TYK2 inhibition reduces type 3 immunity and modifies disease progression in murine spondyloarthritis
Bibliographic record
Abstract
Spondyloarthritis (SpA) represents a family of inflammatory diseases of the spine and peripheral joints. Ankylosing spondylitis (AS) is the prototypic form of SpA in which progressive disease can lead to fusion of the spine. Therapeutically, knowledge of type 3 immunity has translated into the development of IL-23- and IL-17A-blocking antibodies for the treatment of SpA. Despite being able to provide symptomatic control, the current biologics do not prevent the fusion of joints in AS patients. Thus, there is an unmet need for disease-modifying drugs. Genetic studies have linked the Janus kinase TYK2 to AS. TYK2 is a mediator of type 3 immunity through intracellular signaling of IL-23. Here, we describe and characterize a potentially novel small-molecule inhibitor of TYK2 that blocked IL-23 signaling in vitro and inhibited disease progression in animal models of SpA. The effect of the inhibitor appears to be TYK2 specific, using TYK2-inactive mice, which further revealed a duality in the induction of IL-17A and IL-22 by IL-23. Specifically, IL-22 production was TYK2/JAK2/STAT3 dependent, while IL-17A was mostly JAK2 dependent. Finally, we examined the effects of AS-associated TYK2 SNPs on TYK2 expression and function and correlated them with AS disease progression. This work provides evidence that TYK2 inhibitors have great potential as an orally delivered therapeutic for SpA.
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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 | 0.000 | 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".