HLA-DQB1 6672G>C (rs113332494) is associated with clozapine-induced neutropenia and agranulocytosis in individuals of European ancestry
Bibliographic record
Abstract
Abstract The atypical antipsychotic clozapine is the only effective medication for treatment-resistant schizophrenia. However, it can also induce serious adverse drug reactions, including agranulocytosis and neutropenia. The mechanism by which it does so is largely unknown, but there is evidence for contributing genetic factors. Several studies identified HLA-DQB1 variants and especially a polymorphism located in HLA-DQB1 (6672G>C, rs113332494) as associated with clozapine-induced agranulocytosis and neutropenia. We analysed the risk allele distribution of SNP rs113332494 in a sample of 1396 controls and 178 neutropenia cases of which 60 developed agranulocytosis. Absolute neutrophil counts of 500/mm 3 and 1500/mm 3 were used for defining agranulocytosis and neutropenia cases, respectively. We also performed association analyses and analysed local ancestry patterns in individuals of European ancestry, seeking replication and extension of earlier findings. HLA-DQB1 (6672G>C, rs113332494) was associated with neutropenia (OR = 6.20, P = 2.20E−06) and agranulocytosis (OR = 10.49, P = 1.83E−06) in individuals of European ancestry. The association signal strengthened after including local ancestry estimates (neutropenia: OR = 10.38, P = 6.05E−08; agranulocytosis: OR = 16.31, P = 1.39E−06), with effect sizes being considerably larger for agranulocytosis. Using local ancestry estimates for prediction, the sensitivity of rs113332494 increased from 11.28 to 55.64% for neutropenia and from 16.67 to 53.70% for agranulocytosis. Our study further strengthens the evidence implicating HLA-DQB1 in agranulocytosis and neutropenia, suggesting components of the immune system as contributing to this serious adverse drug reaction. Using local ancestry estimates might help in identifying risk variants and improve prediction of haematological adverse effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".