1
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Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
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Affiliation(s)
- Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kristine R Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - James M Hoffman
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
- Office of Quality and Safety, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kelly E Caudle
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
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2
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McDermott JH, Wright S, Sharma V, Newman WG, Payne K, Wilson P. Characterizing pharmacogenetic programs using the consolidated framework for implementation research: A structured scoping review. Front Med (Lausanne) 2022; 9:945352. [PMID: 36059837 PMCID: PMC9433561 DOI: 10.3389/fmed.2022.945352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/29/2022] [Indexed: 12/11/2022] Open
Abstract
Several healthcare organizations have developed pre-emptive pharmacogenetic testing programs, where testing is undertaken prior to the prescription of a medicine. This review characterizes the barriers and facilitators which influenced the development of these programs. A bidirectional citation searching strategy identified relevant publications before a standardized data extraction approach was applied. Publications were grouped by program and data synthesis was undertaken using the Consolidated Framework for Implementation Research (CFIR). 104 publications were identified from 40 programs and 4 multi-center initiatives. 26 (66%) of the programs were based in the United States and 95% in high-income countries. The programs were heterogeneous in their design and scale. The Characteristics of the Intervention, Inner Setting, and Process domains were referenced by 92.5, 80, and 77.5% of programs, respectively. A positive institutional culture, leadership engagement, engaging stakeholders, and the use of clinical champions were frequently described as facilitators to implementation. Clinician self-efficacy, lack of stakeholder knowledge, and the cost of the intervention were commonly cited barriers. Despite variation between the programs, there were several similarities in approach which could be categorized via the CFIR. These form a resource for organizations planning the development of pharmacogenetic programs, highlighting key facilitators which can be leveraged to promote successful implementation.
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Affiliation(s)
- John H. McDermott
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
- *Correspondence: John H. McDermott,
| | - Stuart Wright
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Videha Sharma
- Division of Informatics, Centre for Health Informatics, Imaging and Data Science, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - William G. Newman
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
| | - Katherine Payne
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Paul Wilson
- Division of Population Health, Centre for Primary Care and Health Services Research, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
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3
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Sperber NR, Cragun D, Roberts MC, Bendz LM, Ince P, Gonzales S, Haga SB, Wu RR, Petry NJ, Ramsey L, Uber R. A Mixed-Methods Protocol to Identify Best Practices for Implementing Pharmacogenetic Testing in Clinical Settings. J Pers Med 2022; 12:jpm12081313. [PMID: 36013262 PMCID: PMC9410119 DOI: 10.3390/jpm12081313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/05/2022] [Accepted: 08/09/2022] [Indexed: 11/16/2022] Open
Abstract
Using a patient’s genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers—the cases—at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.
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Affiliation(s)
- Nina R. Sperber
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA
- Durham VA Health Care System, Durham, NC 27705, USA
- Correspondence:
| | - Deborah Cragun
- College of Public Health, University of South Florida, Tampa, FL 33612, USA
| | - Megan C. Roberts
- UNC Eshelman School of Pharmacy, University of North Carolina–Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lisa M. Bendz
- Center for Medication Policy and Drug Information, Department of Pharmacy, Duke University Hospital, Durham, NC 27710, USA
| | - Parker Ince
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA
| | - Sarah Gonzales
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA
| | - Susanne B. Haga
- Department of Medicine, Duke University, Durham, NC 27701, USA
| | - R. Ryanne Wu
- Durham VA Health Care System, Durham, NC 27705, USA
- Department of Medicine, Duke University, Durham, NC 27701, USA
| | - Natasha J. Petry
- School of Pharmacy, North Dakota State University/Sanford Health Imagenetics, Fargo, ND 58108, USA
| | - Laura Ramsey
- Department of Pediatrics, Divisions of Clinical Pharmacology and Research in Patient Services, University of Cincinnati College of Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Ryley Uber
- Center for Pharmacy Innovation and Outcomes, Geisinger, Danville, CA 17822, USA
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4
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Joo J, Himes B. Gene-Based Analysis Reveals Sex-Specific Genetic Risk Factors of COPD. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2022; 2021:601-610. [PMID: 35308900 PMCID: PMC8861659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Sex-specific differences have been noted among people with chronic obstructive pulmonary disease (COPD), but whether these differences are attributable to genetic variation is poorly understood. The availability of large biobanks with deeply phenotyped subjects such as the UK Biobank enables the investigation of sex-specific genetic associations that may provide new insights into COPD risk factors. We performed sex-stratified genome-wide association studies (GWAS) of COPD (male: 12,958 cases and 95,631 controls; female: 11,311 cases and 123,714 controls) and found that while most associations were shared between sexes, several regions had sex-specific contributions, including respiratory viral infection-related loci in/near C5orf56 and PELI1. Using the newly developed R package 'snpsettest', we performed gene-based association tests and identified gene-level sex-specific associations, including C5orf56 on 5q31.1, CFDP1/TMEM170A/CHST6 on 16q23.1 and ASTN2/TRIM32 on 9q33.1. Our results identified promising genes to pursue in functional studies to better understand sexual dimorphism in COPD.
