S100A9 promotes inflammasome-dependent autoinflammation by blocking the degradation of SYK tyrosine kinase
Bibliographic record
Abstract
Autoinflammatory diseases such as cryopyrin-associated periodic fever syndrome and familial Mediterranean fever involve an aberrant secretion of interleukin-1β due to genetic defects in the NLRP3 (NOD-, LRR-, and pyrin domain-containing protein 3) or pyrin inflammasomes. The regulatory mechanisms and possible interactions between inflammasome pathways remain unclear. In addition, these conditions show a high expression of the inflammatory alarmins S100A8/A9. Spleen tyrosine kinase is a known regulator of NLRP3 activity, but its connection to S100 proteins and pyrin-driven inflammation has not been described so far. This study demonstrates that S100A9 controls inflammasome activation via spleen tyrosine kinase expression in monocytes. Loss of S100A9 leads to decreased USP10 deubiquitinase expression, resulting in increased autophagosomal degradation of spleen tyrosine kinase. This impairs the S100A9-USP10-SYK pathway inhibiting NLRP3 inflammasome activation and reducing secretion of proinflammatory cytokines and S100A9. Strikingly, blocking this pathway in familial Mediterranean fever monocytes unraveled a so far unknown link between pyrin and NLRP3-driven autoinflammation. These findings identify intracellular S100A9 as a direct regulator of NLRP3 activity and a driver of autoinflammatory responses.
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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 | 0.000 |
| 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".