Retention of hexanucleotide repeat-containing intron in C9orf72 mRNA: implications for the pathogenesis of ALS/FTD
Bibliographic record
Abstract
INTRODUCTION: The most common forms of amyotrophic lateral sclerosis and frontotemporal dementia are caused by a large GGGGCC repeat expansion in the first intron of the C9orf72 gene. The repeat-containing intron should be degraded after being spliced out, however GGGGCC repeat-containing RNA species either accumulate in nuclear foci or are exported to the cytoplasm where they are translated into potentially toxic dipeptide repeat proteins by repeat-associated non-AUG-initiated (RAN) translation. RESULTS: In order to determine the mechanisms of repeat-containing intron misprocessing, we have analyzed C9orf72 transcripts in lymphoblasts from C9orf72 expansion carriers (n = 15) and control individuals (n = 15). We have identified polyadenylated C9orf72 RNA species retaining the repeat-containing intron and in which downstream exons are spliced correctly resulting in a C9orf72 mRNA with an enlarged 5'-UTR containing the GGGGCC repeats. Intron-retaining transcripts are produced from both wild-type and mutant alleles. Intron-retaining C9orf72 transcripts were also detected in brain with a 2.7 fold increase measured in the frontal cortex from heterozygous expansion carriers (n = 11) compared to controls (n = 10). The level of intron-retaining transcripts was increased 5.9 fold in a case homozygous for the expansion. We also show that a large proportion of intron 1-retaining C9orf72 transcripts accumulate in the nucleus. CONCLUSIONS: Retention of the repeat-containing intron in mature C9orf72 mRNA can potentially explain nuclear foci formation as well as nuclear export of GGGGCC repeat RNA and suggests that the misprocessing of C9orf72 transcripts initiates the pathogenic process caused by C9orf72 hexanucleotide repeat expansions as well as provides the basis for novel therapeutic strategies.
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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 | 0.000 | 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".