Hepatocyte Nuclear Factor-4α P2 Promoter Haplotypes Are Associated With Type 2 Diabetes in the Japanese Population
Bibliographic record
Abstract
Hepatocyte nuclear factor (HNF)-4alpha is a transcription factor known as a key molecule in the development and functions of the beta-cells. In a previously performed genome-wide scan of Japanese type 2 diabetic sibpairs, we observed linkage of type 2 diabetes to chromosome 20q12-q13, a region in which the HNF4A gene is located. Recent studies have reported associations between type 2 diabetes and polymorphisms in the P2 promoter region specific to beta-cells. In this study, we attempted to assess whether the HNF4A gene plays a role in the genetic susceptibility to type 2 diabetes in the Japanese population by analyzing polymorphisms and haplotypes of the HNF4A gene. Linkage disequilibrium across the P2 promoter region was preserved in the Japanese population, consistent with previous reports. Although none of the individual polymorphisms examined showed any significant association with type 2 diabetes, we found very strong evidence of the association between type 2 diabetes and the haplotype consisting of two polymorphisms in the P2 promoter region of the HNF4A gene (P = 3.82 x 10(-4)). In contrast, there was no association between type 2 diabetes and haplotypes consisting of polymorphisms not located in the P2 promoter region, suggesting that the type 2 diabetes susceptibility loci are localized in the P2 promoter region of the HNF4A gene. The association was replicated using two additional cohorts (P = 1.51 x 10(-4) and 0.019, respectively). The results of the present analysis revealed that the HNF4A gene might be a type 2 diabetes susceptibility gene common to different ethnic groups. The study also suggested the possible existence of an as-yet-unidentified but functional polymorphism in the P2 promoter region of the HNF4A gene that directly influences susceptibility to type 2 diabetes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".