Tregitopes Improve Asthma by Promoting Highly Suppressive and Antigen-Specific Tregs
Bibliographic record
Abstract
Tregitopes (T regulatory epitopes) are IgG-derived peptides with high affinity to major histocompatibility complex class II (MHCII), that are known to promote tolerance by activating T regulatory cell (Treg) activity. Here we characterized the effect of IgG Tregitopes in a well-established murine model of allergic asthma, demonstrating in vivo antigen-specific tolerance via adoptive transfer of Tregitope-and-allergen-activated Tregs. Asthma is a heterogeneous chronic inflammatory condition affecting the airways and impacting over 300 million individuals worldwide. Treatment is suppressive, and no current therapy addresses immune regulation in severely affected asthmatics. Although high dose intra-venous immunoglobulin (IVIg) is not commonly used in the asthma clinic setting, it has been shown to improve severe asthma in children and in adults. In our laboratory, we previously demonstrated that IVIg abrogates airway hyperresponsiveness (AHR) in a murine model of asthma and induces suppressive antigen-specific T-regulatory cells. We hypothesized that IgG-derived Tregitopes would modulate allergic airway disease by inducing highly suppressive antigen-specific Tregs capable of diminishing T effector cell responses and establishing antigen-specific tolerance. Using ovalbumin (OVA-) and ragweed-driven murine models of allergic airway disease, we characterized the immunoregulatory properties of Tregitopes and performed Treg adoptive transfer to OVA- and ragweed-allergic mice to test for allergen specificity. Treatment with Tregitopes attenuated allergen-induced airway hyperresponsiveness and lung inflammation. We demonstrated that Tregitopes induce highly suppressive allergen-specific Tregs. The tolerogenic action of IgG Tregitopes in our model is very similar to that of IVIg, so we foresee that IgG Tregitopes could potentially replace steroid-based treatment and can offer a synthetic alternative to IVIg in a range of inflammatory and allergic conditions.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".