Cardiovascular diseases (CVDs) remain a leading cause of mortality worldwide, and in the US one out of three men and women will die from CVD. These statistics are prompting researchers and healthcare professionals to continually explore innovative approaches to not only prevent the development of CVD but also to enhance treatment outcomes. One such groundbreaking field is pharmacogenomics, which focuses on understanding how an individual's genetic makeup influences their response to drugs. In recent years, pharmacogenomics has emerged as a promising avenue for tailoring cardiovascular disease treatments, optimizing efficacy, minimizing adverse effects, and personalizing medicine for better patient outcomes.
Pharmacogenomics combines pharmacology (the study of drugs) and genomics (the study of genes and their functions) to tailor drug therapies to an individual's unique genetic profile. This approach recognizes that genetic variations in specific genes can significantly impact drug absorption, metabolism, efficacy, and safety. By analyzing an individual's genetic information, healthcare providers can identify specific genetic markers that influence drug responses, allowing for personalized treatment plans.
In the field of cardiovascular medicine, there are several widely prescribed drugs that now carry PGx testing recommendations on their drug labels. This was only made possible through extensive studies that correlated drug performance with PGx profiles, resulting in evidence-based guidelines for prescription best-practices.
In this blog we review the various classes of drugs used to treat CVD and how PGx is supporting their optimal use and enhancing patient care in the field of cardiac medicine.
Metabolism of Antiplatelet Agents
Antiplatelet agents play a crucial role in preventing blood clots and reducing the risk of heart attacks and strokes. However, the effectiveness of drugs such as clopidogrel is influenced by genetic variations in the CYP2C19 gene (Empey et. al. 2018). The FDA-approval label for clopidogrel was updated in 2016 to include PGx testing to identify individuals with reduced CYP2C19 enzyme activity, who will not efficiently convert the pro-drug to its active form. PGx profiling of CYP2C19 enables physicians to classify patients as poor-, intermediate-, normal-, or ultra-rapid metabolizers of clopidogrel, and adjust drug dosage or select alternative medications such as ticagrelor or prasugrel to ensure optimal therapeutic effects. PGx testing for clopidogrel also helps identify individuals at a higher risk of adverse cardiovascular events due to suboptimal responses. By tailoring treatment based on PGx information, healthcare providers aim to minimize the risk of recurrent cardiovascular events, including stent thrombosis in individuals undergoing percutaneous coronary intervention (PCI) (Martin et. al. 2020).
For many years Warfarin was the only prescribed anticoagulant, and even today, this is the most widely used anticoagulant in the world. However, it is not without its issues, and requires careful dosage adjustments due to its narrow therapeutic range and has many well characterized drug interactions.
Genetic variations in the VKORC1 and CYP2C9 genes can affect an individual’s sensitivity to warfarin, leading to a risk of bleeding or insufficient anticoagulation (D’Andrea, et al. 2005; Rieder, et al. 2005). The VKORC1 gene encodes the enzyme vitamin K epoxide reductase, a target of warfarin, while CYP2C9 is responsible for the metabolism of warfarin. Certain genetic variants, such as VKORC1 -1639G>A and various CYP2C9 variants, are associated with either increased or decreased sensitivity to warfarin. PGx testing enables healthcare providers to personalize warfarin dosages, minimizing adverse events and ensuring therapeutic efficacy.
