building the single nucleotide polymorphism (SNP) profile. In this study, genomic variation using allele frequency differences of pharmacologically important genes for Gujarati Indians in Houston (GIH) and Indian Telugu in the U.K. (ITU) from the 1000 Genomes Project vis-à-vis global population data was studied to understand its role in drug response. METHODS Joint genotyping approach was used to derive variants of GIH and ITU independently. SNPs of both these populations with significant allele frequency variation (minor allele frequency ≥ 0.05) with super-populations from the 1000 Genomes Project and gnomAD based on Chi-square distribution with p-value of ≤ 0.05 and Bonferroni's multiple adjustment tests were identified. Population stratification and fixation index analysis was carried out to understand genetic differentiation. Functional annotation of variants was carried out using SnpEff, VEP and CADD score. RESULTS Population stratification of VIP genes revealed four clusters viz., single cluster of GIH and ITU, one cluster each of East Asian, European, African populations and Admixed American was found to be admixed. A total of 13 SNPs belonging to ten pharmacogenes were identified to have significant allele frequency variation in both GIH and ITU populations as compared to one or more super-populations. These SNPs belong to VKORC1 (rs17708472, rs2359612, rs8050894) involved in Vitamin K cycle, cytochrome P450 isoforms CYP2C9 (rs1057910), CYP2B6 (rs3211371), CYP2A2 (rs4646425) and CYP2A4 (rs4646440); ATP-binding cassette (ABC) transporter ABCB1 (rs12720067), DPYD1 (rs12119882, rs56160474) involved in pyrimidine metabolism, methyltransferase COMT (rs9332377) and transcriptional factor NR1I2 (rs6785049). SNPs rs1544410 (VDR), rs2725264 (ABCG2), rs5215 and rs5219 (KCNJ11) share high fixation index (≥ 0.5) with either EAS/AFR populations. Missense variants rs1057910 (CYP2C9), rs1801028 (DRD2) and rs1138272 (GSTP1), rs116855232 (NUDT15); intronic variants rs1131341 (NQO1) and rs115349832 (DPYD) are identified to be 'deleterious'. CONCLUSIONS Analysis of SNPs pertaining to pharmacogenes in GIH and ITU populations using population structure, fixation index and allele frequency variation provides a premise for understanding the role of genetic diversity in drug response in Asian Indians.
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Affiliation(s)
- Neeraj Bharti
- High Performance Computing: Medical & Bioinformatics Applications Group, Centre for Development of Advanced Computing, Pune, Maharashtra, India
| | - Ruma Banerjee
- High Performance Computing: Medical & Bioinformatics Applications Group, Centre for Development of Advanced Computing, Pune, Maharashtra, India
| | - Archana Achalere
- High Performance Computing: Medical & Bioinformatics Applications Group, Centre for Development of Advanced Computing, Pune, Maharashtra, India
| | - Sunitha Manjari Kasibhatla
- High Performance Computing: Medical & Bioinformatics Applications Group, Centre for Development of Advanced Computing, Pune, Maharashtra, India
| | - Rajendra Joshi
- High Performance Computing: Medical & Bioinformatics Applications Group, Centre for Development of Advanced Computing, Pune, Maharashtra, India
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21
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Mulder N, Zass L, Hamdi Y, Othman H, Panji S, Allali I, Fakim YJ. African Global Representation in Biomedical Sciences. Annu Rev Biomed Data Sci 2021; 4:57-81. [PMID: 34465182 DOI: 10.1146/annurev-biodatasci-102920-112550] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
African populations are diverse in their ethnicity, language, culture, and genetics. Although plagued by high disease burdens, until recently the continent has largely been excluded from biomedical studies. Along with limitations in research and clinical infrastructure, human capacity, and funding, this omission has resulted in an underrepresentation of African data and disadvantaged African scientists. This review interrogates the relative abundance of biomedical data from Africa, primarily in genomics and other omics. The visibility of African science through publications is also discussed. A challenge encountered in this review is the relative lack of annotation of data on their geographical or population origin, with African countries represented as a single group. In addition to the abovementioned limitations,the global representation of African data may also be attributed to the hesitation to deposit data in public repositories. Whatever the reason, the disparity should be addressed, as African data have enormous value for scientists in Africa and globally.
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Affiliation(s)
- Nicola Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa; .,Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-AFRICA), Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa
| | - Lyndon Zass
- Computational Biology Division, Department of Integrative Biomedical Sciences and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa;
| | - Yosr Hamdi
- Laboratory of Biomedical Genomics and Oncogenetics and Laboratory of Human and Experimental Pathology, Institut Pasteur de Tunis, University of Tunis El Manar, 1002 Tunis, Tunisia
| | - Houcemeddine Othman
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg 2193, South Africa
| | - Sumir Panji
- Computational Biology Division, Department of Integrative Biomedical Sciences and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa;
| | - Imane Allali
- Laboratory of Human Pathologies Biology, Department of Biology, Faculty of Sciences, and Genomic Center of Human Pathologies, Faculty of Medicine and Pharmacy, Mohammed V University in Rabat, 1014 Rabat, Morocco
| | - Yasmina Jaufeerally Fakim
- Biotechnology Unit, Department of Agricultural and Food Science, Faculty of Agriculture, University of Mauritius, Réduit 80837, Mauritius
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22
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Chong CS, Limviphuvadh V, Maurer-Stroh S. Global spectrum of population-specific common missense variation in cytochrome P450 pharmacogenes. Hum Mutat 2021; 42:1107-1123. [PMID: 34153149 DOI: 10.1002/humu.24243] [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: 10/09/2020] [Revised: 04/12/2021] [Accepted: 06/08/2021] [Indexed: 11/06/2022]
Abstract
Next-generation sequencing technology has afforded the discovery of many novel variants that are of significance to inheritable pharmacogenomics (PGx) traits but a large proportion of them have unknown consequences. These include missense variants resulting in single amino acid substitutions in cytochrome P450 (CYP) proteins that can impair enzyme function, leading to altered drug efficacy and toxicity. While most unknown variants are rare, an overlooked minority are variants that are collectively rare but enriched in specific populations. Here, we analyzed sequence variation data in 141,456 individuals from across eight study populations in gnomAD for 38 CYP genes to identify such variants in addition to common variants. By further comparison with data from two PGx-specific databases (PharmVar and PharmGKB) and ClinVar, we identified 234 missense variants in 35 CYP genes, of which 107 were unknown to these databases. Most unknown variants (n = 83) were population-specific common variants and several (n = 7) were found in important CYP pharmacogenes (CYP2D6, CYP4F2, and CYP2C19). Overall, 29% (n = 31) of 107 unknown variants were predicted to affect CYP enzyme function although further biochemical characterization is necessary. These variants may elucidate part of the unexplained interpopulation differences observed in drug response.
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Affiliation(s)
- Cheng-Shoong Chong
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,Innovations in Food and Chemical Safety Programme (IFCS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,National University of Singapore Graduate School for Integrative Sciences and Engineering (NGS), National University of Singapore, Singapore, Singapore
| | - Vachiranee Limviphuvadh
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,Innovations in Food and Chemical Safety Programme (IFCS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,Innovations in Food and Chemical Safety Programme (IFCS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.,National University of Singapore Graduate School for Integrative Sciences and Engineering (NGS), National University of Singapore, Singapore, Singapore.,Department of Biological Sciences, National University of Singapore, Singapore, Singapore
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23
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Russell LE, Zhou Y, Almousa AA, Sodhi JK, Nwabufo CK, Lauschke VM. Pharmacogenomics in the era of next generation sequencing - from byte to bedside. Drug Metab Rev 2021; 53:253-278. [PMID: 33820459 DOI: 10.1080/03602532.2021.1909613] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.
