Dataset Information

Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis.

ABSTRACT: In recent years, intense research has been conducted to explore the diagnostic value of mRNA expression differences in atherosclerosis (AS). Nevertheless, because various technology platforms are applied and sample sizes are small, the results are inconsistent among the studies. We conducted a comprehensive analysis of a total of 161 tissue samples from 4 published studies after evaluating 230 datasets from the Gene Expression Omnibus and ArrayExpress. Adopting the newly published robust rank aggregation approach, combined with Kyoto Encyclopedia of Genes and Genomes pathway analysis, Gene Ontology functional enrichment analysis, and protein-protein interaction network construction, we identified four significantly upregulated genes (CCL4, CCL18, MMP9 and SPP1) for diagnosing AS, even in the advanced stage. Then, we performed gene set enrichment analysis to identify the pathways that were most affected by altered mRNA expression in atherosclerotic plaques. We found that four hub genes cooperatively targeted lipid metabolism and inflammatory immune-related pathways and validated their high expression levels in ruptured plaques by qRT-PCR, western blot analysis and immunohistochemical staining. In summary, our study showed that these genes can be used as interventional targets for plaque progression, and the results suggested we should focus on small changes in these key indicators in the clinical setting.

SUBMITTER: Chen P

PROVIDER: S-EPMC6738408 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis.

Chen Peipei P Chen Yuexin Y Wu Wei W Chen Lianfeng L Yang Xufei X Zhang Shuyang S

Aging 20190826 16

In recent years, intense research has been conducted to explore the diagnostic value of mRNA expression differences in atherosclerosis (AS). Nevertheless, because various technology platforms are applied and sample sizes are small, the results are inconsistent among the studies. We conducted a comprehensive analysis of a total of 161 tissue samples from 4 published studies after evaluating 230 datasets from the Gene Expression Omnibus and ArrayExpress. Adopting the newly published robust rank ag ...[more]

PMID: 31449494

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Project description:BackgroundAtherosclerotic 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.MethodsWhole 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.Results239 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.ConclusionsOverexpression 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.

Project description:ObjectiveThis study identified underlying genetic molecules associated with histologically unstable carotid atherosclerotic plaques through bioinformatics analysis that may be potential biomarkers and therapeutic targets.MethodsThree transcriptome datasets (GSE41571, GSE120521 and E-MTAB-2055) and one non-coding RNA dataset (GSE111794) that met histological grouping criteria of unstable plaque were downloaded. The common differentially expressed genes (co-DEGs) of unstable plaques identified from three mRNA datasets were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG). A protein-protein interaction (PPI) network was constructed to present the interaction between co-DEGs and screen out hub genes. MiRNet database and GSE111794 dataset were used to identify the miRNAs targeting hub genes. Associated transcription factors (TFs) and drugs were also predicted. These predicted results were used to construct miRNA/TFs-hub gene and drug-hub gene regulatory networks.ResultsA total of 105 co-DEGs were identified, including 42 up-regulated genes and 63 down-regulated genes, which were mainly enriched in collagen-containing extracellular matrix, focal adhesion, actin filament bundle, chemokine signaling pathway and regulates of actin cytoskeleton. Ten hub genes (up-regulated: HCK, C1QC, CD14, FCER1G, LCP1 and RAC2; down-regulated: TPM1, MYH10, PLS3 and FMOD) were screened. HCK and RAC2 were involved in chemokine signaling pathway, MYH10 and RAC2 were involved in regulation of actin cytoskeleton. We also predicted 12 miRNAs, top5 TFs and 25 drugs targeting hub genes. In the miRNA/TF-hub gene regulatory network, PLS3 was the most connected hub genes and was targeted by six miRNAs and all five screened TFs. In the drug-hub gene regulatory network, HCK was targeted by 20 drugs including 10 inhibitors.ConclusionsWe screened 10 hub genes and predicted miRNAs and TFs targeting them. These molecules may play a crucial role in the progression of histologically unstable carotid plaques and serve as potential biomarkers and therapeutic targets.

Dataset Information

Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis.

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Identification and validation of four hub genes involved in the plaque deterioration of atherosclerosis.

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