Quantitative DNA methylation analysis improves epigenotype-phenotype correlations in Beckwith-Wiedemann syndrome
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Bibliographic record
Abstract
Beckwith-Wiedemann syndrome (BWS) is a rare disorder characterized by overgrowth and predisposition to embryonal tumors. BWS is caused by various epigenetic and/or genetic alterations that dysregulate the imprinted genes on chromosome region 11p15.5. Molecular analysis is required to reinforce the clinical diagnosis of BWS and to identify BWS patients with cancer susceptibility. This is particularly crucial prenatally because most signs of BWS cannot be recognized in utero. We established a reliable molecular assay by pyrosequencing to quantitatively evaluate the methylation profiles of ICR1 and ICR2. We explored epigenotype-phenotype correlations in 19 patients that fulfilled the clinical diagnostic criteria for BWS, 22 patients with suspected BWS, and three fetuses with omphalocele. Abnormal methylation was observed in one prenatal case and 19 postnatal cases, including seven suspected BWS. Seven cases showed ICR1 hypermethylation, five cases showed ICR2 hypomethylation, and eight cases showed abnormal methylation of ICR1 and ICR2 indicating paternal uniparental disomy (UPD). More cases of ICR1 alterations and UPD were found than expected. This is likely due to the sensitivity of this approach, which can detect slight deviations in methylation from normal levels. There was a significant correlation (p<0.001) between the percentage of ICR1 methylation and BWS features: severe hypermethylation (range: 75-86%) was associated with macroglossia, macrosomia, and visceromegaly, whereas mild hypermethylation (range: 55-59%) was associated with umbilical hernia and diastasis recti. Evaluation of ICR1 and ICR2 methylation by pyrosequencing in BWS can improve epigenotype-phenotype correlations, detection of methylation alterations in suspected cases, and identification of UPD.
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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 | 0.001 |
| 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 it