Acetylsalicylic acid, aging and coronary artery disease are associated with ABCA1 DNA methylation in men
Bibliographic record
Abstract
BACKGROUND: Previous studies have suggested that DNA methylation contributes to coronary artery disease (CAD) risk variability. DNA hypermethylation at the ATP-binding cassette transporter A1 (ABCA1) gene, an important modulator of high-density lipoprotein cholesterol and reverse cholesterol transport, has been previously associated with plasma lipid levels, aging and CAD, but the association with CAD has yet to be replicated. RESULTS: ABCA1 DNA methylation levels were measured in leucocytes of 88 men using bis-pyrosequencing. We first showed that DNA methylation at the ABCA1 gene promoter locus is associated with aging and CAD occurrence in men (P < 0.05). The latter association is stronger among older men with CAD (≥61 years old; n = 19), who showed at least 4.7% higher ABCA1 DNA methylation levels as compared to younger men with CAD (<61 years old; n = 19) or men without CAD (n = 50; P < 0.001). Higher ABCA1 DNA methylation levels in older men were also associated with higher total cholesterol (r = 0.34, P = 0.03), low-density lipoprotein cholesterol (r = 0.32, P = 0.04) and triglyceride levels (r = 0.26, P = 0.09). Furthermore, we showed that acetylsalicylic acid therapy is associated with 3.6% lower ABCA1 DNA methylation levels (P = 0.006), independent of aging and CAD status of patients. CONCLUSIONS: This study provides new evidence that the ABCA1 epigenetic profile is associated with CAD and aging, and highlights that epigenetic modifications might be a significant molecular mechanism involved in the pathophysiological processes associated with CAD. Acetylsalicylic acid treatment for CAD prevention might involve epigenetic mechanisms.
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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 | 0.000 | 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) | 0.002 | 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".