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Updated: Jul 18, 2025

A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene
Published on: April 1, 2019
Implications of Pharmacogenetic Testing for Clopidogrel Therapy in a Tertiary Healthcare Hospital in North India
Jayachandra Amarapalli1, Prabhat Sharma1, Rajat Datta2
1Cardiology, Base Hospital, Delhi Cantt, New Delhi, IND.
Abstract:
Background Clopidogrel hyporesponsiveness with decreased antiplatelet activity is prevalent in percutaneous coronary intervention (PCI) patients due to reduced function polymorphism in the CYP2C19 enzyme gene which results in poor conversion of this prodrug to an active metabolite. However, pharmacogenetic testing is not part of routine clinical practice in India. Methodology In this retrospective observational study, we observed the prevalence of loss of function (LOF) gene variants of CYP2C19 (*2, *3) in 60 patients undergoing PCI with complex anatomies in a tertiary healthcare hospital in North India. We do not have follow-up data for a few patients. However, the treatment regimen was recorded, and the occurrence of any clinical event was monitored for the remaining 52 patients for six months. Results The mean age of the patients was 61.76 ± 10.14 years. We found that 52% of patients carried these LOF mutations, of which 37% were intermediate metabolizers, while 15% were poor metabolizers of clopidogrel. However, out of 52 patients for whom follow-up data were available, 22 (42.3%) were intermediate metabolizers, while six (11.54%) showed genotypes associated with poor metabolism of clopidogrel. Clopidogrel (75 mg BD) was the primary replacement drug in place of ticagrelor (90 mg BD) during follow-up after four weeks (based on the clinician's discretion). Conclusions No major ischemic event was reported during the follow-up of these 52 patients. The intermediate metabolizers' LOF in one copy of the CYP2C19 gene seems to overcome genetic deficiency with the clopidogrel 75 mg BD regime, which is comparable to maintenance with ticagrelor 90 mg BD. This study can be extrapolated to a larger cohort to observe statistically significant differences among various groups.
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