Autoreactive IgE: pathogenic role and therapeutic target in autoimmune diseases
Bibliographic record
Abstract
Autoimmunity is the break of tolerance to self-antigens that leads to organ-specific or systemic diseases characterized by the presence of pathogenic autoreactive antibodies (AAb) produced by plasmablast and/or plasma cells. AAb are prevalent in the general population and not systematically associated with clinical symptoms. In contrast, in some individuals, these AAb are pathogenic and drive the development of signs and symptoms of antibody-mediated autoimmune diseases (AbAID). AAb production, isotype profiles, and glycosylations are promoted by pro-inflammatory triggers linked to genetic, environmental, and hormonal parameters. Recent evidence supports a role for pathogenic AAb of the IgE isotype in a number of AbAID. Autoreactive IgE can drive the activation of mast cells, basophils and other types of FcεRI-bearing cells and may play a role in promoting autoantibody production and other pro-inflammatory pathways. In this review, we discuss the current knowledge on the pathogenicity of autoreactive IgE in AbAID and their status as therapeutic targets. We also highlight unresolved issues including the need for assays that reproducibly quantify IgE AAbs, to validate their diagnostic and prognostic value, and to further study their pathophysiological contributions to AbAID.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".