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Affiliation(s)
- Jaehyun Joo
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Blanca Himes
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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5
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Liu M, Van Driest SL, Vnencak-Jones CL, Saucier LAG, Roland BP, Gatto CL, Just SL, Weitkamp AO, Peterson JF. Impact of Updating Pharmacogenetic Results: Lessons Learned from the PREDICT Program. J Pers Med 2021; 11:jpm11111051. [PMID: 34834403 PMCID: PMC8617828 DOI: 10.3390/jpm11111051] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/09/2021] [Accepted: 10/13/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomic (PGx) evidence for selective serotonin reuptake inhibitors (SSRIs) continues to evolve. For sites offering testing, maintaining up-to-date interpretations and implementing new clinical decision support (CDS) driven by existing results creates practical and technical challenges. Vanderbilt University Medical Center initiated panel testing in 2010, added CYP2D6 testing in 2017, and released CDS for SSRIs in 2020. We systematically reinterpreted historic CYP2C19 and CYP2D6 genotypes to update phenotypes to current nomenclature and to launch provider CDS and patient-oriented content for SSRIs. Chart review was conducted to identify and recontact providers caring for patients with current SSRI therapy and new actionable recommendations. A total of 15,619 patients’ PGx results were reprocessed. Of the non-deceased patients reprocessed, 21% (n = 3278) resulted in CYP2C19*1/*17 reinterpretations. Among 289 patients with an actionable recommendation and SSRI medication prescription, 31.8% (n = 92) did not necessitate contact of a clinician, while 43.2% (n = 125) resulted in clinician contacted, and for 25% (n = 72) no appropriate clinician was able to be identified. Maintenance of up-to-date interpretations and recommendations for PGx results over the lifetime of a patient requires continuous effort. Reprocessing is a key strategy for maintenance and expansion of PGx content to be periodically considered and implemented.
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Affiliation(s)
- Michelle Liu
- Department of Pharmacy, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Correspondence:
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.L.V.D.); (J.F.P.)
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Cindy L. Vnencak-Jones
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leigh Ann G. Saucier
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
| | - Bartholomew P. Roland
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
| | - Cheryl L. Gatto
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Shari L. Just
- Health IT Decision Support and Knowledge Engineering, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Asli O. Weitkamp
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.L.V.D.); (J.F.P.)
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
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6
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Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide. Hum Genet 2021; 141:1137-1157. [PMID: 34599365 DOI: 10.1007/s00439-021-02369-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023]
Abstract
Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.
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7
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Wake DT, Bell GC, Gregornik DB, Ho TT, Dunnenberger HM. Synthesis of major pharmacogenomics pretest counseling themes: a multisite comparison. Pharmacogenomics 2021; 22:165-176. [PMID: 33461326 DOI: 10.2217/pgs-2020-0168] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The accessibility of pharmacogenomic (PGx) testing has grown substantially over the last decade and with it has arisen a demand for patients to be counseled on the use of these tests. While guidelines exist for the use of PGx results; objective determinants for who should receive PGx testing remain incomplete. PGx clinical services have been created to meet these screening and education needs and significant variability exists between these programs. This article describes the practices of four PGx clinics during pretest counseling sessions. A description of the major tenets of the benefits, limitations and risks of testing are compiled. Additional tools are provided to serve as a foundation for those wishing to begin or expand their own counseling service.
