TDP-43 pathology triggers SRRM4-dependent cryptic splicing of G3BP1 in ALS/FTD
Bibliographic record
Abstract
SUMMARY Loss of nuclear TDP-43 is a defining feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), yet how this leads to selective neuronal vulnerability is poorly understood. Here, using human iPSC-derived neurons and a large multi-omics dataset of ALS/FTD patients, we demonstrate that TDP-43 pathology induces the inclusion of an in-frame cryptic exon in human G3BP1 . The resulting CRYPTIC G3BP1 protein contains an additional 10–amino acids within the highly conserved NTF2L domain, which acts as a dominant negative and disrupts stress granule dynamics. We further show that cryptic exon inclusion in G3BP1 upon TDP-43 loss is enriched in neurons. Mechanistically, the loss of TDP-43 unmasks a binding site for the neuron-specific splicing regulator SRRM4 within intron 2 of G3BP1, enabling the inclusion of the cryptic exon. Collectively, our findings reveal that neuron-specific regulatory mechanisms intersect with TDP-43 -mediated splicing and suggest a mechanistic basis for the increased neuronal vulnerability observed in ALS/FTD.
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) | 0.000 | 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 | 0.000 | 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".