Influence of Catechol-O-Methyltransferase Gene Polymorphism on the Correlation between Alexithymia and Hypervigilance to Pain
Bibliographic record
Abstract
The psychological characteristic of having difficulty expressing emotions, known as alexithymia, is associated with hypervigilance to pain and is considered one of the risk factors for chronic pain. The correlation between alexithymia and hypervigilance to pain can be observed even in healthy individuals. However, the factors influencing this correlation remain unknown. We explored the dopamine system, which is known to be involved in emotion and pain. The dopamine-degrading enzyme catechol-O-methyltransferase (COMT) has a genetic polymorphism known to influence dopamine metabolism in the prefrontal cortex. COMT polymorphism reportedly affects various aspects of pain and increases pain sensitivity in Met allele carriers. Therefore, we investigated whether the correlation between alexithymia and hypervigilance to pain is influenced by COMT polymorphism in healthy individuals. The results revealed a significant positive correlation between the "difficulty describing feelings" of the 20-item Toronto Alexithymia Scale and the "attention to changes in pain" of the pain vigilance and awareness questionnaire in COMT Met carriers but not in Val/Val individuals. This finding suggests that the correlation between alexithymia and hypervigilance to pain is influenced by COMT polymorphism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".