Direct and indirect regulation of β-glucocerebrosidase by the transcription factors USF2 and ONECUT2
Bibliographic record
Abstract
Mutations in GBA1 encoding the lysosomal enzyme β-glucocerebrosidase (GCase) are among the most prevalent genetic susceptibility factors for Parkinson's disease (PD), with 10-30% of carriers developing the disease. To identify genetic modifiers contributing to the incomplete penetrance, we examined the effect of 1634 human transcription factors (TFs) on GCase activity in lysates of an engineered human glioblastoma line homozygous for the pathogenic GBA1 L444P variant. Using an arrayed CRISPR activation library, we uncovered 11 TFs as regulators of GCase activity. Among these, activation of MITF and TFEC increased lysosomal GCase activity in live cells, while activation of ONECUT2 and USF2 decreased it. While MITF, TFEC, and USF2 affected GBA1 transcription, ONECUT2 might control GCase trafficking. The effects of MITF, TFEC, and USF2 on lysosomal GCase activity were reproducible in iPSC-derived neurons from PD patients. Our study provides a systematic approach to identifying modulators of GCase activity and deepens our understanding of the mechanisms regulating GCase.
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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".