Multi-exon Skipping Using Cocktail Antisense Oligonucleotides in the Canine X-linked Muscular Dystrophy
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is one of the most common lethal genetic diseases worldwide, caused by mutations in the dystrophin (DMD) gene. Exon skipping employs short DNA/RNA-like molecules called antisense oligonucleotides (AONs) that restore the reading frame and produce shorter but functional proteins. However, exon skipping therapy faces two major hurdles: limited applicability (up to only 13% of patients can be treated with a single AON drug), and uncertain function of truncated proteins. These issues were addressed with a cocktail AON approach. While approximately 70% of DMD patients can be treated by single exon skipping (all exons combined), one could potentially treat more than 90% of DMD patients if multiple exon skipping using cocktail antisense drugs can be realized. The canine X-linked muscular dystrophy (CXMD) dog model, whose phenotype is more similar to human DMD patients, was used to test the systemic efficacy and safety of multi-exon skipping of exons 6 and 8. The CXMD dog model harbors a splice site mutation in intron 6, leading to a lack of exon 7 in dystrophin mRNA. To restore the reading frame in CXMD requires multi-exon skipping of exons 6 and 8; therefore, CXMD is a good middle-sized animal model for testing the efficacy and safety of multi-exon skipping. In the current study, a cocktail of antisense morpholinos targeting exon 6 and exon 8 was designed and it restored dystrophin expression in body-wide skeletal muscles. Methods for transfection/injection of cocktail oligos and evaluation of the efficacy and safety of multi-exon skipping in the CXMD dog model are presented.
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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 | 0.000 | 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".