Pathogenic variants in <scp><i>KCNQ2</i></scp> cause intellectual deficiency without epilepsy: Broadening the phenotypic spectrum of a potassium channelopathy
Bibliographic record
Abstract
High-throughput sequencing (HTS) improved the molecular diagnosis in individuals with intellectual deficiency (ID) and helped to broaden the phenotype of previously known disease-causing genes. We report herein four unrelated patients with isolated ID, carriers of a likely pathogenic variant in KCNQ2, a gene usually implicated in benign familial neonatal seizures (BFNS) or early onset epileptic encephalopathy (EOEE). Patients were diagnosed by targeted HTS or exome sequencing. Pathogenicity of the variants was assessed by multiple in silico tools. Patients' ID ranged from mild to severe with predominance of speech disturbance and autistic features. Three of the four variants disrupted the same amino acid. Compiling all the pathogenic variants previously reported, we observed a strong overlap between variants causing EOEE, isolated ID, and BFNS and an important intra-familial phenotypic variability, although missense variants in the voltage-sensing domain and the pore are significantly associated to EOEE (p < 0.01, Fisher test). Thus, pathogenic variants in KCNQ2 can be associated with isolated ID. We did not highlight strong related genotype-phenotype correlations in KCNQ2-related disorders. A second genetic hit, a burden of rare variants, or other extrinsic factors may explain such a phenotypic variability. However, it is of interest to study encephalopathy genes in non-epileptic ID patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".