参与新冠肺炎发病机制的铁下垂生物学过程及与该病发生和严重程度相关的核心铁下垂基因

IF 1.7 4区 生物学 Q4 EVOLUTIONARY BIOLOGY Evolutionary Bioinformatics Pub Date : 2023-01-01 DOI:10.1177/11769343231153293
Zhengzhong Zhang, Tingting Pang, Min Qi, Gengyun Sun
{"title":"参与新冠肺炎发病机制的铁下垂生物学过程及与该病发生和严重程度相关的核心铁下垂基因","authors":"Zhengzhong Zhang,&nbsp;Tingting Pang,&nbsp;Min Qi,&nbsp;Gengyun Sun","doi":"10.1177/11769343231153293","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>A worldwide outbreak of coronavirus disease 2019 (COVID-19) has resulted in millions of deaths. Ferroptosis is a form of iron-dependent cell death which is characterized by accumulation of lipid peroxides on cellular membranes, and is related with many physiological and pathophysiological processes of diseases such as cancer, inflammation and infection. However, the role of ferroptosis in COVID-19 has few been studied.</p><p><strong>Material and method: </strong>Based on the RNA-seq data of 100 COVID-19 cases and 26 Non-COVID-19 cases from GSE157103, we identified ferroptosis related differentially expressed genes (FRDEGs, adj.<i>P</i>-value < .05) using the \"Deseq2\" R package. By using the \"clusterProfiler\" R package, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Next, a protein-protein interaction (PPI) network of FRDEGs was constructed and top 30 hub genes were selected by cytoHubba in Cytoscape. Subsequently, we established a prediction model for COVID-19 by utilizing univariate logistic regression and the least absolute shrinkage and selection operator (LASSO) regression. Based on core FRDEGs, COVID-19 patients were identified as two clusters using the \"ConsenesusClusterPlus\" R package. Finally, the miRNA-mRNA network was built by Targetscan online database and visualized by Cytoscape software.</p><p><strong>Results: </strong>A total of 119 FRDEGs were identified and the GO and KEGG enrichment analyses showed the most important biologic processes are oxidative stress response, MAPK and PI3K-AKT signaling pathway. The top 30 hub genes were selected, and finally, 7 core FRDEGs (JUN, MAPK8, VEGFA, CAV1, XBP1, HMOX1, and HSPB1) were found to be associated with the occurrence of COVID-19. Next, the two patterns of COVID-19 patients had constructed and the cluster A patients were likely to be more severe.</p><p><strong>Conclusion: </strong>Our study suggested that ferroptosis was involved in the pathogenesis of COVID-19 disease and the functions of core FRDEGs may become a new research aspect of this disease.</p>","PeriodicalId":50472,"journal":{"name":"Evolutionary Bioinformatics","volume":"19 ","pages":"11769343231153293"},"PeriodicalIF":1.7000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9f/a8/10.1177_11769343231153293.PMC9929189.pdf","citationCount":"1","resultStr":"{\"title\":\"The Biological Processes of Ferroptosis Involved in Pathogenesis of COVID-19 and Core Ferroptoic Genes Related With the Occurrence and Severity of This Disease.\",\"authors\":\"Zhengzhong Zhang,&nbsp;Tingting Pang,&nbsp;Min Qi,&nbsp;Gengyun Sun\",\"doi\":\"10.1177/11769343231153293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>A worldwide outbreak of coronavirus disease 2019 (COVID-19) has resulted in millions of deaths. Ferroptosis is a form of iron-dependent cell death which is characterized by accumulation of lipid peroxides on cellular membranes, and is related with many physiological and pathophysiological processes of diseases such as cancer, inflammation and infection. However, the role of ferroptosis in COVID-19 has few been studied.</p><p><strong>Material and method: </strong>Based on the RNA-seq data of 100 COVID-19 cases and 26 Non-COVID-19 cases from GSE157103, we identified ferroptosis related differentially expressed genes (FRDEGs, adj.<i>P</i>-value < .05) using the \\\"Deseq2\\\" R package. By using the \\\"clusterProfiler\\\" R package, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Next, a protein-protein interaction (PPI) network of FRDEGs was constructed and top 30 hub genes were selected by cytoHubba in Cytoscape. Subsequently, we established a prediction model for COVID-19 by utilizing univariate logistic regression and the least absolute shrinkage and selection operator (LASSO) regression. Based on core FRDEGs, COVID-19 patients were identified as two clusters using the \\\"ConsenesusClusterPlus\\\" R package. Finally, the miRNA-mRNA network was built by Targetscan online database and visualized by Cytoscape software.</p><p><strong>Results: </strong>A total of 119 FRDEGs were identified and the GO and KEGG enrichment analyses showed the most important biologic processes are oxidative stress response, MAPK and PI3K-AKT signaling pathway. The top 30 hub genes were selected, and finally, 7 core FRDEGs (JUN, MAPK8, VEGFA, CAV1, XBP1, HMOX1, and HSPB1) were found to be associated with the occurrence of COVID-19. Next, the two patterns of COVID-19 patients had constructed and the cluster A patients were likely to be more severe.</p><p><strong>Conclusion: </strong>Our study suggested that ferroptosis was involved in the pathogenesis of COVID-19 disease and the functions of core FRDEGs may become a new research aspect of this disease.</p>\",\"PeriodicalId\":50472,\"journal\":{\"name\":\"Evolutionary Bioinformatics\",\"volume\":\"19 \",\"pages\":\"11769343231153293\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/9f/a8/10.1177_11769343231153293.PMC9929189.pdf\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Evolutionary Bioinformatics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1177/11769343231153293\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"EVOLUTIONARY BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evolutionary Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1177/11769343231153293","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"EVOLUTIONARY BIOLOGY","Score":null,"Total":0}
引用次数: 1

