Cholestatic liver diseases of genetic etiology: Advances and controversies
Bibliographic record
Abstract
With the application of modern investigative technologies, cholestatic liver diseases of genetic etiology are increasingly identified as the root cause of previously designated "idiopathic" adult and pediatric liver diseases. Here, we review advances in the field enhanced by a deeper understanding of the phenotypes associated with specific gene defects that lead to cholestatic liver diseases. There are evolving areas for clinicians in the current era specifically regarding the role for biopsy and opportunities for a "sequencing first" approach. Risk stratification based on the severity of the genetic defect holds promise to guide the decision to pursue primary liver transplantation versus medical therapy or nontransplant surgery, as well as early screening for HCC. In the present era, the expanding toolbox of recently approved therapies for hepatologists has real potential to help many of our patients with genetic causes of cholestasis. In addition, there are promising agents under study in the pipeline. Relevant to the current era, there are still gaps in knowledge of causation and pathogenesis and lack of fully accepted biomarkers of disease progression and pruritus. We discuss strategies to overcome the challenges of genotype-phenotype correlation and draw attention to the extrahepatic manifestations of these diseases. Finally, with attention to identifying causes and treatments of genetic cholestatic disorders, we anticipate a vibrant future of this dynamic field which builds upon current and future therapies, real-world evaluations of individual and combined therapeutics, and the potential incorporation of effective gene editing and gene additive technologies.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".