Abstract 47: Genetically Elevated Low-Density Lipoprotein Cholesterol is Associated with Aortic Valve Calcification and Incident Aortic Stenosis
Bibliographic record
Abstract
Background: Although plasma low density lipoprotein cholesterol (LDL-C) appears to be a causative factor in animal models of aortic valve (AV) disease, randomized trials with cholesterol lowering therapies in established disease have failed to reduce progression. We sought to evaluate whether life-long genetic elevations in LDL-C, high density lipoprotein cholesterol (HDL-C) and triglycerides (TG) are associated with AV disease. Methods: Using 144 single nucleotide polymorphisms associated with LDL-C, HDL-C or TG in genomewide association studies (GWAS), we constructed three separate genetic risk scores (GRS). We estimated the association between each GRS and (1) the presence of AV calcium determined by computed tomography in 6942 participants of white European ancestry from the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) consortium using summary level GWAS data and; (2) incidence of aortic stenosis in 28,585 participants from the Malmo Diet and Cancer Study (MDCS) over a mean follow-up time of 15.8 years. Results: The LDL-C GRS, but not the HDL-C or the TG GRS, was associated with presence of AV calcium (OR per predicted mmol/L LDL-C, 1.38 95% CI 1.09-1.74; p=0.007). The LDL-C GRS was also associated with incident aortic stenosis (HR per mmol/L LDL-C, 3.04 (1.34-6.91, p=0.008). In sensitivity analyses excluding SNPs also associated with HDL-C or TG to reduce pleiotropy, the LDL-C GRS remained associated with AV calcium (OR per predicted mmol/L LDL-C 1.39 95% CI 1.04-1.90; p=0.03) and aortic stenosis (HR per mmol/L LDL-C 3.85, 95% CI 1.37-10.79, p=0.01). Further analyses to exclude residual pleiotropic effects of HDL-C and TG, did not materially change these findings. Conclusions: Genetic predisposition to increased LDL-C is associated with presence of AV calcium and incidence of aortic stenosis, providing novel supportive evidence that LDL-C is a causal factor for the development of AV disease. Earlier intervention to reduce LDL-C merits further investigation to prevent AV disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".