Missense variant in <i>SRCAP</i> with distinct DNA methylation signature associated with non‐FLHS SRCAP‐related neurodevelopmental disorder
Bibliographic record
Abstract
Floating-Harbor syndrome (FLHS) is a neurodevelopmental disorder (NDD) caused by truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein gene (SRCAP). Truncating variants proximal to this location in SRCAP result in a non-FLHS SRCAP-associated NDD; an overlapping but distinct NDD characterized by developmental delay with or without intellectual disability (ID), hypotonia, normal stature, and behavioral and psychiatric issues. Here, we report a young woman who initially presented in childhood with significant delays in speech and mild ID. In young adulthood, she developed schizophrenia. On physical examination, she had facial features suggestive of 22q11 deletion syndrome. After non-diagnostic chromosomal microarray and trio exome sequencing (ES), a re-analysis of trio ES data identified a de novo missense variant in SRCAP that was proximal to the FLHS critical region. Subsequent DNA methylation studies showed the unique methylation signature associated with pathogenic sequence variants in non-FLHS SRCAP-related NDD. This clinical report describes an individual with non-FLHS SRCAP-related NDD caused by an SRCAP missense variant, and it also demonstrates the clinical utility of ES re-analysis and DNA methylation analysis for undiagnosed patients, in particular, those with variants of uncertain significance.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".