Deciphering the mechanistic basis for the pathological effect of the Gα <sub>o</sub> E246K mutation in neurodevelopmental disorder
Bibliographic record
Abstract
Abstract Mutations in the GNAO1 gene, which encodes for Gα o , a major neuronal G protein, are associated with neurodevelopmental disorders, epilepsy, and movement disorders. We identified and characterized a spontaneous heterozygous GNAO1 E246K mutation in an Israeli female infant with complex developmental delays and substantial motor difficulties. This mutation has been reported in other cases as a prevalent pathogenic mutation in patients with motor dysfunction and a broad range of neurological outcomes. To investigate the molecular and functional consequences of the Gα o E246K mutation, we employed structural modeling and analysis, biochemical assays, mass spectrometry-based proteomics, and cellular functional assays. We show that this mutation does not affect nucleotide binding, nor basal or RGS- accelerated GTP hydrolysis. Despite the E246 position located within a predicted effector binding region, proteomics analysis did not identify any new cellular partners. Instead, we demonstrate that the E246K mutation disrupts the Gα o regulatory GTPase cycle by directly impairing Gβγ dissociation. This impairment overrides the presence of wild-type Gα o , explaining the dominant effect of the severe neurogenetic phenotype in the heterozygous background. These findings establish a new molecular mechanism for a GNAO1 mutation with dominant-negative effects on the GTPase regulatory cycle. The insights gained from studying this mechanism of action provide a basis for developing specific and personalized therapeutic strategies based on the outcome of a missense mutation in GNAO1.
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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) | 0.001 | 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) | 0.001 | 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".