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Sherman CA, Claw KG, Lee SB. Pharmacogenetic analysis of structural variation in the 1000 genomes project using whole genome sequences. Sci Rep 2024; 14:22774. [PMID: 39354004 DOI: 10.1038/s41598-024-73748-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 09/20/2024] [Indexed: 10/03/2024] Open
Abstract
While significant strides have been made in understanding pharmacogenetics (PGx) and gene-drug interactions, there remains limited characterization of population-level PGx variation. This study aims to comprehensively profile global star alleles (haplotype patterns) and phenotype frequencies in 58 pharmacogenes associated with drug absorption, distribution, metabolism, and excretion. PyPGx, a star-allele calling tool, was employed to identify star alleles within high-coverage whole genome sequencing (WGS) data from the 1000 Genomes Project (N = 2504; 26 global populations). This process involved detecting structural variants (SVs), such as gene deletions, duplications, hybrids, as well as single nucleotide variants and insertion-deletion variants. The majority of our PyPGx calls for star alleles and phenotype frequencies aligned with the Pharmacogenomics Knowledge Base, although notable population-specific frequencies differed at least twofold. Validation efforts confirmed known SVs while uncovering several novel SVs currently undefined as star alleles. Additionally, we identified 210 small nucleotide variants associated with severe functional consequences that are not defined as star alleles. The study serves as a valuable resource, providing updated population-level star allele and phenotype frequencies while incorporating SVs. It also highlights the burgeoning potential of cost-effective WGS for PGx genotyping, offering invaluable insights to improve tailored drug therapies across diverse populations.
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Affiliation(s)
- Carissa A Sherman
- Department of Biomedical Informatics, Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Katrina G Claw
- Department of Biomedical Informatics, Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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2
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Hodel F, De Min MB, Thorball CW, Redin C, Vollenweider P, Girardin F, Fellay J. Prevalence of actionable pharmacogenetic variants and high-risk drug prescriptions: A Swiss hospital-based cohort study. Clin Transl Sci 2024; 17:e70009. [PMID: 39263940 PMCID: PMC11391267 DOI: 10.1111/cts.70009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Accepted: 08/06/2024] [Indexed: 09/13/2024] Open
Abstract
Drug type and dosing recommendation have been designed and optimized based on average response in the general population. Yet, there is significant inter-individual variability in drug response, which results in treatment inefficacy or adverse drug reactions in a subset of patients. This is partly due to genetic factors that typically affect drug metabolism or clearance. To verify the relevance and applicability of international pharmacogenetic guidelines in the Swiss population, we genotyped 1533 patients from a hospital-based biobank who received at least 30 different drugs, as documented in their electronic health record. We then assessed the prevalence of clinically actionable variants in 13 high-risk pharmacogenes. We compared the allele frequencies obtained in the hospital-based cohort with those of a Swiss population-based cohort of 4791 individuals. The prevalence of clinically actionable variants was comparable between the two cohorts, with most study participants (97.3%) carrying at least one actionable pharmacogenetic variant. We then assessed the frequency of high-risk prescriptions due to actionable gene-drug interactions and observed that 31% of patients in the hospital-based cohort were prescribed at least one drug for which they carried a high-risk variant, and for which international guidelines recommend a change of drug or dosage. Our analysis confirms the high prevalence of actionable pharmacogenetic variants in the Swiss population. It also shows that a substantial minority of patients are exposed to drugs for which they carry potentially problematic variants. Implementing a genetically informed approach to drug prescribing could have a positive impact on the quality of healthcare delivery.
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Affiliation(s)
- Flavia Hodel
- Precision Medicine Unit, Biomedical Data Science CenterLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Maria B. De Min
- Precision Medicine Unit, Biomedical Data Science CenterLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Christian Wandall Thorball
- Precision Medicine Unit, Biomedical Data Science CenterLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Claire Redin
- Precision Medicine Unit, Biomedical Data Science CenterLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Peter Vollenweider
- Division of Internal Medicine, Department of MedicineUniversity of Lausanne and University Hospital of LausanneLausanneSwitzerland
| | - François Girardin
- Division of Clinical Pharmacology, Department of Laboratory Medicine and PathologyLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Jacques Fellay
- Precision Medicine Unit, Biomedical Data Science CenterLausanne University Hospital and University of LausanneLausanneSwitzerland
- Global Health Institute, School of Life Sciences, EPFLLausanneSwitzerland
- Swiss Institute of BioinformaticsLausanneSwitzerland
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3
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Johnson L, Youssef E, O'Shea J, Thornley T, Gallagher J, Ledwidge M, Ryan C. Estimating the prevalence of potential and actionable drug-gene interactions in Irish primary care: A cross-sectional study. Br J Clin Pharmacol 2024; 90:2280-2298. [PMID: 38864275 DOI: 10.1111/bcp.16122] [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: 01/02/2024] [Revised: 04/03/2024] [Accepted: 04/13/2024] [Indexed: 06/13/2024] Open
Abstract
AIMS Pharmacogenetics (PGx) is increasingly recognized as a strategy for medicines optimisation and prevention of adverse drug reactions. According to guidelines produced by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetic Working Group (DPWG), most medicines with drug-gene interactions (DGIs) are prescribed in primary care. This study aimed to estimate the prevalence of potential and actionable DGIs involving all medicines dispensed in Irish primary care. METHODS Dispensings of 46 drugs to General Medical Services (GMS) patients in the Health Service Executive Primary Care Reimbursement Service Irish pharmacy claims database from 01 January 2021 to 31 December 2021 were analysed to estimate the national prevalence of total dispensings and incidence of first-time dispensings of drugs with potential DGIs according to the CPIC and/or DPWG guidelines. Phenotype frequency data from the UK Biobank and the CPIC were used to estimate the incidence of actionable DGIs. RESULTS One in five dispensings (12 443 637 of 62 754 498, 19.8%) were medicines with potential DGIs, 1 878 255 of these dispensed for the first time. On application of phenotype frequencies and linked guideline based therapeutic recommendations, 2 349 055 potential DGIs (18.9%) required action, such as monitoring and guarding against maximum dose, drug or dose change. One in five (369 700, 19.7%) first-time dispensings required action, with 139 169 (7.4%) requiring a change in prescribing. Antidepressants, weak opioids and statins were most commonly identified as having actionable DGIs. CONCLUSIONS This study estimated a high prevalence of DGIs in primary care in Ireland, identifying the need and opportunity to optimize drug therapy through PGx testing.
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Affiliation(s)
- L Johnson
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - E Youssef
- Faculty of Health, Science, Social Care & Education, Kingston University, London, UK
| | - J O'Shea
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - T Thornley
- School of Pharmacy, University of Nottingham, Nottingham, UK
| | - J Gallagher
- School of Medicine, University College Dublin, Dublin, Ireland
| | - M Ledwidge
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- School of Medicine, University College Dublin, Dublin, Ireland
| | - C Ryan
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
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4
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Hernandez S, Hindorff LA, Morales J, Ramos EM, Manolio TA. Patterns of pharmacogenetic variation in nine biogeographic groups. Clin Transl Sci 2024; 17:e70017. [PMID: 39206687 PMCID: PMC11358764 DOI: 10.1111/cts.70017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2024] [Revised: 08/02/2024] [Accepted: 08/10/2024] [Indexed: 09/04/2024] Open
Abstract
Frequencies of pharmacogenetic (PGx) variants are known to differ substantially across populations but much of the available PGx literature focuses on one or a few population groups, often defined in nonstandardized ways, or on a specific gene or variant. Guidelines produced by the Clinical Pharmacogenetic Implementation Consortium (CPIC) provide consistent methods of literature extraction, curation, and reporting, including comprehensive curation of allele frequency data across nine defined "biogeographic groups" from the PGx literature. We extracted data from 23 CPIC guidelines encompassing 19 genes to compare the sizes of the populations from each group and allele frequencies of altered function alleles across groups. The European group was the largest in the curated literature for 16 of the 19 genes, while the American and Oceanian groups were the smallest. Nearly 200 alleles were detected in nonreference groups that were not reported in the largest (reference) group. The genes CYP2B6 and CYP2C9 were more likely to have higher frequencies of altered function alleles in nonreference groups compared to the reference group, while the genes CYP4F2, DPYD, SLCO1B1, and UGT1A1 were less likely to have higher frequencies in nonreference groups. PGx allele frequencies and function differ substantially across nine biogeographic groups, all but two of which are underrepresented in available PGx data. Awareness of these differences and increased efforts to characterize the breadth of global PGx variation are needed to ensure that implementation of PGx-guided drug selection does not further widen existing health disparities among populations currently underrepresented in PGx data.
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Affiliation(s)
- Sophia Hernandez
- National Human Genome Research InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Lucia A. Hindorff
- National Human Genome Research InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Joannella Morales
- National Human Genome Research InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Erin M. Ramos
- National Human Genome Research InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Teri A. Manolio
- National Human Genome Research InstituteNational Institutes of HealthBethesdaMarylandUSA
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Magavern EF, McDermott JH, Caulfield MJ, Newman WG. CYP2C19 genetic testing for Mavacamten and ischaemic stroke treatment: What does the result mean for cardiovascular prescribers in the UK and Europe? EUROPEAN HEART JOURNAL. CARDIOVASCULAR PHARMACOTHERAPY 2024:pvae040. [PMID: 39175266 DOI: 10.1093/ehjcvp/pvae040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/11/2024] [Accepted: 05/17/2024] [Indexed: 08/24/2024]
Affiliation(s)
- Emma F Magavern
- William Harvey Research Institute, Charterhouse Square, Queen Mary University of London, London EC1M 6BQ, UK
| | - John H McDermott
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester M13 9PL, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester M13 9NT, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Charterhouse Square, Queen Mary University of London, London EC1M 6BQ, UK
| | - William G Newman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester M13 9PL, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester M13 9NT, UK
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6
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Delabays B, Trajanoska K, Walonoski J, Mooser V. Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test. Pharmacol Rev 2024; 76:791-827. [PMID: 39122647 DOI: 10.1124/pharmrev.123.000750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 04/24/2024] [Accepted: 05/28/2024] [Indexed: 08/12/2024] Open
Abstract
Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.
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Affiliation(s)
- Benoît Delabays
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
| | - Katerina Trajanoska
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
| | - Joshua Walonoski
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
| | - Vincent Mooser
- Canada Excellence Research Chair in Genomic Medicine, Victor Phillip Dahdaleh Institute of Genomic Medicine, Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada (B.D., K.T., V.M.); and Medeloop Inc., Palo Alto, California, and Montreal, QC, Canada (J.W.)
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7
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Smith H, Dawes M, Katzov-Eckert H, Burrell S, Xin Hui S, Winther MD. Improving prescribing: a feasibility study of pharmacogenetic testing with clinical decision support in primary healthcare in Singapore. Fam Pract 2024; 41:477-483. [PMID: 36417351 PMCID: PMC11324319 DOI: 10.1093/fampra/cmac124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The study of genetic variation as a factor influencing drug safety, efficacy, and effectiveness has brought about significant breakthroughs in understanding the clinical application of gene-drug interactions to better manage drug therapy. OBJECTIVE This study was designed to assess the feasibility of collecting buccal samples by general practitioners (GPs) at private practices in Singapore within a usual consultation, incorporating use of a pharmacogenetics-based medical decision support system to guide subsequent drug dosing. METHODS We used a prospective cohort study design, with GPs recruiting 189 patients between October 2020 and March 2021. The genotypes of 51 biallelic SNPs were determined using Illumina Infinium Global Screening Array. RESULTS Seven GPs from 6 private practices recruited and obtained buccal samples from a total of 189 patients. All patients had at least one actionable variant. The prevalence of patients having 2, 3, or 4 variants was 37.0%, 32.8%, and 12.7%, respectively. Potential alterations to medications were identified using the Clinical Decision Support System. Patients were accepting and the GPs were enthusiastic about the potential of pharmacogenetics to personalize medicine for their patients. CONCLUSION This is the first study in Singapore to demonstrate the feasibility of pharmacogenetic testing in primary care. The high prevalence of genetic variants underscores the potential use of pharmacogenetics in this setting.
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Affiliation(s)
- Helen Smith
- Family Medicine and Primary Care, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Martin Dawes
- Department of Family Practice, The University of British Columbia, Vancouver, BC, Canada
| | | | - Sarah Burrell
- Family Medicine and Primary Care, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Sam Xin Hui
- Family Medicine and Primary Care, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Michael D Winther
- Family Medicine and Primary Care, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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Thompson MD, Reiner-Link D, Berghella A, Rana BK, Rovati GE, Capra V, Gorvin CM, Hauser AS. G protein-coupled receptor (GPCR) pharmacogenomics. Crit Rev Clin Lab Sci 2024:1-44. [PMID: 39119983 DOI: 10.1080/10408363.2024.2358304] [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: 06/15/2023] [Revised: 09/03/2023] [Accepted: 05/18/2024] [Indexed: 08/10/2024]
Abstract
The field of pharmacogenetics, the investigation of the influence of one or more sequence variants on drug response phenotypes, is a special case of pharmacogenomics, a discipline that takes a genome-wide approach. Massively parallel, next generation sequencing (NGS), has allowed pharmacogenetics to be subsumed by pharmacogenomics with respect to the identification of variants associated with responders and non-responders, optimal drug response, and adverse drug reactions. A plethora of rare and common naturally-occurring GPCR variants must be considered in the context of signals from across the genome. Many fundamentals of pharmacogenetics were established for G protein-coupled receptor (GPCR) genes because they are primary targets for a large number of therapeutic drugs. Functional studies, demonstrating likely-pathogenic and pathogenic GPCR variants, have been integral to establishing models used for in silico analysis. Variants in GPCR genes include both coding and non-coding single nucleotide variants and insertion or deletions (indels) that affect cell surface expression (trafficking, dimerization, and desensitization/downregulation), ligand binding and G protein coupling, and variants that result in alternate splicing encoding isoforms/variable expression. As the breadth of data on the GPCR genome increases, we may expect an increase in the use of drug labels that note variants that significantly impact the clinical use of GPCR-targeting agents. We discuss the implications of GPCR pharmacogenomic data derived from the genomes available from individuals who have been well-phenotyped for receptor structure and function and receptor-ligand interactions, and the potential benefits to patients of optimized drug selection. Examples discussed include the renin-angiotensin system in SARS-CoV-2 (COVID-19) infection, the probable role of chemokine receptors in the cytokine storm, and potential protease activating receptor (PAR) interventions. Resources dedicated to GPCRs, including publicly available computational tools, are also discussed.
