Blood and cerebellar abundance of ATXN3 splice variants in spinocerebellar ataxia type 3/Machado-Joseph disease
Bibliographic record
Abstract
Spinocerebellar ataxia type 3 (SCA3)/Machado-Joseph disease (MJD) is a heritable proteinopathy disorder, whose causative gene, ATXN3, undergoes alternative splicing. Ataxin-3 protein isoforms differ in their toxicity, suggesting that certain ATXN3 splice variants may be crucial in driving the selective toxicity in SCA3. Using RNA-seq datasets we identified and determined the abundance of annotated ATXN3 transcripts in blood (n = 60) and cerebellum (n = 12) of SCA3 subjects and controls. The reference transcript (ATXN3-251), translating into an ataxin-3 isoform harbouring three ubiquitin-interacting motifs (UIMs), showed the highest abundance in blood, while the most abundant transcript in the cerebellum (ATXN3-208) was of unclear function. Noteworthy, two of the four transcripts that encode full-length ataxin-3 isoforms but differ in the C-terminus were strongly related with tissue expression specificity: ATXN3-251 (3UIM) was expressed in blood 50-fold more than in the cerebellum, whereas ATXN3-214 (2UIM) was expressed in the cerebellum 20-fold more than in the blood. These findings shed light on ATXN3 alternative splicing, aiding in the comprehension of SCA3 pathogenesis and providing guidance in the design of future ATXN3 mRNA-lowering therapies.
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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 | 0.001 | 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) | 0.001 | 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".