Vitamin C Transporter Gene Polymorphisms, Dietary Vitamin C and Serum Ascorbic Acid
Bibliographic record
Abstract
BACKGROUND/AIMS: Vitamin C transporter proteins SVCT1 and SVCT2 are required for the absorption and transport of vitamin C in humans. This study aims to determine whether common SVCT genotypes modify the association between dietary vitamin C and serum ascorbic acid. METHODS: Non-smoking men and women (n=1,046) aged 20-29 were participants of the Toronto Nutrigenomics and Health Study. Overnight fasting blood samples were collected to determine serum ascorbic acid concentrations by HPLC and to genotype for two SVCT1 (rs4257763 and rs6596473) and two SVCT2 (rs6139591 and rs2681116) polymorphisms. RESULTS: No diet-gene interactions were observed for the vitamin C transporter polymorphisms, however, the average (mean+/-SE) serum ascorbic acid concentrations differed between rs4257763 genotypes (GG: 24.4+/-1.3, GA: 26.8+/-1.1, AA: 29.7+/-1.4 micromol/l; p=0.002). For this polymorphism, the correlation between dietary vitamin C and serum ascorbic acid was only significant in subjects with a G allele. The SVCT2 polymorphisms also appeared to modify the strength of the diet-serum correlation. CONCLUSIONS: Our findings demonstrate that genetic variation in SVCT1 can influence serum ascorbic acid concentrations and that SVCT1 and SVCT2 genotypes modify the strength of the correlation between dietary vitamin C and serum ascorbic acid.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".