Ethnicity interacts with the OPRM1 gene in experimental pain sensitivity
Bibliographic record
Abstract
Robust interindividual variation in pain sensitivity has been observed, and recent evidence suggests that some of the variability may be genetically mediated. Our previous data revealed significantly higher pressure pain thresholds among individuals possessing the minor G allele of the A118G SNP of the mu-opioid receptor gene (OPRM1) compared with those with 2 consensus alleles. Moreover, ethnic differences in pain sensitivity have been widely reported. Yet, little is known about the potential interactive associations of ethnicity and genotype with pain perception. This study aimed to identify ethnic differences in OPRM1 allelic associations with experimental pain responses. A total of 247 healthy young adults from three ethnic groups (81 African Americans; 79 non-white Hispanics; and 87 non-Hispanic whites) underwent multiple experimental pain modalities (thermal, pressure, ischemic, cold pressor). Few African Americans (7.4%) expressed the rare allele of OPRM1 compared to non-Hispanic whites and Hispanics (28.7% vs. 27.8%, respectively). Across the entire sample, OPRM1 genotype did not significantly affect pain sensitivity. However, analysis in each ethnic group separately revealed significant genotype effects for most pain modalities among non-Hispanic-whites (P<.05) but not Hispanics or African Americans. The G allele was associated with decreased pain sensitivity among whites only; a trend in the opposite direction emerged in Hispanics. The reasons for this dichotomy are unclear; they may involve ethnic differences in haplotypic structure, or A118G may be a tag-SNP linked to other functional polymorphisms. These findings demonstrate an ethnicity-dependent association of OPRM1 genotype with pain sensitivity. Additional research is warranted to uncover the mechanisms influencing these relationships.
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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 | 0.009 | 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) | 0.000 | 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".