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基于整合生物信息学方法鉴定和分析与急性心肌梗死相关的关键基因。

Identification and analysis of key genes associated with acute myocardial infarction by integrated bioinformatics methods.

机构信息

Department of Clinical Chinese Pharmacy, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100102, China.

出版信息

Medicine (Baltimore). 2021 Apr 16;100(15):e25553. doi: 10.1097/MD.0000000000025553.

Abstract

BACKGROUND

Acute myocardial infarction (AMI) is a common disease leading threat to human health around the world. Here we aimed to explore new biomarkers and potential therapeutic targets in AMI through adopting integrated bioinformatics tools.

METHODS

The gene expression Omnibus (GEO) database was used to obtain genes data of AMI and no-AMI whole blood. Furthermore, differentially expressed genes (DEGs) were screened using the "Limma" package in R 3.6.1 software. Functional and pathway enrichment analyses of DEGs were performed via "Bioconductor" and "GOplot" package in R 3.6.1 software. In order to screen hub DEGs, the STRING version 11.0 database, Cytoscape and molecular complex detection (MCODE) were applied. Correlation among the hub DEGs was evaluated using Pearson's correlation analysis.

RESULTS

By performing DEGs analysis, 289 upregulated and 62 downregulated DEGs were successfully identified from GSE66360, respectively. And they were mainly enriched in the terms of neutrophil activation, immune response, cytokine, nuclear factor kappa-B (NF-κB) signaling pathway, IL-17 signaling pathway, and tumor necrosis factor (TNF) signaling pathway. Based on the data of protein-protein interaction (PPI), the top 10 hub genes were ranked, including interleukin-8 (CXCL8), TNF, N-formyl peptide receptor 2 (FPR2), growth-regulated alpha protein (CXCL1), transcription factor AP-1 (JUN), interleukin-1 beta (IL1B), platelet basic protein (PPBP), matrix metalloproteinase-9 (MMP9), toll-like receptor 2 (TLR2), and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G). What's more, the results of correlation analysis demonstrated that there was positive correlation between the 10 hub DEGs.

CONCLUSION

Ten DEGs were identified as potential candidate diagnostic biomarkers for patients with AMI in present study. However, further experiments are needed to confirm the functional pathways and hub genes associated with AMI.

摘要

背景

急性心肌梗死(AMI)是一种常见的疾病,对全球人类健康构成严重威胁。本研究旨在通过采用综合生物信息学工具,探索 AMI 的新型生物标志物和潜在治疗靶点。

方法

使用基因表达综合数据库(GEO)获取 AMI 和非 AMI 全血的基因表达数据。然后,使用 R 3.6.1 软件中的“Limma”包筛选差异表达基因(DEGs)。通过 R 3.6.1 软件中的“Bioconductor”和“GOplot”包进行 DEGs 的功能和通路富集分析。为了筛选关键 DEGs,应用了 STRING 版本 11.0 数据库、Cytoscape 和分子复合物检测(MCODE)。使用 Pearson 相关分析评估关键 DEGs 之间的相关性。

结果

通过 DEGs 分析,从 GSE66360 中成功鉴定出 289 个上调和 62 个下调的 DEGs。它们主要富集于中性粒细胞激活、免疫反应、细胞因子、核因子 kappa-B(NF-κB)信号通路、IL-17 信号通路和肿瘤坏死因子(TNF)信号通路等生物学过程。基于蛋白质-蛋白质相互作用(PPI)数据,对前 10 个关键基因进行了排名,包括白细胞介素 8(CXCL8)、肿瘤坏死因子(TNF)、N-甲酰肽受体 2(FPR2)、生长调节蛋白 alpha(CXCL1)、转录因子 AP-1(JUN)、白细胞介素 1β(IL1B)、血小板碱性蛋白(PPBP)、基质金属蛋白酶 9(MMP9)、 toll 样受体 2(TLR2)和高亲和力免疫球蛋白 E 受体亚基 gamma(FCER1G)。此外,相关性分析的结果表明,这 10 个关键 DEGs 之间存在正相关关系。

结论

本研究确定了 10 个 DEG 作为 AMI 患者潜在的候选诊断生物标志物。然而,需要进一步的实验来验证与 AMI 相关的功能途径和关键基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d07/8052032/7e1135b424f7/medi-100-e25553-g001.jpg

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