TYK2 inhibition enhances Treg differentiation and function while preventing Th1 and Th17 differentiation
Bibliographic record
Abstract
Janus kinase (JAK) inhibitors are widely used to inhibit inflammatory cytokine signaling in autoimmune and inflammatory diseases, but their effect on regulatory T cells (Tregs) is poorly characterized. We investigated the effect of a JAK inhibitor, upadacitinib, on human Treg differentiation and phenotype in comparison to BMS-986202, a selective Tyrosine kinase 2 (TYK2) inhibitor. Both upadacitinib and BMS-986202 blocked naive CD4 + T cell differentiation into Th1/17 cells, but only BMS-986202 and a related TYK2 inhibitor, deucravacitinib, spared interleukin-2 (IL-2) signaling and Treg induction. BMS-986202 also increased Treg suppressive function and stability under Th1/17-polarizing conditions, whereas upadacitinib significantly impaired the phenotype and viability of ex vivo Tregs. In lamina propria mononuclear cells from patients with inflammatory bowel disease cultured under Th17-polarizing conditions, BMS-986202 redirected CD4 + T cells toward a Treg phenotype. The Treg-sparing and enhancing properties of TYK2 inhibition suggest that TYK2 inhibitors are a promising pharmacological approach for tolerance induction.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".