Impact of CYP2C19 Genotype-guided Clopidogrel and Ticagrelor Treatment on Platelet Function Test and Metabolomics Profile

Several studies have shown that pharmacodynamic (PD) response varies between patients treated with clopidogrel and that individuals with reduced response have an increased risk of recurrent ischemic events, particularly in patients undergoing percutaneous coronary intervention. This is due to several factors influencing the response to clopidogrel, including genetic variations of the cytochrome P450 (CYP) 2C19 enzyme. Loss of function (LOF) carriers of the CYP2C19 gene are associated with the decreased generation of the active metabolite clopidogrel and decreased platelet inhibition, which translates to an increased rate of adverse cardiovascular events, particularly in the setting of percutaneous coronary intervention (PCI). Thus, drug regulatory authorities have cautioned about the decreased efficacy of clopidogrel among individuals with CYP2C19 LOF carriers and suggested using alternative therapies to inhibit p2Y12. Ticagrelor is a new generation P2Y12 receptor inhibitor with greater efficacy for PD and reduced rates of ischemic events compared with clopidogrel and are not affected by the CYP2C19 LOF polymorphism. However, in clinical practice, the genotype-guided selection strategy for the oral P2Y12 inhibitor has been limited despite intensive research efforts. This is due to the interaction of cardiovascular risk factors and molecular and biochemical complications that lead to poor response to platelet inhibitor therapy, which impedes physicians' ability to prescribe a more effective and personalized antiplatelet therapy. Therefore, we must move away from traditional approaches and use integrated systems biology study designs and disciplines to bridge the gap between genotype, phenotype, disease manifestation and/or recurrence. Pharmacometabolomics is a rapidly developing field that takes advantage of a systems pharmacology approach to probe the molecular pathways involved in drug response variability to understand metabolic changes and identify novel biomarke