Vitamin C Transporter Gene SLC23A1 Polymorphisms and Fasting Plasma Ascorbate
Bibliographic record
Abstract
Vitamin C transporter protein SVCT1, encoded by the SLC23A1 gene, is required for intestinal absorption and renal reabsorption of vitamin C in humans. The purpose of this study was to determine whether polymorphisms of SLC23A1 alter fasting plasma concentrations of ascorbate (vitamin C). We recruited 406 non‐smokers aged 20–29 years. Blood samples were collected to determine fasting plasma ascorbate concentrations and to isolate DNA to determine SLC23A1 genotypes (1091T>C and 2515G>C) by real‐time PCR. For the 1091T>C polymorphism, the frequency of the C allele differed between Caucasians (63%), Asians (29%) and South East Asians (49%) (p<0.0001). The frequency of the C allele for the 2515G>C polymorphism also differed between Caucasians (34%), Asians (64%) and South East Asians (49%) (p<0.0001). However, average plasma ascorbate concentrations (mean ± SD μmol/L) did not vary between the TT (30.2±13.4), TC (32.8±14.8) and CC (29.8±14.6) genotypes for the 1091T>C polymorphism (p = 0.22), or between the GG (30.8±15.9), GC (31.8±13.7) and CC (30.8±13.8) genotypes for the 2515G>C polymorphism (p = 0.52). These associations were not modified by sex or ethnicity. Our findings indicate that two common polymorphisms of the SLC23A1 gene do not affect concentrations of fasting plasma ascorbate. The role of SLC23A1 genotypes in modifying the association between dietary and plasma ascorbate remains to be determined. (Supported by AFMNet.)
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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) | 0.003 | 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".