Synaptic and Cognitive Improvements by Inhibition of 2-AG Metabolism Are through Upregulation of MicroRNA-188-3p in a Mouse Model of Alzheimer's Disease
Bibliographic record
Abstract
Abnormal accumulation of β-amyloid (Aβ) is the major neuropathological hallmark of Alzheimer's disease (AD). However, the mechanisms underlying aberrant Aβ formation in AD remain unclear. We showed previously that inhibition of monoacylglycerol lipase (MAGL), the primary enzyme that metabolizes the endocannabinoid 2-arachidonoylglycerol (2-AG) in the brain, robustly reduces Aβ by inhibiting β-site amyloid precursor protein cleaving enzyme 1 (BACE1), a key enzyme responsible for Aβ formation. However, the molecular mechanisms responsible for suppression of BACE1 by inhibition of 2-AG metabolism are largely unknown. We demonstrate here that expression of the noncoding small RNA miR-188-3p that targets BACE1 was significantly downregulated both in the brains of AD humans and APP transgenic (TG) mice, a mouse model of AD. The downregulated miR-188-3p expression was restored by MAGL inhibition. Overexpression of miR-188-3p in the hippocampus reduced BACE1, Aβ, and neuroinflammation and prevented deteriorations in hippocampal basal synaptic transmission, long-term potentiation, spatial learning, and memory in TG mice. 2-AG-induced suppression of BACE1 was prevented by miR-188-3p loss of function. Moreover, miR-188-3p expression was upregulated by 2-AG or peroxisome proliferator-activated receptor-γ (PPARγ) agonists and suppressed by PPARγ antagonism or NF-κB activation. Reducing Aβ and neuroinflammation by MAGL inhibition was occluded by PPARγ antagonism. In addition, BACE1 suppression by 2-AG and PPARγ activation was eliminated by knockdown of NF-κB. Our study provides a novel molecular mechanism underlying improved synaptic and cognitive function in TG mice by 2-AG signaling, which upregulates miR-188-3p expression through PPARγ and NF-κB signaling pathway, resulting in suppressions of BACE1 expression and Aβ formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".