Epigenetics for Drug Discovery: Dissecting the Effect of High Antipsychotic Dosage and D2 Blockage on Peripheral DNA Methylation
Bibliographic record
Abstract
INTRODUCTION: The relationship between genetic polymorphisms of antipsychotic drug-metabolizing agents and drug receptors has been often investigated. DNA methylation is a form of epigenetic modification that regulates gene expression. Few studies have analyzed the relationship between genome-wide methylation patterns and antipsychotic dosage. The primary aim of this pilot study was to investigate the association between antipsychotic dosage and genome-wide DNA methylation in patients with schizophrenia (SCZ). METHODS: Current dosage of antipsychotic medications was assessed in 136 patients with SCZ. Dosage was standardized using three different methods: chlorpromazine equivalent dose (CPZe), defined daily dose (DDD), and percentage of Lexicomp maximum dose (PM%). DNA methylation was measured in white blood cells. Antipsychotic dosage was the primary outcome variable in a model, including genome-wide methylation status as the main predictor. RESULTS: This study did not show any association between DNA methylation and dosage variation for CPZe, PM%, and DDD. However, the probe cg271403389 was consistently associated with antipsychotic dosage across the three standardization methods. When looking at the genomic location of the most significant probes, we found that 15% were intergenic, 23% were in the distal promoter, 9% in the 3'untranslated region, 32% in the gene body, 3% in the 5' untranslated region, 15% in the proximal promoter, and 3% in the first exon. DISCUSSION: This study shows the importance of investigating the relationship between DNA methylation and optimal antipsychotic dosage to personalize treatment in SCZ. Future studies require larger prescription databases to build on the results of this analysis.
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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 | 0.001 | 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".