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Affiliation(s)
- Miles D Thompson
- Krembil Brain Institute, Toronto Western Hospital, Toronto, Ontario, Canada
| | - David Reiner-Link
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Alessandro Berghella
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Brinda K Rana
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - G Enrico Rovati
- Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Valerie Capra
- Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, Milan, Italy
| | - Caroline M Gorvin
- Institute of Metabolism and Systems Research (IMSR), University of Birmingham, Birmingham, United Kingdom
| | - Alexander S Hauser
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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9
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Li D, Pain O, Fabbri C, Wong WLE, Lo CWH, Ripke S, Cattaneo A, Souery D, Dernovsek MZ, Henigsberg N, Hauser J, Lewis G, Mors O, Perroud N, Rietschel M, Uher R, Maier W, Baune BT, Biernacka JM, Bondolfi G, Domschke K, Kato M, Liu YL, Serretti A, Tsai SJ, Weinshilboum R, McIntosh AM, Lewis CM. Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis. Transl Psychiatry 2024; 14:296. [PMID: 39025838 PMCID: PMC11258238 DOI: 10.1038/s41398-024-02981-1] [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: 06/27/2023] [Revised: 06/10/2024] [Accepted: 06/18/2024] [Indexed: 07/20/2024] Open
Abstract
Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.
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Affiliation(s)
- Danyang Li
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK
- Cancer Centre, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, CN, China
| | - Oliver Pain
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, GB, UK
| | - Chiara Fabbri
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Win Lee Edwin Wong
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Chris Wai Hang Lo
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, DE, Germany
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Annamaria Cattaneo
- Biological Psychiatry Laboratory, IRCCS Fatebenefratelli, Brescia, Italy
- Department of Pharmacological and Biomedical Sciences, University of Milan, Milan, Italy
| | - Daniel Souery
- Laboratoire de Psychologie Medicale, Universitè Libre de Bruxelles and Psy Pluriel, Centre Européen de Psychologie Medicale, Brussels, Italy
| | - Mojca Z Dernovsek
- University Psychiatric Clinic, University of Ljubliana, Ljubljana, Slovenia
| | - Neven Henigsberg
- Department of Psychiatry, Croatian Institute for Brain Research, University of Zagreb Medical School, Zagreb, HR, Croatia
| | - Joanna Hauser
- Psychiatric Genetic Unit, Poznan University of Medical Sciences, Poznan, Poland
| | - Glyn Lewis
- Division of Psychiatry, University College London, London, GB, UK
| | - Ole Mors
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
| | - Nader Perroud
- Department of Psychiatry, Geneva University Hospitals, Geneva, CH, Switzerland
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, University of Heidelberg, Central Institute of Mental Health, Mannheim, Denmark
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Denmark
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Denmark
- Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
- Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia
| | - Joanna M Biernacka
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Guido Bondolfi
- Department of Psychiatry, Geneva University Hospitals, Geneva, CH, Switzerland
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center, University of Freiburg, Freiburg, Denmark
| | - Masaki Kato
- Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | | | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Richard Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | | | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB, UK.
- Department of Medical & Molecular Genetics, King's College London, London, GB, UK.
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10
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Tesfamicael KG, Zhao L, Fernández-Rodríguez R, Adelson DL, Musker M, Polasek TM, Lewis MD. Efficacy and safety of pharmacogenomic-guided antidepressant prescribing in patients with depression: an umbrella review and updated meta-analysis. Front Psychiatry 2024; 15:1276410. [PMID: 39086729 PMCID: PMC11289719 DOI: 10.3389/fpsyt.2024.1276410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 06/26/2024] [Indexed: 08/02/2024] Open
Abstract
Aim To determine the efficacy and safety of pharmacogenomics (PGx)-guided antidepressant prescribing in patients with depression through an umbrella review and updated meta-analysis. Methods A comprehensive systematic search was conducted on PsycINFO, PubMed, Embase and the Cochrane databases. The pooled effect sizes of randomized controlled trials (RCTs) were expressed as mean differences for continuous data and risk ratios for noncontinuous data. Results Patients who received PGx-guided medications were 41% to 78% more likely to achieve remission and 20% to 49% more likely to respond to antidepressants than patients receiving treatment-as-usual (TAU). Conclusion PGx-guided antidepressant prescribing improves the treatment of depression. However, the significance and magnitude of the benefit varies widely between studies and different PGx testing panels. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD42022321324.
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Affiliation(s)
- Kiflu G. Tesfamicael
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- Lifelong Health, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia
| | - Lijun Zhao
- Lifelong Health, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia
- Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
| | | | - David L. Adelson
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Michael Musker
- Adelaide Nursing School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Thomas M. Polasek
- Centre for Medicine Use and Safety, Monash University, Melbourne, VIC, Australia
| | - Martin David Lewis
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- Lifelong Health, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, SA, Australia
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11
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Singh J, Wilkins G, Goodman-Vincent E, Chishti S, Bonilla Guerrero R, McFadden L, Zahavi Z, Santosh P. Co-Occurring Methylenetetrahydrofolate Reductase ( MTHFR) rs1801133 and rs1801131 Genotypes as Associative Genetic Modifiers of Clinical Severity in Rett Syndrome. Brain Sci 2024; 14:624. [PMID: 39061365 PMCID: PMC11275218 DOI: 10.3390/brainsci14070624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 07/28/2024] Open
Abstract
AIM Remethylation disorders such as 5,10-methylenetetrahydrofolate reductase (MTHFR) deficiency reduce the remethylation of homocysteine to methionine. The resulting hyperhomocysteinemia can lead to serious neurological consequences and multisystem toxicity. The role of MTHFR genotypes has not been investigated in patients with Rett Syndrome (RTT). In this study, we sought to assess the impact of co-occurring MTHFR genotypes on symptom profiles in RTT. METHOD Using pharmacogenomic (PGx) testing, the MTHFR genetic polymorphisms rs1801133 (c.665C>T mutation) and rs1801131 (c.1286A>C mutation) were determined in 65 patients (18.7 years ± 12.1 [mean ± standard deviation]) with RTT as part of routine clinical care within the Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, a National and Specialist Child and Adolescent Mental Health Service (CAMHS) in the UK. The clinical severity of patients was assessed using the RTT-anchored Clinical Global Impression Scale (RTT-CGI). RESULTS The clinical severity symptom distribution varied between the homozygous and heterozygous MTHFR rs1801133 and rs1801131 genotypes. Those with the homozygous genotype had a narrower spread of severity scores across several domains (language and communication, ambulation, hand-use and eye contact clinical domains). Patients with the homozygous genotype had statistically significantly greater CGI-Severity scores than individuals with a non-homozygous MTHFR genotype (Z = -2.44, p = 0.015). When comparing the ratings of moderately impaired (4), markedly impaired (5), severely impaired (6) and extremely impaired (7), individuals with the homozygous MTHFR genotype were more impaired than those with the non-homozygous MTHFR genotype (Z = -2.06, p = 0.039). There was no statistically significant difference in the number of prescribed anti-epileptic drugs between the genotypes. CONCLUSIONS Our findings show that in those with a pathogenic RTT genetic variant, co-occurring homozygotic MTHFR rs1801133 and rs1801131 polymorphisms may act as associative genetic modifiers of clinical severity in a subset of patients. Profiling of rs1801133 and rs1801131 in RTT may therefore be useful, especially for high-risk patients who may be at the most risk from symptom deterioration.
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Affiliation(s)
- Jatinder Singh
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK; (J.S.); (G.W.); (E.G.-V.); (S.C.); (L.M.)
- Centre for Interventional Paediatric Psychopharmacology and Rare Diseases (CIPPRD), South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Georgina Wilkins
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK; (J.S.); (G.W.); (E.G.-V.); (S.C.); (L.M.)
- Centre for Interventional Paediatric Psychopharmacology and Rare Diseases (CIPPRD), South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Ella Goodman-Vincent
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK; (J.S.); (G.W.); (E.G.-V.); (S.C.); (L.M.)
- Centre for Interventional Paediatric Psychopharmacology and Rare Diseases (CIPPRD), South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Samiya Chishti
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK; (J.S.); (G.W.); (E.G.-V.); (S.C.); (L.M.)
- Centre for Interventional Paediatric Psychopharmacology and Rare Diseases (CIPPRD), South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | | | - Leighton McFadden
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK; (J.S.); (G.W.); (E.G.-V.); (S.C.); (L.M.)
- Centre for Interventional Paediatric Psychopharmacology and Rare Diseases (CIPPRD), South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Zvi Zahavi
- Myogenes Limited, Borehamwood WD6 4PJ, UK;
| | - Paramala Santosh
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK; (J.S.); (G.W.); (E.G.-V.); (S.C.); (L.M.)
- Centre for Interventional Paediatric Psychopharmacology and Rare Diseases (CIPPRD), South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
- Centre for Interventional Paediatric Psychopharmacology (CIPP) Rett Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
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12
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Haddad A, Radhakrishnan A, McGee S, Smith JD, Karnes JH, Venner E, Wheeler MM, Patterson K, Walker K, Kalra D, Kalla SE, Wang Q, Gibbs RA, Jarvik GP, Sanchez J, Musick A, Ramirez AH, Denny JC, Empey PE. Frequency of pharmacogenomic variation and medication exposures among All of Us Participants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.12.24304664. [PMID: 38946996 PMCID: PMC11213053 DOI: 10.1101/2024.06.12.24304664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Pharmacogenomics promises improved outcomes through individualized prescribing. However, the lack of diversity in studies impedes clinical translation and equitable application of precision medicine. We evaluated the frequencies of PGx variants, predicted phenotypes, and medication exposures using whole genome sequencing and EHR data from nearly 100k diverse All of Us Research Program participants. We report 100% of participants carried at least one pharmacogenomics variant and nearly all (99.13%) had a predicted phenotype with prescribing recommendations. Clinical impact was high with over 20% having both an actionable phenotype and a prior exposure to an impacted medication with pharmacogenomic prescribing guidance. Importantly, we also report hundreds of alleles and predicted phenotypes that deviate from known frequencies and/or were previously unreported, including within admixed American and African ancestry groups.
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13
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Cernat A, Samaan Z, Abelson J, Ramdyal A, Shaikh H, Vanstone M. Patient perspectives on pharmacogenomic (PGx) testing for antidepressant prescribing in primary care: a qualitative description study. J Community Genet 2024; 15:293-309. [PMID: 38587601 PMCID: PMC11217204 DOI: 10.1007/s12687-024-00705-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 03/28/2024] [Indexed: 04/09/2024] Open
Abstract
Many patients with major depressive disorder (MDD) try multiple antidepressants before finding one that works well and is tolerable. Pharmacogenomic (PGx) testing was developed to facilitate more efficacious prescribing. This technology has not been robustly implemented clinically. Patient perspectives are critical to policy decisions, but the views of patients with MDD about the use of PGx testing to guide antidepressant prescribing have not been extensively examined, particularly in publicly funded healthcare systems. The purpose of this qualitative description study was to produce actionable patient perspectives evidence to inform future technology assessment of PGx testing. We conducted semi-structured interviews with 21 adults with MDD for which antidepressants were indicated in Ontario, Canada, and used the Ontario Decision Determinants Framework to conduct an unconstrained deductive content analysis. Patients expressed views about the overall clinical benefit of PGx testing in depression care, preferences for deployment of testing, perspectives on ethical considerations, opinions about equity and patient care, and beliefs regarding the feasibility of adopting PGx testing into the healthcare system. They also worried about the possibility of conflicts of interest between PGx test manufacturers and pharmaceutical companies. This study provides policymakers with patient priorities to facilitate the development of patient-centred policies. It highlights that formal adoption of PGx testing into the healthcare system requires a focus on equity of access and health outcomes.
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Affiliation(s)
- Alexandra Cernat
- Department of Family Medicine, McMaster University, 100 Main St W, Hamilton, ON, L8P 1H6, Canada
- Health Policy PhD Program, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, L8S 4L8, Canada
| | - Zainab Samaan
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, L8S 4L8, Canada
| | - Julia Abelson
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, L8S 4L8, Canada
| | - Amanada Ramdyal
- Department of Family Medicine, McMaster University, 100 Main St W, Hamilton, ON, L8P 1H6, Canada
| | - Hadia Shaikh
- Department of Family Medicine, McMaster University, 100 Main St W, Hamilton, ON, L8P 1H6, Canada
- Biomedical Discovery and Commercialization Program, Faculty of Health Sciences, McMaster University, Hamilton, L8S 4L8, Canada
| | - Meredith Vanstone
- Department of Family Medicine, McMaster University, 100 Main St W, Hamilton, ON, L8P 1H6, Canada.
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14
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Drent M, Wijnen PA, Jessurun NT, Harmsze AM, Bekers O, Bast A. Drug-Gene Risk Stratification in Patients with Suspected Drug-Induced Interstitial Lung Disease. Drug Saf 2024; 47:355-363. [PMID: 38460070 PMCID: PMC10955005 DOI: 10.1007/s40264-024-01400-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/18/2024] [Indexed: 03/11/2024]
Abstract
BACKGROUND Pulmonary toxicity has been associated with drug use. This is often not recognized in clinical practice, and underestimated. OBJECTIVE We aimed to establish whether polymorphisms in certain genes corresponding with a metabolic pathway of drug(s) used are associated with pulmonary toxicity in patients with suspected drug-induced interstitial lung disease (DI-ILD). METHODS This retrospective observational study explored genetic variations in three clinically relevant cytochrome P450 (CYP) iso-enzymes (i.e., CYP2D6, CYP2C9, and CYP2C19) in a group of patients with a fibroticinterstitial lung disease, either non-specific interstitial pneumonia (n = 211) or idiopathic pulmonary fibrosis (n = 256), with a suspected drug-induced origin. RESULTS Of the 467 patients, 79.0% showed one or more polymorphisms in the tested genes accompanied by the use of drug(s) metabolized by a corresponding affected metabolic pathway (60.0% poor metabolizers and/or using two or more drugs [likely DI-ILD], 37.5% using three or more [highly likely DI-ILD]). Most commonly used drugs were statins (63.1%) with a predominance among men (69.4 vs 47.1%, p < 0.0001). Nitrofurantoin, not metabolized by the tested pathways, was prescribed more frequently among women (51.9 vs 4.5%, p < 0.00001). CONCLUSIONS In our cohort with suspected DI-ILD, 79% carried one or more genetic variants accompanied by the use of drugs metabolized by a corresponding affected pathway. In 60%, the diagnosis of DI-ILD was likely, whereas in 37.5%, it was highly likely, based on CYP analyses. This study underlines the importance of considering both drug use and genetic make-up as a possible cause, or at least a contributing factor, in the development and/or progression of fibrotic lung diseases. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov identifier NCT00267800, registered in 2005.
