Abstract 284: Transcriptional Profiling Of Human Abdominal Aortic Aneurysm Tissue Reveals Distinct Extracellular Vesicle-Derived MicroRNA Cargo
Bibliographic record
Abstract
Aim: Abdominal aortic aneurysm (AAA) contributes to significant post-rupture mortality in aging populations. AAA management with watchful waiting and surgical repair is based on our limited understanding of disease processes, and current research foci including extracellular vesicles (EVs; nano-sized packages of proteins, RNAs, and lipids that facilitate intercellular communication) may aid in developing novel AAA therapies. To characterize this regulatory cargo, we isolated EVs from human AAA tissue or control aortic punch biopsies and profiled EV content with microRNA (miRNA) sequencing to identify dysregulated pathways. Methods: The study was approved by the University Health Network Research Ethics Board. EVs were isolated from human AAA or aortic punch tissue and enriched using size exclusion chromatography (SEC; qEVoriginal columns 70 nm, Izon Science Ltd.) (n=3). EV size and concentration were determined using nanoparticle tracking analysis (NTA; NanoSight NS300, Malvern Panalytical Ltd.). EV-miRNA sequencing was performed with Illumina NextSeq (HTG Molecular Diagnostics Inc.) and analyzed using Partek Genomics Suite (v.10) and MIENTURNET (19-11-25). Results: Patients were selected for infrarenal AAA requiring surgical repair (AAA) or coronary artery disease requiring bypass graft surgery (control). EV size and concentration were confirmed with NTA. Principal components and gene set analyses revealed distinct clustering of tissue types with 901 and 687 miRNAs enriched in AAA and control samples, respectively. Pathway prediction using established AAA miRNAs (e.g., miR-122, miR-146a, and miR-503) identified significant interactions with proaneurysmal signaling pathways (e.g., PI3K-AKT, JAK-STAT, and HIF-1) as well as cell senescence and adhesion processes (FDR < 0.05). Conclusion: EV-derived miRNAs from patients with AAA prominently associate with cell signaling, senescence, and adhesion pathways in aneurysm pathogenesis. To our knowledge, this is the first study to profile the EV-miRNA landscape in human AAA tissue. Further investigation will explore EV-miRNAs as mediators of communication between distinct vascular cell populations that contribute to AAA development.
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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 | 0.001 |
| 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) | 0.002 | 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".