Caspase-1–Processed Cytokines IL-1β and IL-18 Promote IL-17 Production by γδ and CD4 T Cells That Mediate Autoimmunity
Bibliographic record
Abstract
IL-1β plays a critical role in promoting IL-17 production by γδ and CD4 T cells. However, IL-1-targeted drugs, although effective against autoinflammatory diseases, are less effective against autoimmune diseases. Conversely, gain-of-function mutations in the NLRP3 inflammasome complex are associated with enhanced IL-1β and IL-18 production and Th17 responses. In this study, we examined the role of caspase-1-processed cytokines in IL-17 production and in induction of experimental autoimmune encephalomyelitis (EAE). Killed Mycobacterium tuberculosis, the immunostimulatory component in CFA used for inducing EAE, stimulated IL-1β and IL-18 production by dendritic cells through activation of the inflammasome complex and caspase-1. Dendritic cells stimulated with M. tuberculosis and myelin oligodendrocyte glycoprotein promoted IL-17 production by T cells and induced EAE following transfer to naive mice, and this was suppressed by a caspase-1 inhibitor and reversed by administration of IL-1β or IL-18. Direct injection of the caspase-1 inhibitor suppressed IL-17 production by CD4 T cells and γδ T cells in vivo and attenuated the clinical signs of EAE. γδ T cells expressed high levels of IL-18R and the combination of IL-18 and IL-23, as with IL-1β and IL-23, stimulated IL-17 production by γδ T cells, but also from CD4 T cells, in the absence of TCR engagement. Our findings demonstrate that caspase-1-processed cytokines IL-1β and IL-18 not only promote autoimmunity by stimulating innate IL-17 production by T cells but also reveal redundancy in the functions of IL-1β and IL-18, suggesting that caspase-1 or the inflammasome may be an important drug target for autoimmune diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".