Skip to content
2000
Volume 20, Issue 4
  • ISSN: 2772-4328
  • E-ISSN: 2772-4336

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 of pharmacogenomics 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.

Loading

Article metrics loading...

/content/journals/crcep/10.2174/0127724328323600241120113500
2024-12-02
2025-09-02
Loading full text...

Full text loading...

References

  1. GreenE.D. GuyerM.S. InstituteN.H.G.R. Charting a course for genomic medicine from base pairs to bedside.Nature2011470733320421310.1038/nature0976421307933
    [Google Scholar]
  2. MagavernE.F. KaskiJ.C. TurnerR.M. DrexelH. JanmohamedA. ScourfieldA. BurrageD. FloydC.N. AdeyeyeE. TamargoJ. LewisB.S. KjeldsenK.P. NiessnerA. WassmannS. SulzgruberP. BorryP. AgewallS. SembA.G. SavareseG. PirmohamedM. CaulfieldM.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.202281859910.1093/ehjcvp/pvab01833638977
    [Google Scholar]
  3. García-GonzálezX. Salvador-MartínS. Pharmacogenetics to avoid adverse reactions in cardiology: Ready for implementation?J. Pers. Med.20211111118010.3390/jpm1111118034834533
    [Google Scholar]
  4. KataraP. YadavA. Pharmacogenes (PGx-genes): Current understanding and future directions.Gene201971814405010.1016/j.gene.2019.14405031425740
    [Google Scholar]
  5. AnnaloraA.J. MarcusC.B. IversenP.L. Alternative splicing in the cytochrome P450 superfamily expands protein diversity to augment gene function and redirect human drug metabolism.Drug Metab. Dispos.201745437538910.1124/dmd.116.07325428188297
    [Google Scholar]
  6. GaedigkA. SangkuhlK. Whirl-CarrilloM. KleinT. LeederJ.S. Prediction of CYP2D6 phenotype from genotype across world populations.Genet. Med.2017191697610.1038/gim.2016.8027388693
    [Google Scholar]
  7. WaringR.H. Cytochrome P450: Genotype to phenotype.Xenobiotica202050191810.1080/00498254.2019.164891131411087
    [Google Scholar]
  8. TidburyN. PrestonJ. LipG.Y.H. Lessons learned from the influence of CYP2C9 genotype on warfarin dosing.Expert Opin. Drug Metab. Toxicol.202319418518810.1080/17425255.2023.222096137254883
    [Google Scholar]
  9. JohnsonJ.A. CaudleK.E. GongL. Whirl-CarrilloM. SteinC.M. ScottS.A. LeeM.T. GageB.F. KimmelS.E. PereraM.A. AndersonJ.L. PirmohamedM. KleinT.E. LimdiN.A. CavallariL.H. WadeliusM. Clinical pharmacogenetics implementation Consortium (CPIC) guideline for pharmacogenetics-guided Warfarin dosing: 2017 update.Clin. Pharmacol. Ther.2017102339740410.1002/cpt.66828198005
    [Google Scholar]
  10. MagavernE. F. JacobsB. WarrenH. FinocchiaroG. FinerS. van HeelD. A. SmedleyD. CaulfieldM. J. TeamG. H. R. CYP2C19 genotype prevalence and association with recurrent Myocardial infarction in British-South Asians treated with Clopidogrel.JACC Adv.20232710.1016/j.jacadv.2023.100573
    [Google Scholar]
  11. PereiraN.L. FarkouhM.E. SoD. LennonR. GellerN. MathewV. BellM. BaeJ.H. JeongM.H. ChavezI. GordonP. AbbottJ.D. CaginC. BaudhuinL. FuY.P. GoodmanS.G. HasanA. IturriagaE. LermanA. SidhuM. TanguayJ.F. WangL. WeinshilboumR. WelshR. RosenbergY. BaileyK. RihalC. Effect of genotype-guided oral P2Y12 inhibitor selection vs conventional clopidogrel therapy on ischemic outcomes after percutaneous coronary intervention.JAMA2020324876177110.1001/jama.2020.1244332840598
    [Google Scholar]
  12. LeeC.R. LuzumJ.A. SangkuhlK. GammalR.S. SabatineM.S. SteinC.M. KisorD.F. LimdiN.A. LeeY.M. ScottS.A. HulotJ.S. RodenD.M. GaedigkA. CaudleK.E. KleinT.E. JohnsonJ.A. ShuldinerA.R. Clinical pharmacogenetics implementation Consortium guideline for CYP2C19 genotype and Clopidogrel therapy: 2022 update.Clin. Pharmacol. Ther.2022112595996710.1002/cpt.252635034351
