Identification of the key genes and immune infiltrating cells determined by sex differences in ischaemic stroke through co-expression network module

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2021-11-18 DOI:10.1049/syb2.12039
Haipeng Xu, Yanzhi Ge, Yang Liu, Yang Zheng, Rong Hu, Conglin Ren, Qianqian Liu
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引用次数: 8

Abstract

Stroke is one of the leading causes of patients' death and long-term disability worldwide, and ischaemic stroke (IS) accounts for nearly 80% of all strokes. Differential genes and weighted gene co-expression network analysis (WGCNA) in male and female patients with IS were compared. The authors used cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) to analyse the distribution pattern of immune subtypes between male and female patients. In this study, 141 up-regulated and 61 down-regulated genes were gathered and distributed into five modules in response to their correlation degree to clinical traits. The criterion for Gene Ontology (GO) term and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway indicated that detailed analysis had the potential to enhance clinical prediction and to identify the gender-related mechanism. After that, the expression levels of hub genes were measured via the quantitative real-time PCR (qRT-PCR) method. Finally, CCL20, ICAM1 and PTGS2 were identified and these may be some promising targets for sex differences in IS. Besides, the hub genes were further verified by rat experiments. Furthermore, these CIBERSORT results showed that T cells CD8 and Monocytes may be the target for the treatment of male and female patients, respectively.

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通过共表达网络模块鉴定缺血性脑卒中性别差异决定的关键基因和免疫浸润细胞
中风是世界范围内患者死亡和长期残疾的主要原因之一,缺血性中风(is)占所有中风的近80%。比较男女IS患者差异基因和加权基因共表达网络分析(WGCNA)。作者通过估计RNA转录物相对亚群(CIBERSORT)的细胞类型鉴定来分析男性和女性患者之间免疫亚型的分布模式。本研究收集了141个上调基因和61个下调基因,并根据其与临床特征的相关程度将其分为5个模块。基因本体(GO)术语和京都基因与基因组百科全书(KEGG)途径的标准表明,详细分析具有增强临床预测和识别性别相关机制的潜力。之后,通过实时荧光定量PCR (qRT-PCR)方法检测hub基因的表达水平。最后,我们确定了CCL20、ICAM1和PTGS2,这些可能是IS性别差异的一些有希望的靶点。此外,通过大鼠实验进一步验证了枢纽基因。此外,这些CIBERSORT结果表明,T细胞CD8和单核细胞可能分别是治疗男性和女性患者的靶点。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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