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Farmaki A, Manolopoulos E, Natsiavas P. Will Precision Medicine Meet Digital Health? A Systematic Review of Pharmacogenomics Clinical Decision Support Systems Used in Clinical Practice. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:442-460. [PMID: 39136110 DOI: 10.1089/omi.2024.0131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Digital health, an emerging scientific domain, attracts increasing attention as artificial intelligence and relevant software proliferate. Pharmacogenomics (PGx) is a core component of precision/personalized medicine driven by the overarching motto "the right drug, for the right patient, at the right dose, and the right time." PGx takes into consideration patients' genomic variations influencing drug efficacy and side effects. Despite its potentials for individually tailored therapeutics and improved clinical outcomes, adoption of PGx in clinical practice remains slow. We suggest that e-health tools such as clinical decision support systems (CDSSs) can help accelerate the PGx, precision/personalized medicine, and digital health emergence in everyday clinical practice worldwide. Herein, we present a systematic review that examines and maps the PGx-CDSSs used in clinical practice, including their salient features in both technical and clinical dimensions. Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and research of the literature, 29 relevant journal articles were included in total, and 19 PGx-CDSSs were identified. In addition, we observed 10 technical components developed mostly as part of research initiatives, 7 of which could potentially facilitate future PGx-CDSSs implementation worldwide. Most of these initiatives are deployed in the United States, indicating a noticeable lack of, and the veritable need for, similar efforts globally, including Europe.
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Affiliation(s)
- Anastasia Farmaki
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Evangelos Manolopoulos
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupoli, Greece
| | - Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
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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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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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González-Iglesias E, Abad-Santos F. Update on the PriME-PGx initiative: evolution of pharmacogenetics in daily clinical practice. Pharmacogenomics 2024; 25:401-406. [PMID: 39115196 PMCID: PMC11418291 DOI: 10.1080/14622416.2024.2375188] [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: 04/30/2024] [Accepted: 06/28/2024] [Indexed: 09/21/2024] Open
Abstract
In 2021, the Clinical Pharmacology Department of Hospital Universitario de La Princesa launched the PriME-PGx initiative (Multidisciplinary Initiative of the Hospital Universitario de La Princesa for the Implementation of Pharmacogenetics) to promote the expansion of pharmacogenetics in hospitalized patients. We establish seven pharmacogenetic profiles based on the specific needs of seven departments: Oncology, Pain Unit, Neuropsychiatry, Internal or Infectious Medicine, Cardiology, Gastroenterology and Immunosuppressants. The experience of the last 3 years reflects a total of 1421 reports (37.4% being oncology profiles), with a gradual increase in the number of requests each year. With this project, we aim to expand the availability and utility of pharmacogenetic biomarkers to achieve personalised therapy that avoids adverse drug reactions and therapeutic failure.
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Affiliation(s)
- Eva González-Iglesias
- Clinical Pharmacology Department, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-Princesa), Faculty of Medicine, Universidad Autónoma de Madrid (UAM), Madrid, 28006, Spain
| | - Francisco Abad-Santos
- Clinical Pharmacology Department, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-Princesa), Faculty of Medicine, Universidad Autónoma de Madrid (UAM), Madrid, 28006, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, 28029, Spain
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Floris M, Moschella A, Alcalay M, Montella A, Tirelli M, Fontana L, Idda ML, Guarnieri P, Capasso M, Mammì C, Nicoletti P, Miozzo M. Pharmacogenetics in Italy: current landscape and future prospects. Hum Genomics 2024; 18:78. [PMID: 38987819 PMCID: PMC11234611 DOI: 10.1186/s40246-024-00612-w] [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: 02/24/2024] [Accepted: 04/30/2024] [Indexed: 07/12/2024] Open
Abstract
Pharmacogenetics investigates sequence of genes that affect drug response, enabling personalized medication. This approach reduces drug-induced adverse reactions and improves clinical effectiveness, making it a crucial consideration for personalized medical care. Numerous guidelines, drawn by global consortia and scientific organizations, codify genotype-driven administration for over 120 active substances. As the scientific community acknowledges the benefits of genotype-tailored therapy over traditionally agnostic drug administration, the push for its implementation into Italian healthcare system is gaining momentum. This evolution is influenced by several factors, including the improved access to patient genotypes, the sequencing costs decrease, the growing of large-scale genetic studies, the rising popularity of direct-to-consumer pharmacogenetic tests, and the continuous improvement of pharmacogenetic guidelines. Since EMA (European Medicines Agency) and AIFA (Italian Medicines Agency) provide genotype information on drug leaflet without clear and explicit clinical indications for gene testing, the regulation of pharmacogenetic testing is a pressing matter in Italy. In this manuscript, we have reviewed how to overcome the obstacles in implementing pharmacogenetic testing in the clinical practice of the Italian healthcare system. Our particular emphasis has been on germline testing, given the absence of well-defined national directives in contrast to somatic pharmacogenetics.
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Affiliation(s)
- Matteo Floris
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy.
| | - Antonino Moschella
- Unit of Medical Genetics, Grande Ospedale Metropolitano Bianchi-Melacrino-Morelli, Reggio Calabria, Italy
| | - Myriam Alcalay
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milano, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milano, Italy
| | - Annalaura Montella
- CEINGE Biotecnologie Avanzate, Napoli, Italy
- Department of Molecular Medicine and Medical Biotechnology (DMMBM), Università degli Studi di Napoli "Federico II", Napoli, Italy
| | - Matilde Tirelli
- CEINGE Biotecnologie Avanzate, Napoli, Italy
- Department of Molecular Medicine and Medical Biotechnology (DMMBM), Università degli Studi di Napoli "Federico II", Napoli, Italy
| | - Laura Fontana
- Medical Genetics Unit, Department of Health Sciences, ASST Santi Paolo e Carlo, Università degli Studi di Milano, Milan, Italy
| | - Maria Laura Idda
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
| | | | - Mario Capasso
- CEINGE Biotecnologie Avanzate, Napoli, Italy
- Department of Molecular Medicine and Medical Biotechnology (DMMBM), Università degli Studi di Napoli "Federico II", Napoli, Italy
| | - Corrado Mammì
- Unit of Medical Genetics, Grande Ospedale Metropolitano Bianchi-Melacrino-Morelli, Reggio Calabria, Italy
| | - Paola Nicoletti
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Monica Miozzo
- Medical Genetics Unit, Department of Health Sciences, ASST Santi Paolo e Carlo, Università degli Studi di Milano, Milan, Italy.
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Zeng S, Qing Q, Xu W, Yu S, Zheng M, Tan H, Peng J, Huang J. Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors. Front Med (Lausanne) 2024; 11:1365524. [PMID: 38784235 PMCID: PMC11111965 DOI: 10.3389/fmed.2024.1365524] [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: 01/04/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
Precision medicine, characterized by the personalized integration of a patient's genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual's genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence.
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Affiliation(s)
- Shiyue Zeng
- Zhuzhou Clinical College, Jishou University, Jishou, China
| | - Qi Qing
- Zhuzhou Clinical College, Jishou University, Jishou, China
| | - Wei Xu
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Simeng Yu
- Zhuzhou Clinical College, Jishou University, Jishou, China
| | - Mingzhi Zheng
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Hongpei Tan
- Department of Radiology, Third Xiangya Hospital, Central South University, Changsha, China
| | - Junmin Peng
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
| | - Jing Huang
- Department of Anesthesiology, Zhuzhou Central Hospital, Zhuzhou, China
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Gawronski BE, Salloum RG, Duarte JD. Estimating preferences and willingness to pay for pharmacogenetic testing in populations who are medically underserved: a discrete choice experiment. Front Pharmacol 2024; 15:1384667. [PMID: 38595920 PMCID: PMC11002086 DOI: 10.3389/fphar.2024.1384667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 03/14/2024] [Indexed: 04/11/2024] Open
Abstract
Background: The implementation of pharmacogenetic (PGx) testing may contribute to health disparities if access to testing is inequitable, as medically underserved patients are prescribed higher rates of drugs with PGx guidelines and often experience the benefits of emerging health technologies last. Limited research has evaluated potential implementation of PGx testing in populations who are medically underserved and none have evaluated their preferences regarding PGx test characteristics and cost. Our study endeavored to assess the willingness to pay for PGx testing and key PGx test preferences in a nationwide cohort of medically underserved respondents. Methods: A survey was developed to assess willingness to pay and preferences for PGx testing through a discrete choice experiment (DCE). Five attributes of PGx tests were included in the DCE: doctor recommendation, wait time, number of actionable results, benefit of the test (avoid a side effect or address a health problem), and out-of-pocket cost. A convenience sample of U.S. adults with an average yearly household income of $42,000 or less was collected utilizing an online survey fielded by Qualtrics Research Services (Provo, UT). For the DCE analysis, conditional logit and mixed-logit regression models were utilized to determine relative utility of attributes and levels, conditional relative importance for each attribute, and marginal willingness to pay. Results: Respondents completed the survey with an 83.1% response completion rate. Following quality control procedures, 1,060 respondents were included in the final nationwide cohort. Approximately, 82% of respondents were willing to pay less than $100 for PGx testing, and a strong price ceiling was identified at $200. Out-of-pocket cost was the attribute identified as having the greatest relative importance on choice, while wait time had the lowest importance. Greater utility was observed if the PGx test was doctor recommended, had a higher number of actionable results, and resolved major or minor health problems compared with avoiding side effects. Conclusion: This first-of-its-kind study provides important insights into the willingness to pay for PGx testing and PGx test preferences of a large medically underserved population. Applying these findings can potentially lead to improvements in the successful implementation of PGx testing in this population.
