The efficacy of elevating anandamide via inhibition of fatty acid amide hydrolase (FAAH) combined with internet-delivered cognitive behavioral therapy in the treatment of post-traumatic stress disorder: a randomized, placebo-controlled clinical trial
Bibliographic record
Abstract
Post-traumatic stress disorder (PTSD) is a severe mental health disorder with limited treatment options. Gold standard treatment includes cognitive behavioral therapies (CBT) that incorporate exposure to traumatic memories to facilitate extinction. CBT can be effective in PTSD, but effects are incomplete and symptoms are prone to spontaneous return. Pharmacologically facilitating fear extinction could potentiate the effects of exposure-based therapy. Here, we explored whether targeting the endocannabinoid (eCB) system, a neuromodulatory system critically involved in fear extinction, would promote the efficacy of exposure-based CBT. Specifically, we tested the effects of elevating the eCB ligand anandamide (AEA) via inhibition of its main degradative enzyme, fatty acid amide hydrolase (FAAH). In this double-blind, placebo-controlled study, patients with PTSD (N = 100; 85 women) were randomized to the FAAH inhibitor (FAAHi) JNJ-42165279 (25 mg b.i.d.) or placebo for 12 weeks. In weeks 5-12, all participants completed an internet-delivered CBT that included exposure-based modules. The primary outcome was clinician-assessed PTSD symptom severity (CAPS-5). Secondary outcomes included self-reported symptoms of PTSD, depression, anxiety, and sleep quality. Blood samples were taken to measure levels of drug and eCBs. Overall, PTSD symptoms improved over time. While FAAHi increased AEA levels, there was no effect of FAAHi on PTSD symptoms or any secondary measure. FAAHi combined with internet-delivered CBT did not improve PTSD symptoms to a greater extent than internet-delivered CBT alone. Thus, FAAH inhibition does not appear to be a suitable adjunct treatment for enhancing CBT in PTSD. This study was registered as Eudra-CT 2020-001965-36.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".