Reducing huntingtin by immunotherapy delays disease progression in a mouse model of Huntington disease
Bibliographic record
Abstract
In Huntington disease (HD), the mutant huntingtin (mtHTT) protein is the principal cause of pathological changes that initiate primarily along the cortico-striatal axis. mtHTT is ubiquitously expressed and there is, accordingly, growing recognition that HD is a systemic disorder with functional interplay between the brain and the periphery. We have developed a monoclonal antibody, C6-17, targeting an exposed region of HTT near the aa586 Caspase 6 cleavage site. As recently published, mAB C6-17 can block cell-to-cell propagation of mtHTT in vitro. In order to reduce the burden of the mutant protein in vivo, we queried whether extracellular mtHTT could be therapeutically targeted in YAC128 HD mice. In a series of proof of concept experiments, we found that systemic mAB C6-17 treatment resulted in the distribution of the mAB C6-17 to peripheral and CNS tissues and led to the reduction of HTT protein levels. Compared to CTRL mAB or vehicle treated mice, the mAB C6-17 treated YAC128 animals showed improved body weight and motor behaviors, a delayed progression in motor deficits and reduced striatal EM48 immunoreactivity. These results provide the first proof of concept for the feasibility and therapeutic efficacy of an antibody-based anti-HTT passive immunization approach and suggest this modality as a potential new HD treatment strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| 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".