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Affiliation(s)
| | - Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Ahmed A Almousa
- Department of Pharmacy, London Health Sciences Center, Victoria Hospital, London, ON, Canada
| | - Jasleen K Sodhi
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, CA, USA.,Department of Drug Metabolism and Pharmacokinetics, Plexxikon, Inc., Berkeley, CA, USA
| | | | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
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24
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da Rocha JEB, Othman H, Botha G, Cottino L, Twesigomwe D, Ahmed S, Drögemöller BI, Fadlelmola FM, Machanick P, Mbiyavanga M, Panji S, Wright GEB, Adebamowo C, Matshaba M, Ramsay M, Simo G, Simuunza MC, Tiemessen CT, Baldwin S, Chiano M, Cox C, Gross AS, Thomas P, Gamo FJ, Hazelhurst S. The Extent and Impact of Variation in ADME Genes in Sub-Saharan African Populations. Front Pharmacol 2021; 12:634016. [PMID: 34721006 PMCID: PMC8549571 DOI: 10.3389/fphar.2021.634016] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 02/10/2021] [Indexed: 01/13/2023] Open
Abstract
Introduction: Investigating variation in genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs are key to characterizing pharmacogenomic (PGx) relationships. ADME gene variation is relatively well characterized in European and Asian populations, but data from African populations are under-studied-which has implications for drug safety and effective use in Africa. Results: We identified significant ADME gene variation in African populations using data from 458 high-coverage whole genome sequences, 412 of which are novel, and from previously available African sequences from the 1,000 Genomes Project. ADME variation was not uniform across African populations, particularly within high impact coding variation. Copy number variation was detected in 116 ADME genes, with equal ratios of duplications/deletions. We identified 930 potential high impact coding variants, of which most are discrete to a single African population cluster. Large frequency differences (i.e., >10%) were seen in common high impact variants between clusters. Several novel variants are predicted to have a significant impact on protein structure, but additional functional work is needed to confirm the outcome of these for PGx use. Most variants of known clinical outcome are rare in Africa compared to European populations, potentially reflecting a clinical PGx research bias to European populations. Discussion: The genetic diversity of ADME genes across sub-Saharan African populations is large. The Southern African population cluster is most distinct from that of far West Africa. PGx strategies based on European variants will be of limited use in African populations. Although established variants are important, PGx must take into account the full range of African variation. This work urges further characterization of variants in African populations including in vitro and in silico studies, and to consider the unique African ADME landscape when developing precision medicine guidelines and tools for African populations.
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Affiliation(s)
- Jorge E. B. da Rocha
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), 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
| | - Houcemeddine Othman
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Gerrit Botha
- Computational Biology Division and H3ABioNet, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Laura Cottino
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), 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
| | - David Twesigomwe
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), 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
| | - Samah Ahmed
- Centre for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Britt I. Drögemöller
- Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada
| | - Faisal M. Fadlelmola
- Centre for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Philip Machanick
- Department of Computer Science, Rhodes University, Makhanda, South Africa
| | - Mamana Mbiyavanga
- Computational Biology Division and H3ABioNet, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Sumir Panji
- Computational Biology Division and H3ABioNet, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Galen E. B. Wright
- Neuroscience Research Program, Winnipeg Health Sciences Centre and Max Rady College of Medicine, Kleysen for Advanced Medicine, University of Manitoba, Winnipeg, MB, Canada
- Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Clement Adebamowo
- Institute for Human Virology, Abuja, Nigeria
- Institute of Human Virology and Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Mogomotsi Matshaba
- Botswana-Baylor Children’s Clinical Center of Excellence, Gaborone, Botswana
- Baylor College of Medicine, Houston, TX, United States
| | - Michéle Ramsay
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), 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
| | - Sandra Baldwin
- Drug Metabolism and Pharmacokinetics, GlaxoSmithKline R&D, Ware, United Kingdom
| | - Mathias Chiano
- Human Genetics, GlaxoSmithKline R&D, Stevenage, United Kingdom
| | - Charles Cox
- Human Genetics, GlaxoSmithKline R&D, Stevenage, United Kingdom
| | - Annette S. Gross
- Clinical Pharmacology Modelling and Simulation, GlaxoSmithKline R&D, Sydney, NSW, Australia
| | - Pamela Thomas
- Data and Computational Sciences, GlaxoSmithKline R&D, Stevenage, United Kingdom
| | | | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience (SBIMB), 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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25
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Wenric S, Jeff JM, Joseph T, Yee MC, Belbin GM, Owusu Obeng A, Ellis SB, Bottinger EP, Gottesman O, Levin MA, Kenny EE. Rapid response to the alpha-1 adrenergic agent phenylephrine in the perioperative period is impacted by genomics and ancestry. THE PHARMACOGENOMICS JOURNAL 2021; 21:174-189. [PMID: 33168928 PMCID: PMC7997806 DOI: 10.1038/s41397-020-00194-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Revised: 08/21/2020] [Accepted: 10/05/2020] [Indexed: 11/10/2022]
Abstract
The emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes occurring during inpatient clinical care. Here we study the genetic underpinnings of the rapid response to phenylephrine, an α1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery. We quantified this response by extracting blood pressure (BP) measurements 5 min before and after the administration of phenylephrine. Based on this derived phenotype, we show that systematic differences exist between self-reported ancestry groups: European-Americans (EA; n = 1387) have a significantly higher systolic response to phenylephrine than African-Americans (AA; n = 1217) and Hispanic/Latinos (HA; n = 1713) (31.3% increase, p value < 6e-08 and 22.9% increase, p value < 5e-05 respectively), after adjusting for genetic ancestry, demographics, and relevant clinical covariates. We performed a genome-wide association study to investigate genetic factors underlying individual differences in this derived phenotype. We discovered genome-wide significant association signals in loci and genes previously associated with BP measured in ambulatory settings, and a general enrichment of association in these genes. Finally, we discovered two low frequency variants, present at ~1% in EAs and AAs, respectively, where patients carrying one copy of these variants show no phenylephrine response. This work demonstrates our ability to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from dense clinical and physiological measures captured for managing patients during surgery. We identify genetic variants underlying non response to phenylephrine, with implications for preemptive pharmacogenomic screening to improve safety during surgery.
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Affiliation(s)
- Stephane Wenric
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Janina M Jeff
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Joseph
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Muh-Ching Yee
- Stanford Functional Genomics Facility, Stanford, CA, USA
- Invitae Corporation, San Francisco, CA, USA
| | - Gillian M Belbin
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aniwaa Owusu Obeng
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Pharmacy Department, The Mount Sinai Hospital, New York, NY, USA
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stephen B Ellis
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Erwin P Bottinger
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Omri Gottesman
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew A Levin
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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26
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Fonseca DJ, Morel A, Llinás-Caballero K, Bolívar-Salazar D, Laissue P. Whole-Exome Sequencing in Patients Affected by Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis Reveals New Variants Potentially Contributing to the Phenotype. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021; 14:287-299. [PMID: 33688237 PMCID: PMC7935440 DOI: 10.2147/pgpm.s289869] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 12/26/2020] [Indexed: 12/17/2022]
Abstract
Background Adverse drug reactions (ADRs) are frequent occurring events that can essentially be defined as harmful or unpleasant symptoms secondary to the use of a medicinal product. ADRs involve a wide spectrum of clinical manifestations ranging from minor itching and rash to life-threatening reactions. Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare ADRs. SJS-TEN may be considered a polygenic pathology due to additive/epistatic effects caused by sequence variants in numerous genes. Next-generation sequencing (NGS) represents a potentially interesting exploration tool in such scenario as it facilitates the simultaneous analysis of large genomic regions and genes at affordable cost. Methods The present study has involved using whole-exome sequencing (WES) for the first time on SJS-TEN patients. It involved robust and innovative multistep bioinformatics analysis focusing on 313 candidate genes potentially participating in the disease’s aetiology, specific drugs’ metabolism and gene regulation. Results We identified combinations of frequently occurring and rare variants that may contribute to the disease’s pathogenesis. Depending on the specific drug being taken, different variants (and alleles) in NAT2, CYP2D8, CYP2B6, ABCC2, UGT2B7 and TCF3 were identified as coherent candidates representing potential future markers for SJS-TEN. Conclusion The present study proposed and has described (for the first time) a large-scale genomic analysis of patients affected by SJS-TEN. The genes and variants identified represent relevant candidates potentially participating in the disease’s pathogenesis. Corroborating that proposed by others, we found that complex combinations of frequently occurring and rare variants participating in particular drug metabolism molecular cascades could be associated with the phenotype. TCF3 TF may be considered a coherent candidate for SJS-TEN that should be analysed in new cohorts of patients having ADRs.