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Affiliation(s)
- Brian E. Gawronski
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States
| | - Ramzi G. Salloum
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Julio D. Duarte
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States
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Chenchula S, Atal S, Uppugunduri CRS. A review of real-world evidence on preemptive pharmacogenomic testing for preventing adverse drug reactions: a reality for future health care. THE PHARMACOGENOMICS JOURNAL 2024; 24:9. [PMID: 38490995 PMCID: PMC10942860 DOI: 10.1038/s41397-024-00326-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 03/18/2024]
Abstract
Adverse drug reactions (ADRs) are a significant public health concern and a leading cause of hospitalization; they are estimated to be the fourth leading cause of death and increasing healthcare costs worldwide. Carrying a genetic variant could alter the efficacy and increase the risk of ADRs associated with a drug in a target population for commonly prescribed drugs. The use of pre-emptive pharmacogenetic/omic (PGx) testing can improve drug therapeutic efficacy, safety, and compliance by guiding the selection of drugs and/or dosages. In the present narrative review, we examined the current evidence of pre-emptive PGx testing-based treatment for the prevention of ADRs incidence and hospitalization or emergency department visits due to serious ADRs, thus improving patient safety. We then shared our perspective on the importance of preemptive PGx testing in clinical practice for the safe use of medicines and decreasing healthcare costs.
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Affiliation(s)
- Santenna Chenchula
- Department of Pharmacology, All India Institute of Medical Sciences (AIIMS), Bhopal, India
| | - Shubham Atal
- Department of Pharmacology, All India Institute of Medical Sciences (AIIMS), Bhopal, India
| | - Chakradhara Rao S Uppugunduri
- CANSEARCH Research Platform in Pediatric Oncology and Hematology, Department of Pediatrics, Gynecology and Obstetrics, University of Geneva, Geneva, Switzerland.
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Calendo G, Kusic D, Madzo J, Gharani N, Scheinfeldt L. ursaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data. FRONTIERS IN BIOINFORMATICS 2024; 4:1351620. [PMID: 38533129 PMCID: PMC10963438 DOI: 10.3389/fbinf.2024.1351620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 02/28/2024] [Indexed: 03/28/2024] Open
Abstract
Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.
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Affiliation(s)
- Gennaro Calendo
- Coriell Institute for Medical Research, Camden, NJ, United States
| | - Dara Kusic
- Coriell Institute for Medical Research, Camden, NJ, United States
| | - Jozef Madzo
- Coriell Institute for Medical Research, Camden, NJ, United States
- Cooper Medical School of Rowan University, Camden, NJ, United States
| | - Neda Gharani
- Coriell Institute for Medical Research, Camden, NJ, United States
- Gharani Consulting Limited, London, United Kingdom
| | - Laura Scheinfeldt
- Coriell Institute for Medical Research, Camden, NJ, United States
- Cooper Medical School of Rowan University, Camden, NJ, United States
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Gan P, Hajis MIB, Yumna M, Haruman J, Matoha HK, Wahyudi DT, Silalahi S, Oktariani DR, Dela F, Annisa T, Pitaloka TDA, Adhiwijaya PK, Pauzi RY, Hertanto R, Kumaheri MA, Sani L, Irwanto A, Pradipta A, Chomchopbun K, Gonzalez-Porta M. Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip. Front Pharmacol 2024; 15:1349203. [PMID: 38529185 PMCID: PMC10961362 DOI: 10.3389/fphar.2024.1349203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/05/2024] [Indexed: 03/27/2024] Open
Abstract
Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.
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Affiliation(s)
- Pamela Gan
- Nalagenetics Pte Ltd., Singapore, Singapore
| | | | | | | | | | | | | | | | - Fitria Dela
- PT Genomik Solidaritas Indonesia, Jakarta, Indonesia
| | - Tazkia Annisa
- PT Genomik Solidaritas Indonesia, Jakarta, Indonesia
| | | | | | | | | | | | | | | | - Ariel Pradipta
- PT Genomik Solidaritas Indonesia, Jakarta, Indonesia
- Department Biochemistry and Molecular Biology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia
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11
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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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12
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Russell C, Campion M, Grove ME, Matsuda K, Klein TE, Ashley E, Naik H, Wheeler MT, Scott SA. Knowledge and attitudes on implementing cardiovascular pharmacogenomic testing. Clin Transl Sci 2024; 17:e13737. [PMID: 38421234 PMCID: PMC10903329 DOI: 10.1111/cts.13737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/22/2023] [Accepted: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
Pharmacogenomics has the potential to inform drug dosing and selection, reduce adverse events, and improve medication efficacy; however, provider knowledge of pharmacogenomic testing varies across provider types and specialties. Given that many actionable pharmacogenomic genes are implicated in cardiovascular medication response variability, this study aimed to evaluate cardiology providers' knowledge and attitudes on implementing clinical pharmacogenomic testing. Sixty-one providers responded to an online survey, including pharmacists (46%), physicians (31%), genetic counselors (15%), and nurses (8%). Most respondents (94%) reported previous genetics education; however, only 52% felt their genetics education prepared them to order a clinical pharmacogenomic test. In addition, most respondents (66%) were familiar with pharmacogenomics, with genetic counselors being most likely to be familiar (p < 0.001). Only 15% of respondents had previously ordered a clinical pharmacogenomic test and a total of 36% indicated they are likely to order a pharmacogenomic test in the future; however, the vast majority of respondents (89%) were interested in pharmacogenomic testing being incorporated into diagnostic cardiovascular genetic tests. Moreover, 84% of providers preferred pharmacogenomic panel testing compared to 16% who preferred single gene testing. Half of the providers reported being comfortable discussing pharmacogenomic results with their patients, but the majority (60%) expressed discomfort with the logistics of test ordering. Reported barriers to implementation included uncertainty about the clinical utility and difficulty choosing an appropriate test. Taken together, cardiology providers have moderate familiarity with pharmacogenomics and limited experience with test ordering; however, they are interested in incorporating pharmacogenomics into diagnostic genetic tests and ordering pharmacogenomic panels.
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Affiliation(s)
- Callan Russell
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
- Present address:
Northside HospitalAtlantaGeorgiaUSA
| | - MaryAnn Campion
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Megan E. Grove
- Clinical Genomics LaboratoryStanford MedicinePalo AltoCaliforniaUSA
- Present address:
Color HealthBurlingameCaliforniaUSA
| | - Kelly Matsuda
- Division of Pharmacy and CardiologyStanford Health CarePalo AltoCaliforniaUSA
| | - Teri E. Klein
- Department of Biomedical Data ScienceStanford UniversityStanfordCaliforniaUSA
| | - Euan Ashley
- Stanford Center for Inherited Cardiovascular DiseaseStanfordCaliforniaUSA
- Department of Medicine, Division of Cardiovascular MedicineStanford UniversityStanfordCaliforniaUSA
| | - Hetanshi Naik
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Matthew T. Wheeler
- Stanford Center for Inherited Cardiovascular DiseaseStanfordCaliforniaUSA
- Department of Medicine, Division of Cardiovascular MedicineStanford UniversityStanfordCaliforniaUSA
| | - Stuart A. Scott
- Clinical Genomics LaboratoryStanford MedicinePalo AltoCaliforniaUSA
- Department of PathologyStanford UniversityStanfordCaliforniaUSA
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13
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Zhou Y, Lauschke VM. Next-generation sequencing in pharmacogenomics - fit for clinical decision support? Expert Rev Clin Pharmacol 2024; 17:213-223. [PMID: 38247431 DOI: 10.1080/17512433.2024.2307418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/16/2024] [Indexed: 01/23/2024]
Abstract
INTRODUCTION The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial. AREAS COVERED We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing. EXPERT OPINION While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
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14
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Shriver SP, Adams D, McKelvey BA, McCune JS, Miles D, Pratt VM, Ashcraft K, McLeod HL, Williams H, Fleury ME. Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology. J Clin Oncol 2024:JCO2301748. [PMID: 38386947 DOI: 10.1200/jco.23.01748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/08/2023] [Accepted: 12/12/2023] [Indexed: 02/24/2024] Open
Abstract
Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.
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Affiliation(s)
| | | | | | - Jeannine S McCune
- City of Hope/Beckman Research Institute Department of Hematologic Malignancies Translational Sciences, Duarte, CA
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15
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Gharani N, Calendo G, Kusic D, Madzo J, Scheinfeldt L. Star allele search: a pharmacogenetic annotation database and user-friendly search tool of publicly available 1000 Genomes Project biospecimens. BMC Genomics 2024; 25:116. [PMID: 38279110 PMCID: PMC10811916 DOI: 10.1186/s12864-024-09994-6] [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: 08/08/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.
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Affiliation(s)
- N Gharani
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
- Gharani Consulting Limited, 272 Regents Park Road, London, N3 3HN, UK
| | - G Calendo
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
| | - D Kusic
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
| | - J Madzo
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA
- Cooper Medical School of Rowan University, 401 South Broadway, Camden, NJ, 08103, USA
| | - L Scheinfeldt
- Coriell Institute for Medical Research, 403 Haddon Ave, Camden, NJ, 08103, USA.
- Cooper Medical School of Rowan University, 401 South Broadway, Camden, NJ, 08103, USA.
