Genetic variant in the glucose transporter type 2 is associated with higher intakes of sugars in two distinct populations
Bibliographic record
Abstract
Glucose sensing in the brain has been proposed to be involved in regulating food intake, but the mechanism is not known. Glucose transporter type 2 (GLUT2)-null mice fail to control their food intake in response to glucose, suggesting a potential role for this transporter as a glucose sensor in the brain. Here we show that individuals with a genetic variation in GLUT2 (Thr110Ile) have a higher daily intake of sugars in two distinct populations. In the first population, compared with individuals with the Thr/Thr genotype, carriers of the Ile allele had a significantly higher intake of sugars as assessed from 3-day food records administered on two separate visits (visit 1: 112 +/- 9 vs. 86 +/- 4 g/day, P = 0.01; visit 2: 111 +/- 8 vs. 82 +/- 4 g/day, P = 0.003), demonstrating within-population reproducibility. In a second population, carriers of the Ile allele also reported consuming a significantly greater intake of sugars (131 +/- 5 vs. 115 +/- 3 g/day, P = 0.007) over a 1-mo period as measured from a food frequency questionnaire. GLUT2 genotypes were not associated with fat, protein, or alcohol intake in either population. These observations were consistent across older and younger adults as well as among subjects with early Type 2 diabetes and healthy individuals. Taken together, our findings show that a genetic variation in GLUT2 is associated with habitual consumption of sugars, suggesting an underlying glucose-sensing mechanism that regulates food intake.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".