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Affiliation(s)
- Dora Janeth Fonseca
- 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
| | - Kevin Llinás-Caballero
- Center for Research in Genetics and Genomics-CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - David Bolívar-Salazar
- Center for Research in Genetics and Genomics-CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia
| | - Paul Laissue
- Center for Research in Genetics and Genomics-CIGGUR, GENIUROS Research Group, School of Medicine and Health Sciences, Universidad Del Rosario, Bogotá, Colombia.,BIOPAS Laboratoires, Orphan Diseases Unit, BIOPAS GROUP, Bogotá, Colombia
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27
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Park JH, Lim SW, Myung W, Park I, Jang HJ, Kim S, Lee MS, Chang HS, Yum D, Suh YL, Kim JW, Kim DK. Whole-genome sequencing reveals KRTAP1-1 as a novel genetic variant associated with antidepressant treatment outcomes. Sci Rep 2021; 11:4552. [PMID: 33633223 PMCID: PMC7907209 DOI: 10.1038/s41598-021-83887-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 02/08/2021] [Indexed: 12/30/2022] Open
Abstract
Achieving remission following initial antidepressant therapy in patients with major depressive disorder (MDD) is an important clinical result. Making predictions based on genetic markers holds promise for improving the remission rate. However, genetic variants found in previous genetic studies do not provide robust evidence to aid pharmacogenetic decision-making in clinical settings. Thus, the objective of this study was to perform whole-genome sequencing (WGS) using genomic DNA to identify genetic variants associated with the treatment outcomes of selective serotonin reuptake inhibitors (SSRIs). We performed WGS on 100 patients with MDD who were treated with escitalopram (discovery set: 36 remitted and 64 non-remitted). The findings were applied to an additional 553 patients with MDD who were treated with SSRIs (replication set: 185 remitted and 368 non-remitted). A novel loss-of-function variant (rs3213755) in keratin-associated protein 1-1 (KRTAP1-1) was identified in this study. This rs3213755 variant was significantly associated with remission following antidepressant treatment (p = 0.0184, OR 3.09, 95% confidence interval [CI] 1.22-7.80 in the discovery set; p = 0.00269, OR 1.75, 95% CI 1.22-2.53 in the replication set). Moreover, the expression level of KRTAP1-1 in surgically resected human temporal lobe samples was significantly associated with the rs3213755 genotype. WGS studies on a larger sample size in various ethnic groups are needed to investigate genetic markers useful in the pharmacogenetic prediction of remission following antidepressant treatment.
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Affiliation(s)
- Jong-Ho Park
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea.,Clinical Genomics Center, Samsung Medical Center, Seoul, Korea
| | - Shinn-Won Lim
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Inho Park
- Precision Medicine Center, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Hyeok-Jae Jang
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Seonwoo Kim
- Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea
| | - Min-Soo Lee
- Department of Psychiatry, College of Medicine, Korea University, Seoul, Korea
| | - Hun Soo Chang
- Soonchunhyang Medical Institute, College of Medicine, Soonchunhyang University, Asan, Korea
| | - DongHo Yum
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Yeon-Lim Suh
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jong-Won Kim
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea. .,Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 135-710, Korea.
| | - Doh Kwan Kim
- Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul, 135-710, Korea.
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28
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Yu MHC, Chan MCY, Chung CCY, Li AWT, Yip CYW, Mak CCY, Chau JFT, Lee M, Fung JLF, Tsang MHY, Chan JCK, Wong WHS, Yang J, Chui WCM, Chung PHY, Yang W, Lee SL, Chan GCF, Tam PKH, Lau YL, Tang CSM, Yeung KS, Chung BHY. Actionable pharmacogenetic variants in Hong Kong Chinese exome sequencing data and projected prescription impact in the Hong Kong population. PLoS Genet 2021; 17:e1009323. [PMID: 33600428 PMCID: PMC7891783 DOI: 10.1371/journal.pgen.1009323] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 12/30/2020] [Indexed: 12/11/2022] Open
Abstract
Preemptive pharmacogenetic testing has the potential to improve drug dosing by providing point-of-care patient genotype information. Nonetheless, its implementation in the Chinese population is limited by the lack of population-wide data. In this study, secondary analysis of exome sequencing data was conducted to study pharmacogenomics in 1116 Hong Kong Chinese. We aimed to identify the spectrum of actionable pharmacogenetic variants and rare, predicted deleterious variants that are potentially actionable in Hong Kong Chinese, and to estimate the proportion of dispensed drugs that may potentially benefit from genotype-guided prescription. The projected preemptive pharmacogenetic testing prescription impact was evaluated based on the patient prescription data of the public healthcare system in 2019, serving 7.5 million people. Twenty-nine actionable pharmacogenetic variants/ alleles were identified in our cohort. Nearly all (99.6%) subjects carried at least one actionable pharmacogenetic variant, whereas 93.5% of subjects harbored at least one rare deleterious pharmacogenetic variant. Based on the prescription data in 2019, 13.4% of the Hong Kong population was prescribed with drugs with pharmacogenetic clinical practice guideline recommendations. The total expenditure on actionable drugs was 33,520,000 USD, and it was estimated that 8,219,000 USD (24.5%) worth of drugs were prescribed to patients with an implicated actionable phenotype. Secondary use of exome sequencing data for pharmacogenetic analysis is feasible, and preemptive pharmacogenetic testing has the potential to support prescription decisions in the Hong Kong Chinese population. Pharmacogenetic testing provides relevant drug phenotype information to guide personalized drug prescription, which potentially improves drug efficacy and prevent adverse drug reactions. However, its implementation in the Chinese population is limited by the lack of Chinese-specific pharmacogenetics data. In this study, we studied the spectrum of 133 actionable pharmacogenetic variants and rare deleterious variants in 108 pharmacogenes using an exome sequencing consisting of 1116 Hong Kong Chinese subjects. It was found that nearly all individuals carried at least one actionable pharmacogenetic variant and one rare, predicted deleterious pharmacogenetic variant. In addition, we projected the potential prescription impact of actionable pharmacogenetic variants using prescription data of the Hong Kong's public healthcare system. We estimated that one-seventh of the Hong Kong population received at least one of the 36 drugs with clinical pharmacogenetics guideline recommendations. The findings demonstrated the potential of pharmacogenetic testing in improving patient care and resource allocation in Chinese. The cohort dataset also supports clinical implementation of pharmacogenetics in the Chinese population.
