Linkage analysis and exome sequencing identify a novel mutation in <i><scp>KCTD</scp>7</i> in patients with progressive myoclonus epilepsy with ataxia
Bibliographic record
Abstract
Epilepsy affects approximately 1% of the world's population. Genetic factors and acquired etiologies, as well as a range of environmental triggers, together contribute to epileptogenesis. We have identified a family with three daughters affected with progressive myoclonus epilepsy with ataxia. Clinical details of the onset and progression of the neurologic presentation, epileptic seizures, and the natural history of progression over a 10-year period are described. Using autozygosity genetic mapping, we identified a high likelihood homozygous region on chromosome 7p12.1-7q11.22. We subsequently applied whole-exome sequencing and employed a rare variant prioritization analysis within the homozygous region. We identified p.Tyr276Cys in the potassium channel tetramerization domain-containing seven gene, KCTD7, which is expressed predominantly in the brain. Mutations in this gene have been implicated previously in epileptic phenotypes due to disturbances in potassium channel conductance. Pathogenicity of the mutation was supported by bioinformatic predictive analyses and variant cosegregation within the family. Further biologic validation is necessary to fully characterize the pathogenic mechanisms that explain the phenotypic causes of epilepsy with ataxia in these patients.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".