Aβ oligomers induce sex-selective differences in mGluR5 pharmacology and pathophysiological signaling in Alzheimer mice
Bibliographic record
Abstract
ABSTRACT Sex is a key modifier of the prevalence and progression of Alzheimer’s disease (AD). β- Amyloid (Aβ) deposition is a pathological hallmark of AD and aberrant activation of metabotropic glutamate receptor 5 (mGluR5) by Aβ has been linked to AD progression. We find that mGluR5 exhibits distinct sex-dependent pharmacological profiles. Specifically, endogenous mGluR5 from male mouse cortex and hippocampus binds with high-affinity to Aβ oligomers whereas, female mGluR5 exhibits no affinity to Aβ oligomers. The binding affinity of mGluR5 to Aβ oligomer is dependent on its interaction with cellular prion protein (PrP C ) as mGluR5 co-immunoprecipitates with PrP C from male, but not female, mouse brain. Aβ oligomers also bind with high-affinity to human mGluR5 in male, but not female, cortex. The mGluR5/Aβ oligomer/PrP C ternary complex is essential to elicit mGluR5-dependent pathological signaling and as a consequence mGluR5-regulated GSK3β/ZBTB16 autophagic signaling is dysregulated in male, but not female, primary neuronal cultures. These sex-specific differences in mGluR5 signaling translate into in vivo differences in mGluR5-dependent pathological signaling between male and female AD mice. We show that the chronic inhibition of mGluR5 using a mGluR5-selective negative allosteric modulator reactivates GSK3β/ZBTB16-regulated autophagy, mitigates Aβ pathology and reverses cognitive decline in male, but not female, APPswe/PS1ΔE9 mice. Thus, it is evident that, unlike male brain, mGluR5 does not contribute to Aβ pathology in female AD mice. This study highlights the complexity of mGluR5 pharmacology and Aβ oligomer-activated pathological signaling and emphasizes the need for clinical trials redesign and analysis of sex-tailored treatment for AD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".