Tregitope Peptides: The Active Pharmaceutical Ingredient of IVIG?
Bibliographic record
Abstract
Five years ago, we reported the identification and characterization of several regulatory T-cell epitopes (now called Tregitopes) that were discovered in the heavy and light chains of IgG (De Groot et al. Blood, 2008). When added ex vivo to human PBMCs, these Tregitopes activated regulatory T cells (Tregs), increased expression of the transcription factor FoxP3, and induced IL-10 expression in CD4(+) T cells. We have now shown that coadministration of the Tregitopes in vivo, in a number of different murine models of autoimmune disease, can suppress immune responses to antigen in an antigen-specific manner, and that this response is mediated by Tregs. In addition we have shown that, although these are generally promiscuous epitopes, the activity of individual Tregitope peptides is restricted by HLA. In this brief report, we provide an overview of the effects of Tregitopes in vivo, discuss potential applications, and suggest that Tregitopes may represent one of the "active pharmaceutical ingredients" of IVIg. Tregitope applications may include any of the autoimmune diseases that are currently treated almost exclusively with intravenous immunoglobulin G (IVIG), such as Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) and Multifocal Motor Neuropathy (MMN), as well as gene therapy and allergy where Tregitopes may provide a means of inducing antigen-specific tolerance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".