Differential Effects of Aripiprazole on D <sub>2</sub> , 5-HT <sub>2</sub> , and 5-HT <sub>1A</sub> Receptor Occupancy in Patients With Schizophrenia: A Triple Tracer PET Study
Bibliographic record
Abstract
OBJECTIVE: Aripiprazole has a unique pharmacological profile that includes partial agonism at D(2) receptors, antagonism at 5-HT(2) receptors, and partial agonism at 5-HT(1A) receptors. The authors conducted a positron emission tomography (PET) study to characterize the simultaneous effects of aripiprazole at the D(2), 5-HT(2), and 5-HT(1A) receptors in patients with schizophrenia or schizoaffective disorder. METHOD: Twelve patients who had previously received antipsychotic treatment were randomly assigned to receive 10 mg, 15 mg, 20 mg, or 30 mg of aripiprazole. After at least 14 days of treatment, participants underwent high-resolution PET scans using [(11)C]raclopride, [(18)F]setoperone, and [(11)C]WAY100635. RESULTS: Very high occupancy was observed at striatal D(2) receptors (average putamen, 87%; caudate, 93%; and ventral striatum, 91%), lower occupancy at 5-HT(2) receptors (54%-60%), and even lower occupancy at 5-HT(1A) receptors (16%). D(2) occupancy levels were significantly correlated with plasma drug concentrations, and even the lowest dose (10 mg) led to 85% D(2) occupancy. Extrapyramidal side effects were seen only in two of the four participants with occupancies exceeding 90%. CONCLUSIONS: Aripiprazole exhibits a unique occupancy profile as compared with other conventional and atypical antipsychotics. The threshold for response appears to be higher than 60%, extrapyramidal side effects appear to be uncommon even at occupancies that exceed the conventional extrapyramidal side effects threshold of 80%, and 5-HT(2) occupancy is lower than D(2) occupancy. Implications for aripiprazole's mechanism of action are discussed.
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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) | 0.001 | 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) | 0.002 | 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".