Interactive Effect of the KCNJ11 Ile337Val Polymorphism and Cigarette Smoking on the Antihypertensive Response to Irbesartan in Chinese Hypertensive Patients
Bibliographic record
Abstract
OBJECTIVE: This study was designed to detect the association of the potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene polymorphism with antihypertensive therapeutic response to irbesartan in a large-scale Chinese hypertensive population. METHODS: A total of 1,099 patients with essential hypertension were enrolled to receive a daily dose of 150 mg irbesartan for 27 days. Pretreatment baseline blood pressure (BP) and posttreatment BP on the 28th day were measured. Plasma irbesartan concentrations were measured by high-performance liquid chromatography-fluorescence. The KCNJ11 I337V gene polymorphism was determined using high-throughput TaqMan technology. RESULTS: The HapMap data in the Han Chinese population showed that the I337V was used as a representative for 4 common functional polymorphisms. Our results showed that the association of antihypertensive response to irbesartan and the KCNJ11 genetic variant in the total sample was not significant. However, in nonsmokers, relative to the GG genotype, subjects with the homozygous AA genotype had a significantly higher therapeutic response to irbesartan (adjusted beta ± SE: 4.7±1.9 mm Hg, P = 0.015). In smokers, the subjects with the homozygous AA genotype had a significantly lower therapeutic response to irbesartan (adjusted beta ± SE: -5.6±2.5 mm Hg, P = 0.026). A multivariate linear regression model confirmed that there was a significant interactive effect between the KCNJ11 gene and smoking on irbesartan treatment (interaction P = 0.001). CONCLUSION: The interactive effect of smoking status and the KCNJ11 genotype may influence the antihypertensive effects of irbesartan, which indicates a consideration for future individualized antihypertensive drug treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".