Ultra–sensitive droplet digital PCR for detecting a low–prevalence somatic GNAQ mutation in Sturge–Weber syndrome
Bibliographic record
Abstract
Droplet digital PCR (ddPCR), a method for measuring target nucleic acid sequence quantity, is useful for determining somatic mutation rates using TaqMan probes. In this study, the detection limit of copy numbers of test DNA by ddPCR was determined based on Poisson distribution. Peptide nucleic acid (PNA), which strongly hybridises to target lesions, can inhibit target amplification by PCR. Therefore, by combination of PCR with PNA and ddPCR (PNA-ddPCR), the detection limit could be lowered. We reanalysed a somatic GNAQ mutation (c.548G > A) in patients with Sturge-Weber syndrome (SWS) using ddPCR and PNA-ddPCR. Importantly, among three patients previously found to be mutation negative by next-generation sequencing, two patients had the GNAQ mutation with a mutant allele frequency of less than 1%. Furthermore, we were able to find the same mutation in blood leukocyte or saliva DNA derived from four out of 40 SWS patients. Vascular anomalies and blood leukocytes originate from endothelial cells and haemangioblasts, respectively, which are both of mesodermal origin. Therefore, blood leukocytes may harbour the GNAQ mutation, depending on the time when the somatic mutation is acquired. These data suggest the possibility of diagnosis using blood DNA in some patients with SWS.
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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 | 0.001 |
| 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 | 0.001 |
| 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".