Association of GSTM1 and GSTT1 gene polymorphisms with coronary artery disease in relation to tobacco smoking
Bibliographic record
Abstract
BACKGROUND: Recent studies suggest that the common variant in the glutathione S-transferase (GST) M1 (GSTM1) and T1 (GSTT1) gene is associated with the risk of smoking-related coronary artery disease (CAD). Intra-ethnic as well as inter-ethnic differences are known to impact the frequencies of GST gene polymorphisms, thus influencing its interactive effect with tobacco smoking on CAD risk. The aim of the present study was to evaluate the interaction of the genetic polymorphisms of GSTM1 and GSTT1 with cigarette smoking and the risk of CAD in a Chinese population. METHODS: We conducted a study with 277 CAD patients and 277 controls matched by age and sex to examine the prevalence of GSTM1 and GSTT1 polymorphism in CAD. RESULTS: We found that homozygous deletion of GSTM1 had a frequency of 32.1% among patients with CAD and 21.3% among those without CAD (p=0.004). The frequency of the GSTT1(null) genotype was 27.8% among the patients with CAD and 19.1% among CAD-free subjects (p=0.016). Patients who smoked having both the wild-type genotypes of GSTM1 and GSTT1 were protected from developing coronary heart disease (p<0.001). Moreover, smokers with combined GSTM1(null)GSTT1(null) genotypes had a significantly higher number of stenosed vessels than those with the positive genotype (p=0.02). CONCLUSIONS: Our results suggest that GST polymorphisms may be a susceptibility factor to smoking-related CAD in the Chinese population.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".