A Positron Emission Tomography Study of Norepinephrine Transporter Occupancy and Its Correlation with Symptom Response in Depressed Patients Treated with Quetiapine XR
Bibliographic record
Abstract
Background: Quetiapine is effective in treating depressive symptoms in major depressive disorder and bipolar disorder, but the mechanisms underlying its antidepressants effects are unknown. Norquetiapine, a metabolite of quetiapine, has high affinity for norepinephrine transporter, which might account for its therapeutic efficacy. Methods: In this study, we used positron emission tomography with (S,S)-[11C]O-methyl reboxetine to estimate norepinephrine transporter density and assess the relationship between norepinephrine transporter occupancy by quetiapine XR and improvement in depression in patients with major depressive disorder (n=5) and bipolar disorder (n=5). After the baseline positron emission tomography scan, patients were treated with quetiapine XR with a target dose of 150 mg in major depressive disorder and 300 mg in bipolar disorder. Patients had a second positron emission tomography scan at the end of week 2 and a final scan at week 7. Results: Norepinephrine transporter density was significantly lower in locus ceruleus in patients compared with healthy subjects. Further, there was a significant positive correlation between quetiapine XR dose and norepinephrine transporter occupancy in locus ceruleus at week 2. The norepinephrine transporter occupancy at week 2 in hypothalamus but not in other regions predicted improvement in depression as reflected by reduction in MADRS scores from baseline to week 7. The estimated dose of quetiapine XR associated with 50% norepinephrine transporter occupancy in hypothalamus at week 2 was 256 mg and the estimated plasma levels of norquetiapine to achieve 50% norepinephrine transporter occupancy was 36.8 µg/L. Conclusion: These data provide preliminary support for the hypothesis that norepinephrine transporter occupancy by norquetiapine may be a contributor to the antidepressant effects of quetiapine.
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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 | 0.000 | 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) | 0.001 | 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".