Evidence for the spread of human-derived mutant huntingtin protein in mice and non-human primates
Bibliographic record
Abstract
In recent years, substantial evidence has emerged to suggest that spreading of pathological proteins contributes to disease pathology in numerous neurodegenerative disorders. Work from our laboratory and others have shown that, despite its strictly genetic nature, Huntington's disease (HD) may be another condition in which this mechanism contributes to pathology. In this study, we set out to determine if the mutant huntingtin protein (mHTT) present in post-mortem brain tissue derived from HD patients can induce pathology in mice and/or non-human primates. For this, we performed three distinct sets of experiments where homogenates were injected into the brains of adult a) Wild-type (WT) and b) BACHD mice or c) non-human primates. Neuropathological assessments revealed that, while changes in the endogenous huntingtin were not apparent, mHTT could spread between cellular elements and brain structures. Furthermore, behavioural differences only occurred in the animal model of HD which already overexpressed mHTT. Taken together, our results indicate that mHTT derived from human brains has only a limited capacity to propagate between cells and does not depict prion-like characteristics. This contrasts with recent work demonstrating that other forms of mHTT - such as fibrils of a pathological polyQ length or fibroblasts and induced pluripotent stem cells derived from HD cases - can indeed disseminate disease throughout the brain in a prion-like fashion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".