Regional blood flow signatures of opioidergic modulation of ketamine in major depressive disorder: a randomised crossover study
Bibliographic record
Abstract
Abstract Objective Accumulating evidence suggests the opioid system may modulate ketamine’s rapid antidepressant effects. The objective of this study was to test whether opioid system modulation via naltrexone alters ketamine’s acute effects on regional cerebral blood flow (rCBF) in major depressive disorder (MDD), and whether these changes relate to symptom measures and map onto receptor density profiles. Methods In a randomised, double-blind, crossover study, 26 adults (18–50 years) with MDD completed two sessions: oral naltrexone 50 mg or placebo, each followed by intravenous ketamine 0.5 mg/kg over 40 minutes during 3D pseudo-continuous arterial spin labelling (3D-pCASL) MRI to quantify rCBF. Subjective effects were assessed with the Clinician-Administered Dissociative States Scale and the Psychotomimetic States Inventory; clinical outcomes with the Montgomery–Åsberg Depression Rating Scale and the Quick Inventory of Depressive Symptomatology Self-Report. Exploratory analyses spatially correlated CBF maps with receptor density profiles (MOR, KOR, NMDA, mGluR5, GABAA, GABAAα5), correcting for spatial autocorrelation. Results Ketamine increased CBF in subgenual, pregenual, and dorsal anterior cingulate cortices (p < 0.05, voxel-wise FWE-corrected), effects not attenuated by naltrexone. Under placebo pretreatment, baseline-adjusted infusion pregenual relative rCBF was associated with acute subjective effects (PSI-delusional: r = 0.56, p = 0.004; PSI-perceptual distortion: r = 0.64, p < 0.001), and baseline subgenual rCBF (adjusted for global CBF) was associated with day-one antidepressant response (MADRS r = 0.60, p = 0.002; QIDS-SR r = 0.67, p < 0.001). Naltrexone pretreatment disrupted these associations. Ketamine-induced CBF changes aligned with MOR and mGluR5 receptor profiles; naltrexone’s interaction aligned with MOR, mGluR5 and GABAAα5 (pSA-corr < 0.05). Conclusions This study suggests that ketamine’s effects on CBF in MDD are influenced by complex interactions between glutamatergic, opioidergic, and GABAergic systems. These findings provide mechanistic insights with potential implications for optimising ketamine-based treatments. Registration ClinicalTrials.gov Identifier: NCT04977674
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".