As this area of research matures, some healthcare providers are using computerized dosing algorithms that incorporate PGx information to calculate individualized warfarin doses. These algorithms consider genetic factors along with clinical variables such as age, weight, and baseline International Normalized Ratio (INR) values. This approach enables healthcare providers to achieve and maintain the target INR and reduce the time it takes to establish stable and therapeutic anticoagulation levels (Finkelman, et al. 2011)
Statins and Genetic Predisposition
Statins are widely prescribed for managing cholesterol levels; in fact, in the US 50% or men and 40% of women aged 65 to 74 take some form of statin. The eligibility criteria for their use includes patients diagnosed with CVD, diabetes or with low-density lipoprotein (LDL) cholesterol levels of ≥ 100mg/dL (Pencina et. al. 2014). However, these drugs exhibit variable responses among individuals, and reports indicate that most healthcare providers don’t understand the guidelines for dosing statin drugs to high-risk patients. Genetic factors, such as variations in the SLCO1B1 gene, influence statin metabolism and can impact drug efficacy and tolerability (Ramsey et. al. 2014). The SLCO1B1 gene encodes a transporter protein involved in the uptake of statins into liver cells. Variations in this gene can affect statin concentrations in the liver and influence drug response. Specific SLCO1B1 variants are also associated with increased risk of side-effects including statin-induced myopathy. Patients who experience muscle cramping while taking the fat-soluble statin Atorvastatin (Lipitor) have been shown to do better when prescribed water-soluble statins such as Pravastatin or Fluvastatin. Pharmacogenomic analysis allows healthcare providers to identify patients at higher risk of statin-related adverse effects and choose alternative medications or adjust dosages accordingly.
Aspirin (acetylsalicylic acid), a widely used antiplatelet medication, is commonly prescribed to reduce the risk of cardiovascular events, such as heart attacks and strokes. The drug works by inhibiting the cyclooxygenase (COX) channel and acetylates a serine residue of platelet prostaglandin synthase. The response to aspirin can vary among individuals, and genetic factors can influence how the body processes and responds to the drug (Halushka et. al. 2003). About 20% of the population demonstrate some resistance to Aspirin, whereby Aspirin at therapeutic doses fails to inhibit platelet reactivity (Hankey & Eikelboom, 2006). However, the underlying cause of this resistance is not fully understood. In addition, Aspirin use is associated with potential side effects, including gastrointestinal bleeding. Genetic variations can influence an individual's susceptibility to these adverse effects.
One of the genes of interest for PGx testing is PTGS1, which encodes the enzyme cyclooxygenase-1 (COX-1), the target of aspirin. Variations in this gene can impact how aspirin inhibits COX-1, potentially influencing the drug's antiplatelet effects. Some individuals may metabolize aspirin more quickly or slowly due to genetic factors including their PTGS1 allele(s), that affect the duration and intensity of the drug's antiplatelet effects. Personalized dosing aims to ensure that individuals receive an optimal dose that maximizes the antiplatelet benefits while minimizing the risk of adverse effects.
Benefits of Pharmacogenomics in Cardiovascular Disease Treatment
This personalized approach facilitates better control of cardiovascular risk factors, such as blood pressure and cholesterol levels, ultimately reducing the incidence of cardiovascular events. PGx testing also helps identify individuals with a higher risk of experiencing adverse drug reactions and their predisposition to side effects. Using these genetic profiles, healthcare providers can adjust drug dosages, choose alternative medications, or employ preventive measures to minimize the occurrence of adverse events, improving patient safety and their overall adherence to treatment.
Traditional approaches to drug prescribing often involve a trial-and-error process to find the most suitable medication and dosage for an individual. PGx testing reduces this uncertainty by providing clinically relevant insights into how a patient is likely to respond to specific medications. This not only accelerates the treatment decision-making process but also minimizes the potential for ineffective treatments and associated risks.
As this era of personalized medicine is becoming a reality, healthcare providers are finally able to tailor treatment plans based on an individual's genetic profile, and take into account factors such as drug metabolism, enzyme activity, and receptor sensitivity. This approach benefits all stakeholders, from the patients themselves, the busy healthcare providers who can only spend a limited time with each patient, through to the insurance companies covering the costs of care.
Despite the promising potential of pharmacogenomics, widespread implementation in routine clinical practice faces challenges. Integration of PGx testing into healthcare systems requires infrastructure development, education for healthcare professionals, and addressing ethical and privacy concerns associated with genetic testing. Efforts are underway to reduce testing costs, increase insurance coverage, and establish guidelines for reimbursing pharmacogenomic testing to make it more accessible to a broader population, and eventually incorporate PGx testing into the standard of care. To this end, initiatives are ongoing to develop user-friendly platforms and decision support tools that assist healthcare providers in translating genetic information into actionable treatment recommendations.
