Mutant huntingtin's effects on striatal gene expression in mice recapitulate changes observed in human Huntington's disease brain and do not differ with mutant huntingtin length or wild-type huntingtin dosage
Bibliographic record
Abstract
To test the hypotheses that mutant huntingtin protein length and wild-type huntingtin dosage have important effects on disease-related transcriptional dysfunction, we compared the changes in mRNA in seven genetic mouse models of Huntington's disease (HD) and postmortem human HD caudate. Transgenic models expressing short N-terminal fragments of mutant huntingtin (R6/1 and R6/2 mice) exhibited the most rapid effects on gene expression, consistent with previous studies. Although changes in the brains of knock-in and full-length transgenic models of HD took longer to appear, 15- and 22-month CHL2(Q150/Q150), 18-month Hdh(Q92/Q92) and 2-year-old YAC128 animals also exhibited significant HD-like mRNA signatures. Whereas it was expected that the expression of full-length huntingtin transprotein might result in unique gene expression changes compared with those caused by the expression of an N-terminal huntingtin fragment, no discernable differences between full-length and fragment models were detected. In addition, very high correlations between the signatures of mice expressing normal levels of wild-type huntingtin and mice in which the wild-type protein is absent suggest a limited effect of the wild-type protein to change basal gene expression or to influence the qualitative disease-related effect of mutant huntingtin. The combined analysis of mouse and human HD transcriptomes provides important temporal and mechanistic insights into the process by which mutant huntingtin kills striatal neurons. In addition, the discovery that several available lines of HD mice faithfully recapitulate the gene expression signature of the human disorder provides a novel aspect of validation with respect to their use in preclinical therapeutic trials.
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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) | 0.000 | 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 | 0.001 |
| 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".