Variable expressivity of a likely pathogenic variant in <i>KCNQ2</i> in a three‐generation pedigree presenting with intellectual disability with childhood onset seizures
Bibliographic record
Abstract
KCNQ2 has been reported as a frequent cause of autosomal dominant benign familial neonatal seizures. De novo likely pathogenic variants in KCNQ2 have been described in neonatal or early infantile onset epileptic encephalopathy patients. Here, we report a three-generation family with six affected patients with a novel likely pathogenic variant (c.628C>T; p.Arg210Cys) in KCNQ2. Four family members, three adults and a child, presented with a childhood seizure onset with variability in the severity of seizures and response to treatment, intellectual disability (ID) as well as behavioral problems. The two youngest affected patients had a variable degree of global developmental delay with no seizures at their current age. This three-generation family with six affected members expands the phenotypic spectrum of KCNQ2 associated encephalopathy to KCNQ2 associated ID and or childhood onset epileptic encephalopathy. We think that KCNQ2 associated epileptic encephalopathy should be included in the differential diagnosis of childhood onset epilepsy and early onset global developmental delay, cognitive dysfunction, or ID. Furthermore, whole exome sequencing in families with ID and history of autosomal dominant inheritance pattern with or without seizures, may further broaden the phenotypic spectrum of KCNQ2 associated epileptic encephalopathy or encephalopathy.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".