A fully humanized transgenic mouse model of Huntington disease
Bibliographic record
Abstract
Silencing the mutant huntingtin gene (muHTT) is a direct and simple therapeutic strategy for the treatment of Huntington disease (HD) in principle. However, targeting the HD mutation presents challenges because it is an expansion of a common genetic element (a CAG tract) that is found throughout the genome. Moreover, the HTT protein is important for neuronal health throughout life, and silencing strategies that also reduce the wild-type HTT allele may not be well tolerated during the long-term treatment of HD. Several HTT silencing strategies are in development that target genetic sites in HTT that are outside of the CAG expansion, including HD mutation-linked single-nucleotide polymorphisms and the HTT promoter. Preclinical testing of these genetic therapies has required the development of a new mouse model of HD that carries these human-specific genetic targets. To generate a fully humanized mouse model of HD, we have cross-bred BACHD and YAC18 on the Hdh(-/-) background. The resulting line, Hu97/18, is the first murine model of HD that fully genetically recapitulates human HD having two human HTT genes, no mouse Hdh genes and heterozygosity of the HD mutation. We find that Hu97/18 mice display many of the behavioral changes associated with HD including motor, psychiatric and cognitive deficits, as well as canonical neuropathological abnormalities. This mouse line will be useful for gaining additional insights into the disease mechanisms of HD as well as for testing genetic therapies targeting human HTT.
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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) | 0.000 | 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 | 0.000 |
| 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".