Background

This study aimed to screen out the potential diagnostic biomarkers for atherosclerosis (AS).

Methods

We downloaded the gene expression profiles GSE66360, GSE28829, GSE41571, GSE71226, and GSE100927 from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the “limma” package in R. Weighted gene co-expression network analysis (WGCNA) was applied to reveal the correlation between genes in different samples. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. The interaction pairs of proteins were retained by the STRING database, and the protein–protein interaction (PPI) network was visualized with the hub genes. Finally, the R packages “ggpubr” and “preprocessCore” were used to analyze immune cell infiltration.

Results

In total, 40 overlapping genes both in GSE66360 and GSE28829 were found to be related to the occurrence of AS. Further, the top 10 network hub genes including TYROBP, CSF1R, TLR2, CD14, CCL4, FCER1G, CD163, TREM1, PLEK, and C5AR1 were identified as significant key genes. Moreover, four genes (TYROBP, CSF1R, FCGR1B, and CD14) were verified that could efficiently diagnose AS. Finally, the gene TYROBP was found to have a strong correlation with immune-infiltrating cells.

Conclusion

Our study identified four genes (TYROBP, CSF1R, FCGR1B, and CD14) that may be effective biomarkers for AS, with the potential to guide the clinical diagnosis of AS.

中文翻译：

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通过加权基因共表达网络分析鉴定出动脉粥样硬化的新型生物标志物

背景

本研究旨在筛选动脉粥样硬化（AS）的潜在诊断生物标志物。

方法

我们从基因表达综合 (GEO) 数据库下载了基因表达谱 GSE66360、GSE28829、GSE41571、GSE71226 和 GSE100927。使用R中的“limma”包识别差异表达基因（DEG）。加权基因共表达网络分析（WGCNA）用于揭示不同样本中基因之间的相关性。随后，进行了基因本体论（GO）和京都基因和基因组百科全书（KEGG）通路富集分析。蛋白质的相互作用对由 STRING 数据库保留，蛋白质-蛋白质相互作用 (PPI) 网络通过中心基因可视化。最后，使用R包“ggpubr”和“preprocessCore”来分析免疫细胞浸润。

结果

总共发现GSE66360和GSE28829中有40个重叠基因与AS的发生有关。此外，前10个网络枢纽基因包括TYROBP、CSF1R、TLR2、CD14、CCL4、FCER1G、CD163、TREM1、PLEK和C5AR1被确定为重要的关键基因。此外，四个基因（TYROBP、CSF1R、FCGR1B和CD14）被验证可以有效诊断AS。最后，发现基因TYROBP与免疫浸润细胞有很强的相关性。

结论

我们的研究确定了四个基因（TYROBP、CSF1R、FCGR1B和CD14）可能是 AS 的有效生物标志物，有可能指导 AS 的临床诊断。