基于生物信息学策略鉴定动脉粥样硬化的潜在诊断生物标志物。

BACKGROUND: Atherosclerosis is the main pathological change in atherosclerotic cardiovascular disease, and its underlying mechanisms are not well understood. The aim of this study was to explore the hub genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis. METHODS: Three microarray datasets from Gene Expression Omnibus (GEO) identified robust differentially expressed genes (DEGs) by robust rank aggregation (RRA). We performed connectivity map (CMap) analysis and functional enrichment analysis on robust DEGs and constructed a protein‒protein interaction (PPI) network using the STRING database to identify the hub gene using 12 algorithms of cytoHubba in Cytoscape. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic potency of the hub genes.The CIBERSORT algorithm was used to perform immunocyte infiltration analysis and explore the association between the identified biomarkers and infiltrating immunocytes using Spearman's rank correlation analysis in R software. Finally, we evaluated the expression of the hub gene in foam cells. RESULTS: A total of 155 robust DEGs were screened by RRA and were revealed to be mainly associated with cytokines and chemokines by functional enrichment analysis. CD52 and IL1RN were identified as hub genes and were validated in the GSE40231 dataset. Immunocyte infiltration analysis showed that CD52 was positively correlated with gamma delta T cells, M1 macrophages and CD4 memory resting T cells, while IL1RN was positively correlated with monocytes and activated mast cells. RT-qPCR results indicate that CD52 and IL1RN were highly expressed in foam cells, in agreement with bioinformatics analysis. CONCLUSIONS: This study has established that CD52 and IL1RN may play a key role in the occurrence and development of atherosclerosis, which opens new lines of thought for further research on the pathogenesis of atherosclerosis.

背景：动脉粥样硬化是动脉粥样硬化性心血管疾病的主要病理变化，其潜在机制尚不清楚。本研究旨在通过生物信息学分析探讨动脉粥样硬化相关的枢纽基因及其潜在机制。

方法：从基因表达综合数据库（GEO）中筛选出 3 个微阵列数据集，通过稳健秩聚合（RRA）确定稳健差异表达基因（DEGs）。我们对稳健 DEGs 进行连接图谱（CMap）分析和功能富集分析，并使用 STRING 数据库构建蛋白质-蛋白质相互作用（PPI）网络，使用 Cytoscape 中的 12 种 cytoHubba 算法识别枢纽基因。采用受试者工作特征（ROC）分析评估枢纽基因的诊断效力。使用 CIBERSORT 算法进行免疫细胞浸润分析，并使用 R 软件中的 Spearman 秩相关分析探讨鉴定的生物标志物与浸润免疫细胞之间的关联。最后，我们评估了枢纽基因在泡沫细胞中的表达。

结果：通过 RRA 共筛选出 155 个稳健的 DEGs，功能富集分析表明这些基因主要与细胞因子和趋化因子有关。CD52 和 IL1RN 被确定为枢纽基因，并在 GSE40231 数据集得到验证。免疫细胞浸润分析表明，CD52 与γδ T 细胞、M1 巨噬细胞和 CD4 记忆静息 T 细胞呈正相关，而 IL1RN 与单核细胞和活化肥大细胞呈正相关。实时定量 PCR 结果表明，CD52 和 IL1RN 在泡沫细胞中高表达，与生物信息学分析结果一致。

结论：本研究表明 CD52 和 IL1RN 可能在动脉粥样硬化的发生发展中起关键作用，为进一步研究动脉粥样硬化的发病机制提供了新的思路。