Targeting TEAD/YAP-transcription-dependent necrosis, TRIAD, ameliorates Huntington’s disease pathology
Bibliographic record
Abstract
Neuronal cell death in neurodegenerative diseases is not fully understood. Here we report that mutant huntingtin (Htt), a causative gene product of Huntington’s diseases (HD) selectively induces a new form of necrotic cell death, in which endoplasmic reticulum (ER) enlarges and cell body asymmetrically balloons and finally ruptures. Pharmacological and genetic analyses revealed that the necrotic cell death is distinct from the RIP1/3 pathway-dependent necroptosis, but mediated by a functional deficiency of TEAD/YAP-dependent transcription. In addition, we revealed that a cell cycle regulator, Plk1, switches the balance between TEAD/YAP-dependent necrosis and p73/YAP-dependent apoptosis by shifting the interaction partner of YAP from TEAD to p73 through YAP phosphorylation at Thr77. In vivo ER imaging with two-photon microscopy detects similar ER enlargement, and viral vector-mediated delivery of YAP as well as chemical inhibitors of the Hippo pathway such as S1P recover the ER instability and necrosis in HD model mice. Intriguingly S1P completely stops the decline of motor function of HD model mice even after the onset of symptom. Collectively, we suggest approaches targeting the signalling pathway of TEAD/YAP-transcription-dependent necrosis (TRIAD) could lead to a therapeutic development against HD.
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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) | 0.001 | 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".