基于ssGSEA算法和ceRNA调控网络评价的脓毒症早期重要因素筛选

IF 1.7 4区 生物学 Q4 EVOLUTIONARY BIOLOGY
Evolutionary Bioinformatics Pub Date : 2021-11-26 eCollection Date: 2021-01-01 DOI:10.1177/11769343211058463
Liou Huang, Chunrong Wu, Dan Xu, Yuhui Cui, Jianguo Tang
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引用次数: 20

摘要

背景:败血症是一种失调的宿主对病原体的反应。败血症诊断延误已成为患者死亡的主要原因。本研究确定了早期预防脓毒性休克的一些因素,有助于脓毒症的早期治疗。方法:从NCBI GEO数据库获取感染性休克患者的测序数据(RNA-和mirna -测序)。重新注释后,我们获得了lncRNAs、miRNA和mRNA的信息。然后,我们基于ssGSEA算法评估样本的免疫特性。我们通过构建ceRNA调控网络,利用WGCNA算法获取与免疫显著相关的基因,筛选重要的相关因子。结果:重新注释后,我们获得了1708个lncrna, 129个mirna和17 326个mrna。同时,通过ssGSEA算法,我们获得了5个重要的免疫细胞。最后,我们构建了与SS通路相关的ceRNA调控网络。结论:在脓毒性休克早期,我们发现5种免疫细胞发生了显著变化。我们还构建了ceRNA网络,这将有助于我们探索脓毒性休克的发病机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Screening of Important Factors in the Early Sepsis Stage Based on the Evaluation of ssGSEA Algorithm and ceRNA Regulatory Network.

Screening of Important Factors in the Early Sepsis Stage Based on the Evaluation of ssGSEA Algorithm and ceRNA Regulatory Network.

Screening of Important Factors in the Early Sepsis Stage Based on the Evaluation of ssGSEA Algorithm and ceRNA Regulatory Network.

Screening of Important Factors in the Early Sepsis Stage Based on the Evaluation of ssGSEA Algorithm and ceRNA Regulatory Network.

Background: Sepsis is a dysregulated host response to pathogens. Delay in sepsis diagnosis has become a primary cause of patient death. This study determines some factors to prevent septic shock in its early stage, contributing to the early treatment of sepsis.

Methods: The sequencing data (RNA- and miRNA-sequencing) of patients with septic shock were obtained from the NCBI GEO database. After re-annotation, we obtained lncRNAs, miRNA, and mRNA information. Then, we evaluated the immune characteristics of the sample based on the ssGSEA algorithm. We used the WGCNA algorithm to obtain genes significantly related to immunity and screen for important related factors by constructing a ceRNA regulatory network.

Result: After re-annotation, we obtained 1708 lncRNAs, 129 miRNAs, and 17 326 mRNAs. Also, through the ssGSEA algorithm, we obtained 5 important immune cells. Finally, we constructed a ceRNA regulation network associated with SS pathways.

Conclusion: We identified 5 immune cells with significant changes in the early stage of septic shock. We also constructed a ceRNA network, which will help us explore the pathogenesis of septic shock.

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来源期刊
Evolutionary Bioinformatics
Evolutionary Bioinformatics 生物-进化生物学
CiteScore
4.20
自引率
0.00%
发文量
25
审稿时长
12 months
期刊介绍: Evolutionary Bioinformatics is an open access, peer reviewed international journal focusing on evolutionary bioinformatics. The journal aims to support understanding of organismal form and function through use of molecular, genetic, genomic and proteomic data by giving due consideration to its evolutionary context.
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