Pharmacological cAMP stimulation via prostaglandin receptors rescues ciliary defects in CEP290-deficient human and mouse models
Bibliographic record
Abstract
ABSTRACT The retina’s sensitivity to light depends on the primary cilium of photoreceptors, known as the outer segment (OS). OS defects are a primary cause of inherited retinal dystrophies (IRDs) and can also indicate wider ciliary dysfunctions. One such IRD is Leber congenital amaurosis type 10 (LCA10), which occurs as a monosymptomatic retinal disease or the presenting symptom of syndromic ciliopathies within the Senior-Loken-Joubert-Meckel spectrum. LCA10 patients are born blind but retain dormant photoreceptors for decades, offering the potential for reactivation. AAV-based gene therapies for IRDs cannot accommodate the large CEP290 gene, prompting the search for innovative treatments. LCA10 is caused by mutations in CEP290 , which plays a vital role in ciliation, similar to cAMP signaling. Utilizing fibroblasts displaying variable CEP290 mutations and associated ciliary defects, we show that exposure to Taprenepag, a specific PGE2 receptor agonist, substantially stimulated cAMP synthesis and consistently improved cilia formation and elongation. We also found that intraperitoneal injection of Taprenepag in mice reached the retina and slowed retinal degeneration, promoting OS formation, and improving light sensitivity in a Cep290 mutant mouse. These findings demonstrate the potential of Taprenepag to treat the CEP290-related visual dysfunction and suggest evaluation for other CEP290-related organ issues and ciliopathies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".