CYP1A2 Genotype Polymorphism Influences the Effect of Caffeine on Anaerobic Performance in Trained Males
Bibliographic record
Abstract
The purpose was to investigate the effects of CYP1A2 -163C > A polymorphism on the effects of acute caffeine (CAF) supplementation on anaerobic power in trained males. Sixteen trained males (age: 21.6 ± 7.1 years; height: 179.7 ± 5.6 cm; body mass: 72.15 ± 6.8 kg) participated in a randomized, double-blind, placebo (PLA) controlled crossover design. Participants supplemented with CAF (6 mg/kg of body mass) and an isovolumetric PLA (maltodextrin) in random order and separated by 7 days, before an all-out 30-s anaerobic cycling test to determine peak, average, and minimum power output, and fatigue index. Genomic deoxyribonucleic acid was extracted to identify each participants CYP1A2 genotype. Six participants expressed AA homozygote and 10 expressed C alleles. There was a treatment by genotype interaction for peak power output (p = .041, η2 = .265, observed power = 0.552) with only those expressing AA genotype showing improvement following CAF supplementation compared with PLA (CAF: 693 ± 108 watts vs. PLA: 655 ± 97 watts; p = .039), while no difference between treatments was noted in those expressing C alleles (CAF: 614 ± 92 watts vs. PLA: 659 ± 144 watts; p = .135). There were no other interaction or main effects for average or minimum power output, or fatigue index (p > .05). In conclusion, the ingestion of 6 mg/kg of CAF improved peak power output only in participants with the AA genotype compared with PLA; however, expression of the CYP1A2 did not influence average or minimum power output or fatigue index.
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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 | 0.000 |
| 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".