A Genotype-Phenotype Correlation Study of Exon Skip-Equivalent In-Frame Deletions and Exon Skip-Amenable Out-of-Frame Deletions across the DMD Gene to Simulate the Effects of Exon-Skipping Therapies: A Meta-Analysis
Bibliographic record
Abstract
Dystrophinopathies are caused by mutations in the DMD gene. Out-of-frame deletions represent most mutational events in severe Duchenne muscular dystrophy (DMD), while in-frame deletions typically lead to milder Becker muscular dystrophy (BMD). Antisense oligonucleotide-mediated exon skipping converts an out-of-frame transcript to an in-frame one, inducing a truncated but partially functional dystrophin protein. The reading frame rule, however, has many exceptions. We thus sought to simulate clinical outcomes of exon-skipping therapies for DMD exons from clinical data of exon skip-equivalent in-frame deletions, in which the expressed quasi-dystrophins are comparable to those resulting from exon-skipping therapies. We identified a total of 1298 unique patients with exon skip-equivalent mutations in patient registries and the existing literature. We classified them into skip-equivalent deletions of each exon and statistically compared the ratio of DMD/BMD and asymptomatic individuals across the DMD gene. Our analysis identified that five exons are associated with significantly milder phenotypes than all other exons when corresponding exon skip-equivalent in-frame deletion mutations occur. Most exon skip-equivalent in-frame deletions were associated with a significantly milder phenotype compared to corresponding exon skip-amenable out-of-frame mutations. This study indicates the importance of genotype-phenotype correlation studies in the rational design of exon-skipping therapies.
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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) | 0.001 | 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 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".