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A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene
Published on: April 1, 2019
Aspirin & clopidogrel non-responsiveness & its association with genetic polymorphisms in patients with myocardial
Chandra Prakash Pandey1, Ankita Misra2, Mahendra Pal Singh Negi3
1Divisions of Pharmacology, CSIR-Central Drug Research Institute; Department of Cardiology, King George Medical University, Lucknow, India.
Insights
Genetic polymorphisms in CYP2C19*2 and GPVI are linked to dual antiplatelet therapy non-responsiveness in myocardial infarction patients. This finding highlights the role of genetic factors in DAPT efficacy.
Area of Science:
- Pharmacogenomics
- Cardiovascular Medicine
- Clinical Chemistry
Background:
- Dual antiplatelet therapy (DAPT) with aspirin and clopidogrel is standard for myocardial infarction (MI) patients.
- Patient response to DAPT can be influenced by genetic variations in key drug-metabolizing enzymes and platelet receptors.
- Identifying non-responsiveness is crucial for optimizing treatment and preventing adverse cardiovascular events.
Purpose of the Study:
- To investigate the association between specific gene polymorphisms and DAPT non-responsiveness in patients with MI.
- To identify clinical and genetic factors contributing to non-response to aspirin and clopidogrel therapy.
Main Methods:
- Light transmittance aggregometry was used to assess DAPT non-responsiveness in 207 MI patients.
- Plasma levels of thromboxane B2 (TxB2) and soluble CD40 ligand (sCD40L) were measured.
- CYP450, P2Y12, COX1, and GPVI gene polymorphisms were analyzed using DNA sequencing.
Main Results:
- DAPT non-responsiveness was observed in 15.5% of the patients.
- Non-responsiveness was significantly associated with gender, higher TxB2 levels, and the CYP2C19*2 G>A and GPVI T>C polymorphisms.
- These associations remained significant after adjusting for confounding factors.
Conclusions:
- Specific genetic polymorphisms, namely CYP2C19*2 G>A and GPVI T>C, are significantly associated with DAPT non-responsiveness in MI patients.
- These genetic factors may play a role in predicting treatment response.
- Further validation in larger cohorts with clinical follow-up is warranted.
Background & Objectives:
Cytochrome P450, P2Y 12, cyclooxygenase-1 (COX1) and glycoprotein V1 (GPVI) gene polymorphisms are known to affect patient responsiveness towards aspirin and clopidogrel dual antiplatelet therapy (DAPT). The present study was undertaken to identify aspirin and clopidogrel non-responsiveness and its association with genetic polymorphism in patients with myocardial infarction (MI).
Methods:
A total of 207 MI patients who were on DAPT, were included. The DAPT non-responsiveness was determined by light transmittance aggregometry using arachidonic acid and adenosine diphosphate and high platelet reactivity by collagen. Platelet activation biomarkers, thromboxane B2 (TxB2)andsoluble CD40 ligand (sCD40L) were measured in plasma. Patient compliance was checked by estimating drug and its metabolite levels (aspirin and clopidogrel) in plasma using liquid chromatography-mass spectrometry/mass spectrometry. Genomic DNA was extracted, amplified by polymerase chain reaction and subsequently sequenced to identify CYP450, P2Y 12, COX1 and GPVI gene polymorphisms.
Results:
Of the 207 patients, 32 were non-responders. The DAPT non-responsiveness was found in 15.5 per cent patients. The non-responsiveness showed a significant and an independent association with gender [odds ratio (OR)=0.18, 95% confidence interval (CI)=0.01-0.78, P=0.023], TxB2(OR=1.00, 95% CI=1.00-1.01, P=0.013), CYP2C19*2 G>A (OR=3.33, 95% CI=1.04-10.69, P=0.044) and GPVI T>C (OR=0.23, 95% CI=0.08-0.67, P=0.007) after adjusting the demographic, clinical and genetic confounding factors when assessed between non-responder and responder compliant patients.
Interpretation & Conclusions:
The study showed a significant association of genetic polymorphisms (CYP2C19*2 G>A and GPVI T>C) with DAPT non-responsiveness in MI patients. The findings of this study need further validation in a large cohort of patients with clinical follow up.
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