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image of Clinical Application of Pharmacogenomics in the Administratio of Common Cardiovascular Medications

Abstract

Introduction

Genomic variations among individuals can greatly affect their responses to different medications. Pharmacogenomics is the area of study that aims to understand the relationship between these various genetic variations and subsequent drug responses. Many medications used to optimize cardiovascular health are affected by these genetic variants and these relationships can subsequently impact dosing strategies in patients.

Objective

This study aims to review the current literature on the clinical applications ofpharmacogenomics for commonly used cardiovascular medications such as Warfarin, Clopidogrel, Statins, Beta Blockers, and ACE-I/ARBs.

Methods

Databases like PubMed were accessed to gather background information on pharmacogenomics and to collect data on relationships between genetic variants and subsequent drug response. Information on clinical applications and guidelines was obtained by accessing the CPIC and DPWG databases.

Results

This article describes the most up-to-date data on pharmacogenomics relating to commonly used cardiovascular medications. It also discusses the clinical application of pharmacogenomic data as it pertains to medication selection/dosing by detailing current guidelines published by organizations such as the Clinical Pharmacogenetics Implementation Consortium and the Dutch Pharmacogenetics Working Group.

Conclusion

In conclusion, this paper will help medical providers not only better understand pharmacogenomics but also apply it in their day-to-day practice. Clinical guidelines relating to the application of pharmacogenomic data were discussed both in text and graphical format, allowing providers to confidently select medications and adjust doses for common cardiovascular medications so that patients receive the maximum therapeutic benefit with minimal toxicity.

