Strategy for Comprehensive Molecular Testing for Duchenne and Becker Muscular Dystrophies
Bibliographic record
Abstract
Comprehensive molecular testing for mutations in the DMD gene causing Duchenne and Becker muscular dystrophy (DMD/BMD) is challenging because of the large size of the gene and the variety of mutation types. There is an increasing demand for comprehensive DMD gene molecular testing, including deletion/duplication testing of 79 exons and direct sequencing of the 14-kb coding region from genomic DNA, to provide confirmation of clinical diagnoses in affected patients and to determine carrier risk for family members. To determine an efficient strategy to prioritize patients for comprehensive molecular testing of the DMD gene, we tested a consecutive cohort of 165 males referred over a 4-year period because of a suspicion of DMD or BMD using: (1) a new quantitative multiplex polymerase chain reaction (PCR) assay designed to detect deletions or duplications in all exons of the gene and the brain promoter and (2) direct sequencing of the coding region and intron/exon boundaries. For the patients being tested because of a suspicion of DMD, deletion/duplication testing followed by direct sequencing detected pathogenic mutations in 98% (106/108 total patients). However, of the patients tested because of a suspicion of BMD, only 60% (34/57 total patients) had causative mutations identified, all of which were deletions or duplications. Our results suggest that direct genomic sequence analysis of the DMD gene is a useful addition to deletion/duplication testing for diagnosis of DMD, but does not provide an improved sensitivity compared to deletion/duplication analysis alone for the diagnosis of BMD. In addition, due to the relatively common finding of single exon deletions and duplications (22%, 27 of 125 total patients with deletions/duplications), methods to examine all exons of the gene for deletions/duplications should be used as the initial molecular quantitative test for DMD and BMD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".