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Affiliation(s)
- Mullin Ho Chung Yu
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Marcus Chun Yin Chan
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Claudia Ching Yan Chung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Andrew Wang Tat Li
- Department of Pharmacy, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
| | - Chara Yin Wa Yip
- Department of Pharmacy, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
| | - Christopher Chun Yu Mak
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Jeffrey Fong Ting Chau
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Mianne Lee
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Jasmine Lee Fong Fung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Mandy Ho Yin Tsang
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Joshua Chun Ki Chan
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Wilfred Hing Sang Wong
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Jing Yang
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | | | - Patrick Ho Yu Chung
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Wanling Yang
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - So Lun Lee
- Department of Paediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
| | - Godfrey Chi Fung Chan
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, The Hong Kong Children’s Hospital, Kowloon Bay, Hong Kong SAR, China
| | - Paul Kwong Hang Tam
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Dr Li Dak-Sum Research Centre, The University of Hong Kong–Karolinska Institutet Collaboration in Regenerative Medicine, Pokfulam, Hong Kong SAR, China
| | - Yu Lung Lau
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, The Hong Kong Children’s Hospital, Kowloon Bay, Hong Kong SAR, China
| | - Clara Sze Man Tang
- Department of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Dr Li Dak-Sum Research Centre, The University of Hong Kong–Karolinska Institutet Collaboration in Regenerative Medicine, Pokfulam, Hong Kong SAR, China
- * E-mail: (CSMT); (KSY); (BHYC)
| | - Kit San Yeung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- * E-mail: (CSMT); (KSY); (BHYC)
| | - Brian Hon Yin Chung
- Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China
- Department of Paediatrics and Adolescent Medicine, The Hong Kong Children’s Hospital, Kowloon Bay, Hong Kong SAR, China
- * E-mail: (CSMT); (KSY); (BHYC)
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29
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Scheinfeldt LB, Brangan A, Kusic DM, Kumar S, Gharani N. Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants. J Pers Med 2021; 11:jpm11020131. [PMID: 33669176 PMCID: PMC7919641 DOI: 10.3390/jpm11020131] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 02/05/2021] [Accepted: 02/09/2021] [Indexed: 12/15/2022] Open
Abstract
Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new ‘common treatment, common variant’ perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX’s in silico predictions.
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Affiliation(s)
- Laura B. Scheinfeldt
- Coriell Institute for Medical Research, Camden, NJ 08003, USA; (A.B.); (D.M.K.); (N.G.)
- Correspondence:
| | - Andrew Brangan
- Coriell Institute for Medical Research, Camden, NJ 08003, USA; (A.B.); (D.M.K.); (N.G.)
| | - Dara M. Kusic
- Coriell Institute for Medical Research, Camden, NJ 08003, USA; (A.B.); (D.M.K.); (N.G.)
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122, USA;
- Department of Biology, Temple University, Philadelphia, PA 19122, USA
- Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah 21577, Saudi Arabia
| | - Neda Gharani
- Coriell Institute for Medical Research, Camden, NJ 08003, USA; (A.B.); (D.M.K.); (N.G.)
- Gharani Consulting, Surrey KT139PA, UK
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30
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Yang HC, Chen CW, Lin YT, Chu SK. Genetic ancestry plays a central role in population pharmacogenomics. Commun Biol 2021; 4:171. [PMID: 33547344 PMCID: PMC7864978 DOI: 10.1038/s42003-021-01681-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 01/06/2021] [Indexed: 12/12/2022] Open
Abstract
Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD (http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/). Hsin-Chou Yang et al. examine population structure in several genomic databases and identify that pharmacogenetic loci are enriched for markers of genetic ancestry. Their results suggest that genetic ancestry must be carefully considered in population pharmacogenetics studies.
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Affiliation(s)
- Hsin-Chou Yang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. .,Institute of Statistics, National Cheng Kung University, Tainan, Taiwan. .,Institute of Public Health, National Yang-Ming University, Taipei, Taiwan.
| | - Chia-Wei Chen
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Yu-Ting Lin
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Shih-Kai Chu
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
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31
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Prevalence of pharmacogenomic variants in 100 pharmacogenes among Southeast Asian populations under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm). Hum Genome Var 2021; 8:7. [PMID: 33542200 PMCID: PMC7862625 DOI: 10.1038/s41439-021-00135-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/24/2020] [Accepted: 11/28/2020] [Indexed: 02/08/2023] Open
Abstract
Pharmacogenomics can enhance the outcome of treatment by adopting pharmacogenomic testing to maximize drug efficacy and lower the risk of serious adverse events. Next-generation sequencing (NGS) is a cost-effective technology for genotyping several pharmacogenomic loci at once, thereby increasing publicly available data. A panel of 100 pharmacogenes among Southeast Asian (SEA) populations was resequenced using the NGS platform under the collaboration of the Southeast Asian Pharmacogenomics Research Network (SEAPharm). Here, we present the frequencies of pharmacogenomic variants and the comparison of these pharmacogenomic variants among different SEA populations and other populations used as controls. We investigated the different types of pharmacogenomic variants, especially those that may have a functional impact. Our results provide substantial genetic variations at 100 pharmacogenomic loci among SEA populations that may contribute to interpopulation variability in drug response phenotypes. Correspondingly, this study provides basic information for further pharmacogenomic investigations in SEA populations.
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32
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Debortoli G, de Araujo GS, Fortes-Lima C, Parra EJ, Suarez-Kurtz G. Identification of ancestry proportions in admixed groups across the Americas using clinical pharmacogenomic SNP panels. Sci Rep 2021; 11:1007. [PMID: 33441860 PMCID: PMC7806998 DOI: 10.1038/s41598-020-80389-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 12/14/2020] [Indexed: 11/09/2022] Open
Abstract
We evaluated the performance of three PGx panels to estimate biogeographical ancestry: the DMET panel, and the VIP and Preemptive PGx panels described in the literature. Our analysis indicate that the three panels capture quite well the individual variation in admixture proportions observed in recently admixed populations throughout the Americas, with the Preemptive PGx and DMET panels performing better than the VIP panel. We show that these panels provide reliable information about biogeographic ancestry and can be used to guide the implementation of PGx clinical decision-support (CDS) tools. We also report that using these panels it is possible to control for the effects of population stratification in association studies in recently admixed populations, as exemplified with a warfarin dosing GWA study in a sample from Brazil.
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Affiliation(s)
- Guilherme Debortoli
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | | | - Cesar Fortes-Lima
- Sub-Department of Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Esteban J Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada.
| | - Guilherme Suarez-Kurtz
- Instituto Nacional de Câncer and Rede Nacional de Farmacogenética, Rio de Janeiro, Brazil.
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33
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Al-Mahayri ZN, Patrinos GP, Wattanapokayakit S, Iemwimangsa N, Fukunaga K, Mushiroda T, Chantratita W, Ali BR. Variation in 100 relevant pharmacogenes among emiratis with insights from understudied populations. Sci Rep 2020; 10:21310. [PMID: 33277594 PMCID: PMC7718919 DOI: 10.1038/s41598-020-78231-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 11/17/2020] [Indexed: 02/08/2023] Open
Abstract
Genetic variations have an established impact on the pharmacological response. Investigating this variation resulted in a compilation of variants in "pharmacogenes". The emergence of next-generation sequencing facilitated large-scale pharmacogenomic studies and exhibited the extensive variability of pharmacogenes. Some rare and population-specific variants proved to be actionable, suggesting the significance of population pharmacogenomic research. A profound gap exists in the knowledge of pharmacogenomic variants enriched in some populations, including the United Arab Emirates (UAE). The current study aims to explore the landscape of variations in relevant pharmacogenes among healthy Emiratis. Through the resequencing of 100 pharmacogenes for 100 healthy Emiratis, we identified 1243 variants, of which 63% are rare (minor allele frequency ≤ 0.01), and 30% were unique. Filtering the variants according to Pharmacogenomics Knowledge Base (PharmGKB) annotations identified 27 diplotypes and 26 variants with an evident clinical relevance. Comparison with global data illustrated a significant deviation of allele frequencies in the UAE population. Understudied populations display a distinct allelic architecture and various rare and unique variants. We underscored pharmacogenes with the highest variation frequencies and provided investigators with a list of candidate genes for future studies. Population pharmacogenomic studies are imperative during the pursuit of global pharmacogenomics implementation.
