Evidence That HLA Class I and II Associations With Type 1 Diabetes, Autoantibodies to GAD and Autoantibodies to IA-2, Are Distinct
Bibliographic record
Abstract
OBJECTIVE: A major feature of type 1 diabetes is the appearance of islet autoantibodies before diagnosis. However, although the genetics of type 1 diabetes is advanced, the genetics of islet autoantibodies needs further investigation. The primary susceptibility loci in type 1 diabetes, the HLA class I and II genes, are believed to determine the specificity and magnitude of the autoimmune response to islet antigens. We investigated the association of glutamic acid decarboxylase autoantibodies (GADA) and insulinoma-associated antigen-2 autoantibodies (IA-2A) with the HLA region. RESEARCH DESIGN AND METHODS: Associations of GADA and IA-2A with HLA-DRB1, HLA-DQB1, HLA-B, HLA-C, HLA-A, MICA, and 3,779 single nucleotide polymorphisms (SNPs) were analyzed in 2,531 childhood-onset case subjects (median time since diagnosis 5 years). All analyses were adjusted for age-at-diagnosis and duration of diabetes. RESULTS: GADA and IA-2A were associated with an older age-at-diagnosis (P < 10(-19)). For GADA, the primary association was with HLA-DQB1 (P = 9.00 × 10(-18)), with evidence of a second independent effect in the HLA class I region with SNP, rs9266722 (P = 2.84 × 10(-6)). HLA-DRB1 had the strongest association with IA-2A (P = 1.94 × 10(-41)), with HLA-A*24 adding to the association, albeit negatively (P = 1.21 × 10(-10)). There was no evidence of association of either IA-2A or GADA with the highly type 1 diabetes predisposing genotype, HLA-DRB1*03/04. CONCLUSIONS: Despite genetic association of type 1 diabetes and the islet autoantibodies localizing to the same HLA class II genes, HLA-DRB1 and HLA-DQB1, the effects of the class II alleles and genotypes involved are quite different. Therefore, the presence of autoantibodies is unlikely to be causal, and their role in pathogenesis remains to be established.
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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 | 0.001 |
| 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".