Endocannabinoids and related lipids linked to social exclusion in individuals with chronic non-medical prescription opioid use
Bibliographic record
Abstract
Opioid-related overdose deaths are still on the rise in North America, emphasizing the need to better understand the underlying neurobiological mechanisms regarding the development of opioid use disorder (OUD). Recent evidence from preclinical and clinical studies indicate that the endocannabinoid system (ECS) may play a crucial role in stress and reward, both involved in the development and maintenance of substance use disorders. Animal models demonstrate a specific crosstalk between the ECS and the endogenous opioid system. However, translational studies in humans are scarce. Here, we investigated basal plasma levels of the endocannabinoids anandamide (AEA) and 2-arachidonoyglycerol (2-AG), and eight endocannabinoid-related lipids, including oleoylethanolamide (OEA) and palmitoylethanolamide (PEA), as well as whole blood fatty acid amide hydrolase (FAAH) activity in chronic non-medical prescription opioid users (NMPOU; n = 21) compared to opioid-naïve healthy controls (n = 29) considering age, sex, and cannabis use as potential confounders. Additionally, the association of endocannabinoids and related lipids with the participants' response to experimentally induced social exclusion was examined. We found significantly elevated basal AEA, OEA, and PEA levels in NMPOU compared to controls, but no differences in FAAH activity, 2-AG, or other endocannabinoid-related lipids. Within NMPOU, higher AEA levels were associated with lower perception of social exclusion. Robust positive correlations within N-acylethanolamines (i.e., AEA, OEA, and PEA) indicate strong metabolic associations. Together with our recent findings of elevated basal 2-AG levels in dependent cocaine users, present results indicate substance-specific alterations of the ECS that may have implications in the search for novel therapeutic interventions for these populations.
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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 | 0.000 |
| 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) | 0.001 | 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".