Potent and sustained huntingtin lowering via AAV5 encoding miRNA preserves striatal volume and cognitive function in a humanized mouse model of Huntington disease
Bibliographic record
Abstract
Huntington disease (HD) is a fatal neurodegenerative disease caused by a pathogenic expansion of a CAG repeat in the huntingtin (HTT) gene. There are no disease-modifying therapies for HD. Artificial microRNAs targeting HTT transcripts for degradation have shown preclinical promise and will soon enter human clinical trials. Here, we examine the tolerability and efficacy of non-selective HTT lowering with an AAV5 encoded miRNA targeting human HTT (AAV5-miHTT) in the humanized Hu128/21 mouse model of HD. We show that intrastriatal administration of AAV5-miHTT results in potent and sustained HTT suppression for at least 7 months post-injection. Importantly, non-selective suppression of huntingtin was generally tolerated, however high dose AAV5-miHTT did induce astrogliosis. We observed an improvement of select behavioural and modest neuropathological HD-like phenotypes in Hu128/21 mice, suggesting a potential therapeutic benefit of miRNA-mediated non-selective HTT lowering. Finally, we also observed that potent reduction of wild type HTT (wtHTT) in Hu21 control mice was tolerated up to 7 months post-injection but may induce impairment of motor coordination and striatal atrophy. Taken together, our data suggests that in the context of HD, the therapeutic benefits of mHTT reduction may outweigh the potentially detrimental effects of wtHTT loss following non-selective HTT lowering.
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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 | 0.003 |
| 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 | 0.001 |
| 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".