Genetic variants disrupting activity-dependent CELF2 shuttling cause neuronal hyperexcitability, learning deficits, and seizures
Bibliographic record
Abstract
Abstract De novo heterozygous variants in the CELF2 gene have recently been associated with a rare neurodevelopmental disorder. However, the mechanisms linking specific variants to distinct clinical phenotypes remain poorly understood. Here, we report a new cohort of 14 individuals with de novo CELF2 variants, providing evidence that variants causing CELF2 cytoplasmic mislocalization, but not its loss-of-function, are associated with seizures. Using proband induced pluripotent stem cell-derived neurons and transgenic mouse models, we show that CELF2 undergoes activity-dependent nucleocytoplasmic shuttling in excitatory neurons, and its cytoplasmic retention causes neuronal hyperexcitability, leading to learning and memory deficits. In the cytoplasm, CELF2 regulates mRNAs critical for synaptic functions and neuronal excitability implicated in epileptic seizures and intellectual disability. Through drug screening, we identify AKT signaling as a key regulator of CELF2 shuttling and a target for treating CELF2-associated hyperexcitability. Our findings expand the clinical and genetic spectrum of CELF2-related neurodevelopmental disorders and reveal variant-specific mechanisms that link CELF2 mislocalization to neuronal hyperexcitability, learning deficits, and epileptic seizures. One Sentence Summary CELF2 variants link protein mislocalization to neuronal hyperexcitability, learning deficits, and epileptic seizures.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".