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2024-12-02
2025-01-19

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References

  1. Green E.D. Guyer M.S. Institute N.H.G.R. Charting a course for genomic medicine from base pairs to bedside. Nature 2011 470 7333 204 213 10.1038/nature09764 21307933
    [Google Scholar]
  2. Magavern E.F. Kaski J.C. Turner R.M. Drexel H. Janmohamed A. Scourfield A. Burrage D. Floyd C.N. Adeyeye E. Tamargo J. Lewis B.S. Kjeldsen K.P. Niessner A. Wassmann S. Sulzgruber P. Borry P. Agewall S. Semb A.G. Savarese G. Pirmohamed M. Caulfield M.J. The role of pharmacogenomics in contemporary cardiovascular therapy: A position statement from the European society of cardiology working group on cardiovascular pharmacotherapy. Eur. Heart J. Cardiovasc. Pharmacother. 2022 8 1 85 99 10.1093/ehjcvp/pvab018 33638977
    [Google Scholar]
  3. García-González X. Salvador-Martín S. Pharmacogenetics to avoid adverse reactions in cardiology: Ready for implementation? J. Pers. Med. 2021 11 11 1180 10.3390/jpm11111180 34834533
    [Google Scholar]
  4. Katara P. Yadav A. Pharmacogenes (PGx-genes): Current understanding and future directions. Gene 2019 718 144050 10.1016/j.gene.2019.144050 31425740
    [Google Scholar]
  5. Annalora A.J. Marcus C.B. Iversen P.L. Alternative splicing in the cytochrome P450 superfamily expands protein diversity to augment gene function and redirect human drug metabolism. Drug Metab. Dispos. 2017 45 4 375 389 10.1124/dmd.116.073254 28188297
    [Google Scholar]
  6. Gaedigk A. Sangkuhl K. Whirl-Carrillo M. Klein T. Leeder J.S. Prediction of CYP2D6 phenotype from genotype across world populations. Genet. Med. 2017 19 1 69 76 10.1038/gim.2016.80 27388693
    [Google Scholar]
  7. Waring R.H. Cytochrome P450: Genotype to phenotype. Xenobiotica 2020 50 1 9 18 10.1080/00498254.2019.1648911 31411087
    [Google Scholar]
  8. Tidbury N. Preston J. Lip G.Y.H. Lessons learned from the influence of CYP2C9 genotype on warfarin dosing. Expert Opin. Drug Metab. Toxicol. 2023 19 4 185 188 10.1080/17425255.2023.2220961 37254883
    [Google Scholar]
  9. Johnson J.A. Caudle K.E. Gong L. Whirl-Carrillo M. Stein C.M. Scott S.A. Lee M.T. Gage B.F. Kimmel S.E. Perera M.A. Anderson J.L. Pirmohamed M. Klein T.E. Limdi N.A. Cavallari L.H. Wadelius M. Clinical pharmacogenetics implementation Consortium (CPIC) guideline for pharmacogenetics‐guided Warfarin dosing: 2017 update. Clin. Pharmacol. Ther. 2017 102 3 397 404 10.1002/cpt.668 28198005
    [Google Scholar]
  10. Magavern E. F. Jacobs B. Warren H. Finocchiaro G. Finer S. van Heel D. A. Smedley D. Caulfield M. J. Team G. H. R. CYP2C19 genotype prevalence and association with recurrent Myocardial infarction in British-South Asians treated with Clopidogrel. JACC Adv. 2023 2 7 10.1016/j.jacadv.2023.100573
    [Google Scholar]
  11. Pereira N.L. Farkouh M.E. So D. Lennon R. Geller N. Mathew V. Bell M. Bae J.H. Jeong M.H. Chavez I. Gordon P. Abbott J.D. Cagin C. Baudhuin L. Fu Y.P. Goodman S.G. Hasan A. Iturriaga E. Lerman A. Sidhu M. Tanguay J.F. Wang L. Weinshilboum R. Welsh R. Rosenberg Y. Bailey K. Rihal C. Effect of genotype-guided oral P2Y12 Inhibitor Selection vs Conventional Clopidogrel Therapy on Ischemic Outcomes After Percutaneous Coronary Intervention. JAMA 2020 324 8 761 771 10.1001/jama.2020.12443 32840598
    [Google Scholar]
  12. Lee C.R. Luzum J.A. Sangkuhl K. Gammal R.S. Sabatine M.S. Stein C.M. Kisor D.F. Limdi N.A. Lee Y.M. Scott S.A. Hulot J.S. Roden D.M. Gaedigk A. Caudle K.E. Klein T.E. Johnson J.A. Shuldiner A.R. Clinical pharmacogenetics implementation Consortium guideline for CYP2C19 genotype and Clopidogrel therapy: 2022 update. Clin. Pharmacol. Ther. 2022 112 5 959 967 10.1002/cpt.2526 35034351
    [Google Scholar]
  13. Dean L. Kane M. Clopidogrel therapy and CYP2C19 genotype 2022 Available from: https://www.ncbi.nlm.nih.gov/books/NBK84114/
