Glutathione S-transferase T1 mismatch constitutes a risk factor for de novo immune hepatitis after liver transplantation
Bibliographic record
Abstract
A new form of autoimmune hepatitis referred to as de novo, has been reported after liver transplantation during the past 5 years. The features are identical to those of classical autoimmune hepatitis (AIH), but the facts involved in the onset and outcome of this type of graft dysfunction are still unclear. The identification of antibodies directed to glutathione S-transferase T1 (GSTT1) in the sera of patients with de novo immune hepatitis led us to the description of an alloimmune reaction due to a GSTT1 genetic incompatibility between donor and recipient. We analyzed a cohort of 110 liver transplant patients treated in the liver transplant unit of our hospital during a period of 1 year, from September 2002 to October 2003. We found the following distribution of the GSTT1 genotypes (recipient/donor): +/+ = 66, +/- = 23, -/+ = 15, -/- = 6. Six of these patients were diagnosed with de novo immune hepatitis; all of them belong to the group of negative recipients with positive donors, and all produced anti-GSTT1 antibodies. This genetic combination is associated with a statistically significant increased risk of de novo immune hepatitis (IH) in liver transplant patients (P < .0001 by the Fisher exact test). In conclusion, our results clearly establish the importance of the GSTT1 genotype from donor and recipient of a liver transplant as a predictive marker for de novo IH. At the same time, we confirmed our initial results that only this particular donor/recipient combination triggers the anti-GSTT1 antibody production.
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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 | 0.003 |
| 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 | 0.001 | 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".