Catechol-O-methyltransferase val158met genotype determines effect of reboxetine on emotional memory in healthy male volunteers
Bibliographic record
Abstract
BACKGROUND: Catechol-O-methyltransferase (COMT) metabolizes catecholamines in the prefrontal cortex (PFC). A common polymorphism in the COMT gene (COMT val158met) has pleiotropic effects on cognitive and emotional processing. The met allele has been associated with enhanced cognitive processing but impaired emotional processing relative to the val allele. METHODS: We genotyped healthy, white men in relation to the COMT val158met polymorphism. They were given a single 4 mg dose of the selective noradrenaline reuptake inhibitor (NRI) reboxetine or placebo in a randomized, double-blind between-subjects model and then completed an emotional memory task 2 hours later. RESULTS: We included 75 men in the study; 41 received reboxetine and 34 received placebo. In the placebo group, met/met carriers did not demonstrate the usual memory advantage for emotional stimuli that was observed in val carriers. Reboxetine restored this emotional enhancement of memory in met/met carriers, but had no significant effect in val carriers. LIMITATIONS: We studied only men, thus limiting the generalizability of our findings. We also relied on self-reported responses to screening questions to establish healthy volunteer status, and in spite of the double-blind design, participants were significantly better than chance at identifying their intervention allocation. CONCLUSION: Emotional memory is impaired in healthy met homozygotes and selectively improved in this group by reboxetine. This has potential translational implications for the use of reboxetine, which is currently licensed as an antidepressant in several countries, and edivoxetine, a new selective NRI currently in development.
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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) | 0.000 | 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) | 0.002 | 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".