Synergism between mutant <i>HNF1A</i> and the metabolic syndrome in Oji‐Cree Type 2 diabetes
Bibliographic record
Abstract
AIMS: To determine the prevalence of the metabolic syndrome in the Sandy Lake Oji-Cree and to examine its interaction with HNF1A in association with impaired glucose tolerance and Type 2 diabetes. METHODS: Using data collected from the Sandy Lake Health and Diabetes Project (1993-1995), the presence or absence of the metabolic syndrome was determined in 515 Oji-Cree subjects, > or = 18 years of age. In the original study, fasting plasma analytes were measured, a 75-g oral glucose tolerance test was administered, and subjects were genotyped for HNF1A G319S. RESULTS: The unadjusted prevalence of the metabolic syndrome in the Oji-Cree adults was 29.9%. The adjusted odds ratio (OR) and 95% confidence interval for Type 2 diabetes among subjects who carried the HNF1A G319S mutation and had the modified metabolic syndrome (excluding hyperglycaemia) was 20.3 (6.94, 59.6). Adjusted ORs for Type 2 diabetes for subjects with either the HNF1A G319S mutation alone or the modified metabolic syndrome alone were 5.56 (2.85, 10.9) and 4.84 (2.53, 9.27), respectively. The risk of having impaired glucose tolerance was not influenced by the presence of either factor. CONCLUSIONS: The risk of Type 2 diabetes was similar (approximately five-fold increased) for subjects with either the presence of the modified metabolic syndrome or the private HNF1A G319S mutation. Interestingly, when present in combination, the two independent risk factors appeared to act synergistically to confer an even greater increased risk of Type 2 diabetes.
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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 | 0.001 | 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".