CAG-targeted brain-permeable therapy tested in biallelic humanized polyQ mouse models
Bibliographic record
Abstract
In polyglutamine (polyQ) diseases, including Huntington disease (HD) and spinocerebellar ataxia type 3 (SCA3), targeting the mutant CAG tract in mRNA could be a therapeutic strategy for lowering pathogenic protein. We explored the viability of this therapeutic strategy in vivo at the level of the reagent design, toxicity, systemic delivery, brain regions transduction, silencing efficiency, and allele preference. We designed a series of CAG-directed short hairpin RNAs (shRNAs) based on a previous A2 reagent, allele selective in vitro . Humanized HD (Hu 128Q/21Q ) and SCA3 (Ki 150Q/21Q ) mice with mutant ∼100 CAGs and normal 21 CAGs alleles were used to simulate biallelic conditions occurring in patients. We administered AAV-PHP.eB shRNAs-encoding vectors into the blood as an equivalent of non-invasive CAG-directed brain-targeted therapy crossing the blood-brain barrier. We demonstrate that optimized CAG-targeted A4(P10) and A4(P10,11) shReagents can lower mutant huntingtin and ataxin-3 protein and its aggregates by targeting brain regions selectively and with diminished toxicity compared to other tested shRNAs. The important considerations of the approach are the silencing efficiency depending on the transduction region and careful dose adjustment. Moreover, the CAG approach could be suitable to target somatic expansion. Our work paves the way toward developing the therapy for polyQ diseases, potentially shortening drug development.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".