The Common Polymorphisms (Single Nucleotide Polymorphism [SNP] +45 and SNP +276) of the Adiponectin Gene Predict the Conversion From Impaired Glucose Tolerance to Type 2 Diabetes
Bibliographic record
Abstract
Adiponectin is an adipose tissue-specific protein with insulin-sensitizing and antiatherogenic properties. Therefore, the adiponectin gene is a promising candidate gene for type 2 diabetes. We investigated the single nucleotide polymorphisms (SNPs) +45T/G and +276G/T of the adiponectin gene as predictors for the conversion from impaired glucose tolerance to type 2 diabetes in the STOP-NIDDM trial, which aimed to investigate the effect of acarbose compared with placebo on the prevention of type 2 diabetes. Compared with the TT genotype, the G-allele of SNP +45 was associated with a 1.8-fold risk for type 2 diabetes (95% CI 1.12-3.00, P = 0.015) in the placebo group. Subjects treated with placebo and simultaneously having the G-allele of SNP +45 and the T-allele of SNP +276 (the risk genotype combination) had a 4.5-fold (1.78-11.3, P = 0.001) higher risk of developing type 2 diabetes compared with subjects carrying neither of these alleles. Women carrying the risk genotype combination had an especially high risk of conversion to diabetes (odds ratio 22.2, 95% CI 2.7-183.3, P = 0.004). In conclusion, the G-allele of SNP +45 is a predictor for the conversion to type 2 diabetes. Furthermore, the combined effect of SNP +45 and SNP +276 on the development of type 2 diabetes was stronger than that of each SNP alone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".