Sex-specific genetics underlie increased chronic pain risk in women: genome-wide association studies from the UK Biobank
Bibliographic record
Abstract
BACKGROUND: Chronic pain disproportionately affects women, but the reasons for this disparity are unclear. METHODS: We investigated this disparity from a genetic perspective using data from the UK Biobank, focusing on multisite chronic pain, which is highly heritable and manifests a sex bias. RESULTS: Genome-wide association studies (GWAS) revealed that women have approximately 4500 sex-specific causal loci for overlapping pains, four times more than men, accounting for their higher heritability. Heritability partitioning indicated that pain-related loci are primarily enriched in specific brain regions, but only in women. Additionally, 200 imaging-derived brain phenotypes were significantly associated with pain in women, compared with only six in men. GWAS of these brain phenotypes showed stronger genetic correlations with pain in women, particularly regarding cortical thickness and striatal volume. When disentangling pleiotropy from causation in genetically correlated pairs of brain- and pain-related traits, we found that the genetics of brain phenotypes are more often causally implicated with the presence of chronic pain in women. CONCLUSIONS: Our findings suggest that genetics play a crucial role in the increased risk of chronic pain observed in women.
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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 | 0.002 | 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".