  14. Martin J. Williams A.K. Klein M.D. Sriramoju V.B. Madan S. Rossi J.S. Clarke M. Cicci J.D. Cavallari L.H. Weck K.E. Stouffer G.A. Lee C.R. Frequency and clinical outcomes of CYP2C19 genotype-guided escalation and de-escalation of antiplatelet therapy in a real-world clinical setting. Genet. Med. 2020 22 1 160 169 10.1038/s41436‑019‑0611‑1 31316169
    [Google Scholar]
  15. Link E. Parish S. Armitage J. Bowman L. Heath S. Matsuda F. Gut I. Lathrop M. Collins R. Group S.C. SLCO1B1 variants and statin-induced myopathy--A genomewide study. N. Engl. J. Med. 2008 359 8 789 799 10.1056/NEJMoa0801936 18650507
    [Google Scholar]
  16. Cooper-DeHoff R.M. Niemi M. Ramsey L.B. Luzum J.A. Tarkiainen E.K. Straka R.J. Gong L. Tuteja S. Wilke R.A. Wadelius M. Larson E.A. Roden D.M. Klein T.E. Yee S.W. Krauss R.M. Turner R.M. Palaniappan L. Gaedigk A. Giacomini K.M. Caudle K.E. Voora D. The clinical pharmacogenetics implementation Consortium guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and Statin‐associated Musculoskeletal symptoms. Clin. Pharmacol. Ther. 2022 111 5 1007 1021 10.1002/cpt.2557 35152405
    [Google Scholar]
  17. Zisaki A. Miskovic L. Hatzimanikatis V. Antihypertensive drugs metabolism: An update to pharmacokinetic profiles and computational approaches. Curr. Pharm. Des. 2014 21 6 806 822 10.2174/1381612820666141024151119 25341854
    [Google Scholar]
  18. Collett S. Massmann A. Petry N.J. Van Heukelom J. Schultz A. Hellwig T. Baye J.F. Metoprolol and. J. Pers. Med. 2023 13 3 416 10.3390/jpm13030416 36983598
    [Google Scholar]
  19. Dean L. Kane M. Metoprolol therapy and CYP2D6 genotype. 2017 Available from: https://pubmed.ncbi.nlm.nih.gov/28520381/
    [Google Scholar]
  20. Annotation of DPWG guideline for metoprolol and CYP2D6 2018 Available from: https://www.pharmgkb.org/guidelineAnnotation/PA166104995
  21. Duarte J.D. Thomas C.D. Lee C.R. Huddart R. Agundez J.A.G. Baye J.F. Gaedigk A. Klein T.E. Lanfear D.E. Monte A.A. Nagy M. Schwab M. Stein C.M. Uppugunduri C.R.S. van Schaik R.H.N. Donnelly R.S. Caudle K.E. Luzum J.A. Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6, ADRB1, ADRB2, ADRA2C, GRK4, and GRK5 genotypes and beta‐blocker therapy. Clin. Pharmacol. Ther. 2024 116 4 939 947 10.1002/cpt.3351 38951961
    [Google Scholar]
  22. Flaten H.K. Monte A.A. The pharmacogenomic and metabolomic predictors of ACE inhibitor and Angiotensin II receptor blocker effectiveness and safety. Cardiovasc. Drugs Ther. 2017 31 4 471 482 10.1007/s10557‑017‑6733‑2 28741243
    [Google Scholar]
  23. Burnier M. Brunner H.R. Angiotensin II receptor antagonists. Lancet 2000 355 9204 637 645 10.1016/S0140‑6736(99)10365‑9 10696996
    [Google Scholar]
  24. Piepho R.W. Overview of the angiotensin-converting-enzyme inhibitors. Am. J. Health Syst. Pharm. 2000 57 Suppl. 1 S3 S7 10.1093/ajhp/57.suppl_1.S3 11030016
    [Google Scholar]
  25. Herman A.G. Differences in structure of angiotensin-converting enzyme inhibitors might predict differences in action. Am. J. Cardiol. 1992 70 10 102 108 10.1016/0002‑9149(92)91366‑C 1329464
    [Google Scholar]
  26. Hoyer J. Schulte K.L. Lenz T. Clinical pharmacokinetics of angiotensin converting enzyme (ACE) inhibitors in renal failure. Clin. Pharmacokinet. 1993 24 3 230 254 10.2165/00003088‑199324030‑00005 8462229
    [Google Scholar]
  27. Flockhart D.A. Tanus-Santos J.E. Implications of cytochrome P450 interactions when prescribing medication for hypertension. Arch. Intern. Med. 2002 162 4 405 412 10.1001/archinte.162.4.405 11863472
    [Google Scholar]
  28. Jurima-Romet M. Huang H.S. Comparative cytotoxicity of angiotensin-converting enzyme inhibitors in cultured rat hepatocytes. Biochem. Pharmacol. 1993 46 12 2163 2170 10.1016/0006‑2952(93)90605‑V 8274149
    [Google Scholar]
  29. Pare G. Kubo M. Byrd J.B. McCarty C.A. Woodard-Grice A. Teo K.K. Anand S.S. Zuvich R.L. Bradford Y. Ross S. Nakamura Y. Ritchie M. Brown N.J. Genetic variants associated with angiotensin-converting enzyme inhibitor-associated angioedema. Pharmacogenet. Genomics 2013 23 9 470 478 10.1097/FPC.0b013e328363c137 23838604
