The sodium channel SCN2A regulates cortical excitatory and inhibitory neurogenesis
Bibliographic record
Abstract
Voltage-gated sodium channels regulate neuronal excitability and synaptic transmission in the postnatal and adult brain. The gene SCN2A, encoding the sodium channel Nav1.2, regulates synaptic development and variants in SCN2A are associated with autism spectrum disorders (ASD) and a broad spectrum of epilepsy phenotypes, including early-onset developmental and epileptic encephalopathies. The expression pattern of SCN2A begins during prenatal cortical development, prior to the onset of synaptic transmission, but it is unknown whether SCN2A regulates early cortical development through mechanisms independent of synaptic transmission. Here we reveal that isogenic and ASD patient-derived human forebrain organoids modelling a loss of SCN2A function display impaired excitatory and inhibitory neurogenesis, leading to a developmental imbalance. Unexpectedly, we find precocious generation of cortical inhibitory neurons is driven by elevated Sonic hedgehog signaling and is reversible through pharmacological inhibition. Functionally, these developmental phenotypes arise due to Nav1.2-dependent sodium channel dysfunction and reduced action potential generation, leading to abnormal neuronal network activity. Our results identify a mechanism for cortical excitatory and inhibitory neurogenesis involving SCN2A, and reveal that early neurogenesis deficits precede postnatal neural circuit dysfunction in SCN2A-associated disorders. Using human stem-cell-derived neural organoids, Uy et al. show that the autism-linked sodium channel gene SCN2A shapes early brain development, regulating the production of excitatory and inhibitory neurons via Sonic Hedgehog signaling.
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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 | 0.000 |
| 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".