Association of TGFB1 rs1800469 and BCMO1 rs6564851 with coronary heart disease and IL1B rs16944 with all-cause mortality in men from the Northern Ireland PRIME study
Bibliographic record
Abstract
BACKGROUND: Historically, high levels of morbidity and mortality have been associated with cardiovascular disease in the Northern Ireland population. Previously reported associations between single nucleotide polymorphisms (SNPs) and cardiovascular disease within other populations have not always been consistent. OBJECTIVE: To investigate associations between 33 SNPs with fatal or non-fatal incident coronary heart disease (CHD) events and all-cause mortality in the Northern Irish participants of the Prospective Epidemiological Study of Myocardial Infarction (PRIME). METHOD: Phase 2 of the PRIME study prospectively evaluated 2,010 men aged 58-74 years in Northern Ireland for more than 10 years for incident CHD events (myocardial infarction, percutaneous coronary intervention, coronary artery bypass, and cardiac death) and more than 15 years for all-cause mortality. SNPs previously reported in association with cardiovascular outcomes were evaluated against incident CHD events and all-cause mortality using Cox's proportional hazards models adjusted for established cardiovascular disease risk factors. RESULTS: During the follow-up period, 177 incident CHD events were recorded, and 821 men died. Both BCMO1 rs6564851 (Hazard ratio [HR] = 0.76; 95% confidence intervals [CI]: 0.60-0.96; P = 0.02) and TGFB1 rs1800469 (HR = 1.30; CI: 1.02-1.65; P = 0.04) were significantly associated with incident CHD events in adjusted models. Only IL1B rs16944 was significantly associated with all-cause mortality (HR = 1.18; CI: 1.05-1.33; P = 0.005). No associations remained significant following Bonferonni correction for multiple testing. CONCLUSION: We report a novel association between BCMO1 rs6564851 and risk of incident CHD events. In addition, TGFB1 rs1800469 and IL1B rs16944 were associated with the risk of incident CHD events and all-cause mortality outcomes respectively, supporting previously reported associations.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 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".