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Affiliation(s)
- Dyson T Wake
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Gillian C Bell
- Genetics & Personalized Medicine Department, Mission Health, Asheville, NC 28803, USA
| | - David B Gregornik
- Pharmacogenomics Program, Children's Minnesota, Minneapolis, MN 55404, USA
| | - Teresa T Ho
- Department of Pharmacotherapeutics & Clinical Research, University of South Florida Taneja College of Pharmacy, Tampa, FL 33612, USA
| | - Henry M Dunnenberger
- Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
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8
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Scott SA, Scott ER, Seki Y, Chen AJ, Wallsten R, Owusu Obeng A, Botton MR, Cody N, Shi H, Zhao G, Brake P, Nicoletti P, Yang Y, Delio M, Shi L, Kornreich R, Schadt EE, Edelmann L. Development and Analytical Validation of a 29 Gene Clinical Pharmacogenetic Genotyping Panel: Multi-Ethnic Allele and Copy Number Variant Detection. Clin Transl Sci 2020; 14:204-213. [PMID: 32931151 PMCID: PMC7877843 DOI: 10.1111/cts.12844] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 06/16/2020] [Indexed: 12/12/2022] Open
Abstract
To develop a novel pharmacogenetic genotyping panel, a multidisciplinary team evaluated available evidence and selected 29 genes implicated in interindividual drug response variability, including 130 sequence variants and additional copy number variants (CNVs). Of the 29 genes, 11 had guidelines published by the Clinical Pharmacogenetics Implementation Consortium. Targeted genotyping and CNV interrogation were accomplished by multiplex single‐base extension using the MassARRAY platform (Agena Biosciences) and multiplex ligation‐dependent probe amplification (MRC Holland), respectively. Analytical validation of the panel was accomplished by a strategic combination of > 500 independent tests performed on 170 unique reference material DNA samples, which included sequence variant and CNV accuracy, reproducibility, and specimen (blood, saliva, and buccal swab) controls. Among the accuracy controls were 32 samples from the 1000 Genomes Project that were selected based on their enrichment of sequence variants included in the pharmacogenetic panel (VarCover.org). Coupled with publicly available samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM), accuracy validation material was available for the majority (77%) of interrogated sequence variants (100% with average allele frequencies > 0.1%), as well as additional structural alleles with unique copy number signatures (e.g., CYP2D6*5, *13, *36, *68; CYP2B6*29; and CYP2C19*36). Accuracy and reproducibility for both genotyping and copy number were > 99.9%, indicating that the optimized panel platforms were precise and robust. Importantly, multi‐ethnic allele frequencies of the interrogated variants indicate that the vast majority of the general population carries at least one of these clinically relevant pharmacogenetic variants, supporting the implementation of this panel for pharmacogenetic research and/or clinical implementation programs.
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Affiliation(s)
- Stuart A Scott
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Erick R Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Aniwaa Owusu Obeng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mariana R Botton
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Neal Cody
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Paola Nicoletti
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Yao Yang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Lisong Shi
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ruth Kornreich
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Eric E Schadt
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Lisa Edelmann
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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9
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Joo J, Hobbs BD, Cho MH, Himes BE. Trait Insights Gained by Comparing Genome-Wide Association Study Results using Different Chronic Obstructive Pulmonary Disease Definitions. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2020; 2020:278-287. [PMID: 32477647 PMCID: PMC7233028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Biobanks have facilitated the conduct of large-scale genomics studies, but they are challenged by the difficulty of validating some phenotypes, particularly for complex traits that represent heterogeneous groups ofpatients. The guideline definition of COPD, based on objective spirometry measures, has been preferred in genome-wide association studies (GWAS) conducted with epidemiological cohorts, but spirometry measures are seldom available for biobank participants. Defining COPD based on International Classification of Disease (ICD) codes or self-reported measures is highly feasible in biobanks, but it remains unclear whether the misclassification inherent in these definitions prevent the discovery of genetic variants that contribute to COPD. We found that while there was poor agreement in classification of UK Biobank participants as having COPD based on ICD diagnosis codes, self-reported doctor diagnosis or spirometry measures, contrasting GWAS results for these definitions provided insights into what patient characteristics each trait may capture.
