Blood transcriptome analysis revealed the crosstalk between severe COVID-19 and systemic lupus erythematosus

上睑下垂 炎症体 医学 2019年冠状病毒病(COVID-19) 免疫学 内科学 疾病 炎症 传染病(医学专业)
作者
Ruogang Meng,Ning Zhang,Feixiang Yang,Zhihao Xu,Zhengyang Wu,Yinan Du
出处
期刊:Journal of Infection [Elsevier BV]
卷期号:86 (4): e104-e106 被引量:1
标识
DOI:10.1016/j.jinf.2023.02.011
摘要

Dear editor, We have read with great interest the article by Cui et al. that previously reported the correlation between high inflammasome expression and pyroptosis with severe COVID-19 infection in cancer patients.1Cui H. Liu J. Zhang L. The high expression of key components of inflammasome and pyroptosis might lead to severe COVID-19 infection in cancer patients.J Infect. 2022; 84: e19-e21Abstract Full Text Full Text PDF PubMed Scopus (2) Google Scholar We noticed that activation of inflammasome and pyroptosis also function in systemic lupus erythematosus (SLE).2Kong R. Sun L. Li H. Wang D. The role of NLRP3 inflammasome in the pathogenesis of rheumatic disease.Autoimmunity. 2022; 55: 1-7Crossref PubMed Scopus (17) Google Scholar, 3Shin J.I. Lee K.H. Joo Y.H. Lee J.M. Jeon J. Jung H.J. et al.Inflammasomes and autoimmune and rheumatic diseases: a comprehensive review.J Autoimmun. 2019; 103102299Crossref PubMed Scopus (59) Google Scholar Recently, several studies have reported that patients with SLE might have a higher risk of severe COVID-19, and the risk of SLE was substantially higher in COVID-19 individuals.4Ugarte-Gil M.F. Alarcón G.S. Izadi Z. Duarte-García A. Reátegui-Sokolova C. Clarke A.E. et al.Characteristics associated with poor COVID-19 outcomes in individuals with systemic lupus erythematosus: data from the COVID-19 Global Rheumatology Alliance.Ann Rheum Dis. 2022; 81: 970-978Crossref PubMed Scopus (31) Google Scholar, 5Chang R. Yen-Ting Chen T. Wang S.-I. Hung Y.-M. Chen H.-Y. Wei C.-C.J. Risk of autoimmune diseases in patients with COVID-19: a retrospective cohort study.EClinicalMedicine. 2023; 56101783Abstract Full Text Full Text PDF Scopus (7) Google Scholar, 6Yang H. Xu J. Liang X. Shi L. Wang Y. Autoimmune diseases are independently associated with COVID-19 severity: evidence based on adjusted effect estimates.J Infect. 2021; 82: e23-e26Abstract Full Text Full Text PDF PubMed Scopus (16) Google Scholar Severe COVID-19 and SLE seem to have a strong connection; however, the potential molecular mechanisms are unclear. In this study, we used blood transcriptome analysis to explore the potential mechanisms and key genes hiding in the crosstalk between severe COVID-19 and SLE. Two severe COVID-19 datasets (GSE164805 and GSE171110) and one SLE dataset (GSE45291) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/) and then analyzed. We selected 4920 differentially expressed genes (DEGs), including 2310 upregulated genes and 2610 downregulated genes, from 54 patients suffering from severe COVID-19 (Fig. 1A). Furthermore, a total of 1448 DEGs, including 377 upregulated genes and 694 downregulated genes, were identified from 292 SLE patients (Fig. 1B). We then took the intersection of the selected DