A Novel KCNA2 Variant in a Patient with Non-Progressive Congenital Ataxia and Epilepsy: Functional Characterization and Sensitivity to 4-Aminopyridine
Bibliographic record
Abstract
Kv1.2 channels, encoded by the KCNA2 gene, are localized in the central and peripheral nervous system, where they regulate neuronal excitability. Recently, heterozygous mutations in KCNA2 have been associated with a spectrum of symptoms extending from epileptic encephalopathy, intellectual disability, and cerebellar ataxia. Patients are treated with a combination of antiepileptic drugs and 4-aminopyridine (4-AP) has been recently trialed in specific cases. We identified a novel variant in KCNA2, E236K, in a Serbian proband with non-progressive congenital ataxia and early onset epilepsy, treated with sodium valproate. To ascertain the pathogenicity of E236K mutation and to verify its sensitivity to 4-AP, we transfected HEK 293 cells with Kv1.2 WT or E236K cDNAs and recorded potassium currents through the whole-cell patch-clamp. In silico analysis supported the electrophysiological data. E236K channels showed voltage-dependent activation shifted towards negative potentials and slower kinetics of deactivation and activation compared with Kv1.2 WT. Heteromeric Kv1.2 WT+E236K channels, resembling the condition of the heterozygous patient, confirmed a mixed gain- and loss-of-function (GoF/LoF) biophysical phenotype. 4-AP inhibited both Kv1.2 and E236K channels with similar potency. Homology modeling studies of mutant channels suggested a reduced interaction between the residue K236 in the S2 segment and the gating charges at S4. Overall, the biophysical phenotype of E236K channels correlates with the mild end of the clinical spectrum reported in patients with GoF/LoF defects. The response to 4-AP corroborates existing evidence that KCNA2-disorders could benefit from variant-tailored therapeutic approaches, based on functional studies.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".