Autotaxin interacts with lipoprotein(a) and oxidized phospholipids in predicting the risk of calcific aortic valve stenosis in patients with coronary artery disease
Bibliographic record
Abstract
Abstract Background Studies have shown that lipoprotein(a) [Lp(a)], an important carrier of oxidized phospholipids, is causally related to calcific aortic valve stenosis ( CAVS ). Recently, we found that Lp(a) mediates the development of CAVS through autotaxin ( ATX ). Objective To determine the predictive value of circulating ATX mass and activity for CAVS . Methods We performed a case‐control study in 300 patients with coronary artery disease ( CAD ). Patients with CAVS plus CAD (cases, n = 150) were age‐ and gender‐matched (1 : 1) to patients with CAD without aortic valve disease (controls, n = 150). ATX mass and enzymatic activity and levels of Lp(a) and oxidized phospholipids on apolipoprotein B‐100 (Ox PL ‐apoB) were determined in fasting plasma samples. Results Compared to patients with CAD alone, ATX mass ( P < 0.0001), ATX activity ( P = 0.05), Lp(a) ( P = 0.003) and Ox PL ‐apoB ( P < 0.0001) levels were elevated in those with CAVS . After adjustment, we found that ATX mass ( OR 1.06, 95% CI 1.03–1.10 per 10 ng mL −1 , P = 0.001) and ATX activity ( OR 1.57, 95% CI 1.14–2.17 per 10 RFU min −1 , P = 0.005) were independently associated with CAVS . ATX activity interacted with Lp(a) ( P = 0.004) and Ox PL ‐apoB ( P = 0.001) on CAVS risk. After adjustment, compared to patients with low ATX activity (dichotomized at the median value) and low Lp(a) (<50 mg dL −1 ) or Ox PL ‐apoB (<2.02 nmol L −1 , median) levels (referent), patients with both higher ATX activity (≥84 RFU min −1 ) and Lp(a) (≥50 mg dL −1 ) ( OR 3.46, 95% CI 1.40–8.58, P = 0.007) or Ox PL ‐apoB (≥2.02 nmol L −1 , median) ( OR 5.48, 95% CI 2.45–12.27, P < 0.0001) had an elevated risk of CAVS. Conclusion Autotaxin is a novel and independent predictor of CAVS in patients with CAD .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".