The defining DNA methylation signature of Kabuki syndrome enables functional assessment of genetic variants of unknown clinical significance
Bibliographic record
Abstract
Kabuki syndrome (KS) is caused by mutations in KMT2D, which is a histone methyltransferase involved in methylation of H3K4, a histone marker associated with DNA methylation. Analysis of >450,000 CpGs in 24 KS patients with pathogenic mutations in KMT2D and 216 controls, identified 24 genomic regions, along with 1,504 CpG sites with significant DNA methylation changes including a number of Hox genes and the MYO1F gene. Using the most differentiating and significant probes and regions we developed a "methylation variant pathogenicity (MVP) score," which enables 100% sensitive and specific identification of individuals with KS, which was confirmed using multiple public and internal patient DNA methylation databases. We also demonstrated the ability of the MVP score to accurately reclassify variants of unknown significance in subjects with apparent clinical features of KS, enabling its potential use in molecular diagnostics. These findings provide novel insights into the molecular etiology of KS and illustrate that DNA methylation patterns can be interpreted as 'epigenetic echoes' in certain clinical disorders.
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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 | 0.000 | 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".