Inflammatory and Structural Endotypes of Human Atherosclerotic Plaque Revealed by Integrated Transcriptomic Analysis

Background/Objectives: Atherosclerotic plaque instability is driven by complex interactions among inflammatory, structural, and cellular remodeling programs. While bulk RNA sequencing provides insight into tissue-level transcriptional states and single-cell RNA sequencing (scRNA-seq) defines cellular heterogeneity, integration across these transcriptomic layers remains limited. We aimed to identify coordinated transcriptional programs associated with stable and unstable plaque phenotypes and map these programs to specific cellular compartments and regulatory networks. Methods: Paired bulk RNA-seq data from stable and unstable human carotid plaques (GSE120521) and scRNA-seq data from human coronary atherosclerotic lesions (GSE131778) were analyzed. Differential expression and Hallmark gene set enrichment analyses were performed using limma and clusterProfiler. Bulk-derived inflammatory and structural signatures were projected onto single-cell data using Seurat module scoring. Compartment-level transcriptional scores, an inflammatory–structural endotype index, and transcription factor activity inference using decoupleR and DoRothEA were used to characterize plaque-associated transcriptional states. Results: Unstable plaques demonstrated enrichment of inflammatory pathways, including interferon gamma response, inflammatory response, TNFα/NF-κB signaling, IL6/JAK/STAT3 signaling, complement activation, and reactive oxygen species pathways. In contrast, stable plaques demonstrated relative enrichment of myogenesis and structural remodeling programs. Projection of bulk-derived signatures onto single-cell data localized inflammatory programs predominantly to TREM2hi and inflammatory macrophage populations, whereas structural programs localized to smooth muscle cell and fibromyocyte-like compartments. Compartment-level analyses showed increased myeloid and adaptive immune signatures in unstable plaques and increased smooth muscle cell/fibro-remodeling signatures in stable plaques. Transcription factor activity analysis identified increased SPI1, NFKB1, RELA, and STAT1 activity in unstable plaques and higher SRF and TEAD1 activity in stable plaques. Conclusions: Integrative analysis of bulk and single-cell transcriptomic data identified distinct inflammatory and structural plaque transcriptional states associated with unstable and stable plaque phenotypes, respectively. These findings support a systems-level framework linking tissue-level plaque behavior to specific cellular and regulatory programs and provide evidence for inflammatory and structural plaque endotypes in human atherosclerosis.

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Publication Details

Journal
Genes
Published
2026-07-02
DOI
https://doi.org/10.3390/genes17070779
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Inflammatory and Structural Endotypes of Human Atherosclerotic Plaque Revealed by Integrated Transcriptomic Analysis

Song Peng Ang, Meirajuddin Tousif, Anshu Sutihar, Eunseuk Lee et al.
Genes
Single-cell and spatial transcriptomics
article

Inflammatory and Structural Endotypes of Human Atherosclerotic Plaque Revealed by Integrated Transcriptomic Analysis

Song Peng Ang, Meirajuddin Tousif, Anshu Sutihar, Eunseuk Lee, Jose Iglesias, Daniel Tran
article en

Abstract

Background/Objectives: Atherosclerotic plaque instability is driven by complex interactions among inflammatory, structural, and cellular remodeling programs. While bulk RNA sequencing provides insight into tissue-level transcriptional states and single-cell RNA sequencing (scRNA-seq) defines cellular heterogeneity, integration across these transcriptomic layers remains limited. We aimed to identify coordinated transcriptional programs associated with stable and unstable plaque phenotypes and map these programs to specific cellular compartments and regulatory networks. Methods: Paired bulk RNA-seq data from stable and unstable human carotid plaques (GSE120521) and scRNA-seq data from human coronary atherosclerotic lesions (GSE131778) were analyzed. Differential expression and Hallmark gene set enrichment analyses were performed using limma and clusterProfiler. Bulk-derived inflammatory and structural signatures were projected onto single-cell data using Seurat module scoring. Compartment-level transcriptional scores, an inflammatory–structural endotype index, and transcription factor activity inference using decoupleR and DoRothEA were used to characterize plaque-associated transcriptional states. Results: Unstable plaques demonstrated enrichment of inflammatory pathways, including interferon gamma response, inflammatory response, TNFα/NF-κB signaling, IL6/JAK/STAT3 signaling, complement activation, and reactive oxygen species pathways. In contrast, stable plaques demonstrated relative enrichment of myogenesis and structural remodeling programs. Projection of bulk-derived signatures onto single-cell data localized inflammatory programs predominantly to TREM2hi and inflammatory macrophage populations, whereas structural programs localized to smooth muscle cell and fibromyocyte-like compartments. Compartment-level analyses showed increased myeloid and adaptive immune signatures in unstable plaques and increased smooth muscle cell/fibro-remodeling signatures in stable plaques. Transcription factor activity analysis identified increased SPI1, NFKB1, RELA, and STAT1 activity in unstable plaques and higher SRF and TEAD1 activity in stable plaques. Conclusions: Integrative analysis of bulk and single-cell transcriptomic data identified distinct inflammatory and structural plaque transcriptional states associated with unstable and stable plaque phenotypes, respectively. These findings support a systems-level framework linking tissue-level plaque behavior to specific cellular and regulatory programs and provide evidence for inflammatory and structural plaque endotypes in human atherosclerosis.

GenesVol. 17(7)
University of Arizona (US), Community Medical Center (US), Center for Discovery (US)
Openalex Percentile: Top 12%
Single-cell and spatial transcriptomics
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