Additive Effects of Obesity and TCF7L2 Variants on Risk for Type 2 Diabetes Among Cardiac Patients
Bibliographic record
Abstract
A microsatellite marker, DG10S478, in the transcription factor 7-like 2 ( TCF7L2 ) gene was previously associated with type 2 diabetes in three Caucasian populations (1). This association followed earlier reports by the same group (2) and a separate team (3), which showed suggestive linkage to chromosomal 10q. Grant et al. (1) demonstrated that allele X (a composite of all but the shortest allele) of DG10S478 conferred an increased risk for type 2 diabetes of 45 and 141% among heterozygotes and homozygotes, respectively. Since this report, numerous groups have replicated the association in various populations and extended it to include two intronic single nucleotide polymorphisms (rs12255372 and rs7903146) (4–20). In this study, we investigated the combined effect of obesity and genotype at DG10S478 and rs12255372 in predicting type 2 diabetes risk in a sample of French Canadian cardiac patients. Patients of French Canadian descent with established coronary artery disease recruited in two earlier studies, Polymorphisme ( n = 484) and the Epidemiological Study of Acute Coronary Syndromes and the Pathophysiology of Emotions (ESCAPE; n = 596) (21), were included. All participants were identified between November 1998 and April 2002 at the Montreal Heart Institute and Hopital Sacre-Coeur and gave written informed consent. Protocols were approved by the ethics committees at both institutions. Type 2 diabetes was defined as the use of diabetes medications or fasting blood glucose >126 mg/dl (7.0 mmol/l). BMI was calculated as the weight in kilograms …
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".