Preventing mutant huntingtin proteolysis and intermittent fasting promote autophagy in models of Huntington disease
Bibliographic record
Abstract
Huntington disease (HD) is caused by the expression of mutant huntingtin (mHTT) bearing a polyglutamine expansion. In HD, mHTT accumulation is accompanied by a dysfunction in basal autophagy, which manifests as specific defects in cargo loading during selective autophagy. Here we show that the expression of mHTT resistant to proteolysis at the caspase cleavage site D586 (C6R mHTT) increases autophagy, which may be due to its increased binding to the autophagy adapter p62. This is accompanied by faster degradation of C6R mHTT in vitro and a lack of mHTT accumulation the C6R mouse model with age. These findings may explain the previously observed neuroprotective properties of C6R mHTT. As the C6R mutation cannot be easily translated into a therapeutic approach, we show that a scheduled feeding paradigm is sufficient to lower mHTT levels in YAC128 mice expressing cleavable mHTT. This is consistent with a previous model, where the presence of cleavable mHTT impairs basal autophagy, while fasting-induced autophagy remains functional. In HD, mHTT clearance and autophagy may become increasingly impaired as a function of age and disease stage, because of gradually increased activity of mHTT-processing enzymes. Our findings imply that mHTT clearance could be enhanced by a regulated dietary schedule that promotes autophagy.
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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".