Further Characterization of <i>SMC1A</i> Loss of Function Epilepsy Distinct From Cornelia de Lange Syndrome
Bibliographic record
Abstract
Cornelia de Lange syndrome is a rare developmental malformation syndrome characterized by small stature, limb anomalies, distinctive facial features, developmental delays, and behavioral issues. The diagnosis of Cornelia de Lange syndrome is made clinically or on the basis of an identified variant in one of the genes associated with Cornelia de Lange syndrome. SMC1A variants are the cause of 5% of the cases of Cornelia de Lange syndrome. SMC1A is located on the X-chromosome and is thought to escape X-inactivation in some females. Patients with SMC1A variants are being increasingly identified through panel testing or exome sequencing without prior clinical suspicion of Cornelia de Lange syndrome. In general, intractable epilepsy is not considered a prominent feature of Cornelia de Lange syndrome, yet this is found in these patients with SMC1A variants. Here we report on a series of patients with SMC1A variants and intractable epilepsy. In contrast to patients with typical SMC1A-associated Cornelia de Lange syndrome, all of the identified patients were female, and when available, X-inactivation studies were highly skewed with truncating variants. We describe the medical involvement and physical appearance of the participants, compared to the diagnostic criteria used for classical Cornelia de Lange syndrome. We also report on the clinical characteristics of the epilepsy, including age of onset, types of seizures, electroencephalographic (EEG) findings, and response to various antiepileptic medications. These findings allow us to draw conclusions about how this population of patients with SMC1A variants fit into the spectrum of Cornelia de Lange syndrome and the broader spectrum of cohesinopathies and allow generalizations that may impact clinical care and, in particular, epilepsy management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".