Abstract 599: Extracellular Vesicles Secreted by Atherogenic Macrophages Transfer Microrna to Inhibit Cell Migration
Bibliographic record
Abstract
During inflammation, macrophages secrete vesicles carrying RNA, protein and lipids as a form of extracellular communication. In the vessel wall, extracellular vesicles (EVs) have been shown to be transferred between vascular cells during atherosclerosis, however, the role of macrophage-derived EVs in promoting atherogenesis is not known. Here, we hypothesize that atherogenic macrophages secrete microRNAs (miRNA) in EVs to mediate cell-cell communication and promote pro-inflammatory and pro-atherogenic phenotypes in recipient cells. Results: We isolated EVs from mouse and human macrophages treated with an atherogenic stimulus (oxidized LDL) and characterized the EV-derived miRNA expression profile. Using microarrays and Q-PCR, we confirmed the enrichment of miR-146a, miR-128, miR-185, miR-365 and miR-503 in atherogenic EVs compared to controls. Live-cell imaging demonstrated that macrophage-derived EVs are taken up and transfer exogenous miRNA ( C. elegans) to naive recipient macrophages. Bioinformatic analysis suggests that atherogenic EV-derived miRNAs are predicted to target genes involved in cell migration and adhesion pathways. Indeed, treatment of naïve macrophages with EVs from atherogenic but not control macrophages inhibited the migration of naïve cells towards a chemokine stimulus (80% decrease in migration, p≤0.01). In vivo , delivery of EVs also abolished LPS-induced emigration of mouse peritoneal macrophages . Moreover, inhibition of miR-146a (using anti-miR oligonucleotides or miR-146a -/- macrophages), the most enriched miRNA in atherogenic EVs, reduced the inhibitory effect of EVs on macrophage migratory capacity. EV-mediated delivery of miR-146a repressed the expression of target genes IGF2BP1 and HuR in recipient cells, and knockdown of IGF2BP1 and HuR using siRNA reduced macrophage migration, highlighting the importance of these EV-miRNA targets in regulating macrophage motility. Notably, expression of miR-146a was elevated in mouse and human atherosclerotic lesions compared to controls. Thus, EV-derived miRNAs from atherogenic macrophages, in particular miR-146a, may accelerate the development of atherosclerosis by decreasing cell migration and promoting macrophage entrapment in the vessel wall.
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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) | 0.000 | 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 | 0.001 |
| 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".