The Contribution of Baseline Circulating Endocannabinoids to Individual Differences in Human Pain Sensitivity: A Quantitative Sensory Testing Study
Bibliographic record
Abstract
ABSTRACT The endocannabinoid (eCB) system—comprising cannabinoid receptors, eCBs (anandamide— AEA, 2-arachidonoylglycerol—2-AG) and related N -acylethanolamines (NAEs; N- palmitoylethanolamide—PEA, and N- oleoylethanolamide—OEA), and metabolizing enzymes (e.g., fatty acid amide hydrolase; FAAH)—modulates nociceptive circuits in rodents. In humans, the FAAH C385A polymorphism is associated with reduced pain sensitivity, suggesting eCB tone influences individual pain differences, but this has yet to be tested. Here, we determined whether the eCB system is associated with somatosensory and pain sensitivity measured with quantitative sensory testing (QST) in 91 healthy participants (39 males, 52 females). We tested three hypotheses: (1) FAAH C385A polymorphism, cannabis use, and sex affect serum eCB/NAE concentrations; (2) FAAH C385A carriers show altered pain sensitivity versus non-carriers; and (3) baseline serum eCB/NAE concentrations are associated with QST measures. eCB/NAE concentrations were not statistically different based on sex ( p > .05), based on FAAH genotype ( p > .05), and based on cannabis use ( p > .05). To address collinearity of AEA, OEA and PEA, we performed a principal components analysis, which identified a single component of FAAH substrates. Linear regressions found that FAAH genotype did not affect QST measures and that baseline 2-AG and FAAH substrate concentrations were not associated with QST measures, except pressure pain thresholds (PPT; p = 0.003), which were associated with AEA and OEA. Baseline eCB/NAE levels and FAAH genotype are not associated with the outcome measures of standard QST tests that rely on point estimates in healthy adult humans; nonetheless, circulating FAAH substrate levels were associated with PPT.
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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 | 0.003 |
| 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) | 0.002 | 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".