Atherosclerotic plaque instability in symptomatic non-significant carotid stenoses

Abstract

Objective: Carotid endarterectomy for symptomatic carotid stenosis is recommended for patients with >70% stenosis, but not in those with <50%. Because non-significant, low-degree stenoses may still cause strokes, refined risk stratification is necessary, which could be improved by assessing biological features of plaque instability. To challenge risk-stratification based on luminal narrowing, we compared biological features of carotid plaques from symptomatic patients with low-degree (<50%) vs high-degree (>70%) stenosis and explored potential mechanisms behind plaque instability in low-degree stenoses.

Methods: Endarterectomy specimens were taken from symptomatic patients with high-degree (n = 204) and low-degree (n = 34) stenosis, all part of the Biobank of Karolinska Endarterectomies. Patient demographics, image-derived plaque morphology, and gene expression analyses of extracted lesions were used for comparisons. Plaque biology was assessed by transcriptomics using dimensionality reduction, differential gene expression, and gene-set enrichment analyses. Immunohistochemistry was used to study proteins corresponding to upregulated genes.

Results: The demographics of the two groups were statistically similar. Calcification, lipid-rich necrotic core, intraplaque hemorrhage, plaque burden, and fibrous cap thickness were similar in both groups, whereas the sum of lipid-rich necrotic core and intraplaque hemorrhage was higher (P = .033) in the high-degree stenosis group. Dimensionality reduction analysis indicated poor clustering separation of plaque gene expression in low-compared with high-degree stenosis lesions, whereas differential gene expression showed upregulation of hypoxia-inducible factor 3A (log₂ fold change, 0.7212; P = .0003), and gene-set enrichment analyses identified pathways related to tissue hypoxia and angiogenesis in low-degree stenoses. Hypoxia-inducible factor 3-alpha protein was associated with smooth muscle cells in neo-vascularized plaque regions.

Conclusions: Plaques from symptomatic patients with non-significant low-degree carotid stenoses showed morphologic and biological features of atherosclerotic plaque instability that were comparable to plaques from patients with high-degree stenoses, emphasizing the need for improved stroke risk stratification for intervention in all patients with symptomatic carotid stenosis irrespective of luminal narrowing. An increased expression of hypoxia-inducible factor 3A in low-degree stenotic lesions suggested mechanisms of plaque instability associated with tissue hypoxia and plaque angiogenesis, but the exact role of hypoxia-inducible factor 3A in this process remains to be determined.

Clinical relevance: Carotid plaques from symptomatic patients with <50% stenosis show morphologic and biological features of plaque instability, comparable to high-degree stenosis, which emphasizes the need for improved stroke risk stratification beyond stenosis severity.

Keywords: Atherosclerotic plaque instability; Degree of stenosis; Hypoxia; Stroke risk; Symptomatic carotid stenosis.

Graphical abstract

Fig 1

Dimensionality reduction analyses to visualize distribution of gene expression from RNA sequencing (RNA-seq) of carotid endarterectomy (CEA) specimens with <50 % (n = 34) or >70 % (n = 204) carotid stenosis (CS) using Principal Component Analysis (PCA) (A), t–Distributed Stochastic Neighbor Embedding (t-SNE) (B), and Uniform Manifold Approximation and Projection (UMAP) of carotid plaque gene expression from bulk RNAseq data (C). Each point in the scatter plots represents a sample with points colored according to the degree of stenosis for the individual sample. The PCA scatter plot represents the first two principal components (PC1 and PC2) derived from gene expression data and t-SNE and UMAP plots display samples in a two-dimensional space (V1 and V2). Note the absence of clustered data in between the two groups with neither of the analytical methods.

