Clinical and Functional Study of a De Novo Variant in the PVP Motif of Kv1.1 Channel Associated with Epilepsy, Developmental Delay and Ataxia
Bibliographic record
Abstract
Mutations in the KCNA1 gene, encoding the voltage-gated potassium channel Kv1.1, have been associated with a spectrum of neurological phenotypes, including episodic ataxia type 1 and developmental and epileptic encephalopathy. We have recently identified a de novo variant in KCNA1 in the highly conserved Pro-Val-Pro motif within the pore of the Kv1.1 channel in a girl affected by early onset epilepsy, ataxia and developmental delay. Other mutations causing severe epilepsy are located in Kv1.1 pore domain. The patient was initially treated with a combination of antiepileptic drugs with limited benefit. Finally, seizures and ataxia control were achieved with lacosamide and acetazolamide. The aim of this study was to functionally characterize Kv1.1 mutant channel to provide a genotype–phenotype correlation and discuss therapeutic options for KCNA1-related epilepsy. To this aim, we transfected HEK 293 cells with Kv1.1 or P403A cDNAs and recorded potassium currents through whole-cell patch-clamp. P403A channels showed smaller potassium currents, voltage-dependent activation shifted by +30 mV towards positive potentials and slower kinetics of activation compared with Kv1.1 wild-type. Heteromeric Kv1.1+P403A channels, resembling the condition of the heterozygous patient, confirmed a loss-of-function biophysical phenotype. Overall, the functional characterization of P403A channels correlates with the clinical symptoms of the patient and supports the observation that mutations associated with severe epileptic phenotype cluster in a highly conserved stretch of residues in Kv1.1 pore domain. This study also strengthens the beneficial effect of acetazolamide and sodium channel blockers in KCNA1 channelopathies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".