    [Google Scholar]
  30. Mosley J.D. Shaffer C.M. Van Driest S.L. Weeke P.E. Wells Q.S. Karnes J.H. Velez Edwards D.R. Wei W-Q. Teixeira P.L. Bastarache L. Crawford D.C. Li R. Manolio T.A. Bottinger E.P. McCarty C.A. Linneman J.G. Brilliant M.H. Pacheco J.A. Thompson W. Chisholm R.L. Jarvik G.P. Crosslin D.R. Carrell D.S. Baldwin E. Ralston J. Larson E.B. Grafton J. Scrol A. Jouni H. Kullo I.J. Tromp G. Borthwick K.M. Kuivaniemi H. Carey D.J. Ritchie M.D. Bradford Y. Verma S.S. Chute C.G. Veluchamy A. Siddiqui M.K. Palmer C.N.A. Doney A. MahmoudPour S.H. Maitland-van der Zee A.H. Morris A.D. Denny J.C. Roden D.M. A genome-wide association study identifies variants in KCNIP4 associated with ACE inhibitor-induced cough. Pharmacogenomics J. 2016 16 3 231 237 10.1038/tpj.2015.51 26169577
    [Google Scholar]
  31. Mas S. Gassò P. Álvarez S. Ortiz J. Sotoca J.M. Francino A. Carne X. Lafuente A. Pharmacogenetic predictors of angiotensin-converting enzyme inhibitor-induced cough. Pharmacogenet. Genomics 2011 21 9 531 538 10.1097/FPC.0b013e328348c6db 21832968
    [Google Scholar]
  32. Kurland L. Melhus H. Karlsson J. Kahan T. Malmqvist K. Ohman P. Nyström F. Hägg A. Lind L. Aldosterone synthase (CYP11B2) -344 C/T polymorphism is related to antihypertensive response: Results from the swedish irbesartan left ventricular hypertrophy investigation versus atenolol (SILVHIA) trial. Am. J. Hypertens. 2002 15 5 389 393 10.1016/S0895‑7061(02)02256‑2 12022239
    [Google Scholar]
  33. Ortlepp J.R. Hanrath P. Mevissen V. Kiel G. Borggrefe M. Hoffmann R. Variants of the CYP11B2 gene predict response to therapy with candesartan. Eur. J. Pharmacol. 2002 445 1-2 151 152 10.1016/S0014‑2999(02)01766‑1 12065207
    [Google Scholar]
  34. Hallberg P. Karlsson J. Kurland L. Lind L. Kahan T. Malmqvist K. Öhman K.P. Nyström F. Melhus H. The CYP2C9 genotype predicts the blood pressure response to irbesartan: Results from the Swedish Irbesartan Left Ventricular Hypertrophy investigation vs Atenolol (SILVHIA) trial. J. Hypertens. 2002 20 10 2089 2093 10.1097/00004872‑200210000‑00030 12359989
    [Google Scholar]
  35. Roden D.M. McLeod H.L. Relling M.V. Williams M.S. Mensah G.A. Peterson J.F. Van Driest S.L. Pharmacogenomics. Lancet 2019 394 10197 521 532 10.1016/S0140‑6736(19)31276‑0 31395440
    [Google Scholar]
  36. Magavern E.F. Gurdasani D. Ng F.L. Lee S.S.J. Health equality, race and pharmacogenomics. Br. J. Clin. Pharmacol. 2022 88 1 27 33 10.1111/bcp.14983 34251046
    [Google Scholar]
  37. Kimmel S.E. French B. Kasner S.E. Johnson J.A. Anderson J.L. Gage B.F. Rosenberg Y.D. Eby C.S. Madigan R.A. McBane R.B. Abdel-Rahman S.Z. Stevens S.M. Yale S. Mohler E.R. III Fang M.C. Shah V. Horenstein R.B. Limdi N.A. Muldowney J.A.S. III Gujral J. Delafontaine P. Desnick R.J. Ortel T.L. Billett H.H. Pendleton R.C. Geller N.L. Halperin J.L. Goldhaber S.Z. Caldwell M.D. Califf R.M. Ellenberg J.H. A pharmacogenetic versus a clinical algorithm for warfarin dosing. N. Engl. J. Med. 2013 369 24 2283 2293 10.1056/NEJMoa1310669 24251361
    [Google Scholar]
  38. Duarte J.D. Cavallari L.H. Pharmacogenetics to guide cardiovascular drug therapy. Nat. Rev. Cardiol. 2021 18 9 649 665 10.1038/s41569‑021‑00549‑w 33953382
    [Google Scholar]
/content/journals/crcep/10.2174/0127724328323600241120113500
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Clinical Application of Pharmacogenomics in the Administratio of Common Cardiovascular Medications
Bentham Science Publishers ; https://doi.org/10.2174/0127724328323600241120113500
/content/journals/crcep/10.2174/0127724328323600241120113500
/content/journals/crcep/10.2174/0127724328323600241120113500
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  • Article Type:     Review Article
Keywords: drug metabolism ; genetic variants ; Pharmacogenomics ; clinical medicine ; drug response ; cardiovascular medicine

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