Pharmacogenomic evaluation of CYP2C19 alleles linking low clopidogrel response and the risk of acute coronary syndrome in Indians
Bibliographic record
Abstract
BACKGROUND: Clopidogrel is an antiplatelet drug widely prescribed to prevent atherothrombotic events in coronary artery disease patients. However, there is evidence to suggest that the effectiveness of clopidogrel varies owing to genetic diversity in CYP2C19. This heterogeneity in South Asians, who are also known to have high risk of cardiac events than other population groups, highlights the importance of investigating CYP2C19 variants to estimate the risk proportion in the groups. METHODS: Given the high prevalence and genetic heterogeneity, the population-based case control was conducted in a cohort of 1191 subjects comprising 645 acute coronary syndrome (ACS) cases (unstable angina, ST-elevation myocardial infarction, and non-ST-elevation myocardial infarction) and 546 healthy controls of South Asian Indian origin. The metabolization status of CYP2C19 was assessed using *2, *3 and *17 variants in the stated cohorts to determine the prevalence of metabolization and its association with phenotypes. RESULTS: The results suggest a possible genetic association between studied CYP2C19 polymorphisms and ACS, since there was a higher proportion of intermediate and poor metabolizers present in the studied cohorts. The association analyses revealed that the *2 allele of CYP2C19 confers a significant risk for ACS, while the *17 allele provides protection. CONCLUSIONS: These findings contribute to the understanding of CYP2C19 genetic variants and their impact on clopidogrel response in South Asian Indians. Additionally, they underline the significance of assessing CYP2C19 variations in patients receiving clopidogrel therapy in order to improve therapeutic outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".