Functional AGXT2 SNP rs37369 Variant Is a Risk Factor for Diabetes Mellitus: Baseline Data From the Aidai Cohort Study in Japan
Bibliographic record
Abstract
OBJECTIVES: The relationship between alanine-glyoxylate aminotransferase 2 (AGXT2) single-nucleotide polymorphisms (SNPs) and diabetes mellitus (DM) has not been investigated. Therefore, we performed a case-control study to examine this relationship. METHODS: The study subjects included 2,390 Japanese men and women aged 34 to 88 years. In total, 190 cases were defined as having a fasting plasma glucose level ≥126 mg/dL, having a glycated hemoglobin ≥6.5% or currently using diabetic medication. The 2,200 remaining participants served as control subjects. RESULTS: Compared with study subjects with the CC genotype of AGXT2 SNP rs37369, those with the TT, but not CT, genotype had a significantly increased risk of DM: the adjusted odds ratio (OR) for the TT genotype was 1.83 (95% confidence interval [CI], 1.04 to 3.47). AGXT2 SNPs rs37370 and rs180749 were not significantly associated with the risk of DM. The CTA haplotype of rs37370, rs37369 and rs180749 was significantly positively associated with the risk of DM (crude OR, 1.25; 95% CI, 1.01 to 1.56), whereas the CCA haplotype was significantly inversely related to DM (crude OR, 0.53; 95% CI, 0.27 to 0.95). The multiplicative interaction between AGXT2 SNP rs37369 and smoking status with regard to the risk of DM was not significant (p=0.32 for interaction). CONCLUSIONS: This is the first study to show significant associations between AGXT2 SNP rs37369, the CTA haplotype, and the CCA haplotype and DM. No interaction with regard to the risk of DM was observed between rs37369 and smoking.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".