Variants in <i>BSN</i> , encoding the presynaptic protein Bassoon, result in a novel neurodevelopmental disorder with a broad phenotypic range
Bibliographic record
Abstract
Abstract Disease-causing variants in synaptic function genes are a common cause of neurodevelopmental disorders and epilepsy. Here, we describe 14 individuals with de novo disruptive variants in BSN , which encodes the presynaptic protein Bassoon. To expand the phenotypic spectrum, we identified 15 additional individuals with protein-truncating variants (PTVs) from large biobanks. Clinical features were standardized using the Human Phenotype Ontology (HPO) across all 29 individuals, which revealed common clinical characteristics including epilepsy (13/29 45%), febrile seizures (7/29 25%), generalized tonic-clonic seizures (5/29 17%), and focal onset seizures (3/29 10%). Behavioral phenotypes were present in almost half of all individuals (14/29 48%), which comprised ADHD (7/29 25%) and autistic behavior (5/29 17%). Additional common features included developmental delay (11/29 38%), obesity (10/29 34%), and delayed speech (8/29 28%). In adults with BSN PTVs, milder features were common, suggesting phenotypic variability including a range of individuals without obvious neurodevelopmental features (7/29 24%). To detect gene-specific signatures, we performed association analysis in a cohort of 14,895 individuals with neurodevelopmental disorders (NDDs). A total of 66 clinical features were associated with BSN , including febrile seizures (p=1.26e-06) and behavioral disinhibition (p = 3.39e-17). Furthermore, individuals carrying BSN variants were phenotypically more similar than expected by chance (p=0.00014), exceeding phenotypic relatedness in 179/256 NDD-related conditions. In summary, integrating information derived from community-based gene matching and large data repositories through computational phenotyping approaches, we identify BSN variants as the cause of a new class of synaptic disorder with a broad phenotypic range across the age spectrum.
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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 | 0.001 | 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) | 0.002 | 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".