Association Analysis of Type 2 Diabetes Loci in Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To search for a possible association of type 1 diabetes with 10 validated type 2 diabetes loci, i.e., PPARG, KCNJ11, WFS1, HNF1B, IDE/HHEX, SLC30A8, CDKAL1, CDKN2A/B, IGF2BP2, and FTO/RPGRIP1L. RESEARCH DESIGN AND METHODS: Two European population samples were studied: 1) one case-control cohort of 514 type 1 diabetic subjects and 2,027 control subjects and 2) one family cohort of 483 complete type 1 diabetic case-parent trios (total 997 affected). A total of 13 tag single nucleotide polymorphisms (SNPs) from the 10 type 2 diabetes loci were analyzed for type 1 diabetes association. RESULTS: No association of type 1 diabetes was found with any of the 10 type 2 diabetes loci, and no age-at-onset effect was detected. By combined analysis using the Wellcome Trust Case-Control Consortium type 1 diabetes data, SNP rs1412829 in the CDKN2A/B locus bordered on significance (P = 0.039) (odds ratio 0.929 [95% CI 0.867-0.995]), which did not reach the statistical significance threshold adjusted for 13 tests (alpha = 0.00385). CONCLUSIONS: This study suggests that the type 2 diabetes loci do not play any obvious role in type 1 diabetes genetic susceptibility. The distinct molecular mechanisms of the two diseases highlighted the importance of differentiation diagnosis and different treatment principles.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".