Epistasis between polymorphisms in COMT, ESR1, and GCH1 influences COMT enzyme activity and pain
Bibliographic record
Abstract
Abnormalities in the enzymatic activity of catechol-O-methyltransferase (COMT) contribute to chronic pain conditions, such as temporomandibular disorders (TMD). Thus, we sought to determine the effects of polymorphisms in COMT and functionally related pain genes in the COMT pathway (estrogen receptor 1 [ESR1], guanosine-5-triphosphate cyclohydrolase 1 [GCH1], methylenetetrahydrofolate reductase [MTHFR]) on COMT enzymatic activity, musculoskeletal pain, and pain-related intermediate phenotypes among TMD cases and healthy control subjects. Results show that the COMT rs4680 (val(158)met) polymorphism is most strongly associated with outcome measures, such that individuals with the minor A allele (met) exhibit reduced COMT activity, increased TMD risk, and increased musculoskeletal pain. Epistatic interactions were observed between the COMT rs4680 polymorphism and polymorphisms in GCH1 and ESR1. Among individuals with the COMT met allele, those with 2 copies of the GCH1 rs10483639 minor G allele exhibit normalized COMT activity and increased mechanical pain thresholds. Among individuals with the COMT val allele, those with 2 copies of the ESR1 rs3020377 minor A allele exhibit reduced COMT activity, increased bodily pain, and poorer self-reported health. These data reveal that the GCH1 minor G allele confers a protective advantage among met carriers, whereas the ESR1 minor A allele is disadvantageous among val carriers. Furthermore, these data suggest that the ability to predict the downstream effects of genetic variation on COMT activity is critically important to understanding the molecular basis of chronic pain conditions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".