Single Nucleotide Polymorphisms of <i>PPARD</i> in Combination With the Gly482Ser Substitution of <i>PGC-1A</i> and the Pro12Ala Substitution of <i>PPARG2</i> Predict the Conversion From Impaired Glucose Tolerance to Type 2 Diabetes
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor (PPAR)-delta regulates fatty acid oxidation and improves insulin sensitivity. We screened six single nucleotide polymorphisms (SNPs) of the PPAR-delta gene (PPARD) for an association with the conversion from impaired glucose tolerance (IGT) to type 2 diabetes in 769 subjects participating in the STOP-NIDDM trial. A 2.7-fold increase in the risk of diabetes was observed in female carriers of the C allele of rs6902123 (95% CI 1.44-5.30; adjusted P = 0.002). In the placebo group, subjects possessing both the 482Ser allele of the PPAR-gamma coactivator-1alpha gene (PGC-1A) and the rare allele of two SNPs of PPARD (rs6902123 and rs3734254) had up to 2.5-fold increased risk for diabetes. Furthermore, women carrying the C allele of rs6902123 of PPARD and the Pro12Pro genotype of the PPAR-gamma2 gene (PPARG2) had a 3.9-fold (95% CI 1.79-8.63; P = 0.001)-higher risk for diabetes than women with protective genotypes. Expression levels of PPAR-delta in subcutaneous adipose tissue of 87 offspring of Finnish patients with type 2 diabetes did not differ among the genotype groups of SNPs of PPARD. We conclude that SNPs in PPARD modify the conversion from IGT to type 2 diabetes, particularly in combination with the SNPs of PGC-1A and PPARG2.
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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 | 0.001 |
| 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".