The clinical exploration of pharmacogenomic variations continues to enhance our ability to predict treatment outcomes accurately and expand the scope of personalized medicine in cardiovascular disease management. Organizations including CPIC *and PharmGKB** are supporting the translation of data from clinical studies into actionable guidelines across a range of medical fields. The Incite Health team can provide expert support for the development of custom PGx panels that incorporate the latest CPIC guidelines to deliver fit-for-purpose patient profiling and implement data interpretation for optimal clinical utility.
As we continue to unlock the secrets encoded in our genes, the promise of personalized cardiovascular medicine fueled by pharmacogenomics holds the key to better outcomes and improved quality of life for individuals at risk of or living with cardiovascular diseases.
- Empey PE, Stevenson JM, Tuteja S, Weitzel KW, Angiolillo DJ, Beitelshees AL, Coons JC, Duarte JD, Franchi F, Jeng LJB, Johnson JA, Kreutz RP, Limdi NA, Maloney KA, Owusu Obeng A, Peterson JF, Petry N, Pratt VM, Rollini F, Scott SA, Skaar TC, Vesely MR, Stouffer GA, Wilke RA, Cavallari LH, Lee CR, Network I (2018) Multisite Investigation of Strategies for the Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy. Clin Pharmacol Ther 104: 664–674 doi: 10.1002/cpt.1006.
- Martin J, Williams AK, Klein MD, Sriramoju VB, Madan S, Rossi JS, Clarke M, Cicci JD, Cavallari LH, Weck KE, Stouffer GA, Lee CR (2020) Frequency and clinical outcomes of CYP2C19 genotype-guided escalation and de-escalation of antiplatelet therapy in a real-world clinical setting. Genet Med 22: 160–169 doi: 10.1038/s41436-019-0611-1
- D’Andrea G, D’Ambrosio RL, Di Perna P, Chetta M, Santacroce R, Brancaccio V, Grandone E, Margaglione M (2005) A polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood 105: 645–649 doi: DOI 10.1182/blood-2004-06-2111
- Rieder MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL, Blough DK, Thummel KE, Veenstra DL, Rettie AE (2005) Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med 352: 2285–2293 doi: 10.1056/NEJMoa044503
- Finkelman BS, Gage BF, Johnson JA, Brensinger CM, Kimmel SE (2011) Genetic warfarin dosing: tables versus algorithms. J Am Coll Cardiol 57: 612–618 doi: 10.1016/j.jacc.2010.08.643
- Pencina M.J., Navar-Boggan A.M., D’Agostino R.B. Application of new cholesterol guidelines to a population-based sample. J. Vascular Surg. 2014;60(2):534. doi: 10.1016/j.jvs.2014.06.100.
- Ji Y, Skierka JM, Blommel JH, et al. Preemptive pharmacogenomic testing for precision medicine: a comprehensive analysis of five actionable pharmacogenomic genes using next-generation DNA sequencing and a customized CYP2D6 genotyping cascade. J Mol Diagn. 2016;18:438–445.
- Ramsey LB, Johnson SG, Caudle KE, Haidar CE, Voora D, Wilke RA, Maxwell WD, McLeod HL, Krauss RM, Roden DM, Feng Q, Cooper-DeHoff RM, Gong L, Klein TE, Wadelius M, Niemi M (2014) The clinical pharmacogenetics implementation consortium guideline for SLCO1B1 and simvastatin-induced myopathy: 2014 update. Clin Pharmacol Ther 96: 423–428 doi: 10.1038/clpt.2014.125
- Halushka MK, Walker LP, Halushka PV. Genetic variation in cyclooxygenase 1: effects on response to aspirin. Clin Pharmacol Ther. 2003; 73:122–130. doi: 10.1067/mcp.2003.
- Hankey GJ, Eikelboom JW. Aspirin resistance. Lancet. 2006;367:606–617