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Affiliation(s)
- Marjolein Drent
- Department of Pharmacology and Toxicology, Faculty of Health, Medicine, and Life Science, Maastricht University, Maastricht, The Netherlands.
- ILD Center of Excellence, St. Antonius Hospital, Nieuwegein, The Netherlands.
- Research Team, ILD Care Foundation, Heideoordlaan 8, 6711NR, Ede, The Netherlands.
| | - Petal A Wijnen
- ILD Center of Excellence, St. Antonius Hospital, Nieuwegein, The Netherlands
- Research Team, ILD Care Foundation, Heideoordlaan 8, 6711NR, Ede, The Netherlands
- Department of Clinical Chemistry, Central Diagnostic Laboratory, Maastricht University Medical Centre, P Debyelaan 25, 6229 HX, Maastricht, The Netherlands
| | - Naomi T Jessurun
- Research Team, ILD Care Foundation, Heideoordlaan 8, 6711NR, Ede, The Netherlands
- Netherlands Pharmacovigilance Centre Lareb, Goudsbloemvallei 7, 5237 MH, 's-Hertogenbosch, The Netherlands
| | - Ankie M Harmsze
- ILD Center of Excellence, St. Antonius Hospital, Nieuwegein, The Netherlands
- Department of Clinical Pharmacology, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - Otto Bekers
- Department of Pharmacology and Toxicology, Faculty of Health, Medicine, and Life Science, Maastricht University, Maastricht, The Netherlands
- Department of Clinical Chemistry, Central Diagnostic Laboratory, Maastricht University Medical Centre, P Debyelaan 25, 6229 HX, Maastricht, The Netherlands
| | - Aalt Bast
- Department of Pharmacology and Toxicology, Faculty of Health, Medicine, and Life Science, Maastricht University, Maastricht, The Netherlands
- Research Team, ILD Care Foundation, Heideoordlaan 8, 6711NR, Ede, The Netherlands
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15
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Jameson A, Faisal M, Fylan B, Bristow GC, Sohal J, Dalton C, Sagoo GS, Cardno AG, McLean SL. Proportion of Antipsychotics with CYP2D6 Pharmacogenetic (PGx) Associations Prescribed in an Early Intervention in Psychosis (EIP) Cohort: A Cross-Sectional Study. J Psychopharmacol 2024; 38:382-394. [PMID: 38494658 PMCID: PMC11010551 DOI: 10.1177/02698811241238283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
BACKGROUND Prescribing drugs for psychosis (antipsychotics) is challenging due to high rates of poor treatment outcomes, which are in part explained by an individual's genetics. Pharmacogenomic (PGx) testing can help clinicians tailor the choice or dose of psychosis drugs to an individual's genetics, particularly psychosis drugs with known variable response due to CYP2D6 gene variants ('CYP2D6-PGx antipsychotics'). AIMS This study aims to investigate differences between demographic groups prescribed 'CYP2D6-PGx antipsychotics' and estimate the proportion of patients eligible for PGx testing based on current pharmacogenomics guidance. METHODS A cross-sectional study took place extracting data from 243 patients' medical records to explore psychosis drug prescribing, including drug transitions. Demographic data such as age, sex, ethnicity, and clinical sub-team were collected and summarised. Descriptive statistics explored the proportion of 'CYP2D6-PGx antipsychotic' prescribing and the nature of transitions. We used logistic regression analysis to investigate associations between demographic variables and prescription of 'CYP2D6-PGx antipsychotic' versus 'non-CYP2D6-PGx antipsychotic'. RESULTS Two-thirds (164) of patients had been prescribed a 'CYP2D6-PGx antipsychotic' (aripiprazole, risperidone, haloperidol or zuclopenthixol). Over a fifth (23%) of patients would have met the suggested criteria for PGx testing, following two psychosis drug trials. There were no statistically significant differences between age, sex, or ethnicity in the likelihood of being prescribed a 'CYP2D6-PGx antipsychotic'. CONCLUSIONS This study demonstrated high rates of prescribing 'CYP2D6-PGx-antipsychotics' in an EIP cohort, providing a rationale for further exploration of how PGx testing can be implemented in EIP services to personalise the prescribing of drugs for psychosis.
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Affiliation(s)
- Adam Jameson
- Bradford District Care NHS Foundation Trust, Bradford, UK
- School of Pharmacy & Medical Sciences, University of Bradford, Bradford, UK
- Wolfson Centre for Applied Health Research, Bradford, UK
| | - Muhammad Faisal
- Wolfson Centre for Applied Health Research, Bradford, UK
- Faculty of Health Studies, University of Bradford, Bradford, UK
- NIHR Yorkshire and Humber Patient Safety Research Collaboration (YH PSRC), Bradford, UK
| | - Beth Fylan
- School of Pharmacy & Medical Sciences, University of Bradford, Bradford, UK
- Wolfson Centre for Applied Health Research, Bradford, UK
- NIHR Yorkshire and Humber Patient Safety Research Collaboration (YH PSRC), Bradford, UK
| | - Greg C Bristow
- School of Pharmacy & Medical Sciences, University of Bradford, Bradford, UK
| | - Jaspreet Sohal
- Bradford District Care NHS Foundation Trust, Bradford, UK
| | - Caroline Dalton
- Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK
| | - Gurdeep S Sagoo
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Alastair G Cardno
- Leeds Institute of Health Sciences, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Samantha L McLean
- School of Pharmacy & Medical Sciences, University of Bradford, Bradford, UK
- Wolfson Centre for Applied Health Research, Bradford, UK
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16
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Dolin RH, Shenvi E, Alvarez C, Barrows RC, Boxwala A, Lee B, Nathanson BH, Kleyner Y, Hagemann R, Hongsermeier T, Kapusnik-Uner J, Lakdawala A, Shalaby J. PillHarmonics: An Orchestrated Pharmacogenetics Medication Clinical Decision Support Service. Appl Clin Inform 2024; 15:378-387. [PMID: 38388174 PMCID: PMC11098593 DOI: 10.1055/a-2274-6763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
OBJECTIVES Pharmacogenetics (PGx) is increasingly important in individualizing therapeutic management plans, but is often implemented apart from other types of medication clinical decision support (CDS). The lack of integration of PGx into existing CDS may result in incomplete interaction information, which may pose patient safety concerns. We sought to develop a cloud-based orchestrated medication CDS service that integrates PGx with a broad set of drug screening alerts and evaluate it through a clinician utility study. METHODS We developed the PillHarmonics service for implementation per the CDS Hooks protocol, algorithmically integrating a wide range of drug interaction knowledge using cloud-based screening services from First Databank (drug-drug/allergy/condition), PharmGKB (drug-gene), and locally curated content (drug-renal/hepatic/race). We performed a user study, presenting 13 clinicians and pharmacists with a prototype of the system's usage in synthetic patient scenarios. We collected feedback via a standard questionnaire and structured interview. RESULTS Clinician assessment of PillHarmonics via the Technology Acceptance Model questionnaire shows significant evidence of perceived utility. Thematic analysis of structured interviews revealed that aggregated knowledge, concise actionable summaries, and information accessibility were highly valued, and that clinicians would use the service in their practice. CONCLUSION Medication safety and optimizing efficacy of therapy regimens remain significant issues. A comprehensive medication CDS system that leverages patient clinical and genomic data to perform a wide range of interaction checking and presents a concise and holistic view of medication knowledge back to the clinician is feasible and perceived as highly valuable for more informed decision-making. Such a system can potentially address many of the challenges identified with current medication-related CDS.
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Affiliation(s)
| | - Edna Shenvi
- Elimu Informatics, El Cerrito, California, United States
| | - Carla Alvarez
- Elimu Informatics, El Cerrito, California, United States
| | | | - Aziz Boxwala
- Elimu Informatics, El Cerrito, California, United States
| | - Benson Lee
- College of Pharmacy, Touro University California, Vallejo, California, United States
| | | | - Yelena Kleyner
- Elimu Informatics, El Cerrito, California, United States
| | - Rachel Hagemann
- Independent Contractor, San Francisco, California, United States
| | | | | | | | - James Shalaby
- Elimu Informatics, El Cerrito, California, United States
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17
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Skokou M, Karamperis K, Koufaki MI, Tsermpini EE, Pandi MT, Siamoglou S, Ferentinos P, Bartsakoulia M, Katsila T, Mitropoulou C, Patrinos GP. Clinical implementation of preemptive pharmacogenomics in psychiatry. EBioMedicine 2024; 101:105009. [PMID: 38364700 PMCID: PMC10879811 DOI: 10.1016/j.ebiom.2024.105009] [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: 08/03/2023] [Revised: 01/28/2024] [Accepted: 01/30/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Pharmacogenomics (PGx) holds promise to revolutionize modern healthcare. Although there are several prospective clinical studies in oncology and cardiology, demonstrating a beneficial effect of PGx-guided treatment in reducing adverse drug reactions, there are very few such studies in psychiatry, none of which spans across all main psychiatric indications, namely schizophrenia, major depressive disorder and bipolar disorder. In this study we aim to investigate the clinical effectiveness of PGx-guided treatment (occurrence of adverse drug reactions, hospitalisations and re-admissions, polypharmacy) and perform a cost analysis of the intervention. METHODS We report our findings from a multicenter, large-scale, prospective study of pre-emptive genome-guided treatment named as PREemptive Pharmacogenomic testing for preventing Adverse drug REactions (PREPARE) in a large cohort of psychiatric patients (n = 1076) suffering from schizophrenia, major depressive disorder and bipolar disorder. FINDINGS We show that patients with an actionable phenotype belonging to the PGx-guided arm (n = 25) present with 34.1% less adverse drug reactions compared to patients belonging to the control arm (n = 36), 41.2% less hospitalisations (n = 110 in the PGx-guided arm versus n = 187 in the control arm) and 40.5% less re-admissions (n = 19 in the PGx-guided arm versus n = 32 in the control arm), less duration of initial hospitalisations (n = 3305 total days of hospitalisation in the PGx-guided arm from 110 patients, versus n = 6517 in the control arm from 187 patients) and duration of hospitalisation upon readmission (n = 579 total days of hospitalisation upon readmission in the PGx-guided arm, derived from 19 patients, versus n = 928 in the control arm, from 32 patients respectively). It was also shown that in the vast majority of the cases, there was less drug dose administrated per drug in the PGx-guided arm compared to the control arm and less polypharmacy (n = 124 patients prescribed with at least 4 psychiatric drugs in the PGx-guided arm versus n = 143 in the control arm) and smaller average number of co-administered psychiatric drugs (2.19 in the PGx-guided arm versus 2.48 in the control arm. Furthermore, less deaths were reported in the PGx-guided arm (n = 1) compared with the control arm (n = 9). Most importantly, we observed a 48.5% reduction of treatment costs in the PGx-guided arm with a reciprocal slight increase of the quality of life of patients suffering from major depressive disorder (0.935 versus 0.925 QALYs in the PGx-guided and control arm, respectively). INTERPRETATION While only a small proportion (∼25%) of the entire study sample had an actionable genotype, PGx-guided treatment can have a beneficial effect in psychiatric patients with a reciprocal reduction of treatment costs. Although some of these findings did not remain significant when all patients were considered, our data indicate that genome-guided psychiatric treatment may be successfully integrated in mainstream healthcare. FUNDING European Union Horizon 2020.
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Affiliation(s)
- Maria Skokou
- Department of Psychiatry, University of Patras General Hospital, Patras, Greece
| | - Kariofyllis Karamperis
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece; The Golden Helix Foundation, London, UK
| | - Margarita-Ioanna Koufaki
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece; The Golden Helix Foundation, London, UK
| | - Evangelia-Eirini Tsermpini
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece
| | - Maria-Theodora Pandi
- Erasmus University Medical Center, Faculty of Medicine and Health Sciences, Department of Pathology, Clinical Bioinformatics Unit, Rotterdam, the Netherlands
| | - Stavroula Siamoglou
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece
| | - Panagiotis Ferentinos
- 2nd Department of Psychiatry, National and Kapodistrian University of Athens, ATIKON University General Hospital, Athens, Greece
| | - Marina Bartsakoulia
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece
| | - Theodora Katsila
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece
| | | | - George P Patrinos
- Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, University of Patras, School of Health Sciences, Patras, Greece; Erasmus University Medical Center, Faculty of Medicine and Health Sciences, Department of Pathology, Clinical Bioinformatics Unit, Rotterdam, the Netherlands; Department of Genetics and Genomics, United Arab Emirates University, College of Medicine and Health Sciences, Al-Ain, Abu Dhabi, United Arab Emirates; United Arab Emirates University, Zayed Center for Health Sciences, Al-Ain, Abu Dhabi, United Arab Emirates.
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18
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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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19
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Kennedy A, Ma G, Manshaei R, Jobling RK, Kim RH, Lewis T, Cohn I. A call for increased inclusivity and global representation in pharmacogenetic testing. NPJ Genom Med 2024; 9:13. [PMID: 38388691 PMCID: PMC10883987 DOI: 10.1038/s41525-024-00403-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/08/2024] [Indexed: 02/24/2024] Open
Abstract
Commercial pharmacogenetic testing panels capture a fraction of the genetic variation underlying medication metabolism and predisposition to adverse reactions. In this study we compared variation in six pharmacogenes detected by whole genome sequencing (WGS) to a targeted commercial panel in a cohort of 308 individuals with family history of pediatric heart disease. In 1% of the cohort, WGS identified rare variants that altered the interpretation of metabolizer status and would thus prevent potential errors in gene-based dosing.
