P3‐290: ABCA1 is required for the beneficial effects of the liver‐X‐receptor agonist GW3965 on biochemical and cognitive outcomes in the APP/PS1 mouse model of Alzheimer's disease
Bibliographic record
Abstract
Apolipoprotein E (apoE) the major cholesterol carrier in the brain is also the most validated genetic risk factor for late-onset Alzheimer's Disease (AD). We and others have contributed to a growing body of literature demonstrating that the amount of lipids carried by apoE is a major determinant of Aβ and amyloid metabolism. The cholesterol transporter ABCA1 is responsible for moving lipids onto brain apoE. ABCA1 deficiency exacerbates amyloidogenesis, whereas selective overexpression of ABCA1 is sufficient to ameliorate amyloid burden in AD mice. Liver X Receptor (LXR) agonists such as GW3965, which stimulate the expression of several genes including ABCA1 and apoE, reduce Aβ levels and protect against cognitive deficits in AD mice. In this study, we tested the hypothesis that ABCA1 is required for the beneficial effects of GW3965 in AD mice by evaluating behavioural and neuropathogical outcomes in GW3965-treated APP/PS1 mice with and without ABCA1. Here we report that both therapeutic and prophylactic treatment with the LXR agonist GW3965 exhibits a significant improvement in cognition as demonstrated in the Novel Object Recognition and Morris Water maze tasks in the presence of ABCA1. Furthermore, ABCA1 is required to increase apoE levels and lipidation in cerebrospinal fluid in response to GW3965. We are currently performing biochemical and neuropathological analysis of the effect of GW3965 on cortical and hippocampal Aβ levels and amyloid burden. Our results suggest that ABCA1-mediated lipidation of apoE is a crucial mechanism underlying the beneficial effects of LXR agonists on cognitive behaviour and Aβ metabolism and highlights ABCA1 as a potential AD therapeutic target.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.002 |
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".