Genetic associations with clozapine-induced myocarditis in patients with schizophrenia
Bibliographic record
Abstract
Abstract Clozapine is the most effective antipsychotic drug for schizophrenia, yet it can cause life-threatening adverse drug reactions, including myocarditis. The aim of this study was to determine whether schizophrenia patients with clozapine-induced myocarditis have a genetic predisposition compared with clozapine-tolerant controls. We measured different types of genetic variation, including genome-wide single-nucleotide polymorphisms (SNPs), coding variants that alter protein expression, and variable forms of human leucocyte antigen (HLA) genes, alongside traditional clinical risk factors in 42 cases and 67 controls. We calculated a polygenic risk score (PRS) based on variation at 96 different genetic sites, to estimate the genetic liability to clozapine-induced myocarditis. Our genome-wide association analysis identified four SNPs suggestive of increased myocarditis risk (P < 1 × 10−6), with odds ratios ranging 5.5–13.7. The SNP with the lowest P value was rs74675399 (chr19p13.3, P = 1.21 × 10−7; OR = 6.36), located in the GNA15 gene, previously associated with heart failure. The HLA-C*07:01 allele was identified as potentially predisposing to clozapine-induced myocarditis (OR = 2.89, 95% CI: 1.11–7.53), consistent with a previous report of association of the same allele with clozapine-induced agranulocytosis. Another seven HLA alleles, including HLA-B*07:02 (OR = 0.25, 95% CI: 0.05–1.2) were found to be putatively protective. Long-read DNA sequencing provided increased resolution of HLA typing and validated the HLA associations. The PRS explained 66% of liability (P value = 9.7 × 10−5). Combining clinical and genetic factors together increased the proportion of variability accounted for (r2 0.73, P = 9.8 × 10−9). However, due to the limited sample size, individual genetic associations were not statistically significant after correction for multiple testing. We report novel candidate genetic associations with clozapine-induced myocarditis, which may have potential clinical utility, but larger cohorts are required for replication.
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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) | 0.003 | 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".