Abstract 14843: Unveiling the Phenotype of Smooth Muscle Foam Cells in Human Atherosclerotic Lesions: Insights From Bulk and Single Cell RNA Sequencing
Bibliographic record
Abstract
Background and Aims: Our previous studies of human coronary atherosclerosis and ApoE-/- mice indicated that at least 50% and ~70% of foam cells are of smooth muscle cell (SMC) origin, respectively. We also found that SMCs generate a distinct class of foam cells, due to several gene expression and regulatory differences compared to macrophage foam cells. In the current investigation we utilized transcriptomic approaches to identify and characterize the phenotype of SMC foam cells of human coronary plaques and in SMCs treated with aggregated LDL (ag-LDL). Methods: Sections of fresh human coronary artery were subjected to gentle digestion and the isolated cells used for single-cell RNA Sequencing (scRNA-Seq) (n=3) using 10X Genomics Chromium Single Cell 3’ Reagent Kits v3 Technology. Human vascular SMCs were treated with 100 μg/mL ag-LDL for 24 h (n=3) and stained with the fluorescent lipid probe BODIPY493/503. BODIPY high SMCs were collected and subjected to bulk RNA sequencing along with non-treated SMCs as control. Results: Single cell RNA sequencing of cells isolated from human coronary arteries followed by unsupervised Seurat-based clustering (R version 4.2.0) identified 15 distinct clusters including 8 SMC clusters with varying degrees of differentiation and macrophage foam and non-foam cells. The top 70 upregulated genes in ag-LDL treated SMCs were used to identify clusters corresponding to SMC foam cells in the scRNA-seq dataset. We found that these genes are mostly enriched in 2 clusters of less differentiated SMCs. SMC and macrophage foam cell clusters display distinct characteristics. SMC foam cell clusters exhibit upregulation of complement and coagulation cascades, as well as ECM-receptor interaction genes. In contrast, the macrophage foam cell cluster shows enrichment of proinflammatory genes, genes involved in the response to unfolded protein, and both pro- and anti-apoptotic genes. Conclusion: Our studies provide novel tools to investigate the nature of SMC foam cells in human atherosclerosis and may provide unique markers for SMC foam cells. Gaining a comprehensive insight of the significance and characteristics of SMC foam cells is crucial in elucidating their ultimate role and potential as a therapeutic target in atherosclerosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".