Pharmacogenetic markers affecting response to class I and class III anti-arrhythmic drugs in atrial fibrillation treatment
Article Sidebar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Main Article Content
Abstract
The efficacy and safety of Class I and Class III anti-arrhythmic drugs (AADs) in the treatment of Atrial Fibrillation (AF) can vary depending on patient genetics. This prospective cohort study evaluated the association between specific polymorphisms in the CYP2D6, KCNH2, and SCN5A genes and AAD response in 112 AF patients. The CYP2D6 poor metabolizer genotype was found to significantly increase the risk of serious side effects associated with Amiodarone (OR: 4.51, 95% CI: 1.90–10.74). The SCN5A rs7626962 variant was associated with an increased risk of AF recurrence in patients treated with Class I AADs (HR: 2.15, 95% CI: 1.55–2.98). The results suggest that pharmacogenetic testing could guide personalized treatment selection in AF.
Article Details
References
Hindricks, G., et al. (2020). 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association of Cardio-Thoracic Surgery (EACTS). European Heart Journal, 42(5), 373-498. DOI: https://doi.org/10.1093/eurheartj/ehaa798
Nattel, S., & Dobrev, D. (2017). The multidimensional roles of class I and class III antiarrhythmic drugs in atrial fibrillation. Cardiovascular Research, 113(8), 868–876.
Lafuente-López-Herrera, M., & Márquez-Garrido, F. (2018). Efficacy and safety of antiarrhythmic drugs for maintenance of sinus rhythm in atrial fibrillation: a systematic review and meta-analysis. Revista Española de Cardiología (English Edition), 71(12), 1046-1055.
Darbar, D., et al. (2008). Pharmacogenetics of antiarrhythmic drug efficacy and toxicity. Pharmacology & Therapeutics, 119(3), 304–314.
Vandenbroucke, J. P., et al. (2014). Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. International Journal of Surgery, 12(12), 1540–1544. DOI: https://doi.org/10.1016/j.ijsu.2014.07.013
January, C. T., et al. (2019). 2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation. Circulation, 140(13), e125–e151.
Skanes, A. C., et al. (2013). Safety and efficacy of permanent monitoring for the detection of atrial fibrillation: a systematic review and meta-analysis. Heart Rhythm, 10(7), 1083–1091.
Mani, S. (2018). DNA Extraction and Quality Control Procedures for Pharmacogenomic Studies. Methods in Molecular Biology, 1785, 3-12.
Ritchie, M. D., et al. (2020). Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 Genotype and Antiarrhythmic Therapy. Clinical Pharmacology & Therapeutics, 108(4), 693–702.
Livak, K. J. (1999). Allelic discrimination using fluorogenic probes and the 5′ nuclease assay. Genetic Analysis: Biomolecular Engineering, 14(5-6), 143–149. DOI: https://doi.org/10.1016/S1050-3862(98)00019-9
Harrell Jr., F. E. (2015). Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. Springer. DOI: https://doi.org/10.1007/978-3-319-19425-7
Zanger, U. M., Raimundo, S., & Eichelbaum, M. (2003). CYP2D6: "poor metabolizers" - bringing them into the limelight. Pharmacogenomics, 4(1), 17–28.
Darbar, D., et al. (2020). Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for SCN5A and SCN10A Genotypes and Use of Sodium Channel Blockers in Cardiovascular Disorders. Clinical Pharmacology & Therapeutics, 107(4), 793–804.
Kopecky, S. L., et al. (2022). Arrhythmia-Related Adverse Drug Events and Pharmacogenetic Risk. Circulation: Genomic and Precision Medicine, 15(2), e003460.
Tester, D. J., et al. (2006). KCNH2-K897T is a genetic modifier of latent congenital long-QT syndrome. Circulation, 112(9), 1274–1280. DOI: https://doi.org/10.1161/CIRCULATIONAHA.105.549071
[1] Murray, K. T. (2018). Pharmacogenetics of antiarrhythmic drugs. Heart Rhythm, 15(1), 133-138.
Sanguinetti, M. C., & Tristani-Firouzi, G. (2006). hERG potassium channels and cardiac arrhythmia. Nature, 440(7083), 463-469. DOI: https://doi.org/10.1038/nature04710
Hamby, L. E., et al. (2020). Population pharmacokinetics of amiodarone and its active metabolite, N-desethylamiodarone, in patients with atrial fibrillation: the role of CYP2C8 and CYP3A4 genotypes. Clinical Pharmacology & Therapeutics, 107(1), 185-194.
Pirmohamed, M. (2018). The future of pharmacogenomics: is the time right for clinical implementation? British Journal of Clinical Pharmacology, 84(8), 1625-1632.
January, C. T., et al. (2019). 2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation. Circulation, 140(13), e125–e151. DOI: https://doi.org/10.1161/CIR.0000000000000665
Relling, M. V., & Evans, W. E. (2015). Pharmacogenomics in the clinic. Nature, 526(7573), 343–350. DOI: https://doi.org/10.1038/nature15817
Manolio, T. A., et al. (2017). Genomewide association studies and the identification of genetic risk for disease. The New England Journal of Medicine, 377(1), 17–27.
Johnson, J. A. (2017). Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines: 2017 Update. Clinical Pharmacology & Therapeutics, 102(3), 398–400. DOI: https://doi.org/10.1002/cpt.668