P.053 Biallelic SCN1A variants with divergent epilepsy phenotypes
Bibliographic record
Abstract
Background: Dravet syndrome and genetic epilepsy with febrile seizures plus (GEFS+) are associated with pathogenic variants in SCN1A. While most such cases are heterozygous, there have been 16 reported homozygous cases. We report two new biallelic cases associated with divergent phenotypes.Methods: We performed a chart review for two patients with different homozygous SCN1A variants and reviewed all previously published biallelic SCN1A pathogenic variants. Results: Our first patient exhibited early afebrile seizures and severe developmental delay, without febrile seizures or status epilepticus. A homozygous c. 1676T>A, (p. Ile559Asn) variant of uncertain significance was identified, carried by asymptomatic parents. The second patient exhibited early, recurrent, and prolonged febrile seizures, moderate developmental delay, and motor dysfunction; a homozygous pathogenic c. 4970G>A, (p. Arg1657His) variant carried by asymptomatic parents was identified. Of 18 known cases of biallelic SCN1A pathogenic variants, 15/18 (83%) have diagnoses of Dravet or GEFS+. The remaining 3/18 (17%) had pharmacoresponsive epilepsy with prominent GDD. Cognitive phenotypes ranged from intact neurodevelopment to profound developmental delay. Eleven out of 18 cases (61%) had motor concerns. Conclusions: These cases expand the phenotypic spectrum of biallelic SCN1A variants. While some patients present typically for Dravet/GEFS+, others present with developmental delay and controllable epilepsy.
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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) | 0.001 | 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) | 0.006 | 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".