    [Google Scholar]
  13. DeanL. KaneM. Clopidogrel therapy and CYP2C19 genotype2022Available from: https://www.ncbi.nlm.nih.gov/books/NBK84114/
  14. MartinJ. WilliamsA.K. KleinM.D. SriramojuV.B. MadanS. RossiJ.S. ClarkeM. CicciJ.D. CavallariL.H. WeckK.E. StoufferG.A. LeeC.R. Frequency and clinical outcomes of CYP2C19 genotype-guided escalation and de-escalation of antiplatelet therapy in a real-world clinical setting.Genet. Med.202022116016910.1038/s41436‑019‑0611‑131316169
    [Google Scholar]
  15. LinkE. ParishS. ArmitageJ. BowmanL. HeathS. MatsudaF. GutI. LathropM. CollinsR. GroupS.C. SLCO1B1 variants and statin-induced myopathy--A genomewide study.N. Engl. J. Med.2008359878979910.1056/NEJMoa080193618650507
    [Google Scholar]
  16. Cooper-DeHoffR.M. NiemiM. RamseyL.B. LuzumJ.A. TarkiainenE.K. StrakaR.J. GongL. TutejaS. WilkeR.A. WadeliusM. LarsonE.A. RodenD.M. KleinT.E. YeeS.W. KraussR.M. TurnerR.M. PalaniappanL. GaedigkA. GiacominiK.M. CaudleK.E. VooraD. The clinical pharmacogenetics implementation Consortium guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and Statin-associated Musculoskeletal symptoms.Clin. Pharmacol. Ther.202211151007102110.1002/cpt.255735152405
    [Google Scholar]
  17. ZisakiA. MiskovicL. HatzimanikatisV. Antihypertensive drugs metabolism: An update to pharmacokinetic profiles and computational approaches.Curr. Pharm. Des.201421680682210.2174/138161282066614102415111925341854
    [Google Scholar]
  18. CollettS. MassmannA. PetryN.J. Van HeukelomJ. SchultzA. HellwigT. BayeJ.F. Metoprolol and.J. Pers. Med.202313341610.3390/jpm1303041636983598
    [Google Scholar]
  19. DeanL. KaneM. Metoprolol therapy and CYP2D6 genotype.2017Available from: https://pubmed.ncbi.nlm.nih.gov/28520381/
    [Google Scholar]
  20. Annotation of DPWG guideline for metoprolol and CYP2D62018Available from: https://www.pharmgkb.org/guidelineAnnotation/PA166104995
  21. DuarteJ.D. ThomasC.D. LeeC.R. HuddartR. AgundezJ.A.G. BayeJ.F. GaedigkA. KleinT.E. LanfearD.E. MonteA.A. NagyM. SchwabM. SteinC.M. UppugunduriC.R.S. van SchaikR.H.N. DonnellyR.S. CaudleK.E. LuzumJ.A. Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6, ADRB1, ADRB2, ADRA2C, GRK4, and GRK5 genotypes and beta-blocker therapy.Clin. Pharmacol. Ther.2024116493994710.1002/cpt.335138951961
    [Google Scholar]
  22. FlatenH.K. MonteA.A. The pharmacogenomic and metabolomic predictors of ACE inhibitor and Angiotensin II receptor blocker effectiveness and safety.Cardiovasc. Drugs Ther.201731447148210.1007/s10557‑017‑6733‑228741243
    [Google Scholar]
  23. BurnierM. BrunnerH.R. Angiotensin II receptor antagonists.Lancet2000355920463764510.1016/S0140‑6736(99)10365‑910696996
    [Google Scholar]
  24. PiephoR.W. Overview of the angiotensin-converting-enzyme inhibitors.Am. J. Health Syst. Pharm.200057Suppl. 1S3S710.1093/ajhp/57.suppl_1.S311030016
    [Google Scholar]
  25. HermanA.G. Differences in structure of angiotensin-converting enzyme inhibitors might predict differences in action.Am. J. Cardiol.1992701010210810.1016/0002‑9149(92)91366‑C1329464
    [Google Scholar]
  26. HoyerJ. SchulteK.L. LenzT. Clinical pharmacokinetics of angiotensin converting enzyme (ACE) inhibitors in renal failure.Clin. Pharmacokinet.199324323025410.2165/00003088‑199324030‑000058462229
    [Google Scholar]
  27. FlockhartD.A. Tanus-SantosJ.E. Implications of cytochrome P450 interactions when prescribing medication for hypertension.Arch. Intern. Med.2002162440541210.1001/archinte.162.4.40511863472
