HLA-DRB1*16
Bibliographic record
Abstract
OBJECTIVE: Flupirtine is a nonopioid analgesic with regulatory approval in a number of European countries. Because of the risk of serious liver injury, its use is now limited to short-term pain management. We aimed to identify genetic risk factors for flupirtine-related drug-induced liver injury (DILI) as these are unknown. MATERIALS AND METHODS: Six flupirtine-related DILI patients from Germany were included in a genome-wide association study (GWAS) involving a further 614 European cases of DILI because of other drugs and 10,588 population controls. DILI was diagnosed by causality assessment and expert review. Human leucocyte antigen (HLA) and single nucleotide polymorphism genotypes were imputed from the GWAS data, with direct HLA typing performed on selected cases to validate HLA predictions. Four replication cases that were unavailable for the GWAS were genotyped by direct HLA typing, yielding an overall total of 10 flupirtine DILI cases. RESULTS: In the six flupirtine DILI cases included in the GWAS, we found a significant enrichment of the DRB1*16:01-DQB1*05:02 haplotype compared with the controls (minor allele frequency cases 0.25 and minor allele frequency controls 0.013; P=1.4 × 10(-5)). We estimated an odds ratio for haplotype carriers of 18.7 (95% confidence interval 2.5-140.5, P=0.002) using population-specific HLA control data. The result was replicated in four additional cases, also with a haplotype frequency of 0.25. In the combined cohort (six GWAS plus four replication cases), the haplotype was also significant (odds ratio 18.7, 95% confidence interval 4.31-81.42, P=6.7 × 10(-5)). CONCLUSION: We identified a novel HLA class II association for DILI, confirming the important contribution of HLA genotype towards the risk of DILI generally.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.015 | 0.002 |
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".