Loss of ADAM17 in smooth muscle cells enhances their transformation to macrophage-like cells leading to more severe atherosclerosis in mice
Bibliographic record
Abstract
BACKGROUND & AIMS Atherosclerosis is a multicellular disease, and smooth muscle cells (SMCs) can contribute to plaque formation. ADAM17 (a distintegrin and metalloproteinase-17) is a membrane-bound proteinase that is upregulated in vascular disease and can regulate SMC functions. We investigated the role of ADAM17 in SMCs in atherosclerosis. METHODS & RESULTS Human coronary plaques showed a high number of macrophage-like SMCs and ADAM17 expression. Male and female mice with inducible ADAM17 knockdown in SMCs ( Ldlr -/- / Adam17 f/f / Myh11 -Cre ERT2 ; Ldlr -/- / Adam17 SMC-KD ), ADAM17-intact ( Ldlr -/- / Adam17 f/f ; Ldlr -/- ), and genetic control ( Ldlr -/- / Myh11 -Cre ERT2 ) received Western diet (HCD) or regular chow. Ldlr -/- / Adam17 SMC-KD -HCD mice developed significantly more plaques, higher aortic cholesterol content, and aortic valve plaque and stiffness compared to Ldlr -/- -HCD mice, despite a comparable plasma lipid profile. SnRNAseq revealed a marked shift in SMC phenotypes from contractile to macrophage-like forms, and a greater population of proliferating inflammatory macrophages in Ldlr -/- / Adam17 SMC-KD -HCD compared to Ldlr -/- -HCD aortas. The plaques in Ldlr -/- / Adam17 SMC-KD mice showed a higher number of macrophage-like SMCs, decreased expression of SMC proteins (calponin, α-SMA, SM22α) and increased SMC atherogenic marker (galectin-3). In vitro , under atherogenic conditions, Adam17 KD SMCs showed higher lipid content, increased lipid uptake and reduced efflux, associated with increased lipid uptake transporters (CD36, SRA1), and decreased efflux transporter, ABCA1, compared to control SMCs. In Ldlr -/- / Adam17 SMC-KD -HCD aortas, membrane TNFR1 was stabilized, while the suppressed Ikkß-NFκB-LXRα pathway could underlie the decrease in ABCA1 expression. CONCLUSION ADAM17 is a novel regulator of SMC function in atherosclerosis. Its loss increases lipid content in SMCs, transformation into synthetic and macrophage-like states, and worsened 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".