Mutation in the FUS nuclear localisation signal domain causes neurodevelopmental and systemic metabolic alterations
Bibliographic record
Abstract
Variants in the ubiquitously expressed DNA/RNA-binding protein FUS cause aggressive juvenile forms of amyotrophic lateral sclerosis (ALS). Most FUS mutation studies have focused on motor neuron degeneration; little is known about wider systemic or developmental effects. We studied pleiotropic phenotypes in a physiological knock-in mouse model carrying the pathogenic FUSDelta14 mutation in homozygosity. RNA sequencing of multiple organs aimed to identify pathways altered by the mutant protein in the systemic transcriptome, including metabolic tissues, given the link between ALS-frontotemporal dementia and altered metabolism. Few genes were commonly altered across all tissues, and most genes and pathways affected were generally tissue specific. Phenotypic assessment of mice revealed systemic metabolic alterations related to the pathway changes identified. Magnetic resonance imaging brain scans and histological characterisation revealed that homozygous FUSDelta14 brains were smaller than heterozygous and wild-type brains and displayed significant morphological alterations, including a thinner cortex, reduced neuronal number and increased gliosis, which correlated with early cognitive impairment and fatal seizures. These findings show that the disease aetiology of FUS variants can include both neurodevelopmental and systemic alterations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".