Genome‐wide <scp>DNA</scp> methylation profiling confirms a case of low‐level mosaic Kabuki syndrome 1
Bibliographic record
Abstract
Kabuki syndrome is a Mendelian disorder of the epigenetic machinery characterized by typical dysmorphic features, intellectual disability, and postnatal growth deficiency. Pathogenic variants in the genes encoding the chromatin modifiers KMT2D and KDM6A are responsible for Kabuki syndrome 1 (KS1) and Kabuki syndrome 2 (KS2), respectively. In addition, 11 cases of KS1 caused by mosaic variants in KMT2D have been reported in the literature. Some of these individuals display milder craniofacial and growth phenotypes, and most do not have congenital heart defects. We report the case of an infant with severe hypoplastic left heart syndrome with mitral atresia and aortic atresia (HLHS MA-AA), pulmonary vein stenosis, and atypical facies with a somatic mosaic de novo nonsense variant in KMT2D (c.8200C>T, p.R2734*) identified on trio exome sequencing of peripheral blood and present in 11.2% of sequencing reads. KS was confirmed with EpiSign, a diagnostic genome-wide DNA methylation platform used to identify epigenetic signatures. This case suggests that use of this newly available clinical test can guide the interpretation of low-level mosaic variants identified through sequencing and suggests a new lower limit of mosaicism in whole blood required for a diagnosis of KS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".