Characterization of a C9orf72 Knockout <i>Danio rerio</i> model for ALS and cross-species validation of potential therapeutics screened in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
Abstract Intronic hexanucleotide repeat expansions in the C9orf72 gene represent the most common genetic cause of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. This expansion decreases C9orf72 expression in affected patients, indicating that loss of C9orf72 function (LOF) acts as a pathogenic mechanism. Several models using Danio rerio (zebrafish) for C9orf72 depletion have been developed to explore disease mechanisms and the consequences of C9orf72 LOF. However, inconsistencies exist in reported phenotypes, and many have yet to be validated in stable germline ablation models. To address this, we created a zebrafish C9orf72 knockout model using CRISPR/Cas9. The C9orf72 LOF model demonstrates, in a generally dose-dependent manner, increased larval mortality, persistent growth reduction, and motor deficits. Additionally, homozygous C9orf72 LOF larvae exhibited mild overbranching of spinal motoneurons. To identify potential therapeutic compounds, we performed a screen on an established Caenorhabditis elegans ( C. elegans ) C9orf72 homologue ( alfa-1 ) LOF model, identifying 12 compounds that enhanced motility, reduced neurodegeneration, and alleviated paralysis phenotypes. Motivated by the shared motor phenotype, 2 of those compounds were tested in our zebrafish C9orf72 LOF model. Pizotifen malate was found to significantly improve motor deficits in C9orf72 LOF zebrafish larvae. We introduce a novel zebrafish C9orf72 knockout model that exhibits phenotypic differences from depletion models, providing a valuable tool for in vivo C9orf72 research and ALS therapeutic validation. Furthermore, we identify pizotifen malate as a promising compound for further preclinical evaluation. Author Summary Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neurons, with no curative treatments currently available. The most common genetic cause is a hexanucleotide repeat expansion in the C9orf72 gene, which reduces its expression and implicates loss-of-function (LOF) as a disease mechanism. However, the complete functions of C9orf72 and its role in ALS remain unclear. Zebrafish models with indirect partial reduction of C9orf72 expression have shown promise in recapitulating key aspects of ALS, but inconsistencies have been observed across these models. To address these challenges, we developed a stable genetic C9orf72 LOF zebrafish model to study the effects of its LOF, validate previous findings, and test potential ALS therapeutics. Our model displays swimming activity deficits, reduced growth, increased mortality, and mild spinal motor neuron abnormalities. We demonstrated that pizotifen malate significantly improved motor function in both our model and a similar well-established worm model. These results underscore the differences between indirect depletion and direct genetic LOF models while identifying pizotifen malate as a promising candidate for preclinical testing. This zebrafish model serves as a valuable tool for understanding C9orf72 -associated ALS mechanisms and advancing therapeutic development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".