SynTEF1 restores the functional disease phenotype of SCA27B in an hiPSC-derived neuronal disease model
Bibliographic record
Abstract
Abstract Spinocerebellar Ataxia 27B (SCA27B), caused by a deep-intronic GAA•TTC repeat expansion in the first intron of the FGF14 gene, is one of the most frequent genetic ataxias. Its underlying disease mechanisms remain largely unknown, and disease-modifying therapies targeting upstream processes are lacking. Here we hypothesized that (i) SCA27B is driven by transcriptional repression of FGF14 , which encodes a protein regulating ion channels at the axon initial segment (AIS), resulting in reduced Na + channel availability and neuronal excitability, and that (ii) these defects can be restored by a synthetic elongation transcription factor (Syn-TEF1). We assessed FGF14 mRNA levels by qPCR and neuronal function by whole-cell patch-clamp recordings in iPSC-derived neurons from two SCA27B patients and two healthy controls. Patients carried GAA•TTC repeat expansions that were either monoallelic (391/16 repeats) or biallelic (315/290 repeats), exceeding the common pathogenicity threshold of >250 repeats. FGF14 mRNA levels were reduced approximately to 60% and 70% of control levels in monoallelic and biallelic SCA27B neurons, respectively. This was accompanied by impaired excitability, with cumulative action potential (AP) firing reduced to 38% and 45% of control levels in monoallelic and biallelic lines, respectively, and peak Na + current density reduced to 46% and 41%, while voltage-dependent gating of Na + channels remained unchanged. Treatment with Syn-TEF1 significantly increased FGF14 mRNA expression and restored cumulative AP firing to 83% and 135% of control levels in monoallelic and biallelic neurons, respectively, and Na + peak current density to 95% and 138%. These findings strongly suggest that the pathophysiological cascade in SCA27B – from FGF14 repression to impaired Na + currents and decreased neuronal excitability – can be reversed by an elongation transcription factor. Our results thus provide a rationale for further exploring Syn-TEF1 as a first gene-targeted, disease-modifying therapeutic approach for SCA27B.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".