Development of a novel oral treatment that rescues gait ataxia and retinal degeneration in a phenotypic mouse model of familial dysautonomia
Bibliographic record
Abstract
Abstract Familial Dysautonomia (FD) is a rare neurodegenerative disease caused by a splicing mutation in the Elongator complex protein 1 gene ( ELP1 ). This mutation leads to the skipping of exon 20 and a tissue-specific reduction of ELP1 protein, mainly in the central and peripheral nervous systems. FD is a complex neurological disorder accompanied by severe gait ataxia and retinal degeneration. There is currently no effective treatment to restore ELP1 protein expression in individuals with FD, and the disease is ultimately fatal. After identifying kinetin as a small molecule able to correct the ELP1 splicing defect, we worked on its optimization to generate novel splicing modulator compounds (SMCs) that can be used in patients. Here, we optimize the potency, efficacy, and bio-distribution of second-generation kinetin derivatives to develop an oral treatment for FD that can efficiently pass the blood-brain barrier and correct the ELP1 splicing defect in the nervous system. We demonstrate that the novel compound, PTC258, efficiently restores correct ELP1 splicing in mouse tissues, including brain, and most importantly, prevents the progressive neuronal degeneration that is characteristic of FD. Postnatal oral administration of PTC258 to the phenotypic mouse model TgFD9;Elp1 Δ20/flox increases full-length ELP1 transcript in a dose-dependent manner and leads to a two-fold increase in functional ELP1 protein in the brain. Remarkably, PTC258 treatment improves survival, gait ataxia, and retinal degeneration in the phenotypic FD mice. Our findings highlight the great therapeutic potential of this novel class of small molecules as an oral treatment for FD.
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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".