Autoantibody presentation in drug-induced liver injury and idiopathic autoimmune hepatitis
Bibliographic record
Abstract
OBJECTIVES: Positive autoantibody (AAB) titres are commonly encountered in autoimmune hepatitis (AIH) and in a proportion of drug-induced liver injury (DILI) patients. The underlying mechanism for selective AAB occurrence in DILI is unknown, but could be associated with variations in immune-associated genes. Hence, we aimed to analyse human leucocyte antigen (HLA) allele compositions in DILI with positive (+) and negative (-) AAB titres and in AIH patients. METHODS: High-resolution genotyping of HLA class I (A, B, C) and II (DRB1, DQB1) loci was performed on 207 DILI and 50 idiopathic AIH patients and compared with 885 healthy Spanish controls. RESULTS: Compared with controls, HLA-B*08:01 [44 vs. 9.7%, P=3.7E-13/corrected P-value (Pc)=1.0E-11], C*07:01 (46 vs. 24%, P=6.4E-04/Pc=0.012), DRB1*03:01 (58 vs. 21.5%, P=5.0E-09/Pc=1.0E-07) and DQB1*02:01 (56 vs. 22%, P=6.8E-08/Pc=9.0E-07) were significantly more frequent in AIH patients. The HLA-A*01:01 frequency was increased in the same population, but did not reach significance after Bonferroni's correction (34 vs. 19%, P=0.02/Pc=0.37). Fifty-eight of 207 DILI patients presented positive titres for at least one AAB (predominantly antinuclear antibody 76% and antismooth muscle antibody 28%). There was a tendency towards higher representation of DRB1*14:01 and DQB1*05:03 in DILI AAB+ compared with DILI AAB- (13.8 vs. 4.0%, P=0.02/Pc=0.5; 13.8 vs. 4.7%, P=0.04/Pc=0.5). CONCLUSION: The presence of HLA alleles B*08:01, C*07:01, DRB1*03:01, DQB1*02:01 and possibly A*01:01 enhances the risk of AIH (type 1) in Spanish patients. These alleles form part of the ancestral haplotype 8.1. HLA-DRB1*14:01 and DQB1*05:03 could potentially increase the risk of positive AAB (particularly antinuclear antibody) in Spanish DILI patients.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".