A comparative gene expression matrix in Apoe-deficient mice identifies unique and atherosclerotic disease stage-specific gene regulation patterns in monocytes and macrophages
Bibliographic record
Abstract
BACKGROUND AND AIMS: Atherosclerosis is a systemic and chronic inflammatory disease propagated by monocytes and macrophages. Yet, our knowledge on how transcriptome of these cells evolves in time and space is limited. We aimed at characterizing gene expression changes in site-specific macrophages and in circulating monocytes during the course of atherosclerosis. METHODS: We utilized apolipoprotein E-deficient mice undergoing one- and six-month high cholesterol diet to model early and advanced atherosclerosis. Aortic macrophages, peritoneal macrophages, and circulating monocytes from each mouse were subjected to bulk RNA-sequencing (RNA-seq). We constructed a comparative directory that profiles lesion- and disease stage-specific transcriptomic regulation of the three cell types in atherosclerosis. Lastly, the regulation of one gene, Gpnmb, whose expression positively correlated with atheroma growth, was validated using single-cell RNA-seq (scRNA-seq) of atheroma plaque from murine and human. RESULTS: The convergence of gene regulation between the three investigated cell types was surprisingly low. Overall 3245 differentially expressed genes were involved in the biological modulation of aortic macrophages, among which less than 1% were commonly regulated by the remote monocytes/macrophages. Aortic macrophages regulated gene expression most actively during atheroma initiation. Through complementary interrogation of murine and human scRNA-seq datasets, we showcased the practicality of our directory, using the selected gene, Gpnmb, whose expression in aortic macrophages, and a subset of foamy macrophages in particular, strongly correlated with disease advancement during atherosclerosis initiation and progression. CONCLUSIONS: Our study provides a unique toolset to explore gene regulation of macrophage-related biological processes in and outside the atheromatous plaque at early and advanced disease stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".