The landscape of epilepsy-related GATOR1 variants
Bibliographic record
Abstract
PURPOSE: To define the phenotypic and mutational spectrum of epilepsies related to DEPDC5, NPRL2 and NPRL3 genes encoding the GATOR1 complex, a negative regulator of the mTORC1 pathway METHODS: We analyzed clinical and genetic data of 73 novel probands (familial and sporadic) with epilepsy-related variants in GATOR1-encoding genes and proposed new guidelines for clinical interpretation of GATOR1 variants. RESULTS: The GATOR1 seizure phenotype consisted mostly in focal seizures (e.g., hypermotor or frontal lobe seizures in 50%), with a mean age at onset of 4.4 years, often sleep-related and drug-resistant (54%), and associated with focal cortical dysplasia (20%). Infantile spasms were reported in 10% of the probands. Sudden unexpected death in epilepsy (SUDEP) occurred in 10% of the families. Novel classification framework of all 140 epilepsy-related GATOR1 variants (including the variants of this study) revealed that 68% are loss-of-function pathogenic, 14% are likely pathogenic, 15% are variants of uncertain significance and 3% are likely benign. CONCLUSION: Our data emphasize the increasingly important role of GATOR1 genes in the pathogenesis of focal epilepsies (>180 probands to date). The GATOR1 phenotypic spectrum ranges from sporadic early-onset epilepsies with cognitive impairment comorbidities to familial focal epilepsies, and SUDEP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".