FUSDelta14 mutation impairs normal brain development and causes systemic metabolic alterations
Bibliographic record
Abstract
ABSTRACT FUS (Fused in sarcoma) is a ubiquitously expressed DNA/RNA binding protein. Mutations in FUS cause aggressive juvenile forms of amyotrophic lateral sclerosis (ALS), as in the case with the FUSDelta14 mutation. While most studies have focused on the role of FUS in motor neuron degeneration, little is known about the effect of FUS mutations in the whole body, and the impact of FUS mutations in the correct development of the nervous system. We studied pleiotropic phenotypes in a physiological knock-in mouse model carrying the FUSDelta14 mutation in homozygosity. RNA sequencing was conducting in six different tissues (frontal cortex, spinal cord, tibialis anterior muscle, white and brown adipose tissue and liver) to identify the genes and pathways altered by the FUSDelta14 mutant protein in the systemic transcriptome. Additionally, brain structural magnetic resonance imaging (MRI) and histological characterisation was conducted in young mice to study the role of FUS mutation in the brain development. FUS mutant protein was upregulated and mislocalised in the cytoplasm in most cells of the tissues analysed. We identified few genes commonly altered in all tissues by this mutation, although most genes and pathways affected were generally tissue-specific. Phenotypic assessment of mice revealed systemic metabolic alterations related to the pathway changes identified. MRI brain scans revealed that homozygous FUSDelta14 brains were smaller and displayed significant morphological alterations including a thinner cortex, reduced neuronal number and increased gliosis, which correlated with early cognitive impairment and fatal seizures. We demonstrated that the disease aetiology of FUS mutations can include neurodevelopmental and systemic alterations, which should be taken into consideration in the clinic.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".