Identification of Monocyte-Associated Genes Related to the Instability of Atherosclerosis Plaque

Abstract

Background. Atherosclerotic plaque instability is a common cause of stroke and ischemic infarction, and identification of monocyte-associated genes has become a prominent feature in cardiovascular research as a contributing/predictive marker. Methods. Whole genome sequencing data were downloaded from GSE159677, GSE41571, GSE120521, and GSE118481. Single-cell sequencing data analysis was conducted to cluster molecular subtypes of atherosclerotic plaques and identify specific genes. Differentially expressed genes (DEGs) between normal subjects and patients with unstable atheromatous plaques were screened. Weighted gene coexpression network analysis (WGCNA) was performed to find key module genes. In addition, GO and KEGG enrichment analyses explored potential biological signaling pathways to generate protein interaction (PPI) networks. GSEA and GSVA demonstrated activations in plaque instability subtypes. Results. 239 monocyte-associated genes were identified based on bulk and single-cell RNA-sequencing, followed by the recognition of 1221 atherosclerotic plaque-associated DEGs from the pooled matrix. GO and KEGG analyses suggested that DEGs might be related to inflammation response and the PI3K-Akt signaling pathway. Eight no-grey modules were obtained through WGCNA analysis, and the turquoise module has the highest correlation with unstable plaque ( $R^2=0.40$ ), which contained 1323 module genes. After fetching the intersecting genes, CXCL3, FPR1, GK, and LST1 were obtained that were significantly associated with plaque instability, which had an intense specific interaction. Monocyte-associated genes associated with atherosclerotic plaque instability have certain diagnostic significance and are generally overexpressed in this patient population. In addition, 11 overlapping coexpressed genes (CEG) might also activated multiple pathways regulating inflammatory responses, platelet activation, and hypoxia-inducible factors. GSVA showed that the corresponding pathways were significantly activated in high expression samples. Conclusions. Overexpression of CXCL3, GK, FPR1, and LST1 was advanced recognition and intervention factors for unstable plaques, which might become targets for atherosclerosis rupture prevention. We also analyzed the potential mechanisms of CEG from inflammatory and oxidative stress pathways.