Spinal opioid-adrenergic analgesic interactions: mechanistic insights on the role of the delta opioid and the alpha2A adrenergic receptors
Bibliographic record
Abstract
Opioid and α2-adrenergic receptor (α2AR) ligands are both analgesic when administered spinally and show a clinically beneficial synergistic interaction in the treatment of pain when co-administered. The µ- and δ-opioid receptors (MOR and DOR respectively) and the α2AARs have been shown to be capable of mediating opioid-adrenergic synergistic interactions. The development of new therapeutic approaches that exploit the combination of opioids and α2AR agonists is currently hindered by limited mechanistic knowledge on how these drugs interact at the spinal level. It is generally accepted that MOR mediates morphine antinociception. However, since morphine-related interactions between MOR and DOR have been reported at the spinal level, the role of DOR in spinal morphine antinociception requires further evaluation. Therefore, the First Aim of this thesis was to investigate the role of DOR in the antinociceptive effect of morphine and other opioids at the spinal level. Using the hot water tail flick assay, we observed that morphine was equally potent, but less effective in DOR-knockout (KO) mice compared to wild type (WT) mice. On the other hand, the efficacy of the DOR-selective agonists DeltII and SNC80 was maintained in DOR-KO mice. This study therefore suggests that 1) DOR is necessary to obtain full spinal morphine antinociceptive efficacy and 2) that DOR agonists are not selective in the tail flick assay. These observations from Aim 1 raised two important questions: 1) Is DOR necessary to produce a morphine synergistic interaction with an α2AR agonist? 2) Is DOR activation by DOR agonists sufficient to obtain a synergistic interaction with an α2AR agonist? Thus, the Second Aim of this thesis was to determine whether DOR activation is sufficient and necessary to mediate opioid-adrenergic synergistic interactions in the spinal cord. The absence of DeltII antinociception in DOR-KO mice confirmed its selectivity in the substance P behavioral assay, therefore validating the choice of this assay. Opioid-adrenergic drug interactions were evaluated following spinal co-administration of the α2AR agonist clonidine with DeltII, morphine or DAMGO in WT and DOR-KO mice. Our results showed that DeltII+clonidine synergy is DOR-dependent, morphine+clonidine synergy is not DOR-dependent and DAMGO+clonidine do not interact synergistically. These findings confirm that DOR activation is sufficient but not necessary for synergy with α2AR agonists.The Third Aim of this thesis was to investigate the role of α2AAR in spinal opioid-adrenergic synergy and opioid antinociception. We first confirmed that the α2AAR mediates the synergistic interaction between clonidine and either morphine or DeltII. We also observed a potentiation of spinal morphine and spinal DeltII-mediated antinociception in α2AAR-KO mice compared to WT mice; this potentiation could not be attributed to changes in the expression of opioid receptors, to alterations in opioid ligand binding properties or to enhanced noradrenergic tone in the spinal cord. Together, these findings led us to propose a model whereby the α2AAR allosterically modulates spinal opioid receptors in an activation state-dependent manner. These studies improve our understanding of the interaction between α2-adrenergic and opioid drugs at the spinal level, which could lead to new the development of better pharmacological treatments for pain management.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".