HD iPSC-derived neural progenitors accumulate in culture and are susceptible to BDNF withdrawal due to glutamate toxicity
Bibliographic record
Abstract
Huntington's disease (HD) is a fatal neurodegenerative disease, caused by expansion of polyglutamine repeats in the Huntingtin gene, with longer expansions leading to earlier ages of onset. The HD iPSC Consortium has recently reported a new in vitro model of HD based on the generation of induced pluripotent stem cells (iPSCs) from HD patients and controls. The current study has furthered the disease in a dish model of HD by generating new non-integrating HD and control iPSC lines. Both HD and control iPSC lines can be efficiently differentiated into neurons/glia; however, the HD-derived cells maintained a significantly greater number of nestin-expressing neural progenitor cells compared with control cells. This cell population showed enhanced vulnerability to brain-derived neurotrophic factor (BDNF) withdrawal in the juvenile-onset HD (JHD) lines, which appeared to be CAG repeat-dependent and mediated by the loss of signaling from the TrkB receptor. It was postulated that this increased death following BDNF withdrawal may be due to glutamate toxicity, as the N-methyl-d-aspartate (NMDA) receptor subunit NR2B was up-regulated in the cultures. Indeed, blocking glutamate signaling, not just through the NMDA but also mGlu and AMPA/Kainate receptors, completely reversed the cell death phenotype. This study suggests that the pathogenesis of JHD may involve in part a population of 'persistent' neural progenitors that are selectively vulnerable to BDNF withdrawal. Similar results were seen in adult hippocampal-derived neural progenitors isolated from the BACHD model mouse. Together, these results provide important insight into HD mechanisms at early developmental time points, which may suggest novel approaches to HD therapeutics.
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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 | 0.001 |
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".