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Atherosclerosis is a chronic inflammatory disease with high prevalence and mortality. The rupture of atherosclerotic plaque is the main reason for the clinical events caused by atherosclerosis. Making clear the transcriptomic and proteomic profiles between the stabe and unstable atherosclerotic plaques is crucial to prevent the clinical manifestations. In the present study, 5 stable and 5 unstable human carotid atherosclerotic plaques were obtained by carotid endarterectomy. The samples were used for the whole transcriptome sequencing (RNA-Seq) by the Next-Generation Sequencing using the Illumina HiSeq, and for proteome analysis by HPLC-MS/MS. The lncRNA-targeted genes and circRNA-originated genes were identified by analyzing their location and sequence. Gene Ontology and KEGG enrichment was carried out to analyze the functions of differentially expressed RNAs and proteins. The protein-protein interactions (PPI) network was constructed by the online tool STRING. The consistency of transcriptome and proteome were analyzed, and the lncRNA/circRNA-miRNA-mRNA interactions were predicted. As a result, 202 mRNAs, 488 lncRNAs, 91 circRNAs, and 293 proteins were identified to be differentially expressed between stable and unstable atherosclerotic plaques. The 488 lncRNAs might target 381 protein-coding genes by cis -acting mechanisms. Sequence analysis indicated the 91 differentially expressed circRNAs were originated from 97 protein-coding genes. These differentially expressed RNAs and proteins were mainly enriched in the terms of the cellular response to stress or stimulus, the regulation of gene transcription, the immune response, the nervous system functions, the hematologic activities, and the endocrine system. These results were consistent with the previous reported data in the dataset GSE41571. Further analysis identified CD5L, S100A12, CKB (target gene of lncRNA MSTRG.11455.17), CEMIP (target gene of lncRNA MSTRG.12845), and SH3GLB1 (originated gene of hsacirc_000411) to be critical genes in regulating the stability of atherosclerotic plaques. Our results provided a comprehensive transcriptomic and proteomic knowledge on the stability of atherosclerotic plaques. [ABSTRACT FROM AUTHOR]

Objective. Atherosclerosis is a chronic inflammatory disease which is responsible for many clinical manifestations. The present study was to investigate the anti-inflammatory functions and mechanisms of TNK1 in atherosclerosis. Methods. The ApoE(-/-) mice and human carotid endarterectomy (CEA) atherosclerotic plaques were used to investigate the differential expression of TNK1. The ApoE(-/-) mice were fed with high-fat diet (HFD) or normal-fat diet (NFD) for 8 weeks; the aorta was separated and stained with oil red O to evaluate the formation of atherosclerosis. TNK1 in mice aorta was measured by qPCR. The human CEA were obtained and identified as ruptured and stable plaques. The level of TNK1 was measured by qPCR and Western-blot staining. Further studies were conducted in THP-1 cells to explore the anti-inflammatory effects of TNK1. We induced the formation of macrophages by incubating THP-1 cells with PMA (phorbol 12-myristate 13-acetate). Afterwards, oxidized low-density lipoprotein (oxLDL) was used to stimulate the inflammation, and the secretion of inflammatory factors was measured by ELISA and qPCR. The levels of TNK1, total STAT1 and Tyk2, and the phosphorylation of STAT1 and Tyk2 were measured by western blot to uncover the mechanisms of TNK1. Results. The oil red O staining indicated obvious deposition of lipid on the aorta of ApoE(-/-) mice after 8-week HFD treatment. The TNK1 level was much higher in both the HFD-fed ApoE(-/-) mice aorta arch and the ruptured human CEA plaques. We found that TNK1 was highly expressed in THP-1 cells, compared to other atherosclerotic related cells (HUVEC, HBMEC, and HA-VSMC), indicating TNK1 might be involved in the inflammation. Suppressing the expression of TNK1 by shTNK1 inhibited the oxLDL-induced secretion of inflammatory factors, such as IL-12, IL-6, and TNF-α. ShTNK1 also inhibited the uptake of lipid and decreased the cellular cholesterol content in THP-1 cells. Furthermore, the shTNK1 suppressed the oxLDL-induced phosphorylation of Tyk2 and STAT1. Conclusion. TNK1 participated in the inflammation in atherosclerosis. shTNK1 suppressed the oxLDL-induced inflammation and lipid deposition in THP-1 cells. The mechanism might be related to the Tyk2/STAT signal pathway. [ABSTRACT FROM AUTHOR]

The rupture of atherosclerotic plaques is essential for cardiovascular and cerebrovascular events. Identification of the key genes related to plaque rupture is an important approach to predict the status of plaque and to prevent the clinical events. In the present study, we downloaded two expression profiles related to the rupture of atherosclerotic plaques (GSE41571 and GSE120521) from GEO database. 11 samples in GSE41571 were used to identify the differentially expressed genes (DEGs) and to construct the weighted gene correlation network analysis (WGCNA) by R software. The gene oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment tool in DAVID website, and the Protein-protein interactions in STRING website were used to predict the functions and mechanisms of genes. Furthermore, we mapped the hub genes extracted from WGCNA to DEGs, and constructed a sub-network using Cytoscape 3.7.2. The key genes were identified by the molecular complex detection (MCODE) in Cytoscape. Further validation was conducted using dataset GSE120521 and human carotid endarterectomy (CEA) plaques. Results: In our study, 868 DEGs were identified in GSE41571. Six modules with 236 hub genes were identified through WGCNA analysis. Among these six modules, blue and brown modules were of the highest correlations with ruptured plaques (with a correlation of 0.82 and −0.9 respectively). 72 hub genes were identified from blue and brown modules. These 72 genes were the most likely ones being related to cell adhesion, extracellular matrix organization, cell growth, cell migration, leukocyte migration, PI3K-Akt signaling, focal adhesion, and ECM-receptor interaction. Among the 72 hub genes, 45 were mapped to the DEGs (logFC > 1.0, p-value < 0.05). The sub-network of these 45 hub genes and MCODE analysis indicated 3 clusters (13 genes) as key genes. They were LOXL1, FBLN5, FMOD, ELN, EFEMP1 in cluster 1, RILP, HLA-DRA, HLA-DMB, HLA-DMA in cluster 2, and SFRP4, FZD6, DKK3 in cluster 3. Further expression detection indicated EFEMP1, BGN, ELN, FMOD, DKK3, FBLN5, FZD6, HLA-DRA, HLA-DMB, HLA-DMA, and RILP might have potential diagnostic value. [ABSTRACT FROM AUTHOR]