Catechol- <i>O</i> -Methyltransferase Genotype Is Associated with Self-Reported Increased Heart Rate Following Caffeine Consumption
Bibliographic record
Abstract
Rationale: The mechanisms underlying the various acute effects of caffeine are not clear. Some of the physiological effects of caffeine may be mediated through increased catecholamines, which are metabolized by catechol-O-methyltransferase (COMT). A Val158Met polymorphism in COMT affects enzyme activity with Val/Val homozygotes having a 3–4-fold greater activity than Met/Met homozygotes. Objective: To determine whether the self-reported acute effects of caffeine are associated with the COMT Val158Met polymorphism (rs4680). Methods: Subjects were men (n=344) and women (n=801) aged 20–29 years who were participants of the Toronto Nutrigenomics and Health Study. Acute effects were assessed by questionnaire, and caffeine intake was assessed using a semiquantitative food frequency questionnaire. Odds ratios (OR) and 95% confidence intervals (CI) were calculated to determine if the likelihood of reporting an acute effect was associated with COMT genotype. Results: Among individuals consuming more than 200 mg/day of caffeine, COMT genotype was associated with self-reported increased heart rate. Compared to the Val/Val genotype, the adjusted OR (95% CI) of reporting increased heart rate for the Val/Met and the Met/Met genotypes was 1.43 (0.64, 3.20) and 2.98 (1.04, 8.51), respectively. Conclusions: These findings show that the Met/Met genotype, conferring slow COMT activity, is associated with self-reported increased heart rate after caffeine intake. This observation suggests that caffeine may increase heart rate in a genetic subset of the population who have an impaired ability to breakdown catecholamines such as epinephrine and norepinephrine.
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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 | 0.000 |
| 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 | 0.001 | 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".