Striatal Mutant Huntingtin Protein Levels Decline with Age in Homozygous Huntington’s Disease Knock-In Mouse Models
Bibliographic record
Abstract
BACKGROUND: Huntington's disease (HD) is a progressive neurodegenerative disorder associated with aging, caused by an expanded polyglutamine (polyQ) repeat within the Huntingtin (HTT) protein. In HD, degeneration of the striatum and atrophy of the cortex are observed while cerebellum is less affected. OBJECTIVE: To test the hypothesis that HTT protein levels decline with age, which together with HTT mutation could influence disease progression. METHODS: Using whole brain cell lysates, a unique method of SDS-PAGE and western analysis was used to quantitate HTT protein, which resolves as a monomer and as a high molecular weight species that is modulated by the presence of transglutaminase 2. HTT levels were measured in striatum, cortex and cerebellum in congenic homozygous Q140 and HdhQ150 knock-in mice and WT littermate controls. RESULTS: Mutant HTT in both homozygous knock-in HD mouse models and WT HTT in control striatal and cortical tissues significantly declined in a progressive manner over time. Levels of mutant HTT in HD cerebellum remained high during aging. CONCLUSIONS: A general decline in mutant HTT levels in striatum and cortex is observed that may contribute to disease progression in homozygous knock-in HD mouse models through reduction of HTT function. In cerebellum, sustained levels of mutant HTT with aging may be protective to this tissue which is less overtly affected in HD.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".