The MC4R p.Ile269Asn mutation confers a high risk for type 2 diabetes in the Mexican population via obesity dependent and independent effects
Bibliographic record
Abstract
Abstract We investigated the association between the loss-of-function mutation MC4R p.Ile269Asn and T2D risk in the Mexican population. We enrolled 6929 adults [3175 T2D cases and 3754 normal glucose tolerant (NGT) controls] and 994 NGT children in the study. Anthropometric data and T2D-related quantitative traits were studied in 994 NGT children and 3754 NGT adults. The MC4R p.Ile269Asn mutation was genotyped using TaqMan. The MC4R p.Ile269Asn mutation was associated with T2D [OR = 2.00, 95% confidence interval (CI) 1.35–2.97, p = 0.00057] in Mexican adults. Additional adjustment for body-mass index (BMI) attenuated but did not remove the association (OR = 1.70, 95% CI 1.13–2.56, p = 0.011). The MC4R p.Ile269Asn mutation was associated with T2D (OR = 1.88, 95% CI 1.14–3.08, p = 0.013) in a subset of 1269 T2D cases and 1269 NGT controls matched for sex, age, and BMI. A mediation analysis estimated that BMI accounts for 22.7% of the association between MC4R p.Ile269Asn mutation and T2D risk (p = 4.55 × 10–6). An association was observed between the MC4R p.Ile269Asn mutation and BMI in NGT children and adults (children: beta = 3.731 ± 0.958, p = 0.0001; adults: beta = 2.269 ± 0.536, p = 2.3 × 10–5). In contrast, the mutation was not associated with T2D-related quantitative traits. We demonstrate that the MC4R p.Ile269Asn mutation predisposes to T2D via obesity-dependent and independent effects in the Mexican population.
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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 | 0.001 |
| 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) | 0.002 | 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".