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Affiliation(s)
- April Kennedy
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada
| | - Gabriel Ma
- University of Toronto, Toronto, ON, Canada
| | - Roozbeh Manshaei
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, ON, Canada
| | - Rebekah K Jobling
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, ON, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada
- Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada
| | - Raymond H Kim
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, ON, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada
- Fred A. Litwin Family Centre in Genetic Medicine, University Health Network, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Tamorah Lewis
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada
- Division of Neonatology, Department of Paediatrics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Iris Cohn
- Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada.
- Cardiac Genome Clinic, Ted Rogers Centre for Heart Research, The Hospital for Sick Children, Toronto, ON, Canada.
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20
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Thamilselvan M, Mather C, Wang Y, Foo JC, Aitchison KJ. Haplotype phasing of CYP2D6: an allelic ratio method using Agena MassARRAY data. Transl Psychiatry 2024; 14:91. [PMID: 38346976 PMCID: PMC10861455 DOI: 10.1038/s41398-024-02809-y] [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: 05/26/2023] [Revised: 01/18/2024] [Accepted: 01/29/2024] [Indexed: 02/15/2024] Open
Abstract
Pharmacogenomics aims to use the genetic information of an individual to personalize drug prescribing. There is evidence that pharmacogenomic testing before prescription may prevent adverse drug reactions, increase efficacy, and reduce cost of treatment. CYP2D6 is a key pharmacogene of relevance to multiple therapeutic areas. Indeed, there are prescribing guidelines available for medications based on CYP2D6 enzyme activity as deduced from CYP2D6 genetic data. The Agena MassARRAY system is a cost-effective method of detecting genetic variation that has been clinically applied to other genes. However, its clinical application to CYP2D6 has to date been limited by weaknesses such as the inability to determine which haplotype was present in more than one copy for individuals with more than two copies of the CYP2D6 gene. We report application of a new protocol for CYP2D6 haplotype phasing of data generated from the Agena MassARRAY system. For samples with more than two copies of the CYP2D6 gene for which the prior consensus data specified which one was present in more than one copy, our protocol was able to conduct CYP2D6 haplotype phasing resulting in 100% concordance with the prior data. In addition, for three reference samples known to have more than two copies of CYP2D6 but for which the exact number of CYP2D6 genes was unknown, our protocol was able to resolve the number for two out of the three of these, and estimate the likely number for the third. Finally, we demonstrate that our method is applicable to CYP2D6 hybrid tandem configurations.
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Affiliation(s)
- Megana Thamilselvan
- University of Alberta, College of Natural and Applied Sciences, Department of Biological Sciences, Edmonton, Canada
| | - Cheryl Mather
- University of Alberta, College of Health Sciences, Department of Laboratory Medicine and Pathology, Edmonton, Canada
- Alberta Precision Laboratories, Edmonton, Canada
| | - Yabing Wang
- University of Alberta, College of Health Sciences, Department of Psychiatry, Edmonton, Canada
| | - Jerome C Foo
- University of Alberta, College of Health Sciences, Department of Psychiatry, Edmonton, Canada
| | - Katherine J Aitchison
- University of Alberta, College of Health Sciences, Department of Psychiatry, Edmonton, Canada.
- University of Alberta, Neuroscience and Mental Health Institute, Edmonton, Canada.
- University of Alberta, College of Health Sciences, Department of Medical Genetics, Edmonton, Canada.
- Northern Ontario School of Medicine, Thunder Bay, Canada.
- University of Alberta, Women and Children's Health Research Institute, Edmonton, Canada.
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21
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Friedman JM, Bombard Y, Carleton B, Issa AM, Knoppers B, Plon SE, Rahimzadeh V, Relling MV, Williams MS, van Karnebeek C, Vears D, Cornel MC. Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child? Genet Med 2024; 26:101033. [PMID: 38007624 DOI: 10.1016/j.gim.2023.101033] [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: 04/24/2023] [Revised: 11/14/2023] [Accepted: 11/19/2023] [Indexed: 11/27/2023] Open
Abstract
This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.
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Affiliation(s)
- Jan M Friedman
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada.
| | - Yvonne Bombard
- Genomics Health Services Research Program, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Bruce Carleton
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada; Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada; Pharmaceutical Outcomes Programme, British Columbia Children's Hospital, Vancouver, British Columbia, Canada
| | - Amalia M Issa
- Personalized Precision Medicine & Targeted Therapeutics, Springfield, MA; Health Policy, University of the Sciences, Philadelphia, PA; Pharmaceutical Sciences, University of the Sciences, Philadelphia, PA; Family Medicine, McGill University, Montreal, Quebec, Canada
| | - Bartha Knoppers
- Centre of Genomics and Policy, Faculty of Medicine and Health Sciences, McGill University, Montreal, Quebec, Canada
| | - Sharon E Plon
- Department of Pediatrics, Texas Children's Cancer and Hematology Center, Baylor College of Medicine, Houston, TX; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Vasiliki Rahimzadeh
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | | | - Clara van Karnebeek
- Emma Center for Personalized Medicine, Amsterdam UMC, Amsterdam, The Netherlands; Departments of Pediatrics and Human Genetics, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands; United for Metabolic Diseases, The Netherlands; Radboud Center for Mitochondrial and Metabolic Medicine, Department of Pediatrics, Amalia Children's Hospital, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Danya Vears
- University of Melbourne, Carlton, Melbourne, Australia; Biomedical Ethics Research Group, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Martina C Cornel
- Department of Human Genetics and Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, The Netherlands
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22
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Abouelhoda M, Almuqati N, Abogosh A, Alfraih F, Maddirevula S, Alkuraya FS. Mining local exome and HLA data to characterize pharmacogenetic variants in Saudi Arabia. Hum Genet 2024; 143:125-136. [PMID: 38159139 DOI: 10.1007/s00439-023-02628-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 11/24/2023] [Indexed: 01/03/2024]
Abstract
Pharmacogenomics (PGx) is a promising field of precision medicine where efficacy of drugs is maximized while side effects are minimized for individual patients. Knowledge of the frequency of PGx-relevant variants (pharmacovariants) in the local population is a pre-requisite to informed policy making. Unfortunately, such knowledge is largely lacking from the Middle East. Here, we describe the use of a large clinical exome database (n = 13,473) and HLA haplotypes (n = 64,737) from Saudi Arabia, one of the largest countries in the Middle East, along with previously published data from the local population to ascertain allele frequencies of known pharmacovariants. In addition, we queried another exome database (n = 816) of well-phenotyped research subjects from Saudi Arabia to discover novel candidate variants in known PGx genes (pharmacogenes). Although our results show that only 26% (63/242) of class 1A/1B PharmGKB variants were identified, we estimate that 99.57% of the local population have at least one such variant. This translates to a minimum estimated impact of 9% of medications dispensed by our medical center annually. We also highlight the contribution of rare variants where 71% of the pharmacogenes devoid of common pharmacovariants had at least one potentially deleterious rare variant. Thus, we show that approaches that go beyond the use of commercial PGx kits that have been optimized for other populations should be implemented to ensure universal and equitable access of all members of the local population to personalized prescription practices.
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Affiliation(s)
- Mohamed Abouelhoda
- Department of Computational Sciences, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Noura Almuqati
- Department of Translational Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Ahmed Abogosh
- Department of Translational Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Feras Alfraih
- Oncology Centre, Faisal Specialist Hospital and Research Centre, Riyadh, King, Saudi Arabia
| | - Sateesh Maddirevula
- Department of Translational Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Fowzan S Alkuraya
- Department of Translational Genomics, Centre for Genomic Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
- Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, 11533, Riyadh, Saudi Arabia.
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23
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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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24
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Li D, Pain O, Fabbri C, Wong WLE, Lo CWH, Ripke S, Cattaneo A, Souery D, Dernovsek MZ, Henigsberg N, Hauser J, Lewis G, Mors O, Perroud N, Rietschel M, Uher R, Maier W, Baune BT, Biernacka JM, Bondolfi G, Domschke K, Kato M, Liu YL, Serretti A, Tsai SJ, Weinshilboum R, McIntosh AM, Lewis CM. Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.26.23291890. [PMID: 37425775 PMCID: PMC10327261 DOI: 10.1101/2023.06.26.23291890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I2=0%, subgroup difference p=0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19 and CYP2D6, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.
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Affiliation(s)
- Danyang Li
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB
| | - Oliver Pain
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, GB
| | - Chiara Fabbri
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, IT
| | - Win Lee Edwin Wong
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, SG
| | - Chris Wai Hang Lo
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, DE
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, US
| | - Annamaria Cattaneo
- Biological Psychiatry Laboratory, IRCCS Fatebenefratelli, Brescia, IT
- Department of Pharmacological and Biomedical Sciences, University of Milan, Milan, IT
| | - Daniel Souery
- Laboratoire de Psychologie Medicale, Universitè Libre de Bruxelles and Psy Pluriel, Centre Européen de Psychologie Medicale, Brussels, BE
| | - Mojca Z Dernovsek
- University Psychiatric Clinic, University of Ljubliana, Ljubljana, SI
| | - Neven Henigsberg
- Department of Psychiatry, Croatian Institute for Brain Research, University of Zagreb Medical School, Zagreb, HR
| | - Joanna Hauser
- Psychiatric Genetic Unit,, Poznan University of Medical Sciences, Poznan, PL
| | - Glyn Lewis
- Division of Psychiatry, University College London, London, GB
| | - Ole Mors
- Psychosis Research Unit, Aarhus University Hospital - Psychiatry, Aarhus, DK
| | - Nader Perroud
- Department of Psychiatry, Geneva University Hospitals, Geneva, CH
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Medical Faculty Mannheim, University of Heidelberg, Central Institute of Mental Health, Mannheim, DE
| | - Rudolf Uher
- Department of Psychiatry, Dalhousie University, Halifax, NS, CA
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, DE
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, DE
- Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, AU
- Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, AU
| | - Joanna M Biernacka
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Guido Bondolfi
- Department of Psychiatry, Geneva University Hospitals, Geneva, CH
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center, University of Freiburg, Freiburg, DE
| | - Masaki Kato
- Department of Neuropsychiatry, Kansai Medical University, Osaka, JP
| | - Yu-Li Liu
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, TW
| | - Alessandro Serretti
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, IT
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, TW
- Division of Psychiatry, School of Medicine, National Yang-Ming University, Taipei, TW
| | - Richard Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | | | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, GB
- Department of Medical & Molecular Genetics, King's College London, London, GB
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25
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Bousman CA, Maruf AA, Marques DF, Brown LC, Müller DJ. The emergence, implementation, and future growth of pharmacogenomics in psychiatry: a narrative review. Psychol Med 2023; 53:7983-7993. [PMID: 37772416 PMCID: PMC10755240 DOI: 10.1017/s0033291723002817] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 08/24/2023] [Accepted: 08/30/2023] [Indexed: 09/30/2023]
Abstract
Psychotropic medication efficacy and tolerability are critical treatment issues faced by individuals with psychiatric disorders and their healthcare providers. For some people, it can take months to years of a trial-and-error process to identify a medication with the ideal efficacy and tolerability profile. Current strategies (e.g. clinical practice guidelines, treatment algorithms) for addressing this issue can be useful at the population level, but often fall short at the individual level. This is, in part, attributed to interindividual variation in genes that are involved in pharmacokinetic (i.e. absorption, distribution, metabolism, elimination) and pharmacodynamic (e.g. receptors, signaling pathways) processes that in large part, determine whether a medication will be efficacious or tolerable. A precision prescribing strategy know as pharmacogenomics (PGx) assesses these genomic variations, and uses it to inform selection and dosing of certain psychotropic medications. In this review, we describe the path that led to the emergence of PGx in psychiatry, the current evidence base and implementation status of PGx in the psychiatric clinic, and finally, the future growth potential of precision psychiatry via the convergence of the PGx-guided strategy with emerging technologies and approaches (i.e. pharmacoepigenomics, pharmacomicrobiomics, pharmacotranscriptomics, pharmacoproteomics, pharmacometabolomics) to personalize treatment of psychiatric disorders.
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Affiliation(s)
- Chad A. Bousman
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, AB, Canada
- Department of Medical Genetics, University of Calgary, Calgary, AB, Canada
- Departments of Physiology and Pharmacology, and Community Health Sciences, University of Calgary, Calgary, AB, Canada
- AB Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia
| | - Abdullah Al Maruf
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, AB, Canada
- College of Pharmacy, Rady Faculty of Health Sciences, Winnipeg, MB, Canada
| | | | | | - Daniel J. Müller
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Wurzburg, Wurzburg, Germany
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26
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Barthélémy D, Belmonte E, Pilla LD, Bardel C, Duport E, Gautier V, Payen L. Direct Comparative Analysis of a Pharmacogenomics Panel with PacBio Hifi ® Long-Read and Illumina Short-Read Sequencing. J Pers Med 2023; 13:1655. [PMID: 38138882 PMCID: PMC10744512 DOI: 10.3390/jpm13121655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 11/10/2023] [Accepted: 11/23/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Pharmacogenetics (PGx) aims to determine genetic signatures that can be used in clinical settings to individualize treatment for each patient, including anti-cancer drugs, anti-psychotics, and painkillers. Taken together, a better understanding of the impacts of genetic variants on the corresponding protein function or expression permits the prediction of the pharmacological response: responders, non-responders, and those with adverse drug reactions (ADRs). OBJECTIVE This work provides a comparison between innovative long-read sequencing (LRS) and short-read sequencing (SRS) techniques. METHODS AND MATERIALS The gene panel captured using PacBio HiFi® sequencing was tested on thirteen clinical samples on GENTYANE's platform. SRS, using a comprehensive pharmacogenetics panel, was performed in routine settings at the Civil Hospitals of Lyon. We focused on complex regions analysis, including copy number variations (CNVs), structural variants, repeated regions, and phasing-haplotyping for three key pharmacogenes: CYP2D6, UGT1A1, and NAT2. RESULTS Variants and the corresponding expected star (*) alleles were reported. Although only 38.4% concordance was found for haplotype determination and 61.5% for diplotype, this did not affect the metabolism scoring. A better accuracy of LRS was obtained for the detection of the CYP2D6*5 haplotype in the presence of the duplicated wild-type CYP2D6*2 form. A total concordance was performed for UGT1A1 TA repeat detection. Direct phasing using the LRS approach allowed us to correct certain NAT2 profiles. CONCLUSIONS Combining an optimized variant-calling pipeline and with direct phasing analysis, LRS is a robust technique for PGx analysis that can minimize the risk of mis-haplotyping.