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16
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Hellwig LD, Turner C, Olsen C, Libbus J, Markos B, Koehlmoos T, Haigney M, De Castro M, Saunders D. Assessing Clinical Utility of Pharmacogenetic Testing in the Military Health System. Mil Med 2024; 189:e198-e204. [PMID: 37436924 PMCID: PMC11022329 DOI: 10.1093/milmed/usad254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 05/23/2023] [Accepted: 06/30/2023] [Indexed: 07/14/2023] Open
Abstract
INTRODUCTION Response to medications can differ widely among individual patients. Adverse drug reactions can lead to serious morbidity and mortality. Pharmacogenetic (PGx) testing can predict responses to medications and increased risks of adverse events where the genetic basis is understood. Several published manuscripts suggest positive impacts of systematic preemptive PGx testing. However, few studies have been conducted on PGx implementation in the Military Health System (MHS). MATERIAL AND METHODS A cross-sectional study of adult beneficiaries in a primary care clinic at a large military treatment facility was conducted in 2022. Participants underwent PGx genotyping of CYP2C19 and CYP2D6 genes at the Defense Health Agency Genetics Reference Laboratory. Participant medication lists were compared to the current Clinical Pharmacogenetic Implementation Consortium (CPIC) PGx gene-drug guidelines to assess potential actionability of these results. RESULTS Genotyping of CYP2C19 and CYP2D6 in 165 MHS beneficiaries (mean age: 65 years) revealed that 81.2% of participants had at least one abnormal PGx finding. Among those with an abnormal PGx result, 65% were taking a medication listed on the CPIC website with an association with the particular gene in which the finding was identified. In addition, 78% of all of the participants in the study were taking at least one medication that is metabolized by CYP2C19 or CYP2D6 with associated CPIC guidelines. CONCLUSIONS Pharmacogenetic testing for CYP2C19 and CYP2D6 identified a substantial proportion of MHS patients at a single center who could benefit from evaluation of current medication regimens based on the CPIC guidelines. Individualized medical management may be warranted to a greater degree than previously recognized based on the findings given possible differences in medication metabolism. Many MHS beneficiaries already take medications metabolized by CYP2C19 and CYP2D6, and a substantial proportion may be at risk for preventable adverse events for medications metabolized by these enzymes. While preliminary, a large number of actionable polymorphisms among a relatively small set of individuals taking at-risk medications suggest that implementing PGx testing in clinical practice may be beneficial in the MHS with appropriate clinical infrastructure.
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Affiliation(s)
- Lydia D Hellwig
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD 20817, USA
- Center for Military Precision Health (CMPH), Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Clesson Turner
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20894, USA
| | - Cara Olsen
- Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Joya Libbus
- Military Cardiovascular Outcomes Research, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- Metis Foundation, San Antonio, TX 78216, USA
| | - Bethelhem Markos
- Military Cardiovascular Outcomes Research, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- Metis Foundation, San Antonio, TX 78216, USA
| | - Tracey Koehlmoos
- Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Mark Haigney
- Military Cardiovascular Outcomes Research, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- Department of Medicine, Uniformed Services University of the Health Sciences, Uniformed Services University, Bethesda,, MD 20814, USA
| | - Mauricio De Castro
- Keesler Air Force Base, 81st Medical Operations Squadron, Biloxi, MS 39534, USA
| | - David Saunders
- Department of Medicine, Uniformed Services University of the Health Sciences, Uniformed Services University, Bethesda,, MD 20814, USA
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17
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Lteif C, Eddy E, Terrell J, Cavallari LH, Malaty J, Duarte JD. Feasibility of preemptive pharmacogenetic testing and improvement of medication treatment satisfaction among medically underserved patients. Clin Transl Sci 2024; 17:e13692. [PMID: 38013396 PMCID: PMC10772669 DOI: 10.1111/cts.13692] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 11/06/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
Previous findings suggest that medically underserved patients are prescribed medications with pharmacogenetic (PGx) guidelines at a high frequency. Thus, underserved patients may especially benefit from PGx testing, but little evidence exists regarding the effect of testing in this population. This pilot study aimed to generate key feasibility data and explore clinical outcomes of PGx implementation in underserved populations. Black and Latino patients were recruited from an outpatient clinic and underwent PGx testing. Feasibility measures included enrollment metrics and actionable genotype frequencies. The primary clinical outcome was patient medication treatment satisfaction 6 months after testing. Implementation outcomes included the number of healthcare provider encounters and medication changes within the 6-month follow-up. Effectiveness outcomes included medication adherence, patient-perceived test value, and time spent discussing medications with providers. Ninety-nine patients completed the study. Proton-pump inhibitors were the most frequent PGx drug class prescribed at baseline (61%) followed by nonsteroidal anti-inflammatory drugs (36%). Patients with an actionable genotype constituted 96% of the population, whereas 28% had an actionable genotype related to their PGx drug. Patient treatment satisfaction significantly increased over the 6 months after PGx testing. In addition, medication adherence and the number of provider encounters significantly increased over the study period. In a pilot study, preemptive PGx testing was feasible in primary care clinics, improved patient treatment satisfaction and adherence, and increased the number of provider encounters in medically underserved patients. Future clinical trials are warranted to assess the long-term effects of PGx testing in a larger diverse patient population.
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Affiliation(s)
- Christelle Lteif
- Center for Pharmacogenomics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of PharmacyUniversity of FloridaGainesvilleFloridaUSA
| | - Elizabeth Eddy
- Center for Pharmacogenomics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of PharmacyUniversity of FloridaGainesvilleFloridaUSA
| | - Joshua Terrell
- Center for Pharmacogenomics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of PharmacyUniversity of FloridaGainesvilleFloridaUSA
| | - Larisa H. Cavallari
- Center for Pharmacogenomics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of PharmacyUniversity of FloridaGainesvilleFloridaUSA
| | - John Malaty
- Department of Community Health and Family Medicine, College of MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Julio D. Duarte
- Center for Pharmacogenomics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of PharmacyUniversity of FloridaGainesvilleFloridaUSA
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18
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MacKinnon GE, Mills M, Stoddard A, Urrutia RA, Broeckel U. An EMR-Based Approach to Determine Frequency, Prescribing Pattern, and Characteristics of Patients Receiving Drugs with Pharmacogenomic Guidelines. PHARMACY 2023; 11:178. [PMID: 37987388 PMCID: PMC10661282 DOI: 10.3390/pharmacy11060178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 11/07/2023] [Accepted: 11/10/2023] [Indexed: 11/22/2023] Open
Abstract
(1) Background: This retrospective analysis utilizing electronic medical record (EMR) data from a tertiary integrated health system sought to identify patients and prescribers who would benefit from pharmacogenomic (PGx) testing based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. (2) Methods: EMR data from a clinical research data warehouse were analyzed from 845,518 patients that had an encounter between 2015 and 2019 at an academic medical center. Data were collected for 42 commercially available drugs with 52 evidence-based PGx guidelines from CPIC. Provider data were obtained through the EMR linked by specialty via national provider identification (NPI) number. (3) Results: A total of 845,518 patients had an encounter in the extraction period with 590,526 medication orders processed. A total of 335,849 (56.9%) patients had medication orders represented by CPIC drugs prescribed by 2803 providers, representing 239 distinct medications. (4) Conclusions: The results from this study show that over half of patients were prescribed a CPIC actionable medication from a variety of prescriber specialties. Understanding the magnitude of patients that may benefit from PGx testing, will enable the development of preemptive testing processes, physician support strategies, and pharmacist workflows to optimize outcomes should a PGx service be implemented.
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Affiliation(s)
- George E. MacKinnon
- School of Pharmacy, Medical College of Wisconsin, Milwaukee, WI 53226, USA; (M.M.); (U.B.)
| | - Megan Mills
- School of Pharmacy, Medical College of Wisconsin, Milwaukee, WI 53226, USA; (M.M.); (U.B.)
| | - Alexander Stoddard
- Clinical & Translational Science Institute, Medical College of Wisconsin, Milwaukee, WI 53226, USA;
| | - Raul A. Urrutia
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA;
| | - Ulrich Broeckel
- School of Pharmacy, Medical College of Wisconsin, Milwaukee, WI 53226, USA; (M.M.); (U.B.)
- Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- RPRD Diagnostics LLC, Milwaukee, WI 53226, USA
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19
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Principi N, Petropulacos K, Esposito S. Impact of Pharmacogenomics in Clinical Practice. Pharmaceuticals (Basel) 2023; 16:1596. [PMID: 38004461 PMCID: PMC10675377 DOI: 10.3390/ph16111596] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open
Abstract
Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.
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Affiliation(s)
| | | | - Susanna Esposito
- Pediatric Clinic, Department of Medicine and Surgery, University Hospital of Parma, 43126 Parma, Italy
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20
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Zhang L, Zhou S, Allen JD, Wang F, Pittenger AL, Bishop JR. Assessing pharmacogenomic literacy in China through validation of the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy. Clin Transl Sci 2023; 16:2356-2368. [PMID: 37721333 PMCID: PMC10651651 DOI: 10.1111/cts.13637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/09/2023] [Accepted: 08/30/2023] [Indexed: 09/19/2023] Open
Abstract
Pharmacogenomics (PGx) implementation into clinical care is rapidly increasing in China. However, the extent to which the public understands PGx testing and important knowledge domains requiring patient education or counseling remains unclear. To address this, we created and validated the Chinese version of the Minnesota Assessment of Pharmacogenomic Literacy (MAPL-CTM ). The MAPL-C was developed by translating the English MAPL to Chinese following cross-cultural translation guidelines. An online survey validated the MAPL-C and assessed Chinese individuals' PGx literacy. Validation analyses were performed and associations of PGx literacy with participants' characteristics were quantified. Of 959 high-quality responses, the majority of respondents were Han Chinese (96.3%), men (54.5%), aged 18-29 years (70.9%), residing in China (97.3%), and had received college or higher education (95.0%). Out of 15 starting items developed to query specific predefined knowledge domains, two uninformative items were excluded, resulting in a 13-item MAPL-C. Chinese participants' MAPL-C performance was best explained by a three-factor model, encompassing PGx concepts and function, testing limitations, and privacy. Higher MAPL-C performance was associated with younger age, higher education, and previous genetic testing experience. Correct response rates for questions related to testing limitations were lower than those in other domains. The creation and validation of the MAPL-C fills a gap in determining PGx knowledge among Chinese speakers, quantifying PGx literacy within a Chinese cohort, and identifying response patterns and knowledge gaps. The MAPL-C can be useful in clinical practice to guide patient counseling, assess PGx education interventions, and quantify PGx knowledge in relation to outcomes in research studies involving Chinese participants.
