P3‐061: CONSTITUTIVE IN VIVO OVEREXPRESSION OF MIR146A AND MIR200B INDEPENDENTLY MODULATES LEVELS OF ALZHEIMER'S DISEASE (AD)‐ RELATED PROTEINS IN THE MOUSE HIPPOCAMPUS AND CEREBRAL CORTEX
Bibliographic record
Abstract
Alzheimer's disease is the most common age-related neurodegenerative disorder. Recent work suggests close ties between metabolic disorders (diabetes) and AD. Abnormal brain vascularization also accompanies AD. A critical component of vascularization is vascular endothelial growth factor (VEGF). Furthermore, VEGF is dysregulated in diabetes and AD. Micro-RNAs (miRNA) are small RNA species that regulate mRNA translation. miR146a and miR200b regulate VEGF translation and are implicated in diabetes complications (diabetic cardiomypathy and retinopathy). Our aim was to evaluate whether these miRNAs regulate levels of proteins implicated in AD pathology, including amyloid-β (Aβ), Aβ precursor protein (APP), BACE1 or VEGF, and those that impact synaptic integrity (e.g., SNAP25). To characterize this potential activity, we generated mouse lines from B6 wildtype mice (WT) that over-expressed miR146a or miR200b in vascular tissue only. We induced diabetes symptoms in WT mice and those of each transgenic line with streptozotocin (STZ). We harvested mouse brain hippocampus and cortex and quantified levels of Aβ, APP, BACE1, and SNAP25, as well as VEGF protein. We measured levels of miR146a and miR200b (normalized to U6) vs STZ treatment in WT mice by qRT-PCR. Streptozotocin induction of diabetes symptoms significantly reduced miR146a and miR200b in WT mouse brains. Vascular overexpression of miR146a and miR200b altered effects of STZ induction in hippocampus and cerebral cortex, particularly for SNAP25, BACE1, APP, and Aβ40. Notably, neither miRNA has recognition sequences in APP or BACE1. We hence cannot claim that the effects observed here are a direct consequence of miR200b or miR146a overexpression on these proteins’ translation from mRNA. The effects we observed may be an outcome of a more complex network of activity on other mRNAs targeted by miR200b or miR146a, particularly for those AD-associated mRNAs that have no predicted interaction with our miRNAs of interest. Transfection studies with expression vectors would define whether or not some non-canonical (and, thus, difficult to predict in silico) interactions may be responsible. This work both represents an exciting network effect of these two diabetes-associated miRNAs to AD and demonstrates effective use of vascular-based miRNA production in modulating levels of key brain proteins. Supported by NIH-R01 grants.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".