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Affiliation(s)
- Zeina N Al-Mahayri
- Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al-Ain, United Arab Emirates
| | - George P Patrinos
- Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al-Ain, United Arab Emirates.,Department of Pharmacy, School of Health Sciences, University of Patras, University Campus, Rion, Patras, Greece.,Zayed Center for Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates
| | - Sukanya Wattanapokayakit
- Division of Genomic Medicine and Innovation Support, Department of Medical Sciences, Ministry of Public Health, Nonthaburi, Thailand
| | - Nareenart Iemwimangsa
- Center for Medical Genomics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Koya Fukunaga
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Taisei Mushiroda
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Wasun Chantratita
- Center for Medical Genomics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Bassam R Ali
- Department of Pathology, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al-Ain, United Arab Emirates. .,Zayed Center for Health Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates. .,Department of Genetics and Genomics, College of Medicine and Heath Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates.
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34
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A systematic comparison of pharmacogene star allele calling bioinformatics algorithms: a focus on CYP2D6 genotyping. NPJ Genom Med 2020; 5:30. [PMID: 32789024 PMCID: PMC7398905 DOI: 10.1038/s41525-020-0135-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 05/20/2020] [Indexed: 02/07/2023] Open
Abstract
Genetic variation in genes encoding cytochrome P450 enzymes has important clinical implications for drug metabolism. Bioinformatics algorithms for genotyping these highly polymorphic genes using high-throughput sequence data and automating phenotype prediction have recently been developed. The CYP2D6 gene is often used as a model during the validation of these algorithms due to its clinical importance, high polymorphism, and structural variations. However, the validation process is often limited to common star alleles due to scarcity of reference datasets. In addition, there has been no comprehensive benchmark of these algorithms to date. We performed a systematic comparison of three star allele calling algorithms using 4618 simulations as well as 75 whole-genome sequence samples from the GeT-RM project. Overall, we found that Aldy and Astrolabe are better suited to call both common and rare diplotypes compared to Stargazer, which is affected by population structure. Aldy was the best performing algorithm in calling CYP2D6 structural variants followed by Stargazer, whereas Astrolabe had limitations especially in calling hybrid rearrangements. We found that ensemble genotyping, characterised by taking a consensus of genotypes called by all three algorithms, has higher haplotype concordance but it is prone to ambiguities whenever complete discrepancies between the tools arise. Further, we evaluated the effects of sequencing coverage and indel misalignment on genotyping accuracy. Our account of the strengths and limitations of these algorithms is extremely important to clinicians and researchers in the pharmacogenomics and precision medicine communities looking to haplotype CYP2D6 and other pharmacogenes using high-throughput sequencing data.
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35
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Martínez-Magaña JJ, Genis-Mendoza AD, Villatoro Velázquez JA, Camarena B, Martín Del Campo Sanchez R, Fleiz Bautista C, Bustos Gamiño M, Reséndiz E, Aguilar A, Medina-Mora ME, Nicolini H. The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico. Front Pharmacol 2020; 11:324. [PMID: 32390825 PMCID: PMC7188951 DOI: 10.3389/fphar.2020.00324] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 03/05/2020] [Indexed: 12/12/2022] Open
Abstract
Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some mestizo (admixed) populations may require tailoring to different patterns of admixture. The identification and clustering of individuals with related admixture patterns in such populations could help to refine the practice of pharmacogenetic counseling. This study identifies related groups in a highly admixed population-based sample from Mexico, and analyzes the differential distribution of actionable pharmacogenetic variants. A subsample of 1728 individuals from the Mexican Genomic Database for Addiction Research (MxGDAR/Encodat) was analyzed. Genotyping was performed with the commercial PsychArray BeadChip, genome-wide ancestry was estimated using EIGENSOFT, and model-based clustering was applied to defined admixture groups. Actionable pharmacogenetic variants were identified with a query to the Pharmacogenomics Knowledge Base (PharmGKB) database, and functional prediction using the Variant Effect Predictor (VEP). Allele frequencies were compared with chi-square tests and differentiation was estimated by FST. Seven admixture groups were identified in Mexico. Some, like Group 1, Group 4, and Group 5, were found exclusively in certain geographic areas. More than 90% of the individuals, in some groups (Group 1, Group 4 and Group 5) were found in the Central-East and Southeast region of the country. MTRR p.I49M, ABCG2 p.Q141K, CHRNA5 p.D398N, SLCO2B1 rs2851069 show a low degree of differentiation between admixture groups. ANKK1 p.G318R and p.H90R, had the lowest allele frequency of Group 1. The reduction in these alleles reduces the risk of toxicity from anticancer and antihypercholesterolemic drugs. Our analysis identified different admixture patterns and described how they could be used to refine the practice of pharmacogenetic counseling for this admixed population.
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Affiliation(s)
- José Jaime Martínez-Magaña
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
| | - Alma Delia Genis-Mendoza
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico.,Hospital Psiquiátrico Infantil "Juan N. Navarro," Servicios de Atención Psiquiátrica, Mexico City, Mexico
| | - Jorge Ameth Villatoro Velázquez
- Unidad de Encuestas y Análisis de Datos, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM).,Global Studies Seminar, Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Beatriz Camarena
- Laboratorio de Farmacogenética, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM), Mexico City, Mexico
| | - Raul Martín Del Campo Sanchez
- Unidad de Encuestas y Análisis de Datos, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM).,Global Studies Seminar, Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Clara Fleiz Bautista
- Unidad de Encuestas y Análisis de Datos, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM).,Global Studies Seminar, Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Marycarmen Bustos Gamiño
- Unidad de Encuestas y Análisis de Datos, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM)
| | - Esbehidy Reséndiz
- Unidad de Encuestas y Análisis de Datos, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM)
| | - Alejandro Aguilar
- Laboratorio de Farmacogenética, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM), Mexico City, Mexico
| | - María Elena Medina-Mora
- Unidad de Encuestas y Análisis de Datos, Insituto Nacional de Psiquiatría Ramón de la Fuente Muñiz (INPRFM).,Global Studies Seminar, Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Humberto Nicolini
- Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
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36
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Ethnogeographic and inter-individual variability of human ABC transporters. Hum Genet 2020; 139:623-646. [PMID: 32206879 PMCID: PMC7170817 DOI: 10.1007/s00439-020-02150-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Accepted: 03/16/2020] [Indexed: 12/19/2022]
Abstract
ATP-binding cassette (ABC) transporters constitute a superfamily of 48 structurally similar membrane transporters that mediate the ATP-dependent cellular export of a plethora of endogenous and xenobiotic substances. Importantly, genetic variants in ABC genes that affect gene function have clinically important effects on drug disposition and can be predictors of the risk of adverse drug reactions and efficacy of chemotherapeutics, calcium channel blockers, and protease inhibitors. Furthermore, loss-of-function of ABC transporters is associated with a variety of congenital disorders. Despite their clinical importance, information about the frequencies and global distribution of functionally relevant ABC variants is limited and little is known about the overall genetic complexity of this important gene family. Here, we systematically mapped the genetic landscape of the entire human ABC superfamily using Next-Generation Sequencing data from 138,632 individuals across seven major populations. Overall, we identified 62,793 exonic variants, 98.5% of which were rare. By integrating five computational prediction algorithms with structural mapping approaches using experimentally determined crystal structures, we found that the functional ABC variability is extensive and highly population-specific. Every individual harbored between 9.3 and 13.9 deleterious ABC variants, 76% of which were found only in a single population. Carrier rates of pathogenic variants in ABC transporter genes associated with autosomal recessive congenital diseases, such as cystic fibrosis or pseudoxanthoma elasticum, closely mirrored the corresponding population-specific disease prevalence, thus providing a novel resource for rare disease epidemiology. Combined, we provide the most comprehensive, systematic, and consolidated overview of ethnogeographic ABC transporter variability with important implications for personalized medicine, clinical genetics, and precision public health.