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Affiliation(s)
- David Barthélémy
- Institut of Pharmaceutical and Biological Sciences of Lyon, Claude Bernard Lyon I, 69373 Lyon, France; (D.B.); (C.B.)
- Department of Biochemistry and Molecular Biology, Lyon-Sud Hospital, Hospices Civils de Lyon, Réseau Francophone de Pharmacogénétique (RNPGx), 69495 Pierre-Bénite, France; (L.D.P.); (E.D.)
- Center for Innovation in Cancerology of Lyon (CICLY) EA 3738, Faculty of Medicine and Maieutic Lyon Sud, Claude Bernard University Lyon I, 69921 Oullins, France
| | - Elodie Belmonte
- Plateforme Génotypage et Séquençage en Auvergne (GENTYANE) UMR 1095 Génétique, Diversité Ecophysiologie des Céréales INRAE, Université Clermont Auvergne, 63100 Clermont Ferrand, France; (E.B.); (V.G.)
| | - Laurie Di Pilla
- Department of Biochemistry and Molecular Biology, Lyon-Sud Hospital, Hospices Civils de Lyon, Réseau Francophone de Pharmacogénétique (RNPGx), 69495 Pierre-Bénite, France; (L.D.P.); (E.D.)
| | - Claire Bardel
- Institut of Pharmaceutical and Biological Sciences of Lyon, Claude Bernard Lyon I, 69373 Lyon, France; (D.B.); (C.B.)
- Department of Bioinformatics, Hospices Civils de Lyon, 69008 Lyon, France
| | - Eve Duport
- Department of Biochemistry and Molecular Biology, Lyon-Sud Hospital, Hospices Civils de Lyon, Réseau Francophone de Pharmacogénétique (RNPGx), 69495 Pierre-Bénite, France; (L.D.P.); (E.D.)
| | - Veronique Gautier
- Plateforme Génotypage et Séquençage en Auvergne (GENTYANE) UMR 1095 Génétique, Diversité Ecophysiologie des Céréales INRAE, Université Clermont Auvergne, 63100 Clermont Ferrand, France; (E.B.); (V.G.)
| | - Léa Payen
- Institut of Pharmaceutical and Biological Sciences of Lyon, Claude Bernard Lyon I, 69373 Lyon, France; (D.B.); (C.B.)
- Department of Biochemistry and Molecular Biology, Lyon-Sud Hospital, Hospices Civils de Lyon, Réseau Francophone de Pharmacogénétique (RNPGx), 69495 Pierre-Bénite, France; (L.D.P.); (E.D.)
- Center for Innovation in Cancerology of Lyon (CICLY) EA 3738, Faculty of Medicine and Maieutic Lyon Sud, Claude Bernard University Lyon I, 69921 Oullins, France
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27
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McDermott JH, Newman W. Introduction to pharmacogenetics. Drug Ther Bull 2023; 61:168-172. [PMID: 37788890 DOI: 10.1136/dtb.2023.000009] [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: 10/05/2023]
Abstract
There is considerable interindividual variability in the effectiveness and safety of medicines. Although the reasons for this are multifactorial, it is well recognised that genetic changes impacting the absorption or metabolism of these drugs play a significant contributory role. Understanding how these pharmacogenetic variants impact response to medicines, and leveraging this knowledge to guide prescribing, could have significant benefits for patients and health services. This article provides an introduction to the field of pharmacogenetics, including its nomenclature, the existing evidence base and the current state of implementation globally. We discuss the challenges in translating pharmacogenetic research into clinical practice and highlight the considerable benefits which can emerge in those health services where implementation is successful.
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Affiliation(s)
- John Henry McDermott
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, UK
| | - William Newman
- Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, UK
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Li B, Sangkuhl K, Whaley R, Woon M, Keat K, Whirl-Carrillo M, Ritchie MD, Klein TE. Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank. Am J Hum Genet 2023; 110:1628-1647. [PMID: 37757824 PMCID: PMC10577080 DOI: 10.1016/j.ajhg.2023.09.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 09/29/2023] Open
Abstract
Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.
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Affiliation(s)
- Binglan Li
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Ryan Whaley
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Mark Woon
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Karl Keat
- Genomics and Computational Biology PhD Program, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Department of Genetics (by courtesy), Stanford University, Stanford, CA 94305, USA; Department of Medicine (BMIR), Stanford University, Stanford, CA 94305, USA.
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Wong WLE, Fabbri C, Laplace B, Li D, van Westrhenen R, Lewis CM, Dawe GS, Young AH. The Effects of CYP2C19 Genotype on Proxies of SSRI Antidepressant Response in the UK Biobank. Pharmaceuticals (Basel) 2023; 16:1277. [PMID: 37765085 PMCID: PMC10535191 DOI: 10.3390/ph16091277] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/03/2023] [Accepted: 09/06/2023] [Indexed: 09/29/2023] Open
Abstract
Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used psychopharmaceutical treatment for major depressive disorder (MDD), but individual responses to SSRIs vary greatly. CYP2C19 is a key enzyme involved in the metabolism of several drugs, including SSRIs. Variations in the CYP2C19 gene are associated with differential metabolic activity, and thus differential SSRI exposure; accordingly, the CYP2C19 genotype may affect the therapeutic response and clinical outcomes, though existing evidence of this link is not entirely consistent. Therefore, we analysed data from the UK Biobank, a large, deeply phenotyped prospective study, to investigate the effects of CYP2C19 metaboliser phenotypes on several clinical outcomes derived from primary care records, including multiple measures of antidepressant switching, discontinuation, duration, and side effects. In this dataset, 24,729 individuals were prescribed citalopram, 3012 individuals were prescribed escitalopram, and 12,544 individuals were prescribed sertraline. Consistent with pharmacological expectations, CYP2C19 poor metabolisers on escitalopram were more likely to switch antidepressants, have side effects following first prescription, and be on escitalopram for a shorter duration compared to normal metabolisers. CYP2C19 poor and intermediate metabolisers on citalopram also exhibited increased odds of discontinuation and shorter durations relative to normal metabolisers. Generally, no associations were found between metabolic phenotypes and proxies of response to sertraline. Sensitivity analyses in a depression subgroup and metabolic activity scores corroborated results from the primary analysis. In summary, our findings suggest that CYP2C19 genotypes, and thus metabolic phenotypes, may have utility in determining clinical responses to SSRIs, particularly escitalopram and citalopram, though further investigation of such a relationship is warranted.
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Affiliation(s)
- Win Lee Edwin Wong
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117600, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London SE5 8AG, UK; (R.v.W.)
| | - Chiara Fabbri
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, 40127 Bologna, Italy
| | - Benjamin Laplace
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- Psychiatry Department of Research and Innovation, Esquirol Hospital Center, 87000 Limoges, France
| | - Danyang Li
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Roos van Westrhenen
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London SE5 8AG, UK; (R.v.W.)
- Parnassia Psychiatric Institute/PsyQ, 1062 HN Amsterdam, The Netherlands
- Department of Psychiatry & Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands
| | - Cathryn M. Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Gavin Stewart Dawe
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117600, Singapore
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Neurobiology Programme, Life Sciences Institute, National University of Singapore, Singapore 119077, Singapore
| | - Allan H. Young
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London SE5 8AG, UK; (R.v.W.)
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King’s College London, London WC2R 2LS, UK
- South London & Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Monks Orchard Road, London BR3 3BX, UK
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Rodriguez Llorian E, Kopac N, Waliji LA, Borle K, Dragojlovic N, Elliott AM, Lynd LD. A Rapid Review on the Value of Biobanks Containing Genetic Information. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2023; 26:1286-1295. [PMID: 36921900 DOI: 10.1016/j.jval.2023.02.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 01/20/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVES Increasing access to health data through biobanks containing genetic information has the potential to expand the knowledge base and thereby improve screening, diagnosis, and treatment options for many diseases. Nevertheless, although privacy concerns and risks surrounding genetic data sharing are well documented, direct evidence in favor of the hypothesized benefits of data integration is scarce, which complicates decision making in this area. Therefore, the objective of this study is to summarize the available evidence on the research and clinical impacts of biobanks containing genetic information, so as to better understand how to quantify the value of expanding genomic data access. METHODS Using a rapid review methodology, we performed a search of MEDLINE/PubMed and Embase databases; and websites of biobanks and genomic initiatives published from 2010 to 2022. We classified findings into 11 indicators including outputs (a direct product of the biobank activities) and outcomes (changes in scientific and clinical capacity). RESULTS Of 8479 abstracts and 101 gray literature sources were reviewed, 96 records were included. Although most records did not report key indicators systematically, the available evidence concentrated on research indicators such as publications and gene-disorder association discoveries (63% of studies), followed by research infrastructure (26%), and clinical indicators (11%) such as supporting the diagnosis of individual patients. CONCLUSIONS Existing evidence on the benefits of biobanks is skewed toward easily quantifiable research outputs. Measuring a comprehensive set of outputs and outcomes inspired by value frameworks is necessary to generate better evidence on the benefits of genomic data sharing.
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Affiliation(s)
- Elisabet Rodriguez Llorian
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada.
| | - Nicola Kopac
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Louloua Ashikhusein Waliji
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Kennedy Borle
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Nick Dragojlovic
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Alison M Elliott
- Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Larry D Lynd
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada; Centre for Health Evaluation and Outcome Sciences (CHÉOS), St. Paul's Hospital, Vancouver, BC, Canada
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Kleine Schaars K, van Westrhenen R. Pharmacogenomics and the Management of Mood Disorders-A Review. J Pers Med 2023; 13:1183. [PMID: 37511796 PMCID: PMC10381396 DOI: 10.3390/jpm13071183] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/13/2023] [Accepted: 07/22/2023] [Indexed: 07/30/2023] Open
Abstract
Due to the chronic relapsing nature of mental disorders and increased life expectancy, the societal burden of these non-communicable diseases will increase even further. Treatments for mental disorders, such as depression, are available, but their effect is limited due to patients' (genetic) heterogeneity, low treatment compliance and frequent side effects. In general, only one-third of the patients respond to treatment. Today, medication selection in psychiatry relies on a trial-and-error approach based mainly on physicians' experience. Pharmacogenetic (PGx) testing can help in this process by determining the person-specific genetic factors that may predict clinical response and side effects associated with genetic variants that impact drug-metabolizing enzymes, drug transporters or drug targets. PGxis a discipline that investigates genetic factors that affect the absorption, metabolism, and transport of drugs, thereby affecting therapy outcome. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Studies in depressed patients show that genotyping of drug-metabolizing enzymes can increase the effectiveness of treatment, which could benefit millions of patients worldwide. This review highlights these studies, gives recommendations and provides future perspectives on how to proceed with PGx testing. Finally, it is recommended to consider genotyping for CYP2D6 and CYP2C19, when there is an indication (side effects or inefficacy).
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Affiliation(s)
- Kristian Kleine Schaars
- Outpatient Clinic Pharmacogenetics, Parnassia Psychiatric Institute/PsyQ, Overschiestraat 57, 1062 HN Amsterdam, The Netherlands
| | - Roos van Westrhenen
- Outpatient Clinic Pharmacogenetics, Parnassia Psychiatric Institute/PsyQ, Overschiestraat 57, 1062 HN Amsterdam, The Netherlands
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, De Crespigny Park, Denmark Hill, London SES 8AF, UK
- Department of Psychiatry & Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, P.O. Box 6161, 6229 ER Maastricht, The Netherlands
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Bollinger A, Stäuble CK, Jeiziner C, Wiss FM, Hersberger KE, Lampert ML, Meyer zu Schwabedissen HE, Allemann SS. Genotyping of Patients with Adverse Drug Reaction or Therapy Failure: Database Analysis of a Pharmacogenetics Case Series Study. Pharmgenomics Pers Med 2023; 16:693-706. [PMID: 37426898 PMCID: PMC10327911 DOI: 10.2147/pgpm.s415259] [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: 03/31/2023] [Accepted: 06/19/2023] [Indexed: 07/11/2023] Open
Abstract
Purpose Pharmacogenetics (PGx) is an emerging aspect of personalized medicine with the potential to increase efficacy and safety of pharmacotherapy. However, PGx testing is still not routinely integrated into clinical practice. We conducted an observational case series study where PGx information from a commercially available panel test covering 30 genes was integrated into medication reviews. The aim of the study was to identify the drugs that are most frequently object of drug-gene-interactions (DGI) in the study population. Patients and Methods In out-patient and in-patient settings, we recruited 142 patients experiencing adverse drug reaction (ADR) and/or therapy failure (TF). Collected anonymized data from the individual patient was harmonized and transferred to a structured database. Results The majority of the patients had a main diagnosis of a mental or behavioral disorder (ICD-10: F, 61%), of musculoskeletal system and connective tissue diseases (ICD-10: M, 21%), and of the circulatory system (ICD-10: I, 11%). The number of prescribed medicines reached a median of 7 per person, resulting in a majority of patients with polypharmacy (≥5 prescribed medicines, 65%). In total, 559 suspected DGI were identified in 142 patients. After genetic testing, an association with at least one genetic variation was confirmed for 324 suspected DGI (58%) caused by 64 different drugs and 21 different genes in 141 patients. After 6 months, PGx-based medication adjustments were recorded for 62% of the study population, whereby differences were identified in subgroups. Conclusion The data analysis from this study provides valuable insights for the main focus of further research in the context of PGx. The results indicate that most of the selected patients in our sample represent suitable target groups for PGx panel testing in clinical practice, notably those taking drugs for mental or behavioral disorder, circulatory diseases, immunological diseases, pain-related diseases, and patients experiencing polypharmacy.
