The Private Hepatocyte Nuclear Factor-1α G319S Variant Is Associated With Plasma Lipoprotein Variation in Canadian Oji-Cree
Bibliographic record
Abstract
We previously showed an extremely strong association between type 2 diabetes and a private polymorphism, namely G319S, in the hepatocyte nuclear transcription factor (HNF)-1alpha. Because HNF-1alpha is involved in the transcription of several apolipoprotein genes, we tested for an association between the private HNF1A G319S variant and plasma lipoproteins in a sample of 55 unrelated Oji-Cree subjects with type 2 diabetes and 175 unrelated Oji-Cree subjects without type 2 diabetes. In Oji-Cree subjects with type 2 diabetes, we found that the HNF1A G319S genotype was significantly associated with lower plasma concentrations of total cholesterol, low density lipoprotein cholesterol, and apolipoprotein (apo) B. In Oji-Cree subjects without type 2 diabetes, we found that the HNF1A G319S genotype was significantly associated with higher plasma concentrations of high density lipoprotein cholesterol and apo AI. There were no associations with plasma triglycerides or lipoprotein(a). Regression analysis indicated that the HNF1A genotype accounted for approximately 10% of the variation in the apo B-related traits in the diabetic subjects and for approximately 5% of the variation in the apo AI-related traits in the nondiabetic subjects. Furthermore, the regression model indicated that the HNF1A S319 allele affected these traits in a dominant manner in subjects with and without type 2 diabetes. These findings provide the first evidence that a rare variant in a nuclear transcription factor is associated with variation in plasma lipoprotein traits.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.004 | 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".