A patient-derived cellular model for Huntington’s disease reveals phenotypes at clinically relevant CAG lengths
Bibliographic record
Abstract
The huntingtin protein participates in several cellular processes that are disrupted when the polyglutamine tract is expanded beyond a threshold of 37 CAG DNA repeats in Huntington's disease (HD). Cellular biology approaches to understand these functional disruptions in HD have primarily focused on cell lines with synthetically long CAG length alleles that clinically represent outliers in this disease and a more severe form of HD that lacks age onset. Patient-derived fibroblasts are limited to a finite number of passages before succumbing to cellular senescence. We used human telomerase reverse transcriptase (hTERT) to immortalize fibroblasts taken from individuals of varying age, sex, disease onset, and CAG repeat length, which we have termed TruHD cells. TruHD cells display classic HD phenotypes of altered morphology, size and growth rate, increased sensitivity to oxidative stress, aberrant adenosine diphosphate/adenosine triphosphate (ADP/ATP) ratios, and hypophosphorylated huntingtin protein. We additionally observed dysregulated reactive oxygen species (ROS)-dependent huntingtin localization to nuclear speckles in HD cells. We report the generation and characterization of a human, clinically relevant cellular model for investigating disease mechanisms in HD at the single-cell level, which, unlike transformed cell lines, maintains functions critical for huntingtin transcriptional regulation and genomic integrity.
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 | 0.001 | 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".