Expanding the genotypic and phenotypic spectrum in a diverse cohort of 104 individuals with Wiedemann‐Steiner syndrome
Bibliographic record
Abstract
Wiedemann-Steiner syndrome (WSS) is an autosomal dominant disorder caused by monoallelic variants in KMT2A and characterized by intellectual disability and hypertrichosis. We performed a retrospective, multicenter, observational study of 104 individuals with WSS from five continents to characterize the clinical and molecular spectrum of WSS in diverse populations, to identify physical features that may be more prevalent in White versus Black Indigenous People of Color individuals, to delineate genotype-phenotype correlations, to define developmental milestones, to describe the syndrome through adulthood, and to examine clinicians' differential diagnoses. Sixty-nine of the 82 variants (84%) observed in the study were not previously reported in the literature. Common clinical features identified in the cohort included: developmental delay or intellectual disability (97%), constipation (63.8%), failure to thrive (67.7%), feeding difficulties (66.3%), hypertrichosis cubiti (57%), short stature (57.8%), and vertebral anomalies (46.9%). The median ages at walking and first words were 20 months and 18 months, respectively. Hypotonia was associated with loss of function (LoF) variants, and seizures were associated with non-LoF variants. This study identifies genotype-phenotype correlations as well as race-facial feature associations in an ethnically diverse cohort, and accurately defines developmental trajectories, medical comorbidities, and long-term outcomes in individuals with WSS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".