Evidence of Interaction between Type 2 Diabetes Susceptibility Genes and Dietary Fat Intake for Adiposity and Glucose Homeostasis-Related Phenotypes
Bibliographic record
Abstract
BACKGROUND/AIMS: Genome-wide association studies have led to the identification of several susceptibility genes for type 2 diabetes mellitus (T2DM). The objective of this study was to test the hypothesis that the associations between single nucleotide polymorphisms (SNPs) in these genes and adiposity and glucose homeostasis-related phenotypes are influenced by dietary fat intake. METHODS: Thirty-three SNPs in 9 T2DM genes (CDKAL1, CDKN2A/B, HHEX, HNF1B, IGF2BP2, KCNJ11, SLC30A8, TCF7L2 and WFS1) were tested in a maximum of 669 subjects from the Quebec Family Study. Subjects were measured for several adiposity indices and underwent a 75-gram oral glucose tolerance test. Total fat intake was estimated from a 3-day dietary record. RESULTS: We observed 13 significant (p < or = 0.01) SNP-dietary fat interactions. Among them, IGF2BP2 rs4402960, alone or in interaction with dietary fat intake, influenced abdominal total fat (ATF: SNP effect, p = 0.006, interaction effect, p = 0.009) and abdominal visceral fat (AVF: SNP effect, p = 0.007, interaction effect, p = 0.01). Similarly, TCF7L2 rs12573128 alone or in interaction with dietary fat intake, influenced insulin sensitivity (SNP effect and interaction effect, p < or = 0.008) and glucose tolerance (SNP effect p < or= 0.009 and interaction effect, p < or = 0.01). CONCLUSION: These results suggest that gene-dietary fat interactions may influence glucose homeostasis-related phenotypes and play an important role in determining the increased risk of diabetes associated with the T2DM susceptibility genes.
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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".