Long-read sequencing for detection and subtyping of Prader-Willi and Angelman syndromes
Bibliographic record
Abstract
Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are imprinting disorders caused by genetic or epigenetic aberrations of 15q11.2-q13. Their clinical testing is often multitiered; diagnostic testing begins with methylation-specific multiplex ligation-dependent probe amplification or methylation-sensitive PCR and then proceeds to molecular subtyping to determine the mechanism and recurrence risk. Currently, correct classification of a proband’s PWS/AS subtype often requires parental samples, a costly process for families and health systems. The use of nanopore sequencing for molecular diagnosis of PWS and AS has been explored by Yamada et al ; however, to confirm heterodisomy parental data were still required. Here, we investigate genome-wide nanopore sequencing in a larger cohort of PWS (18) and AS (6) as a singular test to detect the molecular subtype, without parental data. We accurately subtyped these cases including uniparental heterodisomy, mixed iso-/heterodisomy, type 1 and 2 deletions, microdeletion and UBE3A indels. One PWS case with a previously unresolved diagnosis subtyped as maternal isodisomy. This work highlights the application of long-read sequencing and other imprinted regions outside of the PWS/AS critical region to resolve the molecular diagnosis and subtyping of PWS and AS without parental data. The work also outlines an approach to generically detect heterodisomy through the interrogation of distant imprinted regions.
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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 | 0.001 | 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".