Pharmacogenomic Impact of CYP2C19 Variation on Clopidogrel Therapy in Precision Cardiovascular Medicine

Abstract

Variability in response to antiplatelet therapy can be explained in part by pharmacogenomics, particularly of the CYP450 enzyme encoded by CYP2C19. Loss-of-function and gain-of-function variants help explain these interindividual differences. Individuals may carry multiple variants, with linkage disequilibrium noted among some alleles. In the current pharmacogenomics era, genomic variation in CYP2C19 has led to the definition of pharmacokinetic phenotypes for response to antiplatelet therapy, in particular, clopidogrel. Individuals may be classified as poor, intermediate, extensive, or ultrarapid metabolizers, based on whether they carry wild type or polymorphic CYP2C19 alleles. Variant alleles differentially impact platelet reactivity, concentration of plasma clopidogrel metabolites, and clinical outcomes. Interestingly, response to clopidogrel appears to be modulated by additional factors, such as sociodemographic characteristics, risk factors for ischemic heart disease, and drug-drug interactions. Furthermore, systems medicine studies suggest that a broader approach may be required to adequately assess, predict, preempt, and manage variation in antiplatelet response. Transcriptomics, epigenomics, exposomics, miRNAomics, proteomics, metabolomics, microbiomics, and mathematical, computational, and molecular modeling should be integrated with pharmacogenomics for enhanced prediction and individualized care. In this review of pharmacogenomic variation of CYP450, a systems medicine approach is described for tailoring antiplatelet therapy in clinical practice of precision cardiovascular medicine.

Keywords: CYP2C19; CYP450; antiplatelet therapy; clopidogrel; genetics variants; pharmacogenomics; precision cardiovascular medicine.

Figure 1

Metabolism of clopidogrel. The pharmacodynamics and pharmacokinetics of clopidogrel (a prodrug) involves intestinal absorption via P-glycoprotein. This is followed by processing of clopidogrel in the liver primarily by cytochrome P450 enzymes, with release of the active metabolite that inhibits the adenosine diphosphate P2Y12 receptor. This leads to decrease in activation of platelets and formation of thrombus. Used with permission of the Sociedad Española de Cardiología; copyright 2011 [22].

Figure 2

Variable platelet response to clopidogrel can associate with risk factors and outcomes. On-treatment platelet reactivity in response to clopidogrel can associate with bleeding risk if low or ischemic risk if high, with a therapeutic window. Various risk factors for ischemic heart disease can impact on-treatment platelet reactivity in individuals treated with clopidogrel. ACS: acute coronary syndrome; CKD: chronic kidney disease; DM: diabetes mellitus. Used with permission of Elsevier; copyright 2013 [107].

Figure 3

Conventional and Genetic Regulators of Response. Conventional clinical (and cellular) factors and also genetic other factors regulate response to clopidogrel. ABCB1: ATP-Binding Cassette Subfamily B Member 1; ADP: adenosine diphosphate; CES: Carboxylesterase 1; CYP: cytochrome P450, particularly CYP2C19; GPIIB/IIIa: Glycoprotein IIB/IIIa; PON1: Serum paraoxonase/arylesterase 1; P2Y: receptor on the surface of platelets. Used with permission of Creative Commons; copyright 2017 [11]; originally adapted from [128].

Figure 4

Systems Medicine tools for CYP450 regulation in Precision Cardiovascular Medicine. Studies in precision cardiovascular medicine have produced results from various omic technologies that help elucidate contributing factors regulating the pharmacogenomic impact of CYP450 variation on antiplatelet therapy. For example, systems biology tools have implicated CYPC219 genomic variants in genome-wide association studies, methylation of P2Y12 in epigenomics, miR-103/107 on CYP2C19 in microRNAomics, transferrin and peroxiredoxin-4 in proteomics, TMAO in metabolomics and microbiomics. Beyond omics, systems medicine and precision medicine incorporate ‘big data’ and clinical variables from the electronic health record with heart rate and activity levels from mobile health technology, along with findings from Imaging (such as high risk plaque, coronary calcium), to predict which individuals may be at low versus high risk for resistance to treatment with clopidogrel. CYP450: cytochrome P450; CYP2C19: cytochrome P450, family 2, subfamily C, polypeptide 19; P2Y12: the adenosine diphosphate receptor on the surface of platelets, to which clopidogrel binds; miR-103/107: microRNA-103 and microRNA-107; TMAO: trimethylene N-oxide.

Figure 5

Proposed Clinical Algorithms for Tailoring Clopidogrel Therapy. Proposed clinical algorithms for tailoring clopidogrel therapy based on CYP2C19 genotype (a,b) or on-treatment platelet reactivity (b). The algorithms do not account for non-genetic or other precision medicine regulators of clopidogrel resistance. ¹ Only the most common CYP2C19 genotypes are illustrated; ² Prasugrel and ticagrelor should be considered when not contraindicated clinically. ACS: acute coronary syndrome; EM: extensive metabolizer; IM: intermediate metabolizer; PCI: percutaneous coronary intervention; PM: poor metabolizer; UM: ultra-rapid metabolizer. Used with permission of John Wiley and Sons; copyright 2013 by Scott et al. Clinical Pharmacogenetics Implementation Consortium guidelines for CYP2C19 genotype and clopidogrel therapy: 2013 update. [68]; and used with permission of Elsevier; copyright 2017 [107].

Figure 6

The P^*3 precision medicine approach to tailoring antiplatelet therapy. In the P^*3 pathway for incorporating precision medicine (PM) data in clinical practice, pre-emption (P1) is depicted in purple, prediction (P2) is depicted in blue, and prevention (P3) is depicted in brown. In P1, precision medicine data should be integrated with socioeconomic demographics, lifestyle habits, family history, medication and adherence history, co-morbid conditions, and other factors in the electronic health record (EHR). Clinical decision aids could support shared decision-making. A composite precision medicine score (CPMS) synthesizes clinical factors, platelet reactivity, and other test results with precision medicine data (such as genotype information) for risk prediction. In the example of clopidogrel, the integrative CPMS could be normalized to produce three risk categories (high, intermediate, and low) as shown. In P3, individualized prevention strategies would aim to maximize efficacy, as well as safety (e.g., with monitoring for any clinical evidence of bleeding). Thus, clopidogrel dosing or alternative antiplatelet therapy would not only depend on assessing CYP2C19 genotype and/or platelet reactivity. Used with permission of the Nature Publishing Group; copyright 2015.