NUAK1 promotes organ fibrosis via YAP and TGF-β/SMAD signaling
Bibliographic record
Abstract
Fibrosis is a central pathway that drives progression of multiple chronic diseases, yet few safe and effective clinical antifibrotic therapies exist. In most fibrotic disorders, transforming growth factor-β (TGF-β)-driven scarring is an important pathologic feature and a key contributor to disease progression. Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are two closely related transcription cofactors that are important for coordinating fibrogenesis after organ injury, but how they are activated in response to tissue injury has, so far, remained unclear. Here, we describe NUAK family kinase 1 (NUAK1) as a TGF-β-inducible profibrotic kinase that is up-regulated in multiple fibrotic organs in mice and humans. Mechanistically, we show that TGF-β induces a rapid increase in NUAK1 in fibroblasts. NUAK1, in turn, can promote profibrotic YAP and TGF-β/SMAD signaling, ultimately leading to organ scarring. Moreover, activated YAP and TAZ can induce further NUAK1 expression, creating a profibrotic positive feedback loop that enables persistent fibrosis. Using mouse models of kidney, lung, and liver fibrosis, we demonstrate that this fibrogenic signaling loop can be interrupted via fibroblast-specific loss of NUAK1 expression, leading to marked attenuation of fibrosis. Pharmacologic NUAK1 inhibition also reduced scarring, either when initiated immediately after injury or when initiated after fibrosis was already established. Together, our data suggest that NUAK1 plays a critical, previously unrecognized role in fibrogenesis and represents an attractive target for strategies that aim to slow fibrotic disease progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".