Interaction Between Smoking and Polymorphism in the Promoter Region of the VEGFA Gene Is Associated with Ischemic Heart Disease and Myocardial Infarction in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To determine whether variants in the vascular endothelial growth factor A (VEGFA) gene are associated with ischemic heart disease (IHD) and/or myocardial infarction (MI) in patients with rheumatoid arthritis (RA), and whether there is evidence of a gene-smoking interaction. METHODS: PCR-RFLP assays were used to determine the genotypes of VEGFA single-nucleotide polymorphisms (SNP) including VEGFA-2578A/C (rs699947), -460C/T (rs833061), +405C/G (rs2010963), and +936C/T (rs3025039) in 418 subjects with RA. Smoking history was obtained on each patient, and IHD and MI status was recorded. Associations with IHD/MI were assessed using contingency tables and logistic regression analyses. RESULTS: Strong linkage disequilibrium was detected among VEGFA-2578, -460, and +405. SNP located in the VEGFA promoter region (-2578, -460) were found to be associated with IHD and MI, whereas +405 and +936, in the 5'-untranslated region (UTR) and 3'-UTR, respectively, were not. Haplotype analysis suggested that the A/C/G haplotype was associated with increased risk of IHD (OR 2.37, 95% CI 1.22-4.62) and MI (OR 4.10, 95% CI 1.45-11.49). Smoking was also independently associated with IHD and MI, and evidence of interaction between smoking and the VEGFA promoter SNP was found. Multivariate analyses indicated that the strongest associations with IHD and MI were due to the combined effect of the VEGFA-2578 A allele and smoking (OR 3.52 and 7.11, respectively), independent of risk factors such as age, sex, diabetes, C-reactive protein, hypercholesterolemia, and hypertension. CONCLUSION: Interaction between smoking and polymorphism in the VEGFA gene is associated with IHD and MI in patients with RA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".