A Rare KIF1A Missense Mutation Enhances Synaptic Function and Increases Seizure Activity
Bibliographic record
Abstract
Although genetic factors are considered a main etiology of epilepsy, the causes of genetic epilepsy in the majority of epilepsy patients remain unknown. Kinesin family member 1A (KIF1A), a neuron-specific motor protein that moves along with microtubules, is responsible for the transport of membranous organelles and synaptic vesicles. Variants of KIF1A have recently been associated with hereditary spastic paraplegia (HSP), hereditary sensory and autonomic neuropathy type 2 (HSANII) and intellectual disability. However, mutations in KIF1A have not been detected in patients with epilepsy. In our study, we conducted customized sequencing of epilepsy-related genes of a family with six patients with generalized epilepsy over three generations and identified a rare heterozygous mutation (c.1190C>A, p. Ala397Asp) in KIF1A. Whole-cell recordings from primary cultured neurons revealed that the mutant KIF1A increases the excitatory synaptic transmission but not the intrinsic excitability of neurons, and phenotype testing in zebrafish showed that this rare mutation results in epileptic seizure-like activity. These results provide new evidence demonstrating that KIF1A dysfunction is involved in epileptogenesis.
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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 | 0.000 |
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".