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 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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.014 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".