Engineered CRISPR-Base Editors as a Permanent Treatment for Familial Dysautonomia
Bibliographic record
Abstract
Abstract Familial dysautonomia (FD) is a fatal autosomal recessive sensory and autonomic neuropathy. FD is caused by a T-to-C point mutation in intron 20 of the Elongator acetyltransferase complex subunit 1 ( ELP1 ) gene, which results in tissue-specific skipping of exon 20 to cause a premature termination codon and thus redues ELP1 protein levels. Here, we developed a CRISPR-Cas-based cytosine base editing strategy to permanently correct the disease-causing mutation and restore canonical mRNA splicing. Through systematic engineering of base editors and guide RNAs, we identified an optimal editor configuration capable of achieving up to 70% on-target correction in human cells and that restored ELP1 exon 20 inclusion. To enable in vivo delivery, a dual adeno-associated virus (AAV) intein-split base editor was delivered via intravenous injections in a humanized FD mouse mode, resulting in genetic correction and significantly increased ELP1 exon 20 inclusion in the brain and other tissues. In FD patient-derived iPSC-sympathetic neurons, we observed ∼10% correction efficiency but rescued disease-associated neuronal hyperactivity, demonstrating that partial correction can restore functional phenotypes. Genome-wide analyses revealed minimal off-target editing across multiple human cell types, supporting the specificity of this approach. Together, these findings establish a precise and permanent genome editing strategy for FD and supports the development of a one-time disease-modifying therapy for FD and highlights the therapeutic potential of base editing for splicing disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".