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鉴定心肌梗死中与免疫细胞浸润相关的基因共表达网络生物标志物。

Identification of Biomarkers Related to Immune Cell Infiltration with Gene Coexpression Network in Myocardial Infarction.

机构信息

Department of Electrocardiogram, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.

Department of Cardiology, The First Affiliated Hospital, Zhejiang University School of Medicine, China.

出版信息

Dis Markers. 2021 Nov 5;2021:2227067. doi: 10.1155/2021/2227067. eCollection 2021.

Abstract

BACKGROUND

There is evidence that the immune system plays a key critical role in the pathogenesis of myocardial infarction (MI). However, the exact mechanisms associated with immunity have not been systematically uncovered.

METHODS

This study used the weighted gene coexpression network analysis (WGCNA) and the CIBERSORT algorithm to analyze the MI expression data from the Gene Expression Omnibus database and then identify the module associated with immune cell infiltration. In addition, we built the coexpression network and protein-protein interactions network analysis to identify the hub genes. Furthermore, the relationship between hub genes and NK cell resting was validated by using another dataset GSE123342. Finally, receiver operating characteristic (ROC) curve analyses were used to assess the diagnostic value of verified hub genes.

RESULTS

Monocytes and neutrophils were markedly increased, and T cell CD8, T cell CD4 naive, T cell CD4 memory resting, and NK cell resting were significantly decreased in MI groups compared with stable coronary artery disease (CAD) groups. The WGCNA results showed that the pink model had the highest correlation with the NK cell resting infiltration level. We identified 11 hub genes whose expression correlated to the NK cell resting infiltration level, among which, 7 hub genes (NKG7, TBX21, PRF1, CD247, KLRD1, FASLG, and EOMES) were successfully validated in GSE123342. And these 7 genes had diagnostic value to distinguish MI and stable CAD.

CONCLUSIONS

NKG7, TBX21, PRF1, CD247, KLRD1, FASLG, and EOMES may be a diagnostic biomarker and therapeutic target associated with NK cell resting infiltration in MI.

摘要

背景

有证据表明,免疫系统在心肌梗死(MI)的发病机制中起着关键作用。然而,与免疫相关的确切机制尚未被系统揭示。

方法

本研究使用加权基因共表达网络分析(WGCNA)和 CIBERSORT 算法分析了来自基因表达综合数据库(GEO)的 MI 表达数据,然后确定与免疫细胞浸润相关的模块。此外,我们构建了共表达网络和蛋白质-蛋白质相互作用网络分析,以识别关键基因。此外,使用另一个数据集 GSE123342 验证了关键基因与 NK 细胞静息的关系。最后,使用受试者工作特征(ROC)曲线分析评估验证的关键基因的诊断价值。

结果

与稳定型冠状动脉疾病(CAD)组相比,MI 组中的单核细胞和中性粒细胞明显增加,而 T 细胞 CD8、T 细胞 CD4 初始、T 细胞 CD4 记忆静息和 NK 细胞静息明显减少。WGCNA 结果显示,粉红色模型与 NK 细胞静息浸润水平相关性最高。我们确定了 11 个与 NK 细胞静息浸润水平相关的关键基因,其中 7 个关键基因(NKG7、TBX21、PRF1、CD247、KLRD1、FASLG 和 EOMES)在 GSE123342 中得到了成功验证。并且这些 7 个基因具有区分 MI 和稳定 CAD 的诊断价值。

结论

NKG7、TBX21、PRF1、CD247、KLRD1、FASLG 和 EOMES 可能是与 MI 中 NK 细胞静息浸润相关的诊断生物标志物和治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6739/8589498/bf5347186a5e/DM2021-2227067.001.jpg

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