Potential of ileal bile acid transporter inhibition as a therapeutic target in Alagille syndrome and progressive familial intrahepatic cholestasis
Bibliographic record
Abstract
Alagille syndrome (ALGS) and progressive familial intrahepatic cholestasis (PFIC) are rare, inherited cholestatic liver disorders that manifest in infants and children and are associated with impaired bile flow (ie cholestasis), pruritus and potentially fatal liver disease. There are no effective or approved pharmacologic treatments for these diseases (standard medical treatments are supportive only), and new, noninvasive options would be valuable. Typically, bile acids undergo biliary secretion and intestinal reabsorption (ie enterohepatic circulation). However, in these diseases, disrupted secretion of bile acids leads to their accumulation in the liver, which is thought to underlie pruritus and liver-damaging inflammation. One approach to reducing pathologic bile acid accumulation in the body is surgical biliary diversion, which interrupts the enterohepatic circulation (eg by diverting bile acids to an external stoma). These procedures can normalize serum bile acids, reduce pruritus and liver injury and improve quality of life. A novel, nonsurgical approach to interrupting the enterohepatic circulation is inhibition of the ileal bile acid transporter (IBAT), a key molecule in the enterohepatic circulation that reabsorbs bile acids from the intestine. IBAT inhibition has been shown to reduce serum bile acids and pruritus in trials of paediatric cholestatic liver diseases. This review explores the rationale of inhibition of the IBAT as a therapeutic target, describes IBAT inhibitors in development and summarizes the current data on interrupting the enterohepatic circulation as treatment for cholestatic liver diseases including ALGS and PFIC.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".