Identification of neurodevelopmental organization of the cell populations of juvenile Huntington’s disease using dorso-ventral HD organoids and HD mouse embryos
Bibliographic record
Abstract
ABSTRACT Huntington’s disease (HD), especially juvenile-onset HD (JOHD), involves early neurodevelopmental pathogenesis alongside the gradual breakdown of the corticostriatal neural axis. To better understand this mechanism, we created fused dorsal–ventral forebrain organoids from induced pluripotent stem cells (iPSCs) from JOHD to mimic early corticostriatal interactions in the disease. We observed characteristic growth phenotypes in HD organoids and found that these phenotypes were influenced by paracrine signals from opposite regions (dorsal-ventral and ventral-dorsal). These phenotypes were only partially rescued by conditioning with medium in HD compared to control organoids. We also investigated humanized HD embryonic mouse forebrains at E13.5 to validate the phenotypes. Using single-cell RNA sequencing (scRNAseq) and immunofluorescence of the internal structure of HD organoids, we observed early neurodevelopmental signs, including stalling during the phase of increased progenitor cell growth, delayed neuron maturation, and disrupted patterning between pallial and subpallial regions. A consistent feature across in vitro and in vivo models was an abnormal expansion of transthyretin (TTR)-positive cells resembling choroid plexus (ChP), along with ectopic expression of neuronal factors in ChP and a reduction in populations expressing intermediate progenitor and interneuron markers. In mosaic organoids that combined healthy and JOHD tissues, the healthy environment helped reduce ChP overgrowth and restore normal progenitor and neuronal development. This suggests that some developmental defects caused by mutant HTT are reversible and influenced by non-cell-autonomous factors. Overall, these findings point to early ChP-related abnormalities as a key aspect of JOHD neurodevelopmental disturbance and propose the ChP–CSF environment as an important area for future mechanistic studies and potential therapies.
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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 | 0.001 | 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".