Allele-Selective LNA Gapmers for the Treatment of Fibrodysplasia Ossificans Progressiva Knock Down the Pathogenic ACVR1 <sup>R206H</sup> Transcript and Inhibit Osteogenic Differentiation
Bibliographic record
Abstract
Fibrodysplasia ossificans progressiva (FOP) is a rare autosomal dominant disorder characterized by episodic heterotopic ossification. The median life span of people with this disorder is ∼40 years, and currently, there is no effective treatment available. More than 95% of cases are caused by a recurrent mutation (c.617G>A; R206H) of Activin A receptor, type I (ACVR1)/Activin receptor-like kinase-2 (ALK2), a bone morphogenetic protein type I receptor. The mutation renders ACVR1 responsive to activin A, which does not activate wild-type ACVR1. Ectopic activation of ACVR1 R206H by activin A induces heterotopic ossification. Since ACVR1 R206H is a hyperactive receptor, a promising therapeutic strategy is to decrease the activity of mutated ACVR1. To accomplish this goal, we developed locked nucleic acid (LNA) gapmers. These are short DNA oligonucleotides with LNA modification at both ends. They induce targeted mRNA degradation and specific knockdown of gene expression. We demonstrated that some of these gapmers efficiently knocked down ACVR1 R206H expression at RNA levels, while ACVR1 WT was mostly unaffected in human FOP fibroblasts. Also, the gapmers suppressed osteogenic differentiation induced by ACVR1 R206H and activin A. These gapmers may be promising drug candidates for FOP. This novel strategy will also pave the way for antisense-mediated therapy of other autosomal dominant disorders.
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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 | 0.001 |
| 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".