Methylation assay in KMT2B-related dystonia: a novel diagnostic validation tool
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: KMT2B-related dystonia (DYT28, OMIM #617284) is a progressive neurological condition characterized by early onset movement disorders with autosomal dominant inheritance. In this study, we describe the use of a genome methylation episignature methodology to functionally validate two variants of uncertain significance (VUS) in the KMT2B gene. METHODS: Genome-wide methylation status was assessed using the EPIC methylation assay in peripheral blood samples from two subjects with early onset movement disorder and missense variants of uncertain significance in the KMT2B gene (p.Leu1720Phe and p.Tyr2515Cys). After QC and normalization steps, we compared the M values for all 144 probes, previously described as an EpiSign for KMT2B-related dystonia, between the two subjects and 14 controls individuals. RESULTS: The individual harboring the p.Tyr2515Cys variant exhibited a hypermethylation profile compatible with pathogenic/likely pathogenic variants in KMT2B, allowing for variant reclassification, conclusive genetic counseling, and patient stratification for deep brain stimulation. In contrast, the individual harboring the p.Leu1720Phe variant had a methylation status similar to controls, practically ruling out KMT2B-related dystonia. CONCLUSION: Investigation of methylation status can be a powerful tool to determine pathogenicity when facing KMT2B variants of uncertain significance. Methylation results may optimize genetic counseling and positively impact patient care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".