Is Huntington's disease a tauopathy?
Bibliographic record
Abstract
Tauopathies are a subclass of neurodegenerative diseases typified by the deposition of abnormal microtubule-associated tau protein within the cerebral tissue. Alzheimer's disease, progressive supranuclear palsy, chronic traumatic encephalopathy and some fronto-temporal dementias are examples of the extended family of tauopathies. In the last decades, intermittent reports of cerebral tau pathology in individuals afflicted with Huntington’s disease—an autosomal dominant neurodegenerative disorder that manifests by severe motor, cognitive and psychiatric problems in adulthood—have also begun to surface. These observations remained anecdotal until recently when a series of publications brought forward compelling evidence that this monogenic disorder may, too, be a tauopathy. Collectively, these studies reported that: (i) patients with Huntington’s disease present aggregated tau inclusions within various structures of the brain; (ii) tau haplotype influences the cognitive function of Huntington’s disease patients; and (iii) that the genetic product of the disease, the mutant huntingtin protein, could alter tau splicing, phosphorylation, oligomerization and subcellular localization. Here, we review the past and current evidence in favour of the postulate that Huntington’s disease is a new member of the family of tauopathies. Recent reports have suggested that Huntington’s disease may be a tauopathy. Gratuze et al . review the evidence, including the mechanisms by which mutant huntingtin may induce tau pathology, and the possibility that tau contributes to the observed cognitive/motor impairments. They conclude by proposing that Huntington’s disease is a secondary tauopathy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".