Regulation of TREM2 expression by transcription factor YY1 and its protective effect against Alzheimer’s disease
Bibliographic record
Abstract
TREM2 encoding the transmembrane receptor protein TREM2 is a risk gene of Alzheimer's disease (AD), and the impairment of TREM2 functions in microglia due to mutations in TREM2 may significantly increase the risk of AD by promoting AD pathologies. However, how the expression of TREM2 is regulated and the transcription factors required for TREM2 expression are largely unknown. By luciferase assay, DNA pull-down, and in silico predictions, we identified Yin Yang 1(YY1) as a binding protein of the minimal promoter of the TREM2 gene, and the binding was further confirmed by EMSA and DNA pull-down assay. shRNA-mediated YY1 silencing significantly reduced the activity of the TREM2 minimal promoter and TREM2 protein levels in the microglial cell line BV2 and the neuroblastoma Neuro2A. Furthermore, we found that the levels of TREM2 and YY1 were both downregulated in lipopolysaccharide-treated BV2 cells and in the brain of AD model mice. These results demonstrated that YY1 plays a crucial role in the regulation of TREM2 expression. Our study suggests that microglial YY1 could be targeted to maintain TREM2 expression for AD prevention and therapy.
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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".