Endogenous opioidergic dysregulation of pain in fibromyalgia: a PET and fMRI study
Bibliographic record
Abstract
Endogenous opioid system dysfunction potentially contributes to chronic pain in fibromyalgia (FM), but it is unknown if this dysfunction is related to established neurobiological markers of hyperalgesia. We previously reported that µ-opioid receptor (MOR) availability was reduced in patients with FM as compared with healthy controls in several pain-processing brain regions. In the present study, we compared pain-evoked functional magnetic resonance imaging with endogenous MOR binding and clinical pain ratings in female opioid-naive patients with FM (n = 18) using whole-brain analyses and regions of interest from our previous research. Within antinociceptive brain regions, including the dorsolateral prefrontal cortex (r = 0.81, P < 0.001) and multiple regions of the anterior cingulate cortex (all r > 0.67; all P < 0.02), reduced MOR availability was associated with decreased pain-evoked neural activity. Additionally, reduced MOR availability was associated with lower brain activation in the nucleus accumbens (r = 0.47, P = 0.050). In many of these regions, pain-evoked activity and MOR binding potential were also associated with lower clinical affective pain ratings. These findings are the first to link endogenous opioid system tone to regional pain-evoked brain activity in a clinical pain population. Our data suggest that dysregulation of the endogenous opioid system in FM could lead to less excitation in antinociceptive brain regions by incoming noxious stimulation, resulting in the hyperalgesia and allodynia commonly observed in this population. We propose a conceptual model of affective pain dysregulation in FM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 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) | 0.000 | 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 teacher head, 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".