Intrinsic mutant HTT-mediated defects in oligodendroglia cause myelination deficits and behavioral abnormalities in Huntington disease
Bibliographic record
Abstract
White matter abnormalities are a nearly universal pathological feature of neurodegenerative disorders including Huntington disease (HD). A long-held assumption is that this white matter pathology is simply a secondary outcome of the progressive neuronal loss that manifests with advancing disease. Using a mouse model of HD, here we show that white matter and myelination abnormalities are an early disease feature appearing before the manifestation of any behavioral abnormalities or neuronal loss. We further show that selective inactivation of mutant huntingtin (mHTT) in the NG2+ oligodendrocyte progenitor cell population prevented myelin abnormalities and certain behavioral deficits in HD mice. Strikingly, the improvements in behavioral outcomes were seen despite the continued expression of mHTT in nonoligodendroglial cells including neurons, astrocytes, and microglia. Using RNA-seq and ChIP-seq analyses, we implicate a pathogenic mechanism that involves enhancement of polycomb repressive complex 2 (PRC2) activity by mHTT in the intrinsic oligodendroglial dysfunction and myelination deficits observed in HD. Our findings challenge the long-held dogma regarding the etiology of white matter pathology in HD and highlight the contribution of epigenetic mechanisms to the observed intrinsic oligodendroglial dysfunction. Our results further suggest that ameliorating white matter pathology and oligodendroglial dysfunction may be beneficial for 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) | 0.000 | 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) | 0.001 | 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".