Targeting the HDAC2/HNF-4A/miR-101b/AMPK Pathway Rescues Tauopathy and Dendritic Abnormalities in Alzheimer’s Disease
Bibliographic record
Abstract
Histone deacetylase 2 (HDAC2) plays a major role in the epigenetic regulation of gene expression. Previous studies have shown that HDAC2 expression is strongly increased in Alzheimer's disease (AD), a major neurodegenerative disorder and the most common form of dementia. Moreover, previous studies have linked HDAC2 to Aβ overproduction in AD; however, its involvement in tau pathology and other memory-related functions remains unclear. Here, we show that increased HDAC2 levels strongly correlate with phosphorylated tau in a mouse model of AD. HDAC2 overexpression induced AD-like tau hyperphosphorylation and aggregation, which were accompanied by a loss of dendritic complexity and spine density. The ectopic expression of HDAC2 resulted in the deacetylation of the hepatocyte nuclear factor 4α (HNF-4A) transcription factor, which disrupted its binding to the miR-101b promoter. The suppression of miR-101b caused an upregulation of its target, AMP-activated protein kinase (AMPK). The introduction of miR-101b mimics or small interfering RNAs (siRNAs) against AMPK blocked HDAC2-induced tauopathy and dendritic impairments in vitro. Correspondingly, miR-101b mimics or AMPK siRNAs rescued tau pathology, dendritic abnormalities, and memory deficits in AD mice. Taken together, the current findings implicate the HDAC2/miR-101/AMPK pathway as a critical mediator of AD pathogenesis. These studies also highlight the importance of epigenetics in AD and provide novel therapeutic targets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".