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Affiliation(s)
- Lusi Zhang
- Department of Experimental and Clinical Pharmacology, College of PharmacyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Shuqin Zhou
- Department of Emergency, Shanghai Tenth People's HospitalTongji UniversityShanghaiChina
| | - Josiah D. Allen
- Department of PharmacySt. Elizabeth HealthcareEdgewoodKentuckyUSA
| | - Fan Wang
- Department of Experimental and Clinical Pharmacology, College of PharmacyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Amy L. Pittenger
- Department of Pharmaceutical Care and Health Systems, College of PharmacyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Jeffrey R. Bishop
- Department of Experimental and Clinical Pharmacology, College of PharmacyUniversity of MinnesotaMinneapolisMinnesotaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of Minnesota Medical SchoolMinneapolisMinnesotaUSA
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21
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Shue SA, Rowe E, Bell LA, Damush T, DeLong A, Gowan T, Skaar T, Haggstrom D. Pharmacogenomics implementation across multiple clinic settings: a qualitative evaluation. Pharmacogenomics 2023; 24:881-893. [PMID: 37975236 DOI: 10.2217/pgs-2023-0179] [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: 11/19/2023] Open
Abstract
Aim: To advance clinical adoption and implementation of pharmacogenomics (PGx) testing, barriers and facilitators to these efforts must be understood. This study identified and examined barriers and facilitators to active implementation of a PGx program across multiple clinic settings in an academic healthcare system. Materials & methods: 28 contributors to the PGx implementation (e.g., clinical providers, informatics specialists) completed an interview to elicit their perceptions of the implementation. Results: Qualitative analysis identified several barriers and facilitators that spanned different stages of the implementation process. Specifically, unclear test payment mechanisms, decision support tool development, rigid workflows and provider education were noted as barriers to the PGx implementation. A multidisciplinary implementation team and leadership support emerged as key facilitators. Furthermore, participants also suggested strategies to overcome or maintain these factors. Conclusion: Assessing real-world implementation perceptions and suggested strategies from a range of implementation contributors facilitates a more comprehensive framework and best-practice guidelines for PGx implementation.
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Affiliation(s)
- Sarah A Shue
- VA HSR&D Center for Health Information & Communication, Roudebush VA Medical Center, Indianapolis, IN 46202, USA
| | - Elizabeth Rowe
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Lauren A Bell
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Teresa Damush
- VA HSR&D Center for Health Information & Communication, Roudebush VA Medical Center, Indianapolis, IN 46202, USA
- Division of General Internal Medicine & Geriatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Alexis DeLong
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Tayler Gowan
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Todd Skaar
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - David Haggstrom
- VA HSR&D Center for Health Information & Communication, Roudebush VA Medical Center, Indianapolis, IN 46202, USA
- Division of General Internal Medicine & Geriatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
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22
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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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Kanji CR, Mbavha BT, Masimirembwa C, Thelingwani RS. Analytical validation of GenoPharm a clinical genotyping open array panel of 46 pharmacogenes inclusive of variants unique to people of African ancestry. PLoS One 2023; 18:e0292131. [PMID: 37788265 PMCID: PMC10547200 DOI: 10.1371/journal.pone.0292131] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/13/2023] [Indexed: 10/05/2023] Open
Abstract
Pharmacogenomic testing may be used to improve treatment outcomes and reduce the frequency of adverse drug reactions (ADRs). Population specific, targeted pharmacogenetics (PGx) panel-based testing methods enable sensitive, accurate and economical implementation of precision medicine. We evaluated the analytical performance of the GenoPharm® custom open array platform which evaluates 120 SNPs across 46 pharmacogenes. Using commercially available reference samples (Coriell Biorepository) and in-house extracted DNA, we assessed accuracy, precision, and linearity of GenoPharm®. We then used GenoPharm® on 218 samples from two Southern African black populations and determined allele and genotype frequencies for selected actionable variants. Across all assays, the GenoPharm® panel demonstrated 99.5% concordance with the Coriell reference samples, with 98.9% reproducibility. We observed high frequencies of key genetic variants in people of African ancestry: CYP2B6*6 (0.35), CYP2C9*8, *11 (0.13, 0.03), CYP2D6*17 (0.21) and *29 (0.11). GenoPharm® open array is therefore an accurate, reproducible and sensitive test that can be used for clinical pharmacogenetic testing and is inclusive of variants specific to the people of African ancestry.
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Affiliation(s)
- Comfort Ropafadzo Kanji
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
- Department of Clinical Pharmacology, University of Zimbabwe (UZ), Harare, Zimbabwe
| | - Bianza Tinotenda Mbavha
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
| | - Collen Masimirembwa
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
| | - Roslyn Stella Thelingwani
- Department of Genomic Medicine, African Institute of Biomedical Science and Technology (AiBST), Beatrice, Zimbabwe
- CradleOmics, Harare, Zimbabwe
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Roberts B, Cooper Z, Lu S, Stanley S, Majda BT, Collins KRL, Gilkes L, Rodger J, Akkari PA, Hood SD. Utility of pharmacogenetic testing to optimise antidepressant pharmacotherapy in youth: a narrative literature review. Front Pharmacol 2023; 14:1267294. [PMID: 37795032 PMCID: PMC10545970 DOI: 10.3389/fphar.2023.1267294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 08/30/2023] [Indexed: 10/06/2023] Open
Abstract
Pharmacogenetics (PGx) is the study and application of how interindividual differences in our genomes can influence drug responses. By evaluating individuals' genetic variability in genes related to drug metabolism, PGx testing has the capabilities to individualise primary care and build a safer drug prescription model than the current "one-size-fits-all" approach. In particular, the use of PGx testing in psychiatry has shown promising evidence in improving drug efficacy as well as reducing toxicity and adverse drug reactions. Despite randomised controlled trials demonstrating an evidence base for its use, there are still numerous barriers impeding its implementation. This review paper will discuss the management of mental health conditions with PGx-guided treatment with a strong focus on youth mental illness. PGx testing in clinical practice, the concerns for its implementation in youth psychiatry, and some of the barriers inhibiting its integration in clinical healthcare will also be discussed. Overall, this paper provides a comprehensive review of the current state of knowledge and application for PGx in psychiatry and summarises the capabilities of genetic information to personalising medicine for the treatment of mental ill-health in youth.
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Affiliation(s)
- Bradley Roberts
- The Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
| | - Zahra Cooper
- The Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Stephanie Lu
- School of Psychological Science, University of Western Australia, Crawley, WA, Australia
| | - Susanne Stanley
- Division of Psychiatry, School of Medicine, University of Western Australia, Crawley, WA, Australia
| | | | - Khan R. L. Collins
- Western Australian Department of Health, North Metropolitan Health Service, Perth, WA, Australia
| | - Lucy Gilkes
- School of Medicine, University of Notre Dame, Fremantle, WA, Australia
- Divison of General Practice, School of Medicine, University of Western Australia, Crawley, WA, Australia
| | - Jennifer Rodger
- The Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
| | - P. Anthony Akkari
- The Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Murdoch, WA, Australia
- Division of Neurology, Duke University Medical Centre, Duke University, Durham, United States
| | - Sean D. Hood
- Division of Psychiatry, School of Medicine, University of Western Australia, Crawley, WA, Australia
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25
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Cecchin E, Posocco B, Mezzalira S, Appetecchia M, Toffoli G. The Role of Gender Pharmacogenetics in the Personalization of Drug Treatment. J Pharmacol Exp Ther 2023; 386:190-197. [PMID: 37001987 DOI: 10.1124/jpet.122.001416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 03/21/2023] [Indexed: 07/20/2023] Open
Abstract
The use of pharmacogenetic guidelines in personalizing treatments has shown the potential to reduce interindividual variability in drug response by enabling genotype-matched dosing and drug selection. However, other important factors, such as patient gender, may interact strongly with pharmacogenetics in determining the individual profile of toxicity and efficacy but are still rarely considered when planning pharmacological treatment. The literature indicates that males and females respond differently to drugs, with women being at higher risk for toxicity and having different plasma exposure to drugs at standard doses. Recent studies have shown that pharmacogenetic variants may have different predictive value in different sexes, as in the case of treatment with opioids, angiotensin-converting enzyme inhibitors, or proton pump inhibitors. Of particular interest is the case of treatment with fluoropyrimidines for cancer. A significant increase in toxicity has been described in female patients, with a more pronounced effect of specific DPYD and TYMS polymorphisms also noted. This manuscript reviews the major findings in the field of sex-specific pharmacogenomics. SIGNIFICANCE STATEMENT: Interindividual variability in drug response is an emerging issue in pharmacology. The genetic profile of patients, as well as their gender, may play a role in the identification of patients more exposed to the risk of adverse drug reactions or poor efficacy. This article reviews the current state of research on the interaction between gender and pharmacogenetics in addressing interindividual variability.
