Recognition of HLA Class I–Restricted β-Cell Epitopes in Type 1 Diabetes
Bibliographic record
Abstract
Type 1 diabetes results from the autoimmune destruction of insulin-producing pancreatic beta-cells by cytotoxic T-lymphocytes (CTLs). In humans, few beta-cell epitopes have been reported, thereby limiting the study of beta-cell-specific CTLs in type 1 diabetes. To identify additional epitopes, HLA class I peptide affinity algorithms were used to identify a panel of peptides derived from the beta-cell proteins islet amyloid polypeptide (IAPP), islet-specific glucose-6-phosphatase catalytic subunit-related protein (IGRP), insulin, insulinoma-associated antigen 2 (IA-2), and phogrin that were predicted to bind HLA-A*0201. Peripheral blood mononuclear cells from 24 HLA-A*0201 recent-onset type 1 diabetic patients and 11 nondiabetic control subjects were evaluated for gamma-interferon secretion in response to peptide stimulation in enzyme-linked immunospot assays. We identified peptides IAPP9-17, IGRP215-223, IGRP152-160, islet IA-2(172-180), and IA-2(482-490) as novel HLA-A*0201-restricted T-cell epitopes in type 1 diabetic patients. Interestingly, we observed a strong inverse correlation between the binding affinity of beta-cell peptides to HLA-A*0201 and CTL responses against those peptides in recent-onset type 1 diabetic patients. In addition, we found that self-reactive CTLs with specificity for an insulin peptide are frequently present in healthy individuals. These data suggest that many beta-cell epitopes are recognized by CTLs in recent-onset type 1 diabetic patients. These epitopes may be important in the pathogenesis of type 1 diabetes.
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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 | 0.000 |
| 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".