PIAS1 modulates striatal transcription, DNA damage repair, and SUMOylation with relevance to Huntington’s disease
Bibliographic record
Abstract
DNA damage repair genes are modifiers of disease onset in Huntington's disease (HD), but how this process intersects with associated disease pathways remains unclear. Here we evaluated the mechanistic contributions of protein inhibitor of activated STAT-1 (PIAS1) in HD mice and HD patient-derived induced pluripotent stem cells (iPSCs) and find a link between PIAS1 and DNA damage repair pathways. We show that PIAS1 is a component of the transcription-coupled repair complex, that includes the DNA damage end processing enzyme polynucleotide kinase-phosphatase (PNKP), and that PIAS1 is a SUMO E3 ligase for PNKP. Pias1 knockdown (KD) in HD mice had a normalizing effect on HD transcriptional dysregulation associated with synaptic function and disease-associated transcriptional coexpression modules enriched for DNA damage repair mechanisms as did reduction of PIAS1 in HD iPSC-derived neurons. KD also restored mutant HTT-perturbed enzymatic activity of PNKP and modulated genomic integrity of several transcriptionally normalized genes. The findings here now link SUMO modifying machinery to DNA damage repair responses and transcriptional modulation in neurodegenerative disease.
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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".