Class III Alleles at the Insulin VNTR Polymorphism Are Associated With Regulatory T-Cell Responses to Proinsulin Epitopes in HLA-DR4, DQ8 Individuals
Bibliographic record
Abstract
A variable number of tandem repeats (VNTR) polymorphism upstream of the insulin promoter is strongly associated with type 1 diabetes. The short class I alleles are predisposing and the long class III alleles are protective. As a possible mechanism for this effect, we previously reported a two- to threefold higher insulin transcription from class III than from class I chromosomes in thymus where insulin is expressed at low levels, presumably for the purpose of self-tolerance. In this article, we confirm this finding with independent methodology and report studies testing the hypothesis that class III alleles are associated with T-cell tolerance to (pro)insulin. Cytokine release in vitro after stimulation with 21 overlapping preproinsulin epitopes was assessed in blood mononuclear cells as well as naive and memory CD4+ T-cell subsets from 33 individuals with the high-risk DRB1*04, DQ8 haplotype (12 type 1 diabetic patients, 11 healthy control subjects, and 10 autoantibody-positive subjects). No significant differences between genotypes (24 I/I subjects versus 10 I/III or III/III subjects) were observed for gamma-interferon, tumor necrosis factor-alpha, or interleukin (IL)-4. By contrast, the I/III + III/III group showed a significant threefold higher IL-10 release in memory T-cells for whole proinsulin and the immunodominant region. Given that IL-10 is a marker of regulatory function, our data are consistent with the hypothesis that higher insulin levels in the thymus promote the formation of regulatory T-cells, a proposed explanation for the protective effect of the class III alleles.
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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 | 0.000 | 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 | 0.001 |
| 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".