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Affiliation(s)
- Jaehyun Joo
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Brian D Hobbs
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael H Cho
- Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Blanca E Himes
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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10
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Aquilante CL, Kao DP, Trinkley KE, Lin CT, Crooks KR, Hearst EC, Hess SJ, Kudron EL, Lee YM, Liko I, Lowery J, Mathias RA, Monte AA, Rafaels N, Rioth MJ, Roberts ER, Taylor MR, Williamson C, Barnes KC. Clinical implementation of pharmacogenomics via a health system-wide research biobank: the University of Colorado experience. Pharmacogenomics 2020; 21:375-386. [PMID: 32077359 PMCID: PMC7226704 DOI: 10.2217/pgs-2020-0007] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
In recent years, the genomics community has witnessed the growth of large research biobanks, which collect DNA samples for research purposes. Depending on how and where the samples are genotyped, biobanks also offer the potential opportunity to return actionable genomic results to the clinical setting. We developed a preemptive clinical pharmacogenomic implementation initiative via a health system-wide research biobank at the University of Colorado. Here, we describe how preemptive return of clinical pharmacogenomic results via a research biobank is feasible, particularly when coupled with strong institutional support to maximize the impact and efficiency of biobank resources, a multidisciplinary implementation team, automated clinical decision support tools, and proactive strategies to engage stakeholders early in the clinical decision support tool development process.
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Affiliation(s)
- Christina L Aquilante
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - David P Kao
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Katy E Trinkley
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Chen-Tan Lin
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,University of Colorado Health, Aurora, CO 80045, USA
| | - Kristy R Crooks
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | | | - Steven J Hess
- University of Colorado Health, Aurora, CO 80045, USA
| | - Elizabeth L Kudron
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Yee Ming Lee
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Ina Liko
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Jan Lowery
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Rasika A Mathias
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Andrew A Monte
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Matthew J Rioth
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Emily R Roberts
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Matthew Rg Taylor
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | | | - Kathleen C Barnes
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
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11
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Glicksberg BS, Johnson KW, Dudley JT. The next generation of precision medicine: observational studies, electronic health records, biobanks and continuous monitoring. Hum Mol Genet 2019; 27:R56-R62. [PMID: 29659828 DOI: 10.1093/hmg/ddy114] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 03/27/2018] [Indexed: 02/06/2023] Open
Abstract
Precision medicine can utilize new techniques in order to more effectively translate research findings into clinical practice. In this article, we first explore the limitations of traditional study designs, which stem from (to name a few): massive cost for the assembly of large patient cohorts; non-representative patient data; and the astounding complexity of human biology. Second, we propose that harnessing electronic health records and mobile device biometrics coupled to longitudinal data may prove to be a solution to many of these problems by capturing a 'real world' phenotype. We envision that future biomedical research utilizing more precise approaches to patient care will utilize continuous and longitudinal data sources.
