A point mutation in the nuclear speckle protein and splicing factor SRRM2 is associated with amyotrophic lateral sclerosis and causes dysregulation of synapse-associated genes
Bibliographic record
Abstract
Abstract Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of motor neuron function. ALS is a multifactorial disease which can originate from complex genetic and environmental factors. The identification of risk factors and their molecular contribution to ALS expand our understanding of the disease mechanism. Here, we describe a family with dominantly inherited degeneration, which carries a mutation in the serine/arginine repetitive matrix 2 gene ( SRRM2) . SRRM2 is essential for nuclear speckle formation and a constitutive member of the RNA splicing machinery. To investigate how the mutation in SRRM2 contributed to the ALS pathogenesis, we examined its effect on a model cell line, where the point mutation was introduced in the endogenous gene. Surprisingly, we found that the resulting single amino acid exchange led to the loss of one protein-protein interaction, between SRRM2 and the splicing factor ACIN1. Transcriptome studies further revealed wide-spread differential gene expression, which converged on the dysregulation of synapse-associated pathways. Together, our findings identify SRRM2 as a novel ALS risk factor and provide mechanistic insights into how its mutation can be linked to ALS pathology.
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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 | 0.000 |
| 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".