Abstract 12775: The Major Contribution and Characteristics of Smooth Muscle Cell Foam Cells in Human Atherosclerotic Lesions Based on Flow Cytometry and Single Cell RNA Sequencing
Bibliographic record
Abstract
Background and Aims: Smooth muscle cells (SMCs) comprise the majority of cells within human atherosclerotic intima. Our previous study of human coronary atherosclerosis found that ≥50% of foam cells are of SMC origin and not primarily of macrophage origin as previously thought. In a recent investigation we reported that ~70% of all foam cells in ApoE-/- mice fed a Western Diet for 6 weeks are SMC-derived. In the current investigation we utilized flow cytometry and single-cell RNA sequencing to study the contribution and characteristics of SMC-derived foam cells in human atherosclerotic plaques. Hypothesis: SMCs comprise the majority of foam cells in human atherosclerosis and SMC foam cells have a unique gene expression pattern compared to macrophage foam cells. Methods: Formalin-fixed coronary and aortic samples were digested, stained with the lipid dye BODIPY and CD45 antibody and separated into CD45+ (leukocyte) and CD45- (non-leukocyte) foam cell and non-foam cell populations using flow cytometry. Pieces of fresh human coronary artery with adventitia removed were subjected to gentle digestion and isolated cells used for single-cell RNA Sequencing (n=3) using 10X Genomics Chromium Single Cell 3’ Reagent Kits v3 Technology. Results: Flow cytometric analysis indicates that approximately 65% of total foam cells of human coronary and aortic atherosclerotic lesions are of non-leukocyte origin. Unsupervised Seurat-based clustering (R version 4.2.0) singled out multiple cell clusters including SMCs, leukocytes, and endothelial cells in all 3 samples. Combining data resulted in identification of 15 distinct clusters including 8 SMC clusters ranging from well-differentiated to varying degrees of dedifferentiation. Combining multiple markers identified by in vitro and in vivo studies of SMC foam cells we were able to identify 2 possible SMC foam cell clusters with gene expression patterns distinct from macrophage foam cells. Conclusions: Our findings further identify SMCs as the major contributors of foam cells in atherosclerosis, and provide novel tools to investigate the nature of SMC foam cells in human atherosclerosis and their responses to anti-atherosclerotic therapies.
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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 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.004 | 0.003 |
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".