Genetics of Calcific Aortic Stenosis: A Systematic Review
Bibliographic record
Abstract
Background: Calcific aortic stenosis is the most prevalent valvular abnormality in the Western world. Factors commonly associated with calcific aortic stenosis include advanced age, male sex, hypertension, diabetes and impaired renal function. This review synthesises the existing literature on genetic associations with calcific aortic stenosis. Methods: A systematic search was conducted in the PubMed, Ovid and Cochrane libraries from inception to 21 July 2024 to identify human studies investigating the genetic factors involved in calcific aortic stenosis. From an initial pool of 1392 articles, 78 were selected for full-text review and 31 were included in the final qualitative synthesis. The risk of bias in these studies was assessed using the Newcastle Ottawa Scale. Results: Multiple genes have been associated with calcific aortic stenosis. These genes are involved in different biological pathways, including the lipid metabolism pathway (PLA, LDL, APO, PCSK9, Lp-PLA2, PONS1), the inflammatory pathway (IL-6, IL-10), the calcification pathway (PALMD, TEX41) and the endocrine pathway (PTH, VIT D, RUNX2, CACNA1C, ALPL). Additional genes such as NOTCH1, NAV1 and FADS1/2 influence different pathways. Mechanistically, these genes may promote a pro-inflammatory and pro-calcific environment in the aortic valve itself, leading to increased osteoblastic activity and subsequent calcific degeneration of the valve. Conclusions: Numerous genetic associations contribute to calcific aortic stenosis. Recognition of these associations can enhance risk stratification for individuals and their first-degree relatives, facilitate family screening, and importantly, pave the way for targeted therapeutic interventions focusing on the identified genetic factors. Understanding these genetic factors can also lead to gene therapy to prevent calcific aortic stenosis in the future.
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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) | 0.004 | 0.005 |
| 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".