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Affiliation(s)
- Benjamin S Glicksberg
- Institute for Next Generation Healthcare Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, NY 10029, USA.,Institute for Computational Health Sciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Kipp W Johnson
- Institute for Next Generation Healthcare Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, NY 10029, USA
| | - Joel T Dudley
- Institute for Next Generation Healthcare Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York City, NY 10029, USA
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Coriolan S, Arikawe N, Moscati A, Zhou L, Dym S, Donmez S, Garba A, Falbaum S, Loewy Z, Lull M, Saad M, Shtaynberg J, Obeng AO. Pharmacy students' attitudes and perceptions toward pharmacogenomics education. Am J Health Syst Pharm 2019; 76:836-845. [PMID: 31415690 PMCID: PMC6523044 DOI: 10.1093/ajhp/zxz060] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
PURPOSE To evaluate final-year pharmacy students' perceptions toward pharmacogenomics education, their attitudes on its clinical relevance, and their readiness to use such knowledge in practice. METHODS A 19-question survey was developed and modified from prior studies and was pretested on a small group of pharmacogenomics faculty and pharmacy students. The final survey was administered to 978 final-year pharmacy students in 8 school/colleges of pharmacy in New York and New Jersey between January and May 2017. The survey targeted 3 main themes: perceptions toward pharmacogenomics education, attitudes toward the clinical relevance of this education, and the students' readiness to use knowledge of pharmacogenomics in practice. RESULTS With a 35% response rate, the majority (81%) of the 339 student participants believed that pharmacogenomics was a useful clinical tool for pharmacists, yet only 40% felt that it had been a relevant part of their training. Almost half (46%) received only 1-3 lectures on pharmacogenomics and the majority were not ready to use it in practice. Survey results pointed toward practice-based trainings such as pharmacogenomics rotations as the most helpful in preparing students for practice. CONCLUSIONS Final-year student pharmacists reported varying exposure to pharmacogenomics content in their pharmacy training and had positive attitudes toward the clinical relevance of the discipline, yet they expressed low confidence in their readiness to use this information in practice.
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Affiliation(s)
- Shanice Coriolan
- Candidate 2019, Albany College of Pharmacy and Health Sciences, Albany, NY
| | - Nimota Arikawe
- Candidate 2020, Albany College of Pharmacy and Health Sciences, Albany, NY
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisheng Zhou
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Stephanie Dym
- Touro College of Pharmacy, Touro College, New York, NY
| | - Seda Donmez
- Wegmans School of Pharmacy, St. John Fisher College, Rochester, NY
| | - Adinoyi Garba
- D’Youville College School of Pharmacy, D’Youville College, Buffalo, NY
| | - Sasha Falbaum
- Fairleigh Dickinson College School of Pharmacy, Fairleigh Dickinson University, Teaneck, NJ
| | - Zvi Loewy
- Touro College of Pharmacy, Touro College, New York, NY
| | - Melinda Lull
- Wegmans School of Pharmacy, St. John Fisher College, Rochester, NY
| | - Maha Saad
- College of Pharmacy and Health Sciences, St. Johns University, Jamaica, NY
| | - Jane Shtaynberg
- Department of Experiential Education, LIU Brooklyn Arnold & Marie Schwartz College of Pharmacy, Brooklyn, NY
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
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Rubanovich CK, Cheung C, Mandel J, Bloss CS. Physician preparedness for big genomic data: a review of genomic medicine education initiatives in the United States. Hum Mol Genet 2018; 27:R250-R258. [PMID: 29750248 PMCID: PMC6061688 DOI: 10.1093/hmg/ddy170] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Revised: 05/02/2018] [Accepted: 05/03/2018] [Indexed: 12/11/2022] Open
Abstract
In the last decade, genomic medicine education initiatives have surfaced across the spectrum of physician training in order to help address a gap in genomic medicine preparedness among physicians. The approaches are diverse and stem from the belief that 21st century physicians must be proficient in genomic medicine applications as they will be leaders in the precision medicine movement. We conducted a review of literature in genomic medicine education and training for medical students, residents, fellows, and practicing physicians with articles published between June 2015 and January 2018 to gain a picture of the current state of genomic medicine education with a focus on the United States. We found evidence of progress in the development of new and innovative educational programs and other resources aimed at increasing physician knowledge and readiness. Three overarching educational approach themes emerged, including immersive and experiential learning; interdisciplinary and interprofessional education; and electronic- and web-based approaches. This review is not exhaustive, nevertheless, it may inform future directions and improvements for genomic medicine education. Important next-steps include: (i) identifying and studying ways to best implement low-cost dissemination of genomic information; (ii) emphasizing genomic medicine education program evaluation and (iii) incorporating interprofessional and interdisciplinary initiatives. Genomic medicine education and training will become more and more relevant in the years to come as physicians increasingly interact with genomic and other precision medicine technologies.
