Rubinstein–Taybi syndrome type 2: report of nine new cases that extend the phenotypic and genotypic spectrum
Bibliographic record
Abstract
Rubinstein-Taybi syndrome (RTS) is an autosomal dominant neurodevelopmental disorder characterized by growth deficiency, broad thumbs and great toes, intellectual disability and characteristic craniofacial appearance. Mutations in CREBBP account for around 55% of cases, with a further 8% attributed to the paralogous gene EP300. Comparatively few reports exist describing the phenotype of Rubinstein-Taybi because of EP300 mutations. Clinical and genetic data were obtained from nine patients from the UK and Ireland with pathogenic EP300 mutations, identified either by targeted testing or by exome sequencing. All patients had mild or moderate intellectual impairment. Behavioural or social difficulties were noted in eight patients, including three with autistic spectrum disorders. Typical dysmorphic features of Rubinstein-Taybi were only variably present. Additional observations include maternal pre-eclampsia (2/9), syndactyly (3/9), feeding or swallowing issues (3/9), delayed bone age (2/9) and scoliosis (2/9). Six patients had truncating mutations in EP300, with pathogenic missense mutations identified in the remaining three. The findings support previous observations that microcephaly, maternal pre-eclampsia, mild growth restriction and a mild to moderate intellectual disability are key pointers to the diagnosis of EP300-related RTS. Variability in the presence of typical facial features of Rubinstein-Taybi further highlights clinical heterogeneity, particularly among patients identified by exome sequencing. Features that overlap with Floating-Harbor syndrome, including craniofacial dysmorphism and delayed osseous maturation, were observed in three patients. Previous reports have only described mutations predicted to cause haploinsufficiency of EP300, whereas this cohort includes the first described pathogenic missense mutations in EP300.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".