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Affiliation(s)
- Anna Bollinger
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - Céline K Stäuble
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
- Institute of Hospital Pharmacy, Solothurner Spitäler AG, Olten, Switzerland
| | - Chiara Jeiziner
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - Florine M Wiss
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
- Institute of Hospital Pharmacy, Solothurner Spitäler AG, Olten, Switzerland
| | - Kurt E Hersberger
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - Markus L Lampert
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
- Institute of Hospital Pharmacy, Solothurner Spitäler AG, Olten, Switzerland
| | | | - Samuel S Allemann
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
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Samarasinghe SR, Hoy W, Jadhao S, McMorran BJ, Guchelaar HJ, Nagaraj SH. The pharmacogenomic landscape of an Indigenous Australian population. Front Pharmacol 2023; 14:1180640. [PMID: 37284308 PMCID: PMC10241071 DOI: 10.3389/fphar.2023.1180640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 04/07/2023] [Indexed: 06/08/2023] Open
Abstract
Background: Population genomic studies of individuals of Indigenous ancestry have been extremely limited comprising <0.5% of participants in international genetic databases and genome-wide association studies, contributing to a "genomic gap" that limits their access to personalised medicine. While Indigenous Australians face a high burden of chronic disease and associated medication exposure, corresponding genomic and drug safety datasets are sorely lacking. Methods: To address this, we conducted a pharmacogenomic study of almost 500 individuals from a founder Indigenous Tiwi population. Whole genome sequencing was performed using short-read Illumina Novaseq6000 technology. We characterised the pharmacogenomics (PGx) landscape of this population by analysing sequencing results and associated pharmacological treatment data. Results: We observed that every individual in the cohort carry at least one actionable genotype and 77% of them carry at least three clinically actionable genotypes across 19 pharmacogenes. Overall, 41% of the Tiwi cohort were predicted to exhibit impaired CYP2D6 metabolism, with this frequency being much higher than that for other global populations. Over half of the population predicted an impaired CYP2C9, CYP2C19, and CYP2B6 metabolism with implications for the processing of commonly used analgesics, statins, anticoagulants, antiretrovirals, antidepressants, and antipsychotics. Moreover, we identified 31 potentially actionable novel variants within Very Important Pharmacogenes (VIPs), five of which were common among the Tiwi. We further detected important clinical implications for the drugs involved with cancer pharmacogenomics such as thiopurines and tamoxifen, immunosuppressants like tacrolimus and certain antivirals used in the hepatitis C treatment due to potential differences in their metabolic processing. Conclusion: The pharmacogenomic profiles generated in our study demonstrate the utility of pre-emptive PGx testing and have the potential to help guide the development and application of precision therapeutic strategies tailored to Tiwi Indigenous patients. Our research provides valuable insights on pre-emptive PGx testing and the feasibility of its use in ancestrally diverse populations, emphasizing the need for increased diversity and inclusivity in PGx investigations.
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Affiliation(s)
| | - Wendy Hoy
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Sudhir Jadhao
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Brendan J McMorran
- John Curtin School of Medical Research, College of Health and Medicine, Australian National University, Canberra, ACT, Australia
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD, Australia
- Translational Research Institute, Queensland University of Technology, Brisbane, QLD, Australia
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Salas-Hernández A, Galleguillos M, Carrasco M, López-Cortés A, Redal MA, Fonseca-Mendoza D, Esperón P, González-Martínez F, Lares-Asseff I, Lazarowski A, Loera-Castañeda V, Remírez D, Martínez MF, Vargas R, Rios-Santos F, Macho A, Cayún JP, Perez GR, Gutierrez C, Cerpa LC, Leiva T, Calfunao S, Xajil L, Sandoval C, Suárez M, Gonzalez A, Echeverría-Garcés G, Sullón-Dextre L, Cordero-García E, Morales AR, Avendaño A, Sánchez E, Bastone LC, Lara C, Zuluaga-Arias P, Soler AM, Da Luz J, Burgueño-Rodríguez G, Vital M, Reyes-Reyes E, Huaccha A, Ariza YV, Tzul N, Rendón AL, Serrano R, Acosta L, Motta-Pardo A, Beltrán-Angarita L, Brand E, Jiménez MA, Hidalgo-Lozada GM, Romero-Prado MMJ, Escobar-Castro K, Umaña-Rivas M, Vivas JD, Lagos P, Martínez YB, Quesada S, Calfio C, Arias ML, Lavanderos MA, Cáceres DD, Salazar-Granara A, Varela NM, Quiñones LA. An updated examination of the perception of barriers for pharmacogenomics implementation and the usefulness of drug/gene pairs in Latin America and the Caribbean. Front Pharmacol 2023; 14:1175737. [PMID: 37251329 PMCID: PMC10213898 DOI: 10.3389/fphar.2023.1175737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/21/2023] [Indexed: 05/31/2023] Open
Abstract
Pharmacogenomics (PGx) is considered an emergent field in developing countries. Research on PGx in the Latin American and the Caribbean (LAC) region remains scarce, with limited information in some populations. Thus, extrapolations are complicated, especially in mixed populations. In this paper, we reviewed and analyzed pharmacogenomic knowledge among the LAC scientific and clinical community and examined barriers to clinical application. We performed a search for publications and clinical trials in the field worldwide and evaluated the contribution of LAC. Next, we conducted a regional structured survey that evaluated a list of 14 potential barriers to the clinical implementation of biomarkers based on their importance. In addition, a paired list of 54 genes/drugs was analyzed to determine an association between biomarkers and response to genomic medicine. This survey was compared to a previous survey performed in 2014 to assess progress in the region. The search results indicated that Latin American and Caribbean countries have contributed 3.44% of the total publications and 2.45% of the PGx-related clinical trials worldwide thus far. A total of 106 professionals from 17 countries answered the survey. Six major groups of barriers were identified. Despite the region's continuous efforts in the last decade, the primary barrier to PGx implementation in LAC remains the same, the "need for guidelines, processes, and protocols for the clinical application of pharmacogenetics/pharmacogenomics". Cost-effectiveness issues are considered critical factors in the region. Items related to the reluctance of clinicians are currently less relevant. Based on the survey results, the highest ranked (96%-99%) gene/drug pairs perceived as important were CYP2D6/tamoxifen, CYP3A5/tacrolimus, CYP2D6/opioids, DPYD/fluoropyrimidines, TMPT/thiopurines, CYP2D6/tricyclic antidepressants, CYP2C19/tricyclic antidepressants, NUDT15/thiopurines, CYP2B6/efavirenz, and CYP2C19/clopidogrel. In conclusion, although the global contribution of LAC countries remains low in the PGx field, a relevant improvement has been observed in the region. The perception of the usefulness of PGx tests in biomedical community has drastically changed, raising awareness among physicians, which suggests a promising future in the clinical applications of PGx in LAC.
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Affiliation(s)
- Aimeé Salas-Hernández
- Department of Pharmacology, Toxicology and Pharmaco-Dependence, Faculty of Pharmacy, University of Costa Rica, San Jose, Costa Rica
| | - Macarena Galleguillos
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Matías Carrasco
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Andrés López-Cortés
- Cancer Research Group (CRG), Faculty of Medicine, Universidad de Las Américas, Quito, Ecuador
| | - María Ana Redal
- Molecular Diagnostic Laboratory, Genetics Division, Faculty of Medicine, Hospital de Clínicas José de San Martín, University of Buenos Aires, Buenos Aires, Argentina
| | - Dora Fonseca-Mendoza
- Universidad del Rosario, School of Medicine and Health Sciences, Center for Research in Genetics and Genomics (CIGGUR), Institute of Translational Medicine (IMT), Bogotá, Colombia
| | - Patricia Esperón
- Molecular Genetic Unit, School of Chemistry, Universidad de la República, General Flores, CP 1800 2124, Montevideo, Uruguay
| | - Farith González-Martínez
- Toxicology and Public Health Research Laboratory, Department of Research, Faculty of Dentistry, University of Cartagena, Cartagena, Colombia
| | - Ismael Lares-Asseff
- Academy of Genomics and Laboratory of Pharmacogenomics and Molecular Biomedicine, Instituto Politécnico Nacional, CIIDIR-Unidad Durango, Durango, Mexico
| | - Alberto Lazarowski
- Instituto de Fisiopatología y Bioquímica Clínica (INFIBIOC), Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires- Argentina, Buenos Aires, Argentina
| | - Verónica Loera-Castañeda
- Academy of Genomics and Laboratory of Pharmacogenomics and Molecular Biomedicine, Instituto Politécnico Nacional, CIIDIR-Unidad Durango, Durango, Mexico
| | | | - Matías F. Martínez
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Department of Pharmaceutical Sciences and Technology, Faculty of Chemical and Pharmaceutical Sciences, University of Chile, Santiago, Chile
| | - Rodrigo Vargas
- Department of Molecular Biology, Galileo University, Guatemala City, Guatemala
| | - Fabricio Rios-Santos
- Department of Health. Faculty of Medicine, Federal University of Mato Grosso (UFMT), Cuibá, Brazil
| | - Antonio Macho
- Morphology and Applied Immunology Research Center (NuPMIA), University of Brasilia (UnB), Brasília, Brazil
| | - Juan P. Cayún
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Germán R. Perez
- Department of Microbiology, Faculty of Biochemical and Pharmaceutical Sciences. National University of Rosario, Rosario, Argentina
| | - Carolina Gutierrez
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Leslie C. Cerpa
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Tamara Leiva
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Susan Calfunao
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Laboratory Pathological Anatomy, Hospital Luis Calvo Mackenna, Santiago, Chile
| | - Lesly Xajil
- Department of Research in Pharmacogenomics, Faculty of Chemical Sciences and Pharmacy, University of San Carlos de Guatemala, Guatemala, Guatemala
| | - Christopher Sandoval
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Clinical Laboratory Blood Biochemistry and Immunoassay Section, Hospital Clínico Félix Bulnes Cerda, Santiago, Chile
| | - Marcelo Suárez
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Pharmacy Service, Hospital UC-Christus, Santiago, Chile
| | | | | | | | - Eugenia Cordero-García
- Department of Pharmacology, Toxicology and Pharmaco-Dependence, Faculty of Pharmacy, University of Costa Rica, San Jose, Costa Rica
| | - Alexis R. Morales
- Department of Toxicology and Pharmacology, Faculty of Pharmacy and Bioanalisis, University of Los Andes, Merida, Venezuela
| | - Andrea Avendaño
- Department of Pediatrics, Medical Genetics Unity, Faculty of Medicine, University of Los Andes, Mérida, Venezuela
| | | | - Laura C. Bastone
- Laboratorio de Medicina Genómica, Gammalab, Grupo Gamma, Rosario, Argentina
| | - Cesar Lara
- Betesda La Alternativa Natural, San José, Costa Rica
| | | | - Ana María Soler
- Laboratorio de Genética Molecular Humana, Departamento de Ciencias Biológicas, Universidad de La República, Montevideo, Uruguay
| | - Julio Da Luz
- Laboratorio de Genética Molecular Humana, Departamento de Ciencias Biológicas, Universidad de La República, Montevideo, Uruguay
| | - Gabriela Burgueño-Rodríguez
- Laboratorio de Genética Molecular Humana, Departamento de Ciencias Biológicas, Universidad de La República, Montevideo, Uruguay
| | - Marcelo Vital
- Molecular Genetic Unit, School of Chemistry, Universidad de la República, General Flores 2124, Montevideo, Uruguay
| | - Elizabeth Reyes-Reyes
- Clinical Experimental Pharmacology Section, Teaching and Research Department, Institute of Oncology and Radiobiology, Havana, Cuba
| | | | - Yeimy V. Ariza
- Pharmaceutical Chemistry Program, El Bosque University, Bogotá, Colombia
| | - Naomi Tzul
- Drug Inspectorate Unit, Ministry of Health and Wellness, Belmopan, Belize
| | - Ana L. Rendón
- Department of Pharmaceutical Technology, National Autonomous University of Honduras, Tegucigalpa, Honduras
| | | | - Larissa Acosta
- Faculty of Biology, Chemistry and Pharmacy, Galileo University, Guatemala, Guatemala
| | - Angelo Motta-Pardo
- GENOBIDC, Faculty of Pharmacy and Biochemistry, Universidad Nacional Mayor de San Marcos (UNMSM), CIGBM, Faculty of Medicine, Universidad de San Martin de Porres (USMP), Lima, Peru
| | - Leonardo Beltrán-Angarita
- Faculty of Heath Sciences, Central Unit of Valle del Cauca, Tuluá, Colombia
- Chemistry School, Universidad Tecnológica de Pereira, Pereira, Colombia
| | - Erika Brand
- Postgraduate Department, Master’s Degree in Immunology, Universidad Cayetano Heredia, Lima, Perú
| | | | | | - Marina M. J. Romero-Prado
- Department of Physiology, Health Sciences University Center, University of Guadalajara, Guadalajara, Jalisco, Mexico
| | - Karla Escobar-Castro
- Laboratory of Histocompatibility and Immunogenetics, Department of Nephrology and Transplant, Hospital General San Juan de Dios, Guatemala, Guatemala
| | - Mariel Umaña-Rivas
- Department of Tropical Medicine, Faculty of Medicine, University of Brasília, Brasília, Brazil
| | - Juan D. Vivas
- Department of Clinical Pharmacology, Faculty of Medicine, University of La Sabana, Chía, Colombia
| | - Paola Lagos
- Recombinant Biopharmaceutical Laboratory, Department of Pharmacology, Faculty of Biological Sciences, University of Concepción, Concepción, Chile
| | - Yineth Ballén Martínez
- Medical Specialist in Epidemiology Clinical Pharmacology Teacher; Medical Scientific and Pharmacovigilance Advisor in the Pharmaceutical Industry, Bogotá, Colombia
| | - Sharleth Quesada
- Faculty of Pharmacy, University of Costa Rica, San Jose, Costa Rica
| | - Camila Calfio
- International Center for Biomedicine ICC, Santiago, Chile
| | - Maria L. Arias
- Tropical Diseases Research Center and Microbiology Faculty, University of Costa Rica, San José, Costa Rica
| | - María A. Lavanderos
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Dante D. Cáceres
- Environmental Health Programme, School of Public Health, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Alberto Salazar-Granara
- Universidad de San Martín de Porres, Facultad de Medicina Humana, Centro de Investigación de Medicina Tradicional y Farmacología, Lima, Perú
| | - Nelson M. Varela
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
| | - Luis A. Quiñones
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department of Basic-Clinical Oncology (DOBC), Faculty of Medicine, University of Chile, Santiago, Chile
- Department of Pharmaceutical Sciences and Technology, Faculty of Chemical and Pharmaceutical Sciences, University of Chile, Santiago, Chile
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Bertholim-Nasciben L, Scliar MO, Debortoli G, Thiruvahindrapuram B, Scherer SW, Duarte YAO, Zatz M, Suarez-Kurtz G, Parra EJ, Naslavsky MS. Characterization of pharmacogenomic variants in a Brazilian admixed cohort of elderly individuals based on whole-genome sequencing data. Front Pharmacol 2023; 14:1178715. [PMID: 37234706 PMCID: PMC10206227 DOI: 10.3389/fphar.2023.1178715] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 04/10/2023] [Indexed: 05/28/2023] Open
Abstract
Introduction: Research in the field of pharmacogenomics (PGx) aims to identify genetic variants that modulate response to drugs, through alterations in their pharmacokinetics (PK) or pharmacodynamics (PD). The distribution of PGx variants differs considerably among populations, and whole-genome sequencing (WGS) plays a major role as a comprehensive approach to detect both common and rare variants. This study evaluated the frequency of PGx markers in the context of the Brazilian population, using data from a population-based admixed cohort from Sao Paulo, Brazil, which includes variants from WGS of 1,171 unrelated, elderly individuals. Methods: The Stargazer tool was used to call star alleles and structural variants (SVs) from 38 pharmacogenes. Clinically relevant variants were investigated, and the predicted drug response phenotype was analyzed in combination with the medication record to assess individuals potentially at high-risk of gene-drug interaction. Results: In total, 352 unique star alleles or haplotypes were observed, of which 255 and 199 had a frequency < 0.05 and < 0.01, respectively. For star alleles with frequency > 5% (n = 97), decreased, loss-of-function and unknown function accounted for 13.4%, 8.2% and 27.8% of alleles or haplotypes, respectively. Structural variants (SVs) were identified in 35 genes for at least one individual, and occurred with frequencies >5% for CYP2D6, CYP2A6, GSTM1, and UGT2B17. Overall 98.0% of the individuals carried at least one high risk genotype-predicted phenotype in pharmacogenes with PharmGKB level of evidence 1A for drug interaction. The Electronic Health Record (EHR) Priority Result Notation and the cohort medication registry were combined to assess high-risk gene-drug interactions. In general, 42.0% of the cohort used at least one PharmGKB evidence level 1A drug, and 18.9% of individuals who used PharmGKB evidence level 1A drugs had a genotype-predicted phenotype of high-risk gene-drug interaction. Conclusion: This study described the applicability of next-generation sequencing (NGS) techniques for translating PGx variants into clinically relevant phenotypes on a large scale in the Brazilian population and explores the feasibility of systematic adoption of PGx testing in Brazil.