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Affiliation(s)
- Erika Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Bianca Posocco
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Silvia Mezzalira
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Marialuisa Appetecchia
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
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26
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Oni-Orisan A, Tuteja S, Hoffecker G, Smith DM, Castrichini M, Crews KR, Murphy WA, Nguyen NHK, Huang Y, Lteif C, Friede KA, Tantisira K, Aminkeng F, Voora D, Cavallari LH, Whirl-Carrillo M, Duarte JD, Luzum JA. An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers. Clin Pharmacol Ther 2023; 114:275-287. [PMID: 37303270 PMCID: PMC10406163 DOI: 10.1002/cpt.2957] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/17/2023] [Indexed: 06/13/2023]
Abstract
Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.
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Affiliation(s)
- Akinyemi Oni-Orisan
- Department of Clinical Pharmacy, University of California San Francisco, San Francisco, California, USA
| | - Sony Tuteja
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Glenda Hoffecker
- Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - D. Max Smith
- MedStar Health, Columbia, Maryland, USA
- Department of Oncology, Georgetown University Medical Center, Washington, DC, USA
| | - Matteo Castrichini
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristine R. Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - William A. Murphy
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nam H. K. Nguyen
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Yimei Huang
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Christelle Lteif
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Kevin A. Friede
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Kelan Tantisira
- Division of Respiratory Medicine, Department of Pediatrics, University of California San Diego, San Diego, California, USA
| | - Folefac Aminkeng
- Departments of Medicine and Biomedical Informatics (DBMI), Yong Loo Lin School of Medicine, National University of Singapore, Singapore City, Singapore
- Centre for Precision Health (CPH), National University Health System (NUHS), Singapore City, Singapore
| | - Deepak Voora
- Precision Medicine Program, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Julio D. Duarte
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Jasmine A. Luzum
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, Michigan, USA
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Suhrie K, Tillman EM. Pharmacogenetic informed care in early childhood: options for improving access and health equity. Pharmacogenomics 2023; 24:579-582. [PMID: 37466126 DOI: 10.2217/pgs-2023-0119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023] Open
Affiliation(s)
- Kristen Suhrie
- Department of Pediatrics, Division of Neonatology, & Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Emma M Tillman
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
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28
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Camargo AC, Matte U, Botton MR. Identification of adverse drug reactions that may be related to pharmacogenetics in a public hospital in the South of Brazil. Expert Opin Drug Saf 2023; 22:621-627. [PMID: 36794346 DOI: 10.1080/14740338.2023.2181337] [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: 08/23/2022] [Accepted: 01/16/2023] [Indexed: 02/17/2023]
Abstract
BACKGROUND Adverse drug reactions (ADRs) are of great concern in clinical practice. Pharmacogenetics can identify individuals and groups at increased risk of developing ADRs, enabling treatment adjustments to improve outcomes. The study aimed to determine the prevalence of ADRs related to drugs with pharmacogenetic evidence level 1A in a public hospital in Southern Brazil. RESEARCH DESIGN AND METHODS ADR information was collected from the pharmaceutical registries from 2017 to 2019. Drugs that have pharmacogenetic evidence level 1A were selected. Public genomic databases were used to estimate the genotypes/phenotypes frequency. RESULTS During the period, 585 ADRs were spontaneously notified. Most were moderate (76.3%), whereas severe reactions accounted for 33.8%. Additionally, 109 ADRs caused by 41 drugs presented pharmacogenetic evidence level 1A, representing 18.6% of all notified reactions. Depending on the drug-gene pair, up to 35% of individuals from Southern Brazil could be at risk of developing ADRs. CONCLUSIONS Relevant amount of ADRs were related to drugs with pharmacogenetic recommendations on drug labels and/or guidelines. Genetic information could guide and improve clinical outcomes, decreasing ADR incidence and reducing treatment costs.
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Affiliation(s)
- Amanda C Camargo
- Department of Genetics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Cells, Tissues and Genes Laboratory, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Ursula Matte
- Department of Genetics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Cells, Tissues and Genes Laboratory, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Mariana R Botton
- Cells, Tissues and Genes Laboratory, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Transplant Immunology and Personalized Medicine Unit, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
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29
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Padmanabhan S, du Toit C, Dominiczak AF. Cardiovascular precision medicine - A pharmacogenomic perspective. CAMBRIDGE PRISMS. PRECISION MEDICINE 2023; 1:e28. [PMID: 38550953 PMCID: PMC10953758 DOI: 10.1017/pcm.2023.17] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 05/24/2023] [Accepted: 06/12/2023] [Indexed: 05/16/2024]
Abstract
Precision medicine envisages the integration of an individual's clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.
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Affiliation(s)
- Sandosh Padmanabhan
- BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Clea du Toit
- BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Anna F. Dominiczak
- BHF Glasgow Cardiovascular Research Centre, School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
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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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Kabbani D, Akika R, Wahid A, Daly AK, Cascorbi I, Zgheib NK. Pharmacogenomics in practice: a review and implementation guide. Front Pharmacol 2023; 14:1189976. [PMID: 37274118 PMCID: PMC10233068 DOI: 10.3389/fphar.2023.1189976] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/03/2023] [Indexed: 06/06/2023] Open
Abstract
Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests' reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.
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Affiliation(s)
- Danya Kabbani
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Reem Akika
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Ahmed Wahid
- Department of Pharmaceutical Biochemistry, Faculty of Pharmacy, Alexandria University, Alexandria, Egypt
| | - Ann K. Daly
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Ingolf Cascorbi
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Nathalie Khoueiry Zgheib
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
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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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Smith DM, Wake DT, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Scoping Review. Clin Pharmacol Ther 2023; 113:803-815. [PMID: 35838358 DOI: 10.1002/cpt.2711] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 07/10/2022] [Indexed: 11/06/2022]
Abstract
Clinical decision support (CDS) is often cited as an essential part of pharmacogenomics (PGx) implementations. A multitude of strategies are available; however, it is unclear which strategies are effective and which metrics are used to quantify clinical utility. The objective of this scoping review was to aggregate previous studies into a cohesive depiction of the current state of PGx CDS implementations and identify areas for future research on PGx CDS. Articles were included if they (i) described electronic CDS tools for PGx and (ii) reported metrics related to PGx CDS. Twenty of 3,449 articles were included and provided data on PGx CDS metrics from 15 institutions, with 93% of programs located at academic medical centers. The most common tools in CDS implementations were interruptive post-test alerts. Metrics for clinical response and alert response ranged from 12-73% and 21-98%, respectively. Few data were found on changes in metrics over time and measures that drove the evolution of CDS systems. Relatively few data were available regarding support of optimal approaches for PGx CDS. Post-test alerts were the most widely studied approach, and their effectiveness varied greatly. Further research on the usability, effectiveness, and optimization of CDS tools is needed.
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Affiliation(s)
- D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, District of Columbia, USA
| | - Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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Rasmussen LV, Agrawal AH, Botsford P, Powers A, Schnoebelen J, Xinos S, Harper G, Thanner J, McCabe S, Moore S, Wicklund CA, Duquette D, Gordon EJ. Challenges of Integrating APOL1 Genetic Test Results into the Electronic Health Record. Appl Clin Inform 2023; 14:321-325. [PMID: 37186083 PMCID: PMC10132929 DOI: 10.1055/s-0043-1767680] [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: 11/29/2022] [Accepted: 02/12/2023] [Indexed: 05/17/2023] Open
Abstract
OBJECTIVES Integrating genetic test results into the electronic health record (EHR) is essential for integrating genetic testing into clinical practice. This article describes the organizational challenges of integrating discrete apolipoprotein L1 (APOL1) genetic test results into the EHR for a research study on culturally sensitive genetic counseling for living kidney donors. METHODS We convened a multidisciplinary team across three institutions (Northwestern University, Northwestern Memorial HealthCare [NMHC], and OHSU Knight Diagnostic Laboratories [KDL]), including researchers, physicians, clinical information technology, and project management. Through a series of meetings over a year between the team and the genetic testing laboratory, we explored and adjusted our EHR integration plan based on regulatory and budgetary constraints. RESULTS Our original proposal was to transmit results from KDL to NMHC as structured data sent via Health Level Seven (HL7) v2 message. This was ultimately deemed infeasible given the time and resources required to establish the interface, and the low number of samples to be processed for the study (n = 316). We next explored the use of Epic's Care Everywhere interoperability platform, but learned it was not possible as a laboratory test ordered for a research study; even though our intent was to study the APOL1 genetic test result's clinical use and impact, test results were still considered "research results." Faced with two remaining options-downloading a PDF from the KDL laboratory portal or scanning a faxed result from KDL-only a PDF of the APOL1 test result could be integrated into the EHR, reinforcing the status quo. CONCLUSION Even with early and ongoing stakeholder engagement, dedicated project management, and funding, unanticipated implementation challenges-especially for research projects-can result in drastic design tradeoffs.
