In vitro characterization of neurite extension using induced pluripotent stem cells derived from lissencephaly patients with TUBA1A missense mutations
Bibliographic record
Abstract
BACKGROUND: Lissencephaly, or smooth brain, is a severe congenital brain malformation that is thought to be associated with impaired neuronal migration during corticogenesis. However, the exact etiology of lissencephaly in humans remains unknown. Research on congenital diseases is limited by the shortage of clinically derived resources, especially for rare pediatric diseases. The research on lissencephaly is further limited because gyration in humans is more evolved than that in model animals such as mice. To overcome these limitations, we generated induced pluripotent stem cells (iPSCs) from the umbilical cord and peripheral blood of two lissencephaly patients with different clinical severities carrying alpha tubulin (TUBA1A) missense mutations (Patient A, p.N329S; Patient B, p.R264C). RESULTS: Neural progenitor cells were generated from these iPSCs (iPSC-NPCs) using SMAD signaling inhibitors. These iPSC-NPCs expressed TUBA1A at much higher levels than undifferentiated iPSCs and, like fetal NPCs, readily differentiated into neurons. Using these lissencephaly iPSC-NPCs, we showed that the neurons derived from the iPSCs obtained from Patient A but not those obtained from Patient B showed abnormal neurite extension, which correlated with the pathological severity in the brains of the patients. CONCLUSION: We established iPSCs derived from lissencephaly patients and successfully modeled one aspect of the pathogenesis of lissencephaly in vitro using iPSC-NPCs and iPSC-derived neurons. The iPSCs from patients with brain malformation diseases helped us understand the mechanism underlying rare diseases and human corticogenesis without the use of postmortem brains.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".