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37
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Lauschke VM, Ingelman-Sundberg M. Emerging strategies to bridge the gap between pharmacogenomic research and its clinical implementation. NPJ Genom Med 2020; 5:9. [PMID: 32194983 PMCID: PMC7057970 DOI: 10.1038/s41525-020-0119-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 01/15/2020] [Indexed: 12/13/2022] Open
Abstract
The genomic inter-individual heterogeneity remains a significant challenge for both clinical decision-making and the design of clinical trials. Although next-generation sequencing (NGS) is increasingly implemented in drug development and clinical trials, translation of the obtained genomic information into actionable clinical advice lags behind. Major reasons are the paucity of sufficiently powered trials that can quantify the added value of pharmacogenetic testing, and the considerable pharmacogenetic complexity with millions of rare variants with unclear functional consequences. The resulting uncertainty is reflected in inconsistencies of pharmacogenomic drug labels in Europe and the United States. In this review, we discuss how the knowledge gap for bridging pharmacogenomics into the clinics can be reduced. First, emerging methods that allow the high-throughput experimental characterization of pharmacogenomic variants combined with novel computational tools hold promise to improve the accuracy of drug response predictions. Second, tapping of large biobanks of therapeutic drug monitoring data allows to conduct high-powered retrospective studies that can validate the clinical importance of genetic variants, which are currently incompletely characterized. Combined, we are confident that these methods will improve the accuracy of drug response predictions and will narrow the gap between variant identification and its utilization for clinical decision-support.
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Affiliation(s)
- Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, SE-171 77 Stockholm, Sweden
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38
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Zhou Y, Lauschke VM. Pharmacogenomic network analysis of the gene-drug interaction landscape underlying drug disposition. Comput Struct Biotechnol J 2020; 18:52-58. [PMID: 31890144 PMCID: PMC6921140 DOI: 10.1016/j.csbj.2019.11.010] [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: 09/01/2019] [Revised: 11/22/2019] [Accepted: 11/22/2019] [Indexed: 11/30/2022] Open
Abstract
In recent decades the identification of pharmacogenomic gene-drug associations has evolved tremendously. Despite this progress, a major fraction of the heritable inter-individual variability remains elusive. Higher-dimensional phenomena, such as gene-gene-drug interactions, in which variability in multiple genes synergizes to precipitate an observable phenotype have been suggested to account at least for part of this missing heritability. However, the identification of such intricate relationships remains difficult partly because of analytical challenges associated with the complexity explosion of the problem. To facilitate the identification of such combinatorial pharmacogenetic associations, we here propose a network analysis strategy. Specifically, we analyzed the landscape of drug metabolizing enzymes and transporters for 100 top selling drugs as well as all compounds with pharmacogenetic germline labels or dosing guidelines. Based on this data, we calculated the posterior probabilities that gene i is involved in metabolism, transport or toxicity of a given drug under the condition that another gene j is involved for all pharmacogene pairs (i, j). Interestingly, these analyses revealed significant patterns between individual genes and across pharmacogene families that provide insights into metabolic interactions. To visualize the gene-drug interaction landscape, we use multidimensional scaling to collapse this similarity matrix into a two-dimensional network. We suggest that Euclidian distance between nodes can inform about the likelihood of epistatic interactions and thus might provide a useful tool to reduce the search space and facilitate the identification of combinatorial pharmacogenomic associations.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm 171 77, Sweden
| | - Volker M. Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm 171 77, Sweden
- Corresponding author at: Department of Physiology and Pharmacology, Karolinska Institutet, SE-171 77 Stockholm, Sweden.
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39
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The genetic landscape of the human solute carrier (SLC) transporter superfamily. Hum Genet 2019; 138:1359-1377. [PMID: 31679053 PMCID: PMC6874521 DOI: 10.1007/s00439-019-02081-x] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Accepted: 10/26/2019] [Indexed: 12/22/2022]
Abstract
The human solute carrier (SLC) superfamily of transporters is comprised of over 400 membrane-bound proteins, and plays essential roles in a multitude of physiological and pharmacological processes. In addition, perturbation of SLC transporter function underlies numerous human diseases, which renders SLC transporters attractive drug targets. Common genetic polymorphisms in SLC genes have been associated with inter-individual differences in drug efficacy and toxicity. However, despite their tremendous clinical relevance, epidemiological data of these variants are mostly derived from heterogeneous cohorts of small sample size and the genetic SLC landscape beyond these common variants has not been comprehensively assessed. In this study, we analyzed Next-Generation Sequencing data from 141,456 individuals from seven major human populations to evaluate genetic variability, its functional consequences, and ethnogeographic patterns across the entire SLC superfamily of transporters. Importantly, of the 204,287 exonic single-nucleotide variants (SNVs) which we identified, 99.8% were present in less than 1% of analyzed alleles. Comprehensive computational analyses using 13 partially orthogonal algorithms that predict the functional impact of genetic variations based on sequence information, evolutionary conservation, structural considerations, and functional genomics data revealed that each individual genome harbors 29.7 variants with putative functional effects, of which rare variants account for 18%. Inter-ethnic variability was found to be extensive, and 83% of deleterious SLC variants were only identified in a single population. Interestingly, population-specific carrier frequencies of loss-of-function variants in SLC genes associated with recessive Mendelian disease recapitulated the ethnogeographic variation of the corresponding disorders, including cystinuria in Jewish individuals, type II citrullinemia in East Asians, and lysinuric protein intolerance in Finns, thus providing a powerful resource for clinical geneticists to inform about population-specific prevalence and allelic composition of Mendelian SLC diseases. In summary, we present the most comprehensive data set of SLC variability published to date, which can provide insights into inter-individual differences in SLC transporter function and guide the optimization of population-specific genotyping strategies in the bourgeoning fields of personalized medicine and precision public health.
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40
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Wright GEB, Drögemöller BI, Ross CJD, Carleton BC. Genome-Wide Association Studies of Drug-Induced Liver Injury Make Progress Beyond the HLA Region. Gastroenterology 2019; 157:1167-1168. [PMID: 31348928 DOI: 10.1053/j.gastro.2019.03.076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 03/18/2019] [Indexed: 12/02/2022]
Affiliation(s)
- Galen E B Wright
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Britt I Drögemöller
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Colin J D Ross
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Bruce C Carleton
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada
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41
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Krebs K, Milani L. Translating pharmacogenomics into clinical decisions: do not let the perfect be the enemy of the good. Hum Genomics 2019; 13:39. [PMID: 31455423 PMCID: PMC6712791 DOI: 10.1186/s40246-019-0229-z] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/31/2019] [Indexed: 12/14/2022] Open
Abstract
The field of pharmacogenomics (PGx) is gradually shifting from the reactive testing of single genes toward the proactive testing of multiple genes to improve treatment outcomes, reduce adverse events, and decrease the burden of unnecessary costs for healthcare systems. Despite the progress in the field of pharmacogenomics, its implementation into routine care has been slow due to several barriers. However, in recent years, the number of studies on the implementation of PGx has increased, all providing a wealth of knowledge on different solutions for overcoming the obstacles that have been emphasized over the past years. This review focuses on some of the challenges faced by these initiatives, the solutions and different approaches for testing that they suggest, and the evidence that they provide regarding the benefits of preemptive PGx testing.