Fig 2

Volcano plot displaying differential gene expression in low-compared with high-degree carotid stenosis (CS) groups. The plot illustrates log₂ fold changes (x-axis) against −log₁₀P-values (y-axis) for each gene. Points above the blue dashed line represent genes with nominal significance (P_nom = .05). Genes of particular interest are annotated and highlighted. A positive log₂ fold change indicates upregulation in <50% stenosis, whereas a negative log₂ fold change indicates downregulation. CLTA4, Cytotoxic T-lymphocyte associated protein 4; FGFR2, fibroblast growth factor receptor 2; HIF3A, hypoxia-inducible factor 3A; KRT14, keratin 14; SEMA3E, semaphorin 3E, TLR7, toll-like receptor 7; TWIST2, Twist Family BHLH Transcription Factor 2.

Fig 3

Enriched biological pathways based on differential gene expression observed between low- and high-degree carotid stenosis (CS) groups as determined by different publicly available resources: Kyoto Encyclopedia of Genes and Genomes (KEGG) 2021 Human (A); Molecular Signatures Database (MSigDB) Hallmark 2020 (B); Reactome 2022 (C). Each bar represents a specific biological pathway enriched in low- compared with high-degree CS groups. The y-axis displays the enriched terms, whereas the x-axis displays the gene count. AGE, Advanced glycation end product; IL2, interleukin 2; mTOR, mammalian target of rapamycin; PTEN, phosphatase and tensin homolog; RAGE, receptor for advanced glycation end product; STAT5, signal transducer and activator of transcription 5; TLR3, toll-like receptor 3; TNF, tumor necrosis factor; VEGFA, vascular endothelial growth factor A; VEGFR2, vascular endothelial growth factor receptor 2.

Fig 4

Gene set enrichment analysis (GSEA) of genes positively (A and B) and negatively (C and D) correlated with hypoxia-inducible factor 3A (HIF3A) expression in the entire cohort (n = 238) as assessed by Gene Ontology (GO) Biological Processes (A and C) or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (B and D). ECM, Extracellular matrix; TNF, tumor necrosis factor.

Fig 5

Validation of hypoxia-inducible factor 3A (HIF3A) and hypoxia-inducible factor 1A (HIF1A) expression in carotid atherosclerotic plaques using two independent cohorts.^, HIF3A (A) and HIF1A (B) gene expression in atherosclerotic plaques with intra-plaque hemorrhage (IPH) (n = 26) or without IPH (no IPH n = 16). Correlation matrix of HIF3A, HIF1A with smooth muscle alpha actin (ACTA2), myosin heavy-chain 11 (MYH11), and cluster of differentiation 68 (CD68) (C). HIF3A (D) and HIF1A (E) gene expression in unstable (n = 4) compared with stable (n = 4) atherosclerotic plaque regions.

Fig 6

Spearman correlation analysis comparing the expression of cell-specific gene markers for smooth muscle cells (SMCs), endothelial cells (ECs), macrophages (Macs), T-cells with expression of genes associated with hypoxia (hypoxia-inducible factor 1A [HIF1A] and hypoxia-inducible factor 3A [HIF3A]) and angiogenesis (endoglin [ENG]) based on RNA sequencing (RNAseq) data from carotid plaques with low-degree carotid stenosis (CS). Each point represents a gene-marker pair, with the size indicating the significance level (−log₁₀ adjusted P-value) and the color indicating the strength of the correlation (corresponding numerical value inserted). Data points marked with an X represent a P-value > .5 and non-significance. ACTA2, Smooth muscle alpha actin; CD, cluster of differentiation; MYH11, myosin heavy-chain 11; PECAM1, platelet endothelial cell adhesion molecule-1; SMTN, smoothelin; VWF, von Willebrand factor.

Fig 7

Immunohistochemical double-staining of carotid plaques from low-degree carotid stenosis (CS) lesions localizing hypoxia-inducible factor 3A (HIF3A) (A and C; Red) and hypoxia-inducible factor 1A (HIF1A) (B and D; Red) to cluster of differentiation 68 (CD68)-positive macrophages (A and B; Green) and alpha-smooth muscle actin (SMA)-positive smooth muscle cells (SMCs) (C and D; Green), or endoglin (ENG) (Red) in von Willebrand factor (VWF) (Green)-positive endothelial cells (E). Control (Ctrl) staining (F). Bar indicates 50 μm.