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Comparing commercial pharmacogenetic testing results and recommendations for antidepressants with established CPIC guidelines
Open accessAbstract
Introduction: Increasingly, pharmacogenetic testing helps providers with medication selection based upon patient-specific DNA results. While several government-funded organizations work towards consensus and standardization for testing and interpretation, compliance to these best practices remains inconsistent. Pharmacogenetic testing companies often develop proprietary practices for interpreting and reporting, which can lead to incongruency of reported results among companies and potential discrepancies in interpretation. Methods: To identify the differences of commercial pharmacogenetic testing vendors’ interpretation of genotype-to-phenotype translations and medication recommendations from the Clinical Pharmacogenetic Implementation Consortium (CPIC) guidelines, a retrospective manual chart review was completed in a large rural healthcare system that utilizes two institution-approved pharmacogenetic vendors. One hundred patients were evaluated: 50 who completed testing through Company A and 50 who completed testing through Company B. Genes of interest for genotype-to-phenotype translation included CYP2B6, CYP2C19, and CYP2D6. Comparison of medication recommendations for drug-gene pairs sertraline (CYP2B6 and/or CYP2C19), escitalopram (CYP2C19), and paroxetine (CYP2D6) were compared with recommendations from CPIC, with consideration of the CPIC Serotonin Reuptake Inhibitor Antidepressants (SSRI) guideline 2023 update. This was accomplished via a novel binning process to enable comparison of company-provided binned medication recommendations with CPIC guideline recommendations. Briefly, the binning system included three categorizations based upon the relevant CPIC guideline recommendations–no action needed (green), recommend monitoring (yellow) and therapeutic intervention or alternative recommended (red). Results: There were 32/250 (12.8%) genotype-to-phenotype translation discrepancies from CPIC guidelines, all from Company A. Of 266 evaluated binned medication recommendations, there were 114 (42.9%) discrepancies between the pharmacogenetic testing companies (Company A: 93 discrepancies, Company B: 21 discrepancies) and CPIC’s guideline based upon comparison with the novel binning system. Discussion: Significant differences were observed between testing companies’ interpretations and recommendations, which is concerning as these discrepancies could lead to providers making medication decisions that are not supported by CPIC’s clinical practice guidelines. This may result in suboptimal outcomes for patients, leading to patient and provider dissatisfaction and erosion of trust with pharmacogenetic testing. A proposed resolution for the discrepancies in company-to-company interpretation is adherence to the CPIC guidelines and transparency in interpretation practices.
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Greden, J. F., Parikh, S. V., Rothschild, A. J., Thase, M. E., Dunlop, B. W., DeBattista, C., Conway, C. R., Forester, B. P., Mondimore, F. M., Shelton, R. C., et al. (2019) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2019.01.003 · Cited by 347
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Research works printed but not linked: 20
- Bank, 2018, Comparison of the guidelines of the clinical pharmacogenetics implementation Consortium and the Dutch pharmacogenetics working group, Clin. Pharmacol. Ther., 103, 599, 10.1002/cpt.762 · DOI
- Blazy, 2022, Variability between clinical pharmacogenetics implementation Consortium (CPIC®) guidelines and a commercial pharmacogenetics laboratory in genotype to phenotype interpretations for patients utilizing psychotropics, Front. Pharmacol., 13, 939313, 10.3389/fphar.2022.939313 · DOI
- Bousman, 2018, Genotype, phenotype, and medication recommendation agreement among commercial pharmacogenetic-based decision support tools, pharmacogenomics J., 18, 613, 10.1038/s41397-018-0027-3 · DOI
- Bousman, 2020, Black box pharmacogenetic decision-support tools in psychiatry, Braz J. Psychiatry, 42, 113, 10.1590/1516-4446-2019-0724 · DOI
