Functional Effects of Epilepsy Associated KCNT1 Mutations Suggest Pathogenesis via Aberrant Inhibitory Neuronal Activity
Bibliographic record
Abstract
KCNT1 (K+ channel subfamily T member 1) is a sodium-activated potassium channel highly expressed in the nervous system which regulates neuronal excitability by contributing to the resting membrane potential and hyperpolarisation following a train of action potentials. Gain of function mutations in the KCNT1 gene are the cause of neurological disorders associated with different forms of epilepsy. To gain insights into the underlying pathobiology we investigated the functional effects of 9 recently published KCNT1 mutations, 4 previously studied KCNT1 mutations, and one previously unpublished KCNT1 variant of unknown significance. We analysed the properties of KCNT1 potassium currents and attempted to find a correlation between the changes in KCNT1 characteristics due to the mutations and severity of the neurological disorder they cause. KCNT1 mutations identified in patients with epilepsy were introduced into the full length human KCNT1 cDNA using quick-change site-directed mutagenesis protocol. Electrophysiological properties of different KCNT1 constructs were investigated using a heterologous expression system (HEK293T cells) and patch clamping. All mutations studied, except T314A, increased the amplitude of KCNT1 currents, and some mutations shifted the voltage dependence of KCNT1 open probability, increasing the proportion of channels open at the resting membrane potential. The T314A mutation did not affect KCNT1 current amplitude but abolished its voltage dependence. We observed a positive correlation between the severity of the neurological disorder and the KCNT1 channel open probability at resting membrane potential. This suggests that gain of function KCNT1 mutations cause epilepsy by increasing resting potassium conductance and suppressing the activity of inhibitory neurons. A reduction in action potential firing in inhibitory neurons due to excessively high resting potassium conductance leads to disinhibition of neural circuits, hyperexcitability and seizures.
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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) | 0.001 | 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".