Poly-hydroxylated bile acids and their prognostic roles in Alagille syndrome
Bibliographic record
Abstract
Abstract The liver manifestations of Alagille syndrome (ALGS) are highly variable, and factors affecting its prognosis are poorly understood. We asked whether or not the composition of bile acids in ALGS patients with good clinical outcomes differs from those with poor outcomes, and whether bile acids could be used as prognostic biomarkers. Blood for bile acid profiling were collected from genetically confirmed JAG1-associated ALGS patients before one year of age. Good prognosis was defined as survival with native liver and total bilirubin (TB) < 85.5 µmol/L, while poor prognosis as either liver transplanted, died of liver failure, or TB ≥ 85.5 µmol/L at last follow-up. We found that the concentrations of two poly-hydroxylated bile acids, tauro-2β,3α,7α,12α-tetrahydroxylated bile acid (THBA), and glyco-hyocholic acid (GHCA), were significantly increased in patients with good prognosis compared to those with poor prognosis (AUC = 0.836 and 0.782, respectively) in the discovery cohort. The same trend was also observed in the molar ratios of GHCA to GCDCA and THCA to TCDCA (both AUC = 0.836). A validation cohort confirmed these findings. Notably, tauro‐2β,3α,7α,12α-THBA achieved the highest prediction accuracy of 88.00% (92.31% sensitivity and 83.33% specificity); GHCA at > 607.69 nmol/L was associated with native liver survival (hazard ratio: 6.456, 95% CI: 1.173–35.545, P = 0.032). We identified two poly-hydroxylated bile acids as the liver prognostic biomarkers of ALGS patients. Enhanced hydroxylation of bile acids may result in better clinical outcomes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".