- Bousman, 2023, Clinical pharmacogenetics implementation Consortium (CPIC) guideline for CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes and Serotonin Reuptake inhibitor Antidepressants, Clin. Pharmacol. Ther., 114, 51, 10.1002/cpt.2903 · DOI · Paper page
- Bousman, 2019, Navigating the labyrinth of pharmacogenetic testing: a guide to test selection, Clin. Pharmacol. Ther., 106, 309, 10.1002/cpt.1432 · DOI
- Caudle, 2014, Incorporation of pharmacogenomics into routine clinical practice: the Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline development process, Curr. drug Metab., 15, 209, 10.2174/1389200215666140130124910 · DOI
- Dunlop, 2020, Beyond the bins: interpreting and discussing pharmacogenomic reports with psychiatric patients, Braz J. Psychiatry, 42, 111, 10.1590/1516-4446-2019-0697 · DOI
- Gaedigk, 2020, PharmVar and the landscape of pharmacogenetic resources, Clin. Pharmacol. Ther., 107, 43, 10.1002/cpt.1654 · DOI
- Hicks, 2015, Clinical pharmacogenetics implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and dosing of selective Serotonin Reuptake inhibitors, Clin. Pharmacol. Ther., 98, 127, 10.1002/cpt.147 · DOI
- Luvsantseren, 2020, Variant interpretation in current pharmacogenetic testing, J. personalized Med., 10, 204, 10.3390/jpm10040204 · DOI
- Oslin, 2022, Effect of pharmacogenomic testing for drug-gene interactions on medication selection and remission of symptoms in major depressive disorder: the PRIME care randomized clinical trial, JAMA, 328, 151, 10.1001/jama.2022.9805 · DOI
- Pratt, 2018, Recommendations for clinical CYP2C19 genotyping allele selection: a report of the association for molecular Pathology, J. Mol. diagnostics JMD, 20, 269, 10.1016/j.jmoldx.2018.01.011 · DOI
- Pritchard, 2022, Comparison of FDA table of pharmacogenetic associations and clinical pharmacogenetics implementation Consortium guidelines, Am. J. health-system Pharm. AJHP official J. Am. Soc. Health-System Pharm., 79, 993, 10.1093/ajhp/zxac064 · DOI
- Relling, 2011, CPIC: clinical pharmacogenetics implementation Consortium of the pharmacogenomics research network, Clin. Pharmacol. Ther., 89, 464, 10.1038/clpt.2010.279 · DOI
- Shugg, 2020, Prevalence and types of inconsistencies in clinical pharmacogenetic recommendations among major U.S. sources, NPJ genomic Med., 5, 48, 10.1038/s41525-020-00156-7 · DOI
- Vande Voort, 2022, A randomized controlled trial of combinatorial pharmacogenetics testing in adolescent depression, J. Am. Acad. Child Adolesc. Psychiatry, 61, 46, 10.1016/j.jaac.2021.03.011 · DOI
- Vo, 2017, Pharmacogenomics implementation: considerations for selecting a reference laboratory, Pharmacotherapy, 37, 1014, 10.1002/phar.1985 · DOI
- Whirl-Carrillo, 2021, An evidence-based framework for evaluating pharmacogenomics knowledge for personalized medicine, Clin. Pharmacol. Ther., 110, 563, 10.1002/cpt.2350 · DOI · Paper page
- Zeier, 2018, Clinical implementation of pharmacogenetic decision support tools for antidepressant drug prescribing, Am. J. psychiatry, 175, 873, 10.1176/appi.ajp.2018.17111282 · DOI
Metadata
- Authors
- Nguyen, T. T., Leary, E. J. W., Lee, J. T., Shukla, S. K., & Griesbach, S. A.
- Affiliations
- Marshfield Clinic (US)
- Marshfield Clinic Research Foundation (US)
- Corresponding author
- Griesbach, Sara A.
- Venue
- Frontiers in Pharmacology
- Publisher
- Frontiers Media SA
- Published
- 2024-11-25
- Volume
- 15
- Pages
- 1500235-1500235
- ISSN
- 1663-9812 (ISSN-L)
- PMC
- PMC11626124
- OpenAlex
- W4404702459
- Cited by
- 7
- References
- 1
- Citations by year
- 2026: 3 · 2025: 4
- FWCI
- 1.69
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Pharmacology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Marshfield Clinic Research Institute
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Pharmacology (medical) › Drug-Induced Adverse Reactions
- Keywords
- pharmacogenetic testing, antidepressants, CYP2B6, CYP2C19, CYP2D6, sertraline, escitalopram, paroxetine, selective serotonin reuptake inhibitors, drug recommendation, guideline adherence, rural health care
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