The Role of Myeloperoxidase in Clozapine-Induced Inflammation: A Mechanistic Update for Idiosyncratic Drug-Induced Agranulocytosis
Bibliographic record
Abstract
The risk of idiosyncratic drug-induced agranulocytosis (IDIAG) markedly constrains the use of clozapine, a neuroleptic with unparalleled efficacy. Most clozapine patients experience an early inflammatory response, likely a necessary step in IDIAG onset. However, most patients do not progress to IDIAG, presumably because of the requirement of specific human leukocyte antigen (HLA) haplotypes, T cell receptors, and other unknown factors. We established that clozapine activates inflammasomes and that myeloperoxidase bioactivation of clozapine generates neoantigens, but the connection between these early mechanistic events remained unknown and, thus, was the aim of this work. We found that the myeloperoxidase inhibitor PF-1355 attenuated myeloperoxidase activity in phorbol myristate acetate (PMA)-differentiated THP-1 macrophages, and it also attenuated clozapine-induced release of inflammatory mediators (e.g., IL-1β, CXCL1, and C-reactive protein). In vivo, pretreatment of Sprague Dawley rats with PF-1355 significantly attenuated clozapine-induced increases in neutrophil mobilization from the bone marrow to the blood and spleen, as determined using differential blood counts and flow cytometry. Moreover, the clozapine-triggered release of inflammatory mediators (e.g., IL-1β, calprotectin, CXCL1, and α-1-acid glycoprotein) from the liver, spleen, and bone marrow was dampened by myeloperoxidase inhibition. These data support the working hypothesis that oxidation of clozapine to a reactive metabolite by myeloperoxidase is critical for induction of the inflammatory response to clozapine. Ultimately, a better mechanistic understanding of the early events involved in the immune response to clozapine may elucidate ways to prevent IDIAG, enabling safer, more frequent therapeutic use of this and potentially other highly efficacious drugs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".