摘要

背景:2019年全球爆发的冠状病毒病(COVID-19)已导致数百万人死亡。铁沉是一种铁依赖性细胞死亡形式,其特征是细胞膜上脂质过氧化物的积累,与癌症、炎症和感染等疾病的许多生理和病理生理过程有关。然而,关于铁下垂在COVID-19中的作用的研究很少。材料与方法:基于GSE157103中100例COVID-19病例和26例非COVID-19病例的RNA-seq数据,我们鉴定了铁死亡相关的差异表达基因(FRDEGs, adj. p值)。结果:共鉴定出119个FRDEGs, GO和KEGG富集分析显示,氧化应激反应、MAPK和PI3K-AKT信号通路是最重要的生物学过程。筛选前30个中心基因,最终发现7个核心frdeg (JUN、MAPK8、VEGFA、CAV1、XBP1、HMOX1和HSPB1)与COVID-19的发生相关。接下来,构建了两种新型冠状病毒肺炎患者模式,A类患者可能更严重。结论:本研究提示铁下垂参与了新冠肺炎的发病机制,核心frdeg的功能可能成为新冠肺炎研究的一个新方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The Biological Processes of Ferroptosis Involved in Pathogenesis of COVID-19 and Core Ferroptoic Genes Related With the Occurrence and Severity of This Disease.

Background: A worldwide outbreak of coronavirus disease 2019 (COVID-19) has resulted in millions of deaths. Ferroptosis is a form of iron-dependent cell death which is characterized by accumulation of lipid peroxides on cellular membranes, and is related with many physiological and pathophysiological processes of diseases such as cancer, inflammation and infection. However, the role of ferroptosis in COVID-19 has few been studied.

Material and method: Based on the RNA-seq data of 100 COVID-19 cases and 26 Non-COVID-19 cases from GSE157103, we identified ferroptosis related differentially expressed genes (FRDEGs, adj.P-value < .05) using the "Deseq2" R package. By using the "clusterProfiler" R package, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Next, a protein-protein interaction (PPI) network of FRDEGs was constructed and top 30 hub genes were selected by cytoHubba in Cytoscape. Subsequently, we established a prediction model for COVID-19 by utilizing univariate logistic regression and the least absolute shrinkage and selection operator (LASSO) regression. Based on core FRDEGs, COVID-19 patients were identified as two clusters using the "ConsenesusClusterPlus" R package. Finally, the miRNA-mRNA network was built by Targetscan online database and visualized by Cytoscape software.

Results: A total of 119 FRDEGs were identified and the GO and KEGG enrichment analyses showed the most important biologic processes are oxidative stress response, MAPK and PI3K-AKT signaling pathway. The top 30 hub genes were selected, and finally, 7 core FRDEGs (JUN, MAPK8, VEGFA, CAV1, XBP1, HMOX1, and HSPB1) were found to be associated with the occurrence of COVID-19. Next, the two patterns of COVID-19 patients had constructed and the cluster A patients were likely to be more severe.

Conclusion: Our study suggested that ferroptosis was involved in the pathogenesis of COVID-19 disease and the functions of core FRDEGs may become a new research aspect of this disease.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
期刊最新文献
Phylodynamic Investigation of Yellow Fever Virus Sheds New Insight on Geographic Dispersal Across Africa. In silico Characterization of a Hypothetical Protein (PBJ89160.1) from Neisseria meningitidis Exhibits a New Insight on Nutritional Virulence and Molecular Docking to Uncover a Therapeutic Target. Comparative Phylogenetic Analysis and Protein Prediction Reveal the Taxonomy and Diverse Distribution of Virulence Factors in Foodborne Clostridium Strains. An Effective Computational Method for Predicting Self-Interacting Proteins Based on VGGNet Convolutional Neural Network and Gray-Level Co-occurrence Matrix. Comprehensive Profiling of Transcriptome and m6A Epitranscriptome Uncovers the Neurotoxic Effects of Yunaconitine on HT22 Cells.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1