    [Google Scholar]
  28. Jurima-RometM. HuangH.S. Comparative cytotoxicity of angiotensin-converting enzyme inhibitors in cultured rat hepatocytes.Biochem. Pharmacol.199346122163217010.1016/0006‑2952(93)90605‑V8274149
    [Google Scholar]
  29. PareG. KuboM. ByrdJ.B. McCartyC.A. Woodard-GriceA. TeoK.K. AnandS.S. ZuvichR.L. BradfordY. RossS. NakamuraY. RitchieM. BrownN.J. Genetic variants associated with angiotensin-converting enzyme inhibitor-associated angioedema.Pharmacogenet. Genomics201323947047810.1097/FPC.0b013e328363c13723838604
    [Google Scholar]
  30. MosleyJ.D. ShafferC.M. Van DriestS.L. WeekeP.E. WellsQ.S. KarnesJ.H. Velez EdwardsD.R. WeiW-Q. TeixeiraP.L. BastaracheL. CrawfordD.C. LiR. ManolioT.A. BottingerE.P. McCartyC.A. LinnemanJ.G. BrilliantM.H. PachecoJ.A. ThompsonW. ChisholmR.L. JarvikG.P. CrosslinD.R. CarrellD.S. BaldwinE. RalstonJ. LarsonE.B. GraftonJ. ScrolA. JouniH. KulloI.J. TrompG. BorthwickK.M. KuivaniemiH. CareyD.J. RitchieM.D. BradfordY. VermaS.S. ChuteC.G. VeluchamyA. SiddiquiM.K. PalmerC.N.A. DoneyA. MahmoudPourS.H. Maitland-van der ZeeA.H. MorrisA.D. DennyJ.C. RodenD.M. A genome-wide association study identifies variants in KCNIP4 associated with ACE inhibitor-induced cough.Pharmacogenomics J.201616323123710.1038/tpj.2015.5126169577
    [Google Scholar]
  31. MasS. GassòP. ÁlvarezS. OrtizJ. SotocaJ.M. FrancinoA. CarneX. LafuenteA. Pharmacogenetic predictors of angiotensin-converting enzyme inhibitor-induced cough.Pharmacogenet. Genomics201121953153810.1097/FPC.0b013e328348c6db21832968
    [Google Scholar]
  32. KurlandL. MelhusH. KarlssonJ. KahanT. MalmqvistK. OhmanP. NyströmF. HäggA. LindL. 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.200215538939310.1016/S0895‑7061(02)02256‑212022239
    [Google Scholar]
  33. OrtleppJ.R. HanrathP. MevissenV. KielG. BorggrefeM. HoffmannR. Variants of the CYP11B2 gene predict response to therapy with candesartan.Eur. J. Pharmacol.20024451-215115210.1016/S0014‑2999(02)01766‑112065207
    [Google Scholar]
  34. HallbergP. KarlssonJ. KurlandL. LindL. KahanT. MalmqvistK. ÖhmanK.P. NyströmF. MelhusH. 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.200220102089209310.1097/00004872‑200210000‑0003012359989
    [Google Scholar]
  35. RodenD.M. McLeodH.L. RellingM.V. WilliamsM.S. MensahG.A. PetersonJ.F. Van DriestS.L. Pharmacogenomics.Lancet20193941019752153210.1016/S0140‑6736(19)31276‑031395440
    [Google Scholar]
  36. MagavernE.F. GurdasaniD. NgF.L. LeeS.S.J. Health equality, race and pharmacogenomics.Br. J. Clin. Pharmacol.2022881273310.1111/bcp.1498334251046
    [Google Scholar]
  37. KimmelS.E. FrenchB. KasnerS.E. JohnsonJ.A. AndersonJ.L. GageB.F. RosenbergY.D. EbyC.S. MadiganR.A. McBaneR.B. Abdel-RahmanS.Z. StevensS.M. YaleS. MohlerE.R.III FangM.C. ShahV. HorensteinR.B. LimdiN.A. MuldowneyJ.A.S.III GujralJ. DelafontaineP. DesnickR.J. OrtelT.L. BillettH.H. PendletonR.C. GellerN.L. HalperinJ.L. GoldhaberS.Z. CaldwellM.D. CaliffR.M. EllenbergJ.H. A pharmacogenetic versus a clinical algorithm for warfarin dosing.N. Engl. J. Med.2013369242283229310.1056/NEJMoa131066924251361
    [Google Scholar]
  38. DuarteJ.D. CavallariL.H. Pharmacogenetics to guide cardiovascular drug therapy.Nat. Rev. Cardiol.202118964966510.1038/s41569‑021‑00549‑w33953382
    [Google Scholar]
/content/journals/crcep/10.2174/0127724328323600241120113500
Loading
/content/journals/crcep/10.2174/0127724328323600241120113500
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test