Mutations in <i><scp>KCNT</scp>1</i> cause a spectrum of focal epilepsies
Bibliographic record
Abstract
Autosomal dominant mutations in the sodium-gated potassium channel subunit gene KCNT1 have been associated with two distinct seizure syndromes, nocturnal frontal lobe epilepsy (NFLE) and malignant migrating focal seizures of infancy (MMFSI). To further explore the phenotypic spectrum associated with KCNT1, we examined individuals affected with focal epilepsy or an epileptic encephalopathy for mutations in the gene. We identified KCNT1 mutations in 12 previously unreported patients with focal epilepsy, multifocal epilepsy, cardiac arrhythmia, and in a family with sudden unexpected death in epilepsy (SUDEP), in addition to patients with NFLE and MMFSI. In contrast to the 100% penetrance so far reported for KCNT1 mutations, we observed incomplete penetrance. It is notable that we report that the one KCNT1 mutation, p.Arg398Gln, can lead to either of the two distinct phenotypes, ADNFLE or MMFSI, even within the same family. This indicates that genotype-phenotype relationships for KCNT1 mutations are not straightforward. We demonstrate that KCNT1 mutations are highly pleiotropic and are associated with phenotypes other than ADNFLE and MMFSI. KCNT1 mutations are now associated with Ohtahara syndrome, MMFSI, and nocturnal focal epilepsy. They may also be associated with multifocal epilepsy and cardiac disturbances.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".