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Affiliation(s)
- Kristi Krebs
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
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42
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Lauschke VM, Zhou Y, Ingelman-Sundberg M. Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity. Pharmacol Ther 2019; 197:122-152. [PMID: 30677473 PMCID: PMC6527860 DOI: 10.1016/j.pharmthera.2019.01.002] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.
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Affiliation(s)
- Volker M Lauschke
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Biomedicum 5B, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Yitian Zhou
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Biomedicum 5B, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Magnus Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Biomedicum 5B, Karolinska Institutet, SE-171 77 Stockholm, Sweden.
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43
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Hočevar K, Maver A, Peterlin B. Actionable Pharmacogenetic Variation in the Slovenian Genomic Database. Front Pharmacol 2019; 10:240. [PMID: 30930780 PMCID: PMC6428035 DOI: 10.3389/fphar.2019.00240] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 02/26/2019] [Indexed: 12/28/2022] Open
Abstract
Background: Genetic variability in some of the genes that affect absorption, distribution, metabolism, and elimination ("pharmacogenes") can significantly influence an individual's response to the drug and consequently the effectiveness of treatment and possible adverse drug events. The rapid development of sequencing methods in recent years and consequently the increased integration of next-generation sequencing technologies into the clinical settings has enabled extensive genotyping of pharmacogenes for personalized treatment. The aim of the present study was to investigate the frequency and variety of potentially actionable pharmacogenetic findings in the Slovenian population. Methods: De-identified data from diagnostic exome sequencing in 1904 cases submitted to our institution were analyzed for variants within 293 genes associated with drug response. Filtered variants were classified according to population frequency, variant type, the functional impact of the variant, pathogenicity predictions and characterization in the Pharmacogenomics Knowledgebase (PharmGKB) and ClinVar. Results: We observed a total of 24 known actionable pharmacogenetic variants (PharmGKB 1A or 1B level of evidence), comprising approximately 26 drugs, of which, 12 were rare, with the population frequency below 1%. Furthermore, we identified an additional 61 variants with PharmGKB 2A or 2B clinical annotations. We detected 308 novel/rare potentially actionable variants: 177 protein-truncating variants and 131 missense variants predicted to be pathogenic based on several pathogenicity predictions. Conclusion: In the present study, we estimated the burden of pharmacogenetic variants in nationally based exome sequencing data and investigated the potential clinical usefulness of detected findings for personalized treatment. We provide the first comprehensive overview of known pharmacogenetic variants in the Slovenian population, as well as reveal a great proportion of novel/rare variants with a potential to influence drug response.
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Affiliation(s)
- Keli Hočevar
- Clinical Institute of Medical Genetics, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Aleš Maver
- Clinical Institute of Medical Genetics, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Borut Peterlin
- Clinical Institute of Medical Genetics, University Medical Centre Ljubljana, Ljubljana, Slovenia
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44
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Supervised Classification of CYP2D6 Genotype and Metabolizer Phenotype With Postmortem Tramadol-Exposed Finns. Am J Forensic Med Pathol 2019; 40:8-18. [DOI: 10.1097/paf.0000000000000447] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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45
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Daneshjou R, Huddart R, Klein TE, Altman RB. Pharmacogenomics in dermatology: tools for understanding gene-drug associations. ACTA ACUST UNITED AC 2019; 38:E19-E24. [PMID: 31051019 DOI: 10.12788/j.sder.2019.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Pharmacogenomics aims to associate human genetic variability with differences in drug phenotypes in order to tailor drug treatment to individual patients. The massive amount of genetic data generated from large cohorts of patients with variable drug phenotypes have led to advances in this field. Understanding the application of pharmacogenomics in dermatology could inform clinical practice and provide insight for future research. The Pharmacogenomics Knowledge Base and the Clinical Pharmacogenetics Implementation Consortium are among the resources to help clinicians and researchers navigate the many gene-drug associations that have already been discovered. The implementation of clinical pharmacogenomics within health care systems remains an area of ongoing development. This review provides an introduction to the field of pharmacogenomics and to current pharmacogenomics resources using examples of gene-drug associations relevant to the field of dermatology.
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Affiliation(s)
- Roxana Daneshjou
- Department of Dermatology, Stanford School of Medicine, Redwood City, California.
| | - Rachel Huddart
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California.,Department of Medicine, Stanford School of Medicine, Stanford, California
| | - Russ B Altman
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California.,Department of Medicine, Stanford School of Medicine, Stanford, California.,Department of Biomedical Engineering, Stanford Schools of Engineering & Medicine, Stanford, California.,Department of Genetics, Stanford School of Medicine, Stanford, California
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46
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Lauschke VM, Ingelman-Sundberg M. Prediction of drug response and adverse drug reactions: From twin studies to Next Generation Sequencing. Eur J Pharm Sci 2019; 130:65-77. [PMID: 30684656 DOI: 10.1016/j.ejps.2019.01.024] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/21/2019] [Accepted: 01/22/2019] [Indexed: 01/12/2023]
Abstract
Understanding and predicting inter-individual differences related to the success of drug therapy is of tremendous importance, both during drug development and for clinical applications. Importantly, while seminal twin studies indicate that the majority of inter-individual differences in drug disposition are driven by hereditary factors, common genetic polymorphisms explain only less than half of this genetically encoded variability. Recent progress in Next Generation Sequencing (NGS) technologies has for the first time allowed to comprehensively map the genetic landscape of human pharmacogenes. Importantly, these projects have unveiled vast numbers of rare genetic variants, which are estimated to contribute substantially to the missing heritability of drug metabolism phenotypes. However, functional interpretation of these rare variants remains challenging and constitutes one of the important frontiers of contemporary pharmacogenomics. Furthermore, NGS technologies face challenges in the interrogation of genes residing in complex genomic regions, such as CYP2D6 and HLA genes. We here provide an update of the implementation of pharmacogenomic variations in the clinical setting and present emerging strategies that facilitate the translation of NGS data into clinically useful information. Importantly, we anticipate that these developments will soon result in a paradigm shift of pre-emptive genotyping away from the interrogation to candidate variants and towards the comprehensive profiling of an individuals genotype, thus allowing for a true individualization of patient drug treatment regimens.
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Affiliation(s)
- Volker M Lauschke
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Magnus Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, SE-171 77 Stockholm, Sweden.
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47
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Huddart R, Fohner AE, Whirl-Carrillo M, Wojcik GL, Gignoux CR, Popejoy AB, Bustamante CD, Altman RB, Klein TE. Standardized Biogeographic Grouping System for Annotating Populations in Pharmacogenetic Research. Clin Pharmacol Ther 2019; 105:1256-1262. [PMID: 30506572 DOI: 10.1002/cpt.1322] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Accepted: 11/16/2018] [Indexed: 12/19/2022]
Abstract
The varying frequencies of pharmacogenetic alleles among populations have important implications for the impact of these alleles in different populations. Current population grouping methods to communicate these patterns are insufficient as they are inconsistent and fail to reflect the global distribution of genetic variability. To facilitate and standardize the reporting of variability in pharmacogenetic allele frequencies, we present seven geographically defined groups: American, Central/South Asian, East Asian, European, Near Eastern, Oceanian, and Sub-Saharan African, and two admixed groups: African American/Afro-Caribbean and Latino. These nine groups are defined by global autosomal genetic structure and based on data from large-scale sequencing initiatives. We recognize that broadly grouping global populations is an oversimplification of human diversity and does not capture complex social and cultural identity. However, these groups meet a key need in pharmacogenetics research by enabling consistent communication of the scale of variability in global allele frequencies and are now used by Pharmacogenomics Knowledgebase (PharmGKB).
