Association Between Caffeine Intake and the Plasma Proteome in Humans
Bibliographic record
Abstract
Background: Caffeine intake has been associated with both an increased and decreased risk of various health conditions. However, many of the physiological pathways affected remain unclear. CYP1A2 is the major enzyme that metabolizes caffeine, and a single nucleotide polymorphism (rs762551) affects the rate of caffeine metabolism. Objective: The aim of this study was to determine the association between caffeine intake and the plasma proteome, and whether CYP1A2 genotype modifies any association. Methods: Subjects (n=1,095) aged 20–29 years from the Toronto Nutrigenomics and Health Study completed a 196-item semi-quantitative food frequency questionnaire and provided a fasting blood sample from which DNA and plasma were obtained for genotyping and proteomics analysis. Fifty-four proteins were measured by mass spectrometry multiple reaction monitoring (MS-MRM). Subjects were categorized into three groups according to habitual caffeine intake (<100 mg/d, 100–200 mg/d, and >200 mg/d) and stratified by CYP1A2 genotype. Results: Among carriers of the C allele (slow metabolizers), plasma concentrations of gelsolin isoform 1 were significantly (p<0.005) lower among those in the highest category of caffeine intake compared to those with the lowest level of intake. No differences in protein concentration were observed for AA homozygotes (fast metabolizers). Conclusion: These findings show that caffeine intake is associated with lower gelsolin levels only among slow caffeine metabolizers, and suggest that gelsolin might mediate some of the biological effects of caffeine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".