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Affiliation(s)
- Luke V. Rasmussen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Akansha H. Agrawal
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Paul Botsford
- Information Services, Digital Solutions, Northwestern Medicine, Chicago, Illinois, United States
| | - Andrew Powers
- Information Services, Clinical Applications, Northwestern Medicine, Chicago, Illinois, United States
| | - Jeffrey Schnoebelen
- Information Services, Business Relationship Management, Northwestern Medicine, Chicago, Illinois, United States
| | - Stavroula Xinos
- Information Services, Digital Administration, Northwestern Medicine, Chicago, Illinois, United States
| | - Gail Harper
- Business Development and Strategic Outreach, Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, Oregon, United States
| | - Jane Thanner
- Information Technology Group, Oregon Health & Science University, Portland, Oregon, United States
| | - Sarah McCabe
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, Oregon, United States
| | - Stephen Moore
- Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, Oregon, United States
| | - Catherine A. Wicklund
- Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Debra Duquette
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
| | - Elisa J. Gordon
- Department of Surgery, Section of Surgical Sciences, and Center for Biomedical Ethics and Society, Vanderbilt University Medical Center, Nashville, Tennessee, United States
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Swen JJ, van der Wouden CH, Manson LE, Abdullah-Koolmees H, Blagec K, Blagus T, Böhringer S, Cambon-Thomsen A, Cecchin E, Cheung KC, Deneer VH, Dupui M, Ingelman-Sundberg M, Jonsson S, Joefield-Roka C, Just KS, Karlsson MO, Konta L, Koopmann R, Kriek M, Lehr T, Mitropoulou C, Rial-Sebbag E, Rollinson V, Roncato R, Samwald M, Schaeffeler E, Skokou M, Schwab M, Steinberger D, Stingl JC, Tremmel R, Turner RM, van Rhenen MH, Dávila Fajardo CL, Dolžan V, Patrinos GP, Pirmohamed M, Sunder-Plassmann G, Toffoli G, Guchelaar HJ. A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study. Lancet 2023; 401:347-356. [PMID: 36739136 DOI: 10.1016/s0140-6736(22)01841-4] [Citation(s) in RCA: 169] [Impact Index Per Article: 169.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/08/2022] [Accepted: 09/16/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. METHODS We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING European Union Horizon 2020.
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Affiliation(s)
- Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands
| | | | - Lisanne En Manson
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands
| | - Heshu Abdullah-Koolmees
- Division Laboratories, Pharmacy and Biomedical Genetics, Hospital Pharmacy, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Kathrin Blagec
- Centre for Medical Statistics, Informatics and Intelligent Systems, Institute of Artificial Intelligence, Medical University of Vienna, Vienna, Austria
| | - Tanja Blagus
- Pharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Stefan Böhringer
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands; Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, Netherlands
| | - Anne Cambon-Thomsen
- CNRS, Centre for Epidemiology and Research in Population health (CERPOP), Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Erika Cecchin
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Ka-Chun Cheung
- Medicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, Netherlands
| | - Vera Hm Deneer
- Division Laboratories, Pharmacy and Biomedical Genetics, Hospital Pharmacy, University Medical Centre Utrecht, Utrecht, Netherlands; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Netherlands
| | - Mathilde Dupui
- Service de pharmacologie médicale et clinique, CEIP-addictovigilance de Toulouse, faculté de médecine, CHU, Toulouse, France
| | | | - Siv Jonsson
- Department of Pharmacy, Uppsala University, Uppsala, Sweden
| | - Candace Joefield-Roka
- Department of Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, Vienna, Austria
| | - Katja S Just
- Institute of Clinical Pharmacology, University Hospital RWTH Aachen, Aachen, Germany
| | | | - Lidija Konta
- Bio.logis Digital Health, Frankfurt am Main, Germany
| | - Rudolf Koopmann
- Bio.logis Digital Health, Frankfurt am Main, Germany; Diagnosticum Centre for Humangenetics, Frankfurt am Main, Germany
| | - Marjolein Kriek
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, Netherlands
| | - Thorsten Lehr
- Clinical Pharmacy, Saarland University, Saarbrücken, Germany
| | - Christina Mitropoulou
- The Golden Helix Foundation, London, UK; Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, Abu Dhabi, United Arab Emirates
| | | | - Victoria Rollinson
- Department of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK
| | - Rossana Roncato
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Matthias Samwald
- Centre for Medical Statistics, Informatics and Intelligent Systems, Institute of Artificial Intelligence, Medical University of Vienna, Vienna, Austria
| | - Elke Schaeffeler
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; iFIT Cluster of Excellence (EXC2180)-Image Guided and Functionally Instructed Tumour Therapies, University of Tuebingen, Tuebingen, Germany
| | - Maria Skokou
- University of Patras School of Health Sciences, Department of Pharmacy, Division of Pharmacology and Biosciences, Laboratory of Pharmacogenomics and Individualised Therapy, Patras, Greece
| | - Matthias Schwab
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany; iFIT Cluster of Excellence (EXC2180)-Image Guided and Functionally Instructed Tumour Therapies, University of Tuebingen, Tuebingen, Germany; Department of Clinical Pharmacology, University of Tuebingen, Tuebingen, Germany; Department of Pharmacy and Biochemistry, University of Tuebingen, Tuebingen, Germany
| | - Daniela Steinberger
- Bio.logis Digital Health, Frankfurt am Main, Germany; Diagnosticum Centre for Humangenetics, Frankfurt am Main, Germany
| | - Julia C Stingl
- Institute of Clinical Pharmacology, University Hospital RWTH Aachen, Aachen, Germany
| | - Roman Tremmel
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
| | - Richard M Turner
- Department of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK
| | - Mandy H van Rhenen
- Medicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, Netherlands
| | - Cristina L Dávila Fajardo
- Clinical Pharmacy Department, Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria Granada, Granada, Spain
| | - Vita Dolžan
- Pharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - George P Patrinos
- Department of Genetics and Genomics, College of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, Abu Dhabi, United Arab Emirates; Zayed Centre for Health Sciences, College of Medicine and Health Sciences, United Arab Emirates University, Al-Ain, Abu Dhabi, United Arab Emirates; University of Patras School of Health Sciences, Department of Pharmacy, Division of Pharmacology and Biosciences, Laboratory of Pharmacogenomics and Individualised Therapy, Patras, Greece; Erasmus University Medical Centre, Faculty of Medicine and Health Sciences, Department of Pathology-Clinical Bioinformatics Unit, Rotterdam, Netherlands
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK
| | - Gere Sunder-Plassmann
- Department of Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, Vienna, Austria
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands.
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Chen T, O'Donnell PH, Middlestadt M, Ruhnke GW, Danahey K, van Wijk XMR, Choksi A, Knoebel R, Hartman S, Yeo KTJ, Friedman PN, Ratain MJ, Nutescu EA, O'Leary KJ, Perera MA, Meltzer DO. Implementation of pharmacogenomics into inpatient general medicine. Pharmacogenet Genomics 2023; 33:19-23. [PMID: 36729768 DOI: 10.1097/fpc.0000000000000487] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Pharmacogenomics is a crucial piece of personalized medicine. Preemptive pharmacogenomic testing is only used sparsely in the inpatient setting and there are few models to date for fostering the adoption of pharmacogenomic treatment in the inpatient setting. We created a multi-institutional project in Chicago to enable the translation of pharmacogenomics into inpatient practice. We are reporting our implementation process and barriers we encountered with solutions. This study, 'Implementation of Point-of-Care Pharmacogenomic Decision Support Accounting for Minority Disparities', sought to implement pharmacogenomics into inpatient practice at three sites: The University of Chicago, Northwestern Memorial Hospital, and the University of Illinois at Chicago. This study involved enrolling African American adult patients for preemptive genotyping across a panel of actionable germline variants predicting drug response or toxicity risk. We report our approach to implementation and the barriers we encountered engaging hospitalists and general medical providers in the inpatient pharmacogenomic intervention. Our strategies included: a streamlined delivery system for pharmacogenomic information, attendance at hospital medicine section meetings, use of physician and pharmacist champions, focus on hospitalists' care and optimizing system function to fit their workflow, hand-offs, and dealing with hospitalists turnover. Our work provides insights into strategies for the initial engagement of inpatient general medicine providers that we hope will benefit other institutions seeking to implement pharmacogenomics in the inpatient setting.
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Affiliation(s)
- Thomas Chen
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Peter H O'Donnell
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Merisa Middlestadt
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois, USA
| | - Gregory W Ruhnke
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Keith Danahey
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois, USA
| | | | - Anish Choksi
- Department of Pharmacy, The University of Chicago, Chicago, Illinois, USA
| | - Randall Knoebel
- Department of Pharmacy, The University of Chicago, Chicago, Illinois, USA
| | - Seth Hartman
- Department of Pharmacy, The University of Chicago, Chicago, Illinois, USA
| | | | - Paula N Friedman
- Department of Pharmacology, Northwestern University, Chicago, Illinois, USA
| | - Mark J Ratain
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Edith A Nutescu
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Kevin J O'Leary
- Department of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Minoli A Perera
- Department of Pharmacology, Northwestern University, Chicago, Illinois, USA
| | - David O Meltzer
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
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Pasternak AL, Ward K, Irwin M, Okerberg C, Hayes D, Fritsche L, Zoellner S, Virzi J, Choe HM, Ellingrod V. Identifying the prevalence of clinically actionable drug-gene interactions in a health system biorepository to guide pharmacogenetics implementation services. Clin Transl Sci 2023; 16:292-304. [PMID: 36510710 PMCID: PMC9926071 DOI: 10.1111/cts.13449] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 10/14/2022] [Accepted: 10/24/2022] [Indexed: 12/15/2022] Open
Abstract
Understanding patterns of drug-gene interactions (DGIs) is important for advancing the clinical implementation of pharmacogenetics (PGx) into routine practice. Prior studies have estimated the prevalence of DGIs, but few have confirmed DGIs in patients with known genotypes and prescriptions, nor have they evaluated clinician characteristics associated with DGI-prescribing. This retrospective chart review assessed prevalence of DGI, defined as a medication prescription in a patient with a PGx phenotype that has a clinical practice guideline recommendation to adjust therapy or monitor drug response, for patients enrolled in a research genetic biorepository linked to electronic health records (EHRs). The prevalence of prescriptions for medications with pharmacogenetic (PGx) guidelines, proportion of prescriptions with DGI, location of DGI prescription, and clinical service of the prescriber were evaluated descriptively. Seventy-five percent (57,058/75,337) of patients had a prescription for a medication with a PGx guideline. Up to 60% (n = 26,067/43,647) of patients had at least one DGI when considering recommendations to adjust or monitor therapy based on genotype. The majority (61%) of DGIs occurred in outpatient prescriptions. Proton pump inhibitors were the most common DGI medication for 11 of 12 clinical services. Almost 25% of patients (n = 10,706/43,647) had more than one unique DGI, and, among this group of patients, 61% had a DGI with more than one gene. These findings can inform future clinical implementation by identifying key stakeholders for initial DGI prescriptions, helping to inform workflows. The high prevalence of multigene interactions identified also support the use of panel PGx testing as an implementation strategy.
