Dysfunction of the Cholesterol Biosynthetic Pathway in Huntington's Disease
Bibliographic record
Abstract
The expansion of a polyglutamine tract in the ubiquitously expressed huntingtin protein causes Huntington's disease (HD), a dominantly inherited neurodegenerative disease. We show that the activity of the cholesterol biosynthetic pathway is altered in HD. In particular, the transcription of key genes of the cholesterol biosynthetic pathway is severely affected in vivo in brain tissue from HD mice and in human postmortem striatal and cortical tissue; this molecular dysfunction is biologically relevant because cholesterol biosynthesis is reduced in cultured human HD cells, and total cholesterol mass is significantly decreased in the CNS of HD mice and in brain-derived ST14A cells in which the expression of mutant huntingtin has been turned on. The transcription of the genes of the cholesterol biosynthetic pathway is regulated via the activity of sterol regulatory element-binding proteins (SREBPs), and we found an approximately 50% reduction in the amount of the active nuclear form of SREBP in HD cells and mouse brain tissue. As a consequence, mutant huntingtin reduces the transactivation of an SRE-luciferase construct even under conditions of SREBP overexpression or in the presence of an exogenous N-terminal active form of SREBP. Finally, the addition of exogenous cholesterol to striatal neurons expressing mutant huntingtin prevents their death in a dose-dependent manner. We conclude that the cholesterol biosynthetic pathway is impaired in HD cells, mice, and human subjects, and that the search for HD therapies should also consider cholesterol levels as both a potential target and disease biomarker.
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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".