The impact of epigenetics on cardiovascular disease
Bibliographic record
Abstract
Mortality and morbidity from cardiovascular diseases (CVDs) represents a huge burden to society. It is recognized that environmental factors and individual lifestyles play important roles in disease susceptibility, but the link between these external risk factors and our genetics has been unclear. However, the discovery of sequence-independent heritable DNA changes (epigenetics) have helped us to explain the link between genes and the environment. Multiple diverse epigenetic processes, including DNA methylation, histone modification, and the expression of non-coding RNA molecules affect the expression of genes that produce important changes in cellular differentiation and function, influencing the health and adaptability of the organism. CVDs such as congenital heart disease, cardiomyopathy, heart failure, cardiac fibrosis, hypertension, and atherosclerosis are now being viewed as much more complex and dynamic disorders. The role of epigenetics in these and other CVDs is currently under intense scrutiny, and we can expect important insights to emerge, including novel biomarkers and new approaches to enable precision medicine. This review summarizes the recent advances in our understanding of the role of epigenetics in CVD.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".