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Affiliation(s)
- Amy L. Pasternak
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Kristen Ward
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Madison Irwin
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Carl Okerberg
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - David Hayes
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
| | - Lars Fritsche
- Department of BiostatisticsUniversity of Michigan School of Public HealthAnn ArborMichiganUSA
| | - Sebastian Zoellner
- Department of BiostatisticsUniversity of Michigan School of Public HealthAnn ArborMichiganUSA
| | - Jessica Virzi
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Hae Mi Choe
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Vicki Ellingrod
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
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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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Gawronski BE, Cicali EJ, McDonough CW, Cottler LB, Duarte JD. Exploring perceptions, knowledge, and attitudes regarding pharmacogenetic testing in the medically underserved. Front Genet 2023; 13:1085994. [PMID: 36712853 PMCID: PMC9880414 DOI: 10.3389/fgene.2022.1085994] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 12/28/2022] [Indexed: 01/15/2023] Open
Abstract
Introduction: Pharmacogenetic testing may hold promise in addressing health disparities, as medically underserved patients appear to be prescribed medications with pharmacogenetic guidelines at higher rates. While routine clinical implementation of testing in medically underserved populations has not yet been achieved, using patient perspectives to inform implementation should increase the likelihood of success. The aim of this study was to assess the perceptions, knowledge, and attitudes regarding pharmacogenetic testing in medically underserved patients. Methods: We developed a survey instrument to assess respondent views on pharmacogenetic testing. The survey instrument was developed through a process of literature review, expert input, iterative pilot testing, and final refinement. The survey instrument was fielded to US adults with an estimated household income of $42,000 per year or less. Results: During the survey instrument development, 59 pilot testers provided 133 comments which lead to 38 revisions to the survey instrument. The nationwide survey resulted in 1,060 respondents, of which half (49.8%) reported having no health insurance or being on Medicaid. Most patients (78.9%) had not previously heard of pharmacogenetic testing. After being provided an explanation of pharmacogenetic testing, 60.5% were very or moderately interested in receiving testing if there were no cost and 75.8% of respondents agreed or strongly agreed that pharmacogenetic testing should be available to help with medication selection regardless of cost. Respondents shared that their greatest concern with pharmacogenetic testing was that the test would cost them money, which was expressed by over half (52.7%). This was followed by concerns that the results could reveal a risk for a disease, could affect health insurance, and would not improve care. Discussion: Our results indicate a strong interest in pharmacogenetic testing and identify key perceptions, attitudes, concerns, and potential barriers that can be addressed as pharmacogenetic testing is clinically implemented in medically underserved patient populations.
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Affiliation(s)
- Brian E. Gawronski
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, United States
| | - Emily J. Cicali
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, United States
| | - Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, United States
| | - Linda B. Cottler
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, United States
| | - Julio D. Duarte
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, United States
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Scheuner MT, Sales P, Hoggatt K, Zhang N, Whooley MA, Kelley MJ. Genetics professionals are key to the integration of genetic testing within the practice of frontline clinicians. Genet Med 2023; 25:103-114. [PMID: 36301261 DOI: 10.1016/j.gim.2022.09.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 09/19/2022] [Accepted: 09/22/2022] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Genetic tests have become widely available. We sought to understand the use of genetic tests in the practice of frontline clinicians within the United States Department of Veterans Affairs (VA). METHODS We administered a web-based survey to clinicians at 20 VA facilities. Physicians, nurse practitioners, physician assistants, and pharmacists were eligible. We excluded genetics providers and clinicians not seeing patients. We used multiple logistic regression to evaluate the associations between clinician characteristics and experience with genetics. RESULTS The response rate was 11.3% (1207/10,680) and of these, 909 respondents were eligible. Only 20.8% of the respondents reported feeling prepared to use genetic tests and 13.0% of the respondents were currently ordering genetic tests; although, it was usually only 1 or 2 a year. Delivery of genetic tests without involving genetics providers was preferred by only 7.9% of the respondents. Characteristics positively associated with currently ordering genetic tests included practice in clinical and research settings, believing improving genetics knowledge could alter their practice, feeling prepared to use genetic tests, and referral of at least 1 patient to genetics in the past year. CONCLUSION Most VA clinicians don't feel prepared to use genetic tests. Those with genetic testing experience are more likely to consult genetics providers. The demand for genetics providers should increase as frontline clinicians use genetic tests in their practice.
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Affiliation(s)
- Maren T Scheuner
- Medicine Service, Hematology-Oncology Section, San Francisco VA Health Care System, San Francisco, CA; Department of Medicine, University of California San Francisco, San Francisco, CA; Department of Pediatrics, University of California San Francisco, San Francisco, CA.
| | - Paloma Sales
- Medicine Service, Hematology-Oncology Section, San Francisco VA Health Care System, San Francisco, CA
| | - Katherine Hoggatt
- Medicine Service, Hematology-Oncology Section, San Francisco VA Health Care System, San Francisco, CA; Department of Medicine, University of California San Francisco, San Francisco, CA
| | - Ning Zhang
- Medicine Service, Hematology-Oncology Section, San Francisco VA Health Care System, San Francisco, CA
| | - Mary A Whooley
- Medicine Service, Hematology-Oncology Section, San Francisco VA Health Care System, San Francisco, CA; Department of Medicine, University of California San Francisco, San Francisco, CA
| | - Michael J Kelley
- National Oncology Program, Specialty Care Services, Department of Veterans Affairs, Washington, DC; Durham VA Health Care System, Durham, NC; Department of Medicine, Duke University, Durham, NC
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Graansma LJ, Zhai Q, Busscher L, Menafra R, van den Berg RR, Kloet SL, van der Lee M. From gene to dose: Long-read sequencing and *-allele tools to refine phenotype predictions of CYP2C19. Front Pharmacol 2023; 14:1076574. [PMID: 36937863 PMCID: PMC10014917 DOI: 10.3389/fphar.2023.1076574] [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: 10/21/2022] [Accepted: 01/31/2023] [Indexed: 03/06/2023] Open
Abstract
Background: Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant arrays currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco) genes. In this study we aimed to assess the value of long-read sequencing for research and clinical PGx focusing on the important and highly polymorphic CYP2C19 gene. Methods and Results: With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign haplotypes to pharmacogenes based on all input variants. Conclusion: We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are a useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual's drug response and improve therapy outcomes. However, the added value in clinical PGx might currently be limited.
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Affiliation(s)
- Lonneke J. Graansma
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Qinglian Zhai
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
| | - Loes Busscher
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Roberta Menafra
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Redmar R. van den Berg
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Susan L. Kloet
- Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Maaike van der Lee
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
- *Correspondence: Maaike van der Lee,
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Bai H, Zhang X, Bush WS. Pharmacogenomic and Statistical Analysis. Methods Mol Biol 2023; 2629:305-330. [PMID: 36929083 DOI: 10.1007/978-1-0716-2986-4_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.
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Affiliation(s)
- Haimeng Bai
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Xueyi Zhang
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
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van der Wouden CH, Guchelaar HJ, Swen JJ. Precision Medicine Using Pharmacogenomic Panel-Testing: Current Status and Future Perspectives. Clin Lab Med 2022; 42:587-602. [PMID: 36368784 DOI: 10.1016/j.cll.2022.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Cathelijne H van der Wouden
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands; Leiden Network for Personalised Therapeutics, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands; Leiden Network for Personalised Therapeutics, Leiden, The Netherlands
| | - Jesse J Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Albinusdreef 2, Leiden 2333ZA, The Netherlands; Leiden Network for Personalised Therapeutics, Leiden, The Netherlands.
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Fragala MS, Shaman JA, Lorenz RA, Goldberg SE. Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers. Popul Health Manag 2022; 25:753-762. [PMID: 36301527 DOI: 10.1089/pop.2022.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.
