Functional annotation of genomic variation: DNA methylation episignatures in neurodevelopmental Mendelian disorders
Bibliographic record
Abstract
The breadth and complexity of genetic testing in patients with suspected Mendelian neurodevelopmental disorders has rapidly expanded in the past two decades. However, in spite of advances in genomic technologies, genetic diagnosis remains elusive in more than half of these patients. Epigenomics, and in particular genomic DNA methylation profiles, are now known to be associated with the underpinning genetic defects in a growing number of Mendelian disorders. These often highly specific and sensitive molecular biomarkers have been used to screen these patient populations, resolve ambiguous clinical cases and interpret genetic variants of unknown clinical significance. Increasing the diagnostic yield beyond genomic sequencing technologies has rapidly propelled epigenomics to clinical utilization, with recent introduction of DNA methylation 'EpiSign' analysis in clinical diagnostic laboratories. This review provides an overview of the principles, applications and limitations of DNA methylation episignature analysis in patients with neurodevelopmental Mendelian disorders, and discusses clinical implications of this emerging diagnostic technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".