Abstract
Atherosclerotic plaque destabilization is a dominating cause of acute cardiovascular events such as myocardial infarction and stroke. This study aims to identify genetic biomarkers related to atherosclerotic plaque destabilization using bioinformatics. Three transcriptome datasets of human carotid atherosclerotic plaque samples were downloaded from ArrayExpress and Gene Expression Omnibus databases, including E-MATB-2055, E-TABM-190, and GSE120521. With Robust Rank Aggregation analysis, we documented 46 differentially expressed genes between stable and unstable/ruptured plaques. Functional enrichment analysis using DAVID tool demonstrated that these genes were mainly related to biological functions such as extracellular matrix disassembly, collagen catabolic process, response to mechanical stimulus, and PPAR signaling pathway. A protein–protein interaction network for the differentially expressed genes was constructed, and eight pivotal genes (ITGAM, MMP9, PLAUR, CCR1, CD163, CD36, ADAM8, and IL1RN) were obtained from the network with a connective degree > 5. The expression patterns of these hub differentially expressed genes could be verified in atherosclerotic plaque samples with intraplaque hemorrhage. Using gene set variation analysis, the eight genes were integrated to generate an atherosclerotic plaque destabilization score, which showed a high performance in not only discriminating individuals with myocardial infarction from those with stable coronary illness, but also in predicting future acute cardiovascular events in atherosclerotic patients. In conclusion, the findings of this study will enhance our knowledge on the pathological mechanisms involved in atherosclerotic plaque destabilization, and provide potential gene biomarkers for risk stratification of patients with atherosclerotic cardiovascular disease.
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