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Affiliation(s)
- Caryn Kseniya Rubanovich
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Cynthia Cheung
- The Qualcomm Institute of Calit2, University of California, San Diego, La Jolla, CA, USA
| | - Jess Mandel
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Cinnamon S Bloss
- The Qualcomm Institute of Calit2, University of California, San Diego, La Jolla, CA, USA
- Departments of Psychiatry and Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, USA
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Blagec K, Koopmann R, Crommentuijn – van Rhenen M, Holsappel I, van der Wouden CH, Konta L, Xu H, Steinberger D, Just E, Swen JJ, Guchelaar HJ, Samwald M. Implementing pharmacogenomics decision support across seven European countries: The Ubiquitous Pharmacogenomics (U-PGx) project. J Am Med Inform Assoc 2018; 25:893-898. [PMID: 29444243 PMCID: PMC6016647 DOI: 10.1093/jamia/ocy005] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 11/23/2017] [Accepted: 01/09/2018] [Indexed: 01/07/2023] Open
Abstract
Clinical pharmacogenomics (PGx) has the potential to make pharmacotherapy safer and more effective by utilizing genetic patient data for drug dosing and selection. However, widespread adoption of PGx depends on its successful integration into routine clinical care through clinical decision support tools, which is often hampered by insufficient or fragmented infrastructures. This paper describes the setup and implementation of a unique multimodal, multilingual clinical decision support intervention consisting of digital, paper-, and mobile-based tools that are deployed across implementation sites in seven European countries participating in the Ubiquitous PGx (U-PGx) project.
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Affiliation(s)
- Kathrin Blagec
- Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria
| | - Rudolf Koopmann
- bio.logis Genetic Information Management GmbH, Frankfurt am Main, Germany
| | | | - Inge Holsappel
- Medicines Information Centre; Royal Dutch Pharmacists Association (KNMP), The Hague, The Netherlands
| | | | - Lidija Konta
- bio.logis Center for Human Genetics, Frankfurt am Main, Germany
| | - Hong Xu
- Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria
| | - Daniela Steinberger
- bio.logis Genetic Information Management GmbH, Frankfurt am Main, Germany
- bio.logis Center for Human Genetics, Frankfurt am Main, Germany
- Institute for Human Genetics, Justus Liebig University, Giessen, Germany
| | - Enrico Just
- bio.logis Genetic Information Management GmbH, Frankfurt am Main, Germany
| | - Jesse J Swen
- Deptartment of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Deptartment of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthias Samwald
- Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria
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Liu J, Friedman C, Finkelstein J. Pharmacogenomic Approaches for Automated Medication Risk Assessment in People with Polypharmacy. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2018; 2017:142-151. [PMID: 29888060 PMCID: PMC5961823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Medication regimen may be optimized based on individual drug efficacy identified by pharmacogenomic testing. However, majority of current pharmacogenomic decision support tools provide assessment only of single drug-gene interactions without taking into account complex drug-drug and drug-drug-gene interactions which are prevalent in people with polypharmacy and can result in adverse drug events or insufficient drug efficacy. The main objective of this project was to develop comprehensive pharmacogenomic decision support for medication risk assessment in people with polypharmacy that simultaneously accounts for multiple drug and gene effects. To achieve this goal, the project addressed two aims: (1) development of comprehensive knowledge repository of actionable pharmacogenes; (2) introduction of scoring approaches reflecting potential adverse effect risk levels of complex medication regimens accounting for pharmacogenomic polymorphisms and multiple drug metabolizing pathways. After pharmacogenomic knowledge repository was introduced, a scoring algorithm has been built and pilot-tested using a limited data set. The resulting total risk score for frequently hospitalized older adults with polypharmacy (72.04±17.84) was statistically significantly different (p<0.05) from the total risk score for older adults with polypharmacy with low hospitalization rate (8.98±2.37). An initial prototype assessment demonstrated feasibility of our approach and identified steps for improving risk scoring algorithms.
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Affiliation(s)
- Jiazhen Liu
- Stevens Institute of Technology, Hoboken, NJ, USA
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Mills RA, Eichmeyer JN, Williams LM, Muskett JA, Schmidlen TJ, Maloney KA, Lemke AA. Patient Care Situations Benefiting from Pharmacogenomic Testing. CURRENT GENETIC MEDICINE REPORTS 2018. [DOI: 10.1007/s40142-018-0136-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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