Abstract 4372183: Cross-species single-cell reconstruction of atherosclerosis reveals predictive monocytes for acute coronary events

Background: Vulnerable plaques are the immediate cause of acute coronary syndromes such as acute myocardial infarction (AMI). However, current preventive strategies including lipid-lowering and imaging-based approaches focus on overall cardiovascular risk and lack precision in identifying high-risk plaques before clinical events. One major limitation is the insufficient understanding of cell-type heterogeneity and dynamic changes across the full course of atherosclerosis. Methods and Results: We established a cross-species, multi-stage framework integrating human single-cell data from advanced stable and unstable plaques with multi-timepoint mouse models. This allowed reconstruction of a continuous trajectory of atherosclerosis and led to identification of a monocyte-derived population, Plaque Instability Monocytes (PIMs), enriched in unstable lesions and characterized by inflammatory and matrix-remodeling programs. To validate their relevance, we profiled additional lesions across multiple arteries and disease states, including in-stent restenosis. PIM signatures were consistently recovered, and spatial transcriptomics revealed preferential localization to fibrous caps, confirmed by confocal imaging. Circulating PIM-like cells were also elevated in patients with unstable plaques. From the PIM transcriptome, we derived a 362-gene blood signature, and used interpretable deep learning to identify a stable 20-gene panel distinguishing unstable from stable cases (AUC = 0.907). A composite risk score built using L1-logistic regression was validated in an independent cohort (n = 338, AUC = 0.92). Cytokine genes within the panel showed elevated plasma levels in AMI patients (n = 26), and UK Biobank proteomics (n = 3,798) confirmed upregulation of key panel proteins in myocardial infarction. Conclusions: By bridging single-cell discoveries with peripheral biomarker modeling and clinical validation, this study identifies a conserved monocyte subset associated with plaque vulnerability and provides a practical tool for early detection and risk stratification in coronary artery disease.

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Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4372183
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Abstract 4372183: Cross-species single-cell reconstruction of atherosclerosis reveals predictive monocytes for acute coronary events

Jinmeng Jia, Xuegong Zhang
Circulation
Single-cell and spatial transcriptomics
article

Abstract 4372183: Cross-species single-cell reconstruction of atherosclerosis reveals predictive monocytes for acute coronary events

Jinmeng Jia, Xuegong Zhang
article en

Abstract

Background: Vulnerable plaques are the immediate cause of acute coronary syndromes such as acute myocardial infarction (AMI). However, current preventive strategies including lipid-lowering and imaging-based approaches focus on overall cardiovascular risk and lack precision in identifying high-risk plaques before clinical events. One major limitation is the insufficient understanding of cell-type heterogeneity and dynamic changes across the full course of atherosclerosis. Methods and Results: We established a cross-species, multi-stage framework integrating human single-cell data from advanced stable and unstable plaques with multi-timepoint mouse models. This allowed reconstruction of a continuous trajectory of atherosclerosis and led to identification of a monocyte-derived population, Plaque Instability Monocytes (PIMs), enriched in unstable lesions and characterized by inflammatory and matrix-remodeling programs. To validate their relevance, we profiled additional lesions across multiple arteries and disease states, including in-stent restenosis. PIM signatures were consistently recovered, and spatial transcriptomics revealed preferential localization to fibrous caps, confirmed by confocal imaging. Circulating PIM-like cells were also elevated in patients with unstable plaques. From the PIM transcriptome, we derived a 362-gene blood signature, and used interpretable deep learning to identify a stable 20-gene panel distinguishing unstable from stable cases (AUC = 0.907). A composite risk score built using L1-logistic regression was validated in an independent cohort (n = 338, AUC = 0.92). Cytokine genes within the panel showed elevated plasma levels in AMI patients (n = 26), and UK Biobank proteomics (n = 3,798) confirmed upregulation of key panel proteins in myocardial infarction. Conclusions: By bridging single-cell discoveries with peripheral biomarker modeling and clinical validation, this study identifies a conserved monocyte subset associated with plaque vulnerability and provides a practical tool for early detection and risk stratification in coronary artery disease.

CirculationVol. 152(Suppl_3)
Tsinghua University (CN)
Openalex Percentile: Top 71%
Single-cell and spatial transcriptomics
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