A novel humanized mouse model of Huntington disease for preclinical development of therapeutics targeting mutant huntingtin alleles
Bibliographic record
Abstract
Huntington disease (HD) is a neurodegenerative disease caused by a mutation in the huntingtin (HTT) gene. HTT is a large protein, interacts with many partners and is involved in many cellular pathways, which are perturbed in HD. Therapies targeting HTT directly are likely to provide the most global benefit. Thus there is a need for preclinical models of HD recapitulating human HTT genetics. We previously generated a humanized mouse model of HD, Hu97/18, by intercrossing BACHD and YAC18 mice with knockout of the endogenous mouse HD homolog (Hdh). Hu97/18 mice recapitulate the genetics of HD, having two full-length, genomic human HTT transgenes heterozygous for the HD mutation and polymorphisms associated with HD in populations of Caucasian descent. We have now generated a companion model, Hu128/21, by intercrossing YAC128 and BAC21 mice on the Hdh-/- background. Hu128/21 mice have two full-length, genomic human HTT transgenes heterozygous for the HD mutation and polymorphisms associated with HD in populations of East Asian descent and in a minority of patients from other ethnic groups. Hu128/21 mice display a wide variety of HD-like phenotypes that are similar to YAC128 mice. Additionally, both transgenes in Hu128/21 mice match the human HTT exon 1 reference sequence. Conversely, the BACHD transgene carries a floxed, synthetic exon 1 sequence. Hu128/21 mice will be useful for investigations of human HTT that cannot be addressed in Hu97/18 mice, for developing therapies targeted to exon 1, and for preclinical screening of personalized HTT lowering therapies in HD patients of East Asian descent.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".