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O'Shea J, Ryan C, Gallagher J, O'Brien C, Morris C, Dwyer E, Laughlin JM, Fitzpatrick L, O'Meara M, Kelly S, Knox S, Ledwidge M. Public perceptions of pharmacogenomic services in Ireland - Are people with chronic disease more likely to want service availability than those without? A questionnaire study. EXPLORATORY RESEARCH IN CLINICAL AND SOCIAL PHARMACY 2022; 8:100182. [PMID: 36200068 PMCID: PMC9529536 DOI: 10.1016/j.rcsop.2022.100182] [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: 07/19/2022] [Revised: 09/20/2022] [Accepted: 09/20/2022] [Indexed: 11/26/2022] Open
Abstract
Background As pharmacogenomic services begin to emerge in primary care, the insight of the public is crucial for its integration into clinical practice. Objectives To establish perceptions of pharmacogenomics (awareness, understanding, openness to availability, perceived benefits and concerns, willingness to pay, and service setting) and investigate if they differ between those with and without chronic disease(s). Methods An anonymous, online questionnaire generated using Qualtrics® and circulated via social media and posters placed in eight participating community pharmacies was conducted with Irish adults. The questions were designed to consider existing literature on patient perceptions of pharmacogenomics. Descriptive statistics were used to summarize questionnaire responses. Chi-square test was used to compare categorical variables, while independent sample t-test and one-way ANOVA were used to compare the mean values of two (with and without chronic disease) and three groups (multimorbidity (two or more chronic conditions) and polypharmacy (prescribed four or more regular medicines) (MMPP), a single chronic disease, and those without existing medical conditions) respectively Logistic regression was used to evaluate age and gender adjusted associations of chronic disease(s) with responses. A p-value <0.05 was considered statistically significant. Results A total of 421 responses were received, 30% (n = 120) of whom reported having a chronic disease. Overall, respondents reported low awareness (44%, n = 166) and poor knowledge (55%, n = 212) of pharmacogenomics. After explaining pharmacogenomics to respondents, patients with chronic disease(s) were 2.17 times more likely (p < 0.001) to want pharmacogenomic services availability than those without existing conditions, adjusted for age and gender (driven by preferences of those with MMPP than those with single chronic disease). Respondents demonstrated a high level of interest and noted both the potential benefits and downsides of pharmacogenomic testing. Willingness-to-pay was not associated with having a chronic disease and respondents were more positive about primary care (community pharmacy or general practice) rather than hospital-based pharmacogenomics implementation. Conclusion The Irish public in general and those with chronic disease in particular are strongly supportive of pharmacogenomic testing, highlighting an unmet need for its incorporation in medicines optimization. These data underline the need for more research on the implementation of community-based pharmacogenomics services for MMPP patients and ubiquitous pharmacogenomics education programs.
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Affiliation(s)
- Joseph O'Shea
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Cristín Ryan
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Joseph Gallagher
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - Claire O'Brien
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Conor Morris
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Eoin Dwyer
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - James Mc Laughlin
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Laura Fitzpatrick
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Maire O'Meara
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Sarah Kelly
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Sophie Knox
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Mark Ledwidge
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
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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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47
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Truong TM, Apfelbaum JL, Danahey K, Schierer E, Ludwig J, George D, House L, Karrison T, Shahul S, Anitescu M, Choksi A, Hartman S, Knoebel RW, van Wijk XM, Yeo KTJ, Meltzer D, Ratain MJ, O’Donnell PH. Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial. Anesth Analg 2022; 135:929-940. [PMID: 35213469 PMCID: PMC9402808 DOI: 10.1213/ane.0000000000005951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
BACKGROUND Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care. METHODS The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers. RESULTS Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow. CONCLUSIONS Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.
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Affiliation(s)
- Tien M. Truong
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
| | - Jeffrey L. Apfelbaum
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Keith Danahey
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Emily Schierer
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Jenna Ludwig
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - David George
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Larry House
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Theodore Karrison
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Sajid Shahul
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Magdalena Anitescu
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Anish Choksi
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Seth Hartman
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Randall W. Knoebel
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Xander M.R. van Wijk
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Kiang-Teck J. Yeo
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - David Meltzer
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Mark J. Ratain
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
| | - Peter H. O’Donnell
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
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Cicali EJ, Lemke L, Al Alshaykh H, Nguyen K, Cavallari LH, Wiisanen K. How to Implement a Pharmacogenetics Service at your Institution. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2022; 5:1161-1175. [PMID: 36589694 PMCID: PMC9799247 DOI: 10.1002/jac5.1699] [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: 01/31/2022] [Accepted: 07/29/2022] [Indexed: 01/05/2023]
Abstract
The vast majority of patients possess one or more pharmacogenetic variants that can influence optimal medication use. When pharmacogenetic data are used to guide drug choice and dosing, evidence points to improved disease outcomes, fewer adverse effects, and lower healthcare spending. Although its science is well established, clinical use of pharmacogenetic data to guide drug therapy is still in its infancy. Pharmacogenetics essentially involves the intersection of an individual's genetic data with their medications, which makes pharmacists uniquely qualified to provide clinical support and education in this field. In fact, most pharmacogenetics implementations, to date, have been led by pharmacists as leaders or members of a multidisciplinary team or as individual practitioners. A successful large-scale pharmacogenetics implementation requires coordination and synergy among administrators, clinicians, informatics teams, laboratories, and patients. Because clinical implementation of pharmacogenetics is in its early stages, there is an urgent need for guidance and dissemination of shared experiences to provide a framework for clinicians. Many early adopters of pharmacogenetics have explored various strategies among diverse practice settings. This article relies on the experiences of early adopters to provide guidance for critical steps along the pathway to implementation, including strategies to engage stakeholders; evaluate pharmacogenetic evidence; coordinate laboratory testing, results interpretation and their integration into the electronic health record; identify reimbursement avenues; educate providers and patients; and maintain a successful program. Learning from early adopters' published experiences and strategies can allow clinicians leading a new pharmacogenetics implementation to avoid pitfalls and adapt and apply lessons learned by others to their own practice.
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Affiliation(s)
- Emily J Cicali
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Lauren Lemke
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Hana Al Alshaykh
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Khoa Nguyen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
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Public Attitudes toward Pharmacogenomic Testing and Establishing a Statewide Pharmacogenomics Database in the State of Minnesota. J Pers Med 2022; 12:jpm12101615. [PMID: 36294754 PMCID: PMC9604616 DOI: 10.3390/jpm12101615] [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: 08/14/2022] [Revised: 09/18/2022] [Accepted: 09/19/2022] [Indexed: 11/07/2022] Open
Abstract
The clinical adoption and implementation of pharmacogenomics (PGx) beyond academic medical centers remains slow, restricting the general population from benefitting from this important component of personalized medicine. As an initial step in the statewide initiative of PGx implementation in Minnesota, we engaged community members and assessed attitudes towards PGx testing and acceptability of establishing a secure statewide PGx database for clinical and research use among Minnesota residents. Data was collected from 808 adult attendees at the 2021 Minnesota State Fair through an electronic survey. Eighty-four percent of respondents felt comfortable getting a PGx test for clinical care. Most respondents trusted health professionals (78.2%) and researchers (73.0%) to keep their PGx data private. The majority expressed their support and interest in participating in a statewide PGx database for clinical and research use (64–72%). Higher acceptability of the statewide PGx database was associated with younger age, higher education, higher health literacy, having health insurance, and prior genetic testing. The study sample representing Minnesota residents expressed high acceptability of receiving PGx testing and willingness to participate in PGx data sharing for clinical and research use. Community support and engagement are needed to advance PGx implementation and research on the state scale.
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50
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Goh LL, Lim CW, Leong KP, Ong KH. TPMT and NUDT15 testing for thiopurine therapy: A major tertiary hospital experience and lessons learned. Front Pharmacol 2022; 13:837164. [PMID: 36210828 PMCID: PMC9537458 DOI: 10.3389/fphar.2022.837164] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
Variants in thiopurine methyltransferase (TPMT) and nudix hydrolase 15 (NUDT15) are associated with an accumulation of cytotoxic metabolites leading to increased risk of drug-related toxicity with standard doses of thiopurine drugs. We established TPMT and NUDT15 genetic testing for clinical use and evaluated the utilization, service outcomes and potential value of multi-gene PGx testing for 210 patients that underwent pharmacogenetics (PGx) testing for thiopurine therapy with the aim to optimize service delivery for future prescribing. The test was most commonly ordered for Gastroenterology (40.0%) and Neurology (31.4%), with an average turnaround time of 2 days. Following testing, 24.3% patients were identified as intermediate or poor metabolizers, resulting in 51 recommendations for a drug or dose change in thiopurine therapy, which were implemented in 28 (54.9%) patients. In the remaining patients, 14 were not adjusted and 9 had no data available. Focusing on drug gene interactions available for testing in our laboratory, multi-gene PGx results would present opportunities for treatment optimization for at least 33.8% of these patients who were on 2 or more concurrent medications with actionable PGx guidance. However, the use of PGx panel testing in clinical practice will require the development of guidelines and education as revealed by a survey with the test providers. The evaluation demonstrated successful implementation of single gene PGx testing and this experience guides the transition to a pre-emptive multi-gene testing approach that provides the opportunity to improve clinical care.
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Affiliation(s)
- Liuh Ling Goh
- Molecular Diagnostic Laboratory, Personalized Medicine Service, Tan Tock Seng Hospital, Singapore, Singapore
- *Correspondence: Liuh Ling Goh,
| | - Chia Wei Lim
- Molecular Diagnostic Laboratory, Personalized Medicine Service, Tan Tock Seng Hospital, Singapore, Singapore
| | - Khai Pang Leong
- Molecular Diagnostic Laboratory, Personalized Medicine Service, Tan Tock Seng Hospital, Singapore, Singapore
- Department of Rheumatology, Allergy & Immunology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Kiat Hoe Ong
- Molecular Diagnostic Laboratory, Personalized Medicine Service, Tan Tock Seng Hospital, Singapore, Singapore
- Department of Haematology, Tan Tock Seng Hospital, Singapore, Singapore
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