The changing landscape of the vulnerable plaque: a call for fine-tuning of preclinical models

A novel predictive model based on pericarotid adipose tissue and lumen stenosis for stroke risk in patients with asymptomatic carotid stenosis

The study aimed to investigate the predictive value of clinical characteristics, major computed tomography angiography (CTA) indexes of carotid AS (carotid lumen stenosis and plaque burden), and inflammatory pericarotid adipose tissue for acute stroke risk in patients with a moderate or higher degree of carotid stenosis. In all, 119 patients with unilateral carotid stenosis who underwent head and neck computed tomography angiography were included and assigned to the stroke group or non-stroke group according to magnetic resonance imaging. Pericarotid adipose tissue attenuation value, net enhancement value in the base phase and the enhancement phase, and atherosclerotic features (plaque burden and lumen stenosis) were recorded. Multivariate logistic regression analysis and the operating characteristic curve (ROC) were performed to establish a predictive model for the presence of acute ischemic stroke. ROC analysis showed that pericarotid adipose tissue attenuation value and lumen stenosis were predictive factors for stroke. The AUC of pericarotid adipose tissue attenuation (PCAT) attenuation, lumen stenosis, the novel prediction model independently constructed based on PCAT attenuation, and lumen stenosis resulted in 0.838 (95% CI 0.759-0.899), 0.700 (95% CI 0.826-0.944), and 0.942 (95% CI 0.884-0.977), respectively. The model had a sensitivity and specificity of 0.909 and 0.893, respectively, when the cutoff value was 0.388. We found that the risk model combining pericarotid adipose tissue attenuation value and lumen stenosis has significant predictive values for the presence of symptomatic stroke among patients with a moderate or higher degree of carotid stenosis.

Vulnerable Atherosclerotic Plaque: Is There a Molecular Signature?

Atherosclerosis and its clinical manifestations, coronary and cerebral artery diseases, are the most common cause of death worldwide. The main pathophysiological mechanism for these complications is the rupture of vulnerable atherosclerotic plaques and subsequent thrombosis. Pathological studies of the vulnerable lesions showed that more frequently, plaques rich in lipids and with a high level of inflammation, responsible for mild or moderate stenosis, are more prone to rupture, leading to acute events. Identifying the vulnerable plaques helps to stratify patients at risk of developing acute vascular events. Traditional imaging methods based on plaque appearance and size are not reliable in prediction the risk of rupture. Intravascular imaging is a novel technique able to identify vulnerable lesions, but it is invasive and an operator-dependent technique. This review aims to summarize the current data from literature regarding the main biomarkers involved in the attempt to diagnose vulnerable atherosclerotic lesions. These biomarkers could be the base for risk stratification and development of the new therapeutic drugs in the treatment of patients with vulnerable atherosclerotic plaques.

Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis

Aims

Genome-wide association studies (GWASs) have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to the identification of candidate genes. However, previously studied tissues are often non-diseased and heterogeneous in cell composition, hindering accurate candidate prioritization. Therefore, we analysed single-cell transcriptomics from atherosclerotic plaques for cell-type-specific expression to identify atherosclerosis-associated candidate gene–cell pairs.

Methods and results

We applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic and cardiovascular disease, risk factors, and other traits. We then intersected these candidates with single-cell RNA sequencing (scRNA-seq) data to identify genes specific for individual cell (sub)populations in atherosclerotic plaques. The coronary artery disease (CAD) loci demonstrated a prominent signal in plaque smooth muscle cells (SMCs) (SKI, KANK2, and SORT1) P-adj. = 0.0012, and endothelial cells (ECs) (SLC44A1, ATP2B1) P-adj. = 0.0011. Finally, we used liver-derived scRNA-seq data and showed hepatocyte-specific enrichment of genes involved in serum lipid levels.

Conclusion

We discovered novel and known gene–cell pairs pointing to new biological mechanisms of atherosclerotic disease. We highlight that loci associated with CAD reveal prominent association levels in mainly plaque SMC and EC populations. We present an intuitive single-cell transcriptomics-driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits. Collectively, our workflow allows for the identification of cell-specific targets relevant for atherosclerosis and can be universally applied to other complex genetic diseases and traits.