Abstract 9316: Role of Bile Acids in Calcific Aortic Valve Stenosis
Bibliographic record
Abstract
Introduction: Calcific aortic valve stenosis (CAVS) is the most common valvular pathology seen in the Western world. Patients with symptomatic CAVS have a poor prognosis with the only therapy being valvular intervention. There is currently no known mechanism and therefore medical therapy for controlling the progression of CAVS. Our recent metabolomics analysis of human aortic valve tissue identified bile acid biosynthesis as a potential mitigator of valvular stenosis. In this study, utilizing a targeted metabolomics approach, we investigated the role of valvular and plasma bile acids in the degree of severity and the rate of progression of CAVS. Methods: Human aortic valves from 102 patients who underwent AVR surgery were collected. Bile acid profiling (80 bile acids) of valvular tissues along with 19 plasma samples was carried out by a targeted mass spectrometry approach. The explanted aortic valves were graded from mild, moderate, and severe categories based on mean pressure gradient (MPG) and valvular calcification score by transthoracic echocardiography. CAVS progression was determined in a subset of our cohort (N=49), categorizing patients as “fast” and “slow” progressors based on echocardiography measures of the peak jet velocity. Results: Bile acids nordeoxycholic acid, norcholic acid, and glycodeoxycholic acid were significantly altered (p<0.05) across CAVS severity stages based on MPG. Similarly, six bile acids namely nordeoxycholic acid, norcholic acid, 3β,7α-diOH-5-cholestenoic acid, 3β-OH-5-cholestenoic acid, glycolithocholic acid, and glycoallocholic acid were significantly altered (p<0.05) based on valvular calcification scores. Taurodeoxycholic acid showed a significant difference (p<0.05) between the slow and fast progressors. Additionally, valvular tissue levels of these bile acids correlate with plasma levels. Conclusions: In this report, we present a potential novel mechanistic pathway correlating bile acids with the pathogenesis of CAVS. Our goal is to validate these findings in a large cohort of patients with CAVS. Given that bile acid modulating therapies are already used in clinical practice, this represents a potential novel therapeutic target to prevent or delay the progression of CAVS.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".