Genetic variant rs3750625 in the 3′UTR of ADRA2A affects stress-dependent acute pain severity after trauma and alters a microRNA-34a regulatory site
Bibliographic record
Abstract
α2A adrenergic receptor (α2A-AR) activation has been shown in animal models to play an important role in regulating the balance of acute pain inhibition vs facilitation after both physical and psychological stress. To our knowledge, the influence of genetic variants in the gene encoding α2A-AR, ADRA2A, on acute pain outcomes in humans experiencing traumatic stress has not been assessed. In this study, we tested whether a genetic variant in the 3'UTR of ADRA2A, rs3750625, is associated with acute musculoskeletal pain (MSP) severity following motor vehicle collision (MVC, n = 948) and sexual assault (n = 84), and whether this influence was affected by stress severity. We evaluated rs3750625 because it is located in the seed binding region of miR-34a, a microRNA (miRNA) known to regulate pain and stress responses. In both cohorts, the minor allele at rs3750625 was associated with increased musculoskeletal pain in distressed individuals (stress*rs3750625 P = 0.043 for MVC cohort and P = 0.007 for sexual assault cohort). We further found that (1) miR-34a binds the 3'UTR of ADRA2A, (2) the amount of repression is greater when the minor (risk) allele is present, (3) miR-34a in the IMR-32 adrenergic neuroblastoma cell line affects ADRA2A expression, (4) miR-34a and ADRA2A are expressed in tissues known to play a role in pain and stress, (5) following forced swim stress exposure, rat peripheral nerve tissue expression changes are consistent with miR-34a regulation of ADRA2A. Together, these results suggest that ADRA2A rs3750625 contributes to poststress musculoskeletal pain severity by modulating miR-34a regulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".