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Affiliation(s)
- Rachel Huddart
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Alison E Fohner
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA.,Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | | | - Genevieve L Wojcik
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Christopher R Gignoux
- Department of Biostatistics, Division of Bioinformatics and Personalized Medicine, University of Colorado, Aurora, Colorado, USA
| | - Alice B Popejoy
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA.,Stanford Center for Integration of Research on Genetics and Ethics, Stanford, California, USA
| | - Carlos D Bustamante
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA.,Department of Genetics, Stanford University, Stanford, California, USA
| | - Russ B Altman
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA.,Department of Genetics, Stanford University, Stanford, California, USA.,Department of Biomedical Engineering, Stanford University, Stanford, California, USA.,Department of Medicine, Stanford University, Stanford, California, USA
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA.,Department of Medicine, Stanford University, Stanford, California, USA.,Shriram Center for BioE & ChemE, Stanford, California, USA
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48
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Mohammed Ismail W, Pagel KA, Pejaver V, Zhang SV, Casasa S, Mort M, Cooper DN, Hahn MW, Radivojac P. The sequencing and interpretation of the genome obtained from a Serbian individual. PLoS One 2018; 13:e0208901. [PMID: 30566479 PMCID: PMC6300249 DOI: 10.1371/journal.pone.0208901] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 11/26/2018] [Indexed: 02/07/2023] Open
Abstract
Recent genetic studies and whole-genome sequencing projects have greatly improved our understanding of human variation and clinically actionable genetic information. Smaller ethnic populations, however, remain underrepresented in both individual and large-scale sequencing efforts and hence present an opportunity to discover new variants of biomedical and demographic significance. This report describes the sequencing and analysis of a genome obtained from an individual of Serbian origin, introducing tens of thousands of previously unknown variants to the currently available pool. Ancestry analysis places this individual in close proximity to Central and Eastern European populations; i.e., closest to Croatian, Bulgarian and Hungarian individuals and, in terms of other Europeans, furthest from Ashkenazi Jewish, Spanish, Sicilian and Baltic individuals. Our analysis confirmed gene flow between Neanderthal and ancestral pan-European populations, with similar contributions to the Serbian genome as those observed in other European groups. Finally, to assess the burden of potentially disease-causing/clinically relevant variation in the sequenced genome, we utilized manually curated genotype-phenotype association databases and variant-effect predictors. We identified several variants that have previously been associated with severe early-onset disease that is not evident in the proband, as well as putatively impactful variants that could yet prove to be clinically relevant to the proband over the next decades. The presence of numerous private and low-frequency variants, along with the observed and predicted disease-causing mutations in this genome, exemplify some of the global challenges of genome interpretation, especially in the context of under-studied ethnic groups.
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Affiliation(s)
- Wazim Mohammed Ismail
- Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America
| | - Kymberleigh A. Pagel
- Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America
| | - Vikas Pejaver
- Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America
| | - Simo V. Zhang
- Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America
| | - Sofia Casasa
- Department of Biology, Indiana University, Bloomington, Indiana, United States of America
| | - Matthew Mort
- Institute of Medical Genetics, Cardiff University, Cardiff, United Kingdom
| | - David N. Cooper
- Institute of Medical Genetics, Cardiff University, Cardiff, United Kingdom
| | - Matthew W. Hahn
- Department of Computer Science, Indiana University, Bloomington, Indiana, United States of America
- Department of Biology, Indiana University, Bloomington, Indiana, United States of America
| | - Predrag Radivojac
- College of Computer and Information Science, Northeastern University, Boston, Massachusetts, United States of America
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49
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Sivadas A, Scaria V. Population-scale genomics-Enabling precision public health. ADVANCES IN GENETICS 2018; 103:119-161. [PMID: 30904093 DOI: 10.1016/bs.adgen.2018.09.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The current excitement for affordable genomics technologies and national precision medicine initiatives marks a turning point in worldwide healthcare practices. The last decade of global population sequencing efforts has defined the enormous extent of genetic variation in the human population resulting in insights into differential disease burden and response to therapy within and between populations. Population-scale pharmacogenomics helps to provide insights into the choice of optimal therapies and an opportunity to estimate, predict and minimize adverse events. Such an approach can potentially empower countries to formulate national selection and dosing policies for therapeutic agents thereby promoting public health with precision. We review the breadth and depth of worldwide population-scale sequencing efforts and its implications for the implementation of clinical pharmacogenetics toward making precision medicine a reality.
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Affiliation(s)
- Ambily Sivadas
- GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), New Delhi, India
| | - Vinod Scaria
- GN Ramachandran Knowledge Center for Genome Informatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India; Academy of Scientific and Innovative Research (AcSIR), New Delhi, India.
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50
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Fereidouni M, Moossavi M, Kazemi T, Nouranihassankiade S, Asghari A. Association between polymorphisms of VKORC1 and CYP2C9 genes with warfarin maintenance dose in a group of warfarin users in Birjand city, Iran. J Cell Biochem 2018; 120:9588-9593. [PMID: 30525241 DOI: 10.1002/jcb.28235] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 11/15/2018] [Indexed: 01/05/2023]
Abstract
Warfarin is the cardinal anticoagulant drug prescribed around the world. Due to stochastic bleeding in patients, it is essential to adjust the dose for every individual. The aim of the present study was to evaluate the frequency of CYP2C9 and VKORC1 gene polymorphisms and their association with warfarin maintenance dose in a sample of cardiovascular patients in Birjand, South-Khorasan province of Iran. Patients with a history of cardiovascular disorders who take warfarin daily were selected. CYP2C9 and VKORC1 gene polymorphisms were detected by polymerase chain reaction-restriction fragment length polymorphism in all participants. A total of 114 patients (mean age: 52.7 ± 14.9 years, M/F ratio: 0.76) participated in this study. Regarding CYP2C9 gene polymorphisms, the most frequent genotype was 1*/1* (80.4% in females and 62.5% in males). The frequency of 1*/2* and 2*/2* variants was 13% and 6.5% in females and 25% and 12.5% in males, respectively. The frequency of VKORC1 gene (1639 G > A), was 31.5%, 39.5%, and 29% for GG, GA, and AA in males, respectively. Besides, the mentioned genotype frequencies for females were 50%, 40.5%, and 9.5%, respectively. Moreover, there was a statistically significant correlation between VKORC1 gene -1639 G > A variant and warfarin maintenance dose (P < 0.001) but not for CYP2C9 variants. The results of the current study confirmed that the mutant variants of CYP2C9 are not frequent and do not have any impact on warfarin dose. In the case of VKORC1, the mutant allele (A) showed a positive correlation with warfarin dose adjustment.
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Affiliation(s)
- Mohammad Fereidouni
- Cellular and Molecular Research Center, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran
| | - Maryam Moossavi
- Student Research Committee, Birjand University of Medical Science, Birjand, Iran
| | - Touba Kazemi
- Cardiovascular Diseases Research Center, Professor of cardiology, Birjand University of Medical Sciences, Birjand, Iran
| | | | - Arghavan Asghari
- Student Research Committee, Birjand University of Medical Science, Birjand, Iran.,Asthma, Allergy, and Immunology Research Center, Faculty of Medicine, Birjand University of Medical Science, Birjand, Iran
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