Resequencing and Clinical Associations of the 9p21.3 Region
Bibliographic record
Abstract
BACKGROUND: 9p21.3 is among the most strongly replicated regions for cardiovascular disease. There are few reports of sequencing the associated 9p21.3 interval. We set out to sequence the 9p21.3 region followed by a comprehensive study of genetic associations with clinical and subclinical cardiovascular disease and its risk factors, as well as with copy number variation and gene expression, in the Framingham Heart Study (FHS). METHODS AND RESULTS: We sequenced 281 individuals (94 with myocardial infarction, 94 with high coronary artery calcium levels, and 93 control subjects free of elevated coronary artery calcium or myocardial infarction), followed by genotyping and association in >7000 additional FHS individuals. We assessed genetic associations with clinical and subclinical cardiovascular disease, risk factor phenotypes, and gene expression levels of the protein-coding genes CDKN2A and CDKN2B and the noncoding gene ANRIL in freshly harvested leukocytes and platelets. Within this large sample, we found strong associations of 9p21.3 variants with increased risk for myocardial infarction, higher coronary artery calcium levels, and larger abdominal aorta diameters and no evidence for association with traditional cardiovascular disease risk factors. No common protein-coding variation, variants in splice donor or acceptor sites, or copy number variation events were observed. By contrast, strong associations were observed between genetic variants and gene expression, particularly for a short isoform of ANRIL and for CDKN2B. CONCLUSIONS: Our thorough genomic characterization of 9p21.3 suggests common variants likely account for observed disease associations and provides further support for the hypothesis that complex regulatory variation affecting ANRIL and CDKN2B gene expression may contribute to increased risk for clinically apparent and subclinical coronary artery disease and aortic disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 | 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".