Genetic Predisposition to Higher Blood Pressure Increases Coronary Artery Disease Risk
Bibliographic record
Abstract
Hypertension is a risk factor for coronary artery disease. Recent genome-wide association studies have identified 30 genetic variants associated with higher blood pressure at genome-wide significance (P<5 × 10(-8)). If elevated blood pressure is a causative factor for coronary artery disease, these variants should also increase coronary artery disease risk. Analyzing genome-wide association data from 22 233 coronary artery disease cases and 64 762 controls, we observed in the Coronary ARtery DIsease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) consortium that 88% of these blood pressure-associated polymorphisms were likewise positively associated with coronary artery disease, that is, they had an odds ratio >1 for coronary artery disease, a proportion much higher than expected by chance (P=4 × 10(-5)). The average relative coronary artery disease risk increase per each of the multiple blood pressure-raising alleles observed in the consortium was 3.0% for systolic blood pressure-associated polymorphisms (95% confidence interval, 1.8%-4.3%) and 2.9% for diastolic blood pressure-associated polymorphisms (95% confidence interval, 1.7%-4.1%). In substudies, individuals carrying most systolic blood pressure- and diastolic blood pressure-related risk alleles (top quintile of a genetic risk score distribution) had 70% (95% confidence interval, 50%-94%) and 59% (95% confidence interval, 40%-81%) higher odds of having coronary artery disease, respectively, as compared with individuals in the bottom quintile. In conclusion, most blood pressure-associated polymorphisms also confer an increased risk for coronary artery disease. These findings are consistent with a causal relationship of increasing blood pressure to coronary artery disease. Genetic variants primarily affecting blood pressure contribute to the genetic basis of coronary artery disease.
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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 | 0.000 | 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 | 0.001 | 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".