DNA methylation episignature and comparative epigenomic profiling for Pitt-Hopkins syndrome caused by TCF4 variants
Bibliographic record
Abstract
Pitt-Hopkins syndrome (PTHS) is a neurodevelopmental disorder caused by pathogenic variants in TCF4, leading to intellectual disability, specific morphological features, and autonomic nervous system dysfunction. Epigenetic dysregulation has been implicated in PTHS, prompting the investigation of a DNA methylation (DNAm) "episignature" specific to PTHS for diagnostic purposes and variant reclassification and functional insights into the molecular pathophysiology of this disorder. A cohort of 67 individuals with genetically confirmed PTHS and three individuals with intellectual disability and a variant of uncertain significance (VUS) in TCF4 were studied. The DNAm episignature was developed with an Infinium Methylation EPIC BeadChip array analysis using peripheral blood cells. Support vector machine (SVM) modeling and clustering methods were employed to generate a DNAm classifier for PTHS. Validation was extended to an additional cohort of 11 individuals with PTHS. The episignature was assessed in relation to other neurodevelopmental disorders and its specificity was examined. A specific DNAm episignature for PTHS was established. The classifier exhibited high sensitivity for TCF4 haploinsufficiency and missense variants in the basic-helix-loop-helix domain. Notably, seven individuals with TCF4 variants exhibited negative episignatures, suggesting complexities related to mosaicism, genetic factors, and environmental influences. The episignature displayed degrees of overlap with other related disorders and biological pathways. This study defines a DNAm episignature for TCF4-related PTHS, enabling improved diagnostic accuracy and VUS reclassification. The finding that some cases scored negatively underscores the potential for multiple or nested episignatures and emphasizes the need for continued investigation to enhance specificity and coverage across PTHS-related variants.
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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) | 0.000 | 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".