IL-2 as a therapeutic target for the restoration of Foxp3+ regulatory T cell function in organ-specific autoimmunity: implications in pathophysiology and translation to human disease
Bibliographic record
Abstract
Peripheral immune tolerance requires a finely controlled balance between tolerance to self-antigens and protective immunity against enteric and invading pathogens. Self-reactive T cells sometimes escape thymic clonal deletion, and can subsequently provoke autoimmune diseases such as type 1 diabetes (T1D) unless they are controlled by a network of tolerance mechanisms in the periphery, including CD4+ regulatory T cells (Treg) cells. CD4+ Treg cells are characterized by the constitutive expression of the IL-2Rα chain (CD25) and preferentially express the forkhead winged helix transcriptional regulator Foxp3. These cells have been shown to possess immunosuppressive properties towards various immune cell subsets and their defects are thought to contribute to many autoimmune disorders. Strong evidence shows that IL-2 is one of the important stimulatory signals for the development, function and fitness of Treg cells. The non-obese diabetic (NOD) mouse model, a prototypic model of spontaneous autoimmunity, mimics many features of human T1 D. Using this model, the contribution of the IL-2-IL-2R pathway to the development of T1 D and other autoimmune disorders has been extensively studied. In the past years, strong genetic and molecular evidence has indicated an essential role for the IL-2/IL-2R pathway in autoimmune disorders. Thus, the major role of IL-2 is to maintain immune tolerance by promoting Treg cell development, functional fitness and stability. Here we first summarize the genetic and experimental evidence demonstrating a role for IL-2 in autoimmunity, mainly through the study of the NOD mouse model, and analyze the cellular and molecular mechanisms of its action on Treg cells. We then move on to describe how this data can be translated to applications for human autoimmune diseases by using IL-2 as a therapeutic agent to restore Treg cell fitness, numbers and functions.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".