Enhanced Delivery of Ligand-Conjugated Antisense Oligonucleotides (C16-HA-ASO) Targeting Dystrophia Myotonica Protein Kinase Transcripts for the Treatment of Myotonic Dystrophy Type 1
Bibliographic record
Abstract
Myotonic dystrophy type 1 (DM1) is a neuromuscular disorder that affects many organs. It is caused by the expansion of a cytosine–thymine–guanine triplet repeat in the 3′ untranslated region of the human dystrophia myotonica protein kinase (h DMPK ) gene, which results in a toxic gain of function of mutant h DMPK RNA transcripts. Antisense oligonucleotides (ASOs) have emerged in recent years as a potential gene therapy to treat DM1. However, the clinical efficacy of the systemic administration of ASOs is limited by a combination of insufficient potency and poor tissue distribution. In the present study, we assessed the potential of a new ligand-conjugated ASO (IONIS-877864; C16-HA-ASO) to target mutant h DMPK mRNA transcripts in the DMSXL mouse model of DM1 carrying over 1000 CTG pathogenic repeats. DMSXL mice were treated subcutaneously for 9 weeks with either IONIS-877864 (12.5 or 25 mg/kg) or IONIS-486178 (12.5 or 25 mg/kg), an unconjugated ASO with the same sequence. At 25 mg/kg, IONIS-877864 significantly enhanced ASO delivery into the striated muscles of DMSXL mice following systemic administration compared with the unconjugated control. IONIS-877864 was also more efficacious than IONIS-486178, reducing mutant h DMPK transcripts by up to 92% in the skeletal muscles and 78% in the hearts of DMSXL mice. The decrease in mutant h DMPK transcripts in skeletal muscles caused by IONIS-877864 was associated with a significant improvement in muscle strength. IONIS-877864 was nontoxic in the DMSXL mouse model. The present study showed that the C16-HA-conjugated ASO is a powerful tool for the development of gene therapy for DM1.
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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 | 0.000 | 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) | 0.001 | 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".