Identification of a β-Cell-Specific HLA Class I Restricted Epitope in Type 1 Diabetes
Bibliographic record
Abstract
Type 1 diabetes is an autoimmune disease in which pancreatic beta-cells are destroyed by cytotoxic T-cells that recognize peptide epitopes presented by HLA class I molecules. The identification of human beta-cell epitopes may significantly improve the prospects for immunodiagnosis and immunotherapy in type 1 diabetes. Using algorithms to predict nonameric beta-cell peptides that would bind to the common HLA allele, HLA-A*0201, we identified a potential epitope from the leader sequence of islet amyloid polypeptide (human islet amyloid polypeptide [IAPP] precursor protein [preproIAPP] 5-13: KLQVFLIVL). Peripheral blood mononuclear cells (PBMCs) were isolated from 18 HLA-A*0201 patients with type 1 diabetes (9 with recent-onset [<180 days; range, 1-120 days] and 9 with long-standing diabetes [>180 days; range, 183-3,273 days]) and 9 healthy, nondiabetic control subjects. PBMCs were screened for peptide recognition using interferon-gamma enzyme-linked immunospot (ELISpot) assays. Of the nine patients with recent-onset type 1 diabetes, six had ELISpot responses to preproIAPP 5-13 that were >3 SDs above the mean of the nondiabetic control subjects (P = 0.002). In contrast, no patients with type 1 diabetes for >180 days had a response above this threshold. In summary, preproIAPP 5-13 is a novel HLA class I epitope recognized by a significant proportion of cytotoxic T-cells from HLA-A*0201 patients with recent-onset type 1 diabetes and may prove to be a useful tool for the prediction and/or prevention of this disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".