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Affiliation(s)
- Luciana Bertholim-Nasciben
- School of Public Health, University of São Paulo, São Paulo, Brazil
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Marilia O. Scliar
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
| | - Guilherme Debortoli
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | | | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Yeda A. O. Duarte
- Medical-Surgical Nursing Department, School of Nursing, University of São Paulo, São Paulo, Brazil
| | - Mayana Zatz
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
| | - Guilherme Suarez-Kurtz
- Divisão de Pesquisa Clínica e Desenvolvimento Tecnológico, Instituto Nacional de Câncer, Rio de Janeiro, Brazil
| | - Esteban J. Parra
- Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON, Canada
| | - Michel S. Naslavsky
- Human Genome and Stem Cell Research Center, University of São Paulo, São Paulo, Brazil
- Department of Genetics and Evolutionary Biology, Biosciences Institute, University of São Paulo, São Paulo, Brazil
- Hospital Israelita Albert Einstein, São Paulo, Brazil
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Nunez-Torres R, Pita G, Peña-Chilet M, López-López D, Zamora J, Roldán G, Herráez B, Álvarez N, Alonso MR, Dopazo J, Gonzalez-Neira A. A Comprehensive Analysis of 21 Actionable Pharmacogenes in the Spanish Population: From Genetic Characterisation to Clinical Impact. Pharmaceutics 2023; 15:pharmaceutics15041286. [PMID: 37111771 PMCID: PMC10140932 DOI: 10.3390/pharmaceutics15041286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 04/03/2023] [Accepted: 04/16/2023] [Indexed: 04/29/2023] Open
Abstract
The implementation of pharmacogenetics (PGx) is a main milestones of precision medicine nowadays in order to achieve safer and more effective therapies. Nevertheless, the implementation of PGx diagnostics is extremely slow and unequal worldwide, in part due to a lack of ethnic PGx information. We analysed genetic data from 3006 Spanish individuals obtained by different high-throughput (HT) techniques. Allele frequencies were determined in our population for the main 21 actionable PGx genes associated with therapeutical changes. We found that 98% of the Spanish population harbours at least one allele associated with a therapeutical change and, thus, there would be a need for a therapeutical change in a mean of 3.31 of the 64 associated drugs. We also identified 326 putative deleterious variants that were not previously related with PGx in 18 out of the 21 main PGx genes evaluated and a total of 7122 putative deleterious variants for the 1045 PGx genes described. Additionally, we performed a comparison of the main HT diagnostic techniques, revealing that after whole genome sequencing, genotyping with the PGx HT array is the most suitable solution for PGx diagnostics. Finally, all this information was integrated in the Collaborative Spanish Variant Server to be available to and updated by the scientific community.
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Affiliation(s)
- Rocio Nunez-Torres
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Guillermo Pita
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - María Peña-Chilet
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centre for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, 41013 Sevilla, Spain
- Computational Systems Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Seville, Spain
| | - Daniel López-López
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centre for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, 41013 Sevilla, Spain
- Computational Systems Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Seville, Spain
| | - Jorge Zamora
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Gema Roldán
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
| | - Belén Herráez
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Nuria Álvarez
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - María Rosario Alonso
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
| | - Joaquín Dopazo
- Computational Medicine Platform, Fundación Progreso y Salud (FPS), Hospital Virgen del Rocío, 41013 Sevilla, Spain
- Bioinformatics in Rare Diseases (BiER), Centre for Biomedical Network Research on Rare Diseases (CIBERER), ISCIII, 41013 Sevilla, Spain
- Computational Systems Medicine Group, Institute of Biomedicine of Seville, IBiS, University Hospital Virgen del Rocío/CSIC/University of Sevilla, 41013 Seville, Spain
- Functional Genomics Node, FPS/ELIXIR-ES, Hospital Virgen del Rocío, 41013 Sevilla, Spain
| | - Anna Gonzalez-Neira
- Human Genotyping Unit (CEGEN), Cancer Genetics Program, National Cancer Research Center (CNIO), 28029 Madrid, Spain
- Centre for Biomedical Network Research on Rare Diseases (CIBERER-U706), ISCIII, 28029 Madrid, Spain
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Scarpa JR, Elemento O. Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review. Br J Anaesth 2023:S0007-0912(23)00125-3. [PMID: 37055274 DOI: 10.1016/j.bja.2023.03.006] [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: 11/11/2022] [Revised: 02/21/2023] [Accepted: 03/04/2023] [Indexed: 04/15/2023] Open
Abstract
Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.
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Affiliation(s)
- Joseph R Scarpa
- Department of Anesthesiology, Weill Cornell Medicine, New York, NY, USA.
| | - Olivier Elemento
- Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
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Huang Q, Liao Y, Yu T, Lei W, Liang H, Wen J, Liu Q, Chen Y, Huang K, Jing L, Huang X, Liu Y, Yu X, Su K, Liu T, Yang L, Huang M. A retrospective analysis of preemptive pharmacogenomic testing in 22,918 individuals from China. J Clin Lab Anal 2023; 37:e24855. [PMID: 36916827 PMCID: PMC10098050 DOI: 10.1002/jcla.24855] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/11/2023] [Accepted: 02/13/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Pharmacogenomics (PGx) examines the influence of genetic variation on drug responses. With more and more Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines published, PGx is gradually shifting from the reactive testing of single gene toward the preemptive testing of multiple genes. But the profile of PGx genes, especially for the intra-country diversity, is not well understood in China. METHODS We retrospectively collected preemptive PGx testing data of 22,918 participants from 20 provinces of China, analyzed frequencies of alleles, genotypes and phenotypes of pharmacogenes, predicted drug responses for each participant, and performed comparisons between different provinces. RESULTS AND CONCLUSION After analyzing 15 pharmacogenes from CPIC guidelines of 31 drugs, we found that 99.97% of individuals may have an atypical response to at least one drug; the participants carry actionable genotypes leading to atypical dosage recommendation for a median of eight drugs. Over 99% of the participants were recommended a decreased warfarin dose based on genetic factors. There were 20 drugs with high-risk ratios from 0.18% to 58.25%, in which clopidogrel showed the highest high-risk ratio. In addition, the high-risk ratio of rasburicase in GUANGDONG (risk ratio (RR) = 13.17, 95%CI:4.06-33.22, p < 0.001) and GUANGXI (RR = 23.44, 95%CI:8.83-52.85, p < 0.001) were significantly higher than that in all provinces. Furthermore, the diversity we observed among 20 provinces suggests that preemptive PGx testing in different geographical regions in China may need to pay more attention to specific genes. These results emphasize the importance of preemptive PGx testing and provide essential evidence for promoting clinical implementation in China.
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Affiliation(s)
- Quanfei Huang
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Yuwei Liao
- Precision Medical Lab Center, People's Hospital of Yangjiang, Yangjiang, China
| | - Tao Yu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Wei Lei
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Hongfeng Liang
- Precision Medical Lab Center, People's Hospital of Yangjiang, Yangjiang, China
| | - Jianxin Wen
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Qing Liu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Yu Chen
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Kaisheng Huang
- CapitalBio Technology Co. Ltd., Beijing, China.,Guangdong CapitalBio Medical Laboratory, Dongguan, China
| | - Lifang Jing
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Xiaoyan Huang
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Yuanru Liu
- CapitalBio Technology Co. Ltd., Beijing, China.,Guangdong CapitalBio Medical Laboratory, Dongguan, China
| | - Xiaokang Yu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Kaichan Su
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Tengfei Liu
- CapitalBio Genomics Co., Ltd., Dongguan, China.,CapitalBio Technology Co. Ltd., Beijing, China
| | - Liye Yang
- Precision Medical Lab Center, People's Hospital of Yangjiang, Yangjiang, China
| | - Min Huang
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
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39
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Mostaid MS, Aziz MA, Maisha JA, Islam MS, Maruf AA. A review of pharmacogenetic studies in the Bangladeshi population. Drug Metab Pers Ther 2023:dmdi-2022-0194. [PMID: 36854045 DOI: 10.1515/dmpt-2022-0194] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 01/25/2023] [Indexed: 03/02/2023]
Abstract
Pharmacogenetics (PGx)-guided prescribing is an evidence-based precision medicine strategy. Although the past two decades have reported significant advancements in both the quality and quantity of PGx research studies, they are seldom done in developing countries like Bangladesh. This review identified and summarized PGx studies conducted in the Bangladeshi population by searching PubMed and Google Scholar. Additionally, a quality evaluation of the identified studies was also carried out. Eleven PGx studies were identified that looked at the effects of genetic variants on blood thinners (CYP2C9, VKORC1, and ITGB3), cancer drugs (TPMT, MTHFR, DPYD, ERCC1, GSTP1, XPC, XRCC1, TP53, XPD, and ABCC4), statins (COQ2, CYP2D6, and CYP3A5), and prednisolone (ABCB1, CYP3A5, and NR3C1) in the Bangladeshi population. Most studies were of low to moderate quality. Although the identified studies demonstrated the potential for PGx testing, the limited PGx literature in the Bangladeshi population poses a significant challenge in the widespread implementation of PGx testing in Bangladesh.
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Affiliation(s)
- Md Shaki Mostaid
- Department of Pharmaceutical Sciences, North South University, Dhaka, Bangladesh
| | - Md Abdul Aziz
- Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Jeba Atkia Maisha
- Department of Mathematics and Natural Sciences, Brac University, Dhaka, Bangladesh
| | - Mohammad Safiqul Islam
- Laboratory of Pharmacogenomics and Molecular Biology, Department of Pharmacy, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Abdullah Al Maruf
- The Mathison Centre for Mental Health Research & Education, Cumming School of Medicine, University of Calgary, Calgary, Canada
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40
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Abstract
Inter-individual variability in drug response, be it efficacy or safety, is common and likely to become an increasing problem globally given the growing elderly population requiring treatment. Reasons for this inter-individual variability include genomic factors, an area of study called pharmacogenomics. With genotyping technologies now widely available and decreasing in cost, implementing pharmacogenomics into clinical practice - widely regarded as one of the initial steps in mainstreaming genomic medicine - is currently a focus in many countries worldwide. However, major challenges of implementation lie at the point of delivery into health-care systems, including the modification of current clinical pathways coupled with a massive knowledge gap in pharmacogenomics in the health-care workforce. Pharmacogenomics can also be used in a broader sense for drug discovery and development, with increasing evidence suggesting that genomically defined targets have an increased success rate during clinical development.
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41
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Application of Pharmacogenetics for the Use of Antiplatelet and Anticoagulant Drugs. CURRENT CARDIOVASCULAR RISK REPORTS 2023. [DOI: 10.1007/s12170-022-00713-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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42
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Chan AP, Choi Y, Rangan A, Zhang G, Podder A, Berens M, Sharma S, Pirrotte P, Byron S, Duggan D, Schork NJ. Interrogating the Human Diplome: Computational Methods, Emerging Applications, and Challenges. Methods Mol Biol 2023; 2590:1-30. [PMID: 36335489 DOI: 10.1007/978-1-0716-2819-5_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Human DNA sequencing protocols have revolutionized human biology, biomedical science, and clinical practice, but still have very important limitations. One limitation is that most protocols do not separate or assemble (i.e., "phase") the nucleotide content of each of the maternally and paternally derived chromosomal homologs making up the 22 autosomal pairs and the chromosomal pair making up the pseudo-autosomal region of the sex chromosomes. This has led to a dearth of studies and a consequent underappreciation of many phenomena of fundamental importance to basic and clinical genomic science. We discuss a few protocols for obtaining phase information as well as their limitations, including those that could be used in tumor phasing settings. We then describe a number of biological and clinical phenomena that require phase information. These include phenomena that require precise knowledge of the nucleotide sequence in a chromosomal segment from germline or somatic cells, such as DNA binding events, and insight into unique cis vs. trans-acting functionally impactful variant combinations-for example, variants implicated in a phenotype governed by compound heterozygosity. In addition, we also comment on the need for reliable and consensus-based diploid-context computational workflows for variant identification as well as the need for laboratory-based functional verification strategies for validating cis vs. trans effects of variant combinations. We also briefly describe available resources, example studies, as well as areas of further research, and ultimately argue that the science behind the study of human diploidy, referred to as "diplomics," which will be enabled by nucleotide-level resolution of phased genomes, is a logical next step in the analysis of human genome biology.
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Affiliation(s)
- Agnes P Chan
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
| | - Yongwook Choi
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
| | - Aditya Rangan
- Courant Institute of Mathematical Sciences at New York University, New York, NY, USA
| | - Guangfa Zhang
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
| | - Avijit Podder
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
| | - Michael Berens
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
- The City of Hope National Medical Center, Duarte, CA, USA
| | - Sunil Sharma
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
- The City of Hope National Medical Center, Duarte, CA, USA
| | - Patrick Pirrotte
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
- The City of Hope National Medical Center, Duarte, CA, USA
| | - Sara Byron
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
- The City of Hope National Medical Center, Duarte, CA, USA
| | - Dave Duggan
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA
- The City of Hope National Medical Center, Duarte, CA, USA
| | - Nicholas J Schork
- The Translational Genomics Research Institute (TGen), part of the City of Hope National Medical Center, Phoenix, AZ, USA.
- The City of Hope National Medical Center, Duarte, CA, USA.
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Boeschen M, Le Duc D, Stiller M, von Laffert M, Schöneberg T, Horn S. Interactive webtool for analyzing drug sensitivity and resistance associated with genetic signatures of cancer cell lines. J Cancer Res Clin Oncol 2022:10.1007/s00432-022-04503-2. [PMID: 36472769 PMCID: PMC10356876 DOI: 10.1007/s00432-022-04503-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022]
Abstract
Abstract
Purpose
A wide therapeutic repertoire has become available to oncologists including radio- and chemotherapy, small molecules and monoclonal antibodies. However, drug efficacy can be limited by genetic heterogeneity. Here, we designed a webtool that facilitates the data analysis of the in vitro drug sensitivity data on 265 approved compounds from the GDSC database in association with a plethora of genetic changes documented for 1001 cell lines in the CCLE data.
Methods
The webtool computes odds ratios of drug resistance for a queried set of genetic alterations. It provides results on the efficacy of single compounds or groups of compounds assigned to cellular signaling pathways. Webtool availability: https://tools.hornlab.org/GDSC/.
Results
We first replicated established associations of genetic driver mutations in BRAF, RAS genes and EGFR with drug response. We then tested the ‘BRCAness’ hypothesis and did not find increased sensitivity to the assayed PARP inhibitors. Analyzing specific PIK3CA mutations related to cancer and mendelian overgrowth, we found support for the described sensitivity of H1047 mutants to GSK690693 targeting the AKT pathway. Testing a co-mutated gene pair, GATA3 activation abolished PTEN-related sensitivity to PI3K/mTOR inhibition. Finally, the pharmacogenomic modifier ABCB1 was associated with olaparib resistance.
Conclusions
This tool could identify potential drug candidates in the presence of custom sets of genetic changes and moreover, improve the understanding of signaling pathways. The underlying computer code can be adapted to larger drug response datasets to help structure and accommodate the increasingly large biomedical knowledge base.
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44
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Jukic M, Milosavljević F, Molden E, Ingelman-Sundberg M. Pharmacogenomics in treatment of depression and psychosis: an update. Trends Pharmacol Sci 2022; 43:1055-1069. [PMID: 36307251 DOI: 10.1016/j.tips.2022.09.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 11/11/2022]
Abstract
Genetic factors can, to a certain extent, successfully predict the therapeutic effects, metabolism, and adverse reactions of drugs. This research field, pharmacogenomics, is well developed in oncology and is currently expanding in psychiatry. Here, we summarize the latest development in pharmacogenomic psychiatry, where results of several recent large studies indicate a true benefit and cost-effectiveness of pre-emptive genotyping for more successful psychotherapy. However, it is apparent that we still lack knowledge of many additional heritable genetic factors of importance for explanation of the interindividual differences in response to psychiatric drugs. Thus, more effort to further develop pharmacogenomic psychiatry should be invested to achieve a broader clinical implementation.
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Affiliation(s)
- Marin Jukic
- Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Filip Milosavljević
- Department of Physiology, Faculty of Pharmacy, University of Belgrade, Belgrade, Serbia
| | - Espen Molden
- Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway; Section for Pharmacology and Pharmaceutical Biosciences, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Magnus Ingelman-Sundberg
- Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
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Validation of Pharmacogenomic Interaction Probability (PIP) Scores in Predicting Drug-Gene, Drug-Drug-Gene, and Drug-Gene-Gene Interaction Risks in a Large Patient Population. J Pers Med 2022; 12:jpm12121972. [PMID: 36556194 PMCID: PMC9783707 DOI: 10.3390/jpm12121972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 10/31/2022] [Accepted: 11/21/2022] [Indexed: 12/02/2022] Open
Abstract
Utilizing pharmacogenomic (PGx) testing and integrating evidence-based guidance in drug therapy enables an improved treatment response and decreases the occurrence of adverse drug events. We conducted a retrospective analysis to validate the YouScript® PGx interaction probability (PIP) algorithm, which predicts patients for whom PGx testing would identify one or more evidence-based, actionable drug-gene, drug-drug-gene, or drug-gene-gene interactions (EADGIs). PIP scores generated for 36,511 patients were assessed according to the results of PGx multigene panel testing. PIP scores versus the proportion of patients in whom at least one EADGI was found were 22.4% vs. 22.4% (p = 1.000), 23.5% vs. 23.4% (p = 0.6895), 30.9% vs. 29.4% (p = 0.0667), and 27.3% vs. 26.4% (p = 0.3583) for patients tested with a minimum of 3-, 5-, 14-, and 25-gene panels, respectively. These data suggest a striking concordance between the PIP scores and the EAGDIs found by gene panel testing. The ability to identify patients most likely to benefit from PGx testing has the potential to reduce health care costs, enable patient access to personalized medicine, and ultimately improve drug efficacy and safety.
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Verma SS, Keat K, Li B, Hoffecker G, Risman M, Sangkuhl K, Whirl-Carrillo M, Dudek S, Verma A, Klein TE, Ritchie MD, Tuteja S. Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population. J Transl Med 2022; 20:550. [PMID: 36443877 PMCID: PMC9703665 DOI: 10.1186/s12967-022-03745-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/30/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Pharmacogenomics (PGx) aims to utilize a patient's genetic data to enable safer and more effective prescribing of medications. The Clinical Pharmacogenetics Implementation Consortium (CPIC) provides guidelines with strong evidence for 24 genes that affect 72 medications. Despite strong evidence linking PGx alleles to drug response, there is a large gap in the implementation and return of actionable pharmacogenetic findings to patients in standard clinical practice. In this study, we evaluated opportunities for genetically guided medication prescribing in a diverse health system and determined the frequencies of actionable PGx alleles in an ancestrally diverse biobank population. METHODS A retrospective analysis of the Penn Medicine electronic health records (EHRs), which includes ~ 3.3 million patients between 2012 and 2020, provides a snapshot of the trends in prescriptions for drugs with genotype-based prescribing guidelines ('CPIC level A or B') in the Penn Medicine health system. The Penn Medicine BioBank (PMBB) consists of a diverse group of 43,359 participants whose EHRs are linked to genome-wide SNP array and whole exome sequencing (WES) data. We used the Pharmacogenomics Clinical Annotation Tool (PharmCAT), to annotate PGx alleles from PMBB variant call format (VCF) files and identify samples with actionable PGx alleles. RESULTS We identified ~ 316.000 unique patients that were prescribed at least 2 drugs with CPIC Level A or B guidelines. Genetic analysis in PMBB identified that 98.9% of participants carry one or more PGx actionable alleles where treatment modification would be recommended. After linking the genetic data with prescription data from the EHR, 14.2% of participants (n = 6157) were prescribed medications that could be impacted by their genotype (as indicated by their PharmCAT report). For example, 856 participants received clopidogrel who carried CYP2C19 reduced function alleles, placing them at increased risk for major adverse cardiovascular events. When we stratified by genetic ancestry, we found disparities in PGx allele frequencies and clinical burden. Clopidogrel users of Asian ancestry in PMBB had significantly higher rates of CYP2C19 actionable alleles than European ancestry users of clopidrogrel (p < 0.0001, OR = 3.68). CONCLUSIONS Clinically actionable PGx alleles are highly prevalent in our health system and many patients were prescribed medications that could be affected by PGx alleles. These results illustrate the potential utility of preemptive genotyping for tailoring of medications and implementation of PGx into routine clinical care.
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Affiliation(s)
- Shefali S. Verma
- grid.25879.310000 0004 1936 8972Department of Pathology & Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Karl Keat
- grid.25879.310000 0004 1936 8972Genomics & Computational Biology PhD Program, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Binglan Li
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Glenda Hoffecker
- grid.25879.310000 0004 1936 8972Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Marjorie Risman
- grid.25879.310000 0004 1936 8972Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | | | - Katrin Sangkuhl
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Michelle Whirl-Carrillo
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA
| | - Scott Dudek
- grid.25879.310000 0004 1936 8972Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Anurag Verma
- grid.25879.310000 0004 1936 8972Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Teri E. Klein
- grid.168010.e0000000419368956Department of Biomedical Data Science, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Department of Biomedical Data Science and Medicine (BMIR), Stanford University, Stanford, CA USA
| | - Marylyn D. Ritchie
- grid.25879.310000 0004 1936 8972Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
| | - Sony Tuteja
- grid.25879.310000 0004 1936 8972Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA USA
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Asiimwe IG, Pirmohamed M. Drug-Drug-Gene Interactions in Cardiovascular Medicine. Pharmgenomics Pers Med 2022; 15:879-911. [PMID: 36353710 PMCID: PMC9639705 DOI: 10.2147/pgpm.s338601] [Citation(s) in RCA: 4] [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: 08/23/2022] [Accepted: 10/21/2022] [Indexed: 11/18/2022] Open
Abstract
Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.
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Affiliation(s)
- Innocent G Asiimwe
- The Wolfson Centre for Personalized Medicine, MRC Centre for Drug Safety Science, Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Munir Pirmohamed
- The Wolfson Centre for Personalized Medicine, MRC Centre for Drug Safety Science, Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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Wittwer NL, Meier CR, Huber CA, Meyer zu Schwabedissen HE, Allemann S, Schneider C. Utilization of Drugs with Pharmacogenetic Dosing Recommendations in Switzerland: A Descriptive Study Using the Helsana Database. Pharmgenomics Pers Med 2022; 15:967-976. [DOI: 10.2147/pgpm.s382214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 10/21/2022] [Indexed: 11/24/2022] Open
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Genetic Variation among Pharmacogenes in the Sardinian Population. Int J Mol Sci 2022; 23:ijms231710058. [PMID: 36077453 PMCID: PMC9456055 DOI: 10.3390/ijms231710058] [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: 07/26/2022] [Revised: 08/25/2022] [Accepted: 08/29/2022] [Indexed: 11/22/2022] Open
Abstract
Pharmacogenetics (PGx) aims to identify the genetic factors that determine inter-individual differences in response to drug treatment maximizing efficacy while decreasing the risk of adverse events. Estimating the prevalence of PGx variants involved in drug response, is a critical preparatory step for large-scale implementation of a personalized medicine program in a target population. Here, we profiled pharmacogenetic variation in fourteen clinically relevant genes in a representative sample set of 1577 unrelated sequenced Sardinians, an ancient island population that accounts for genetic variation in Europe as a whole, and, at the same time is enriched in genetic variants that are very rare elsewhere. To this end, we used PGxPOP, a PGx allele caller based on the guidelines created by the Clinical Pharmacogenetics Implementation Consortium (CPIC), to identify the main phenotypes associated with the PGx alleles most represented in Sardinians. We estimated that 99.43% of Sardinian individuals might potentially respond atypically to at least one drug, that on average each individual is expected to have an abnormal response to about 17 drugs, and that for 27 drugs the fraction of the population at risk of atypical responses to therapy is more than 40%. Finally, we identified 174 pharmacogenetic variants for which the minor allele frequency was at least 10% higher among Sardinians as compared to other European populations, a fact that may contribute to substantial interpopulation variability in drug response phenotypes. This study provides baseline information for further large-scale pharmacogenomic investigations in the Sardinian population and underlines the importance of PGx characterization of diverse European populations, such as Sardinians.
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Abstract
PURPOSE OF REVIEW Sarcoidosis is a chronic multisystemic inflammatory disease of unknown aetiology with a wide range of highly variable clinical manifestations and unpredictable disease course. Sarcoidosis patients may present with specific organ-related symptoms involving functional impairments, and less specific symptoms. The decision whether and when to treat a sarcoidosis patient with pharmacotherapy depends on two major factors: risk of organ failure and/or death and impairment of quality of life. This decision is complex and not standardized. RECENT FINDINGS Glucocorticoids (GCs) are recommended as initial treatment, when needed. Subsequent GC-sparing alternatives frequently follow. Comorbidities or adverse drug reactions (ADRs) from drugs used in sarcoidosis treatment are sometimes very hard to differentiate from symptoms associated with the disease itself, which may cause diagnostic dilemmas. An ideal approach to minimalize ADRs would involve genetic screening prior to prescribing certain 'high-risk drugs' and therapeutic drug monitoring during treatment. Pharmacogenomic testing aims to guide appropriate selection of medicines, with the potential of reducing unnecessary polypharmacy while improving clinical outcomes. SUMMARY A multidisciplinary approach to the management of sarcoidosis may avoid unnecessary ADRs. It is important to consider the possibility of drug-induced damage in sarcoidosis, especially if the clinical situation deteriorates after the introduction of a particular drug.
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Affiliation(s)
- Marjolein Drent
- Department of Pharmacology and Toxicology, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht
- ILD Center of Excellence, Department of Respiratory Medicine, St. Antonius Hospital, Nieuwegein
- ILD Care Foundation Research Team, Ede
| | - Naomi T. Jessurun
- ILD Care Foundation Research Team, Ede
- Netherlands Pharmacovigilance Centre Lareb, ‘s-Hertogenbosch
| | - Petal A. Wijnen
- ILD Care Foundation Research Team, Ede
- Central Diagnostic Laboratory, Department of Clinical Chemistry, MUMC, Maastricht, The Netherlands
| | - Otto Bekers
- Central Diagnostic Laboratory, Department of Clinical Chemistry, MUMC, Maastricht, The Netherlands
| | - Aalt Bast
- Department of Pharmacology and Toxicology, Faculty of Health, Medicine and Life Science, Maastricht University, Maastricht
- ILD Care Foundation Research Team, Ede
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