The Spectrum of Neurologic Phenotypes Associated With <scp><i>NUS1</i></scp> Pathogenic Variants: A Comprehensive Case Series
Bibliographic record
Abstract
OBJECTIVE: A growing body of evidence indicates a strong genetic overlap between developmental and epileptic encephalopathies (DEEs) and movement disorders. De novo loss-of-function variants in NUS1 have been recently identified in DEE cases. Herein, we report a large cohort of cases with pathogenic NUS1 variants and describe their clinical presentation and the details of the associated epilepsy and movement disorders. METHODS: Cases with NUS1-related disorders were identified through a multicentric international collaboration made possible by the GeneMatcher platform. Clinical data were acquired through retrospective case-note review. RESULTS: We identified 41 subjects carrying 38 different pathogenic or likely pathogenic heterozygous NUS1 variants. The majority of cases displayed developmental delays and intellectual disability of variable severity. Epilepsy was present in 68.3% of cases (28/41) with onset typically in early childhood. Strikingly, 87.8% of cases (36/41) presented with movement disorders and for 13 of these cases the movement disorder was not accompanied by epilepsy. The phenomenology of the movement disorders was complex with myoclonus observed in 68.3% of cases (28/41), either in isolation or in combination with dystonia, ataxia, and/or parkinsonism. Seven cases that otherwise did not have prominent movement disorders had mild incoordination and intention tremor, suggestive of cerebellar dysfunction. There was no observed genotype-phenotype correlation, suggesting that other genetic or acquired factors impact the clinical presentation. INTERPRETATION: Heterozygous NUS1 pathogenic variants cause a complex neurological disorder, variably featuring developmental and epileptic encephalopathies and a broad spectrum of movement disorders, which represent the major source of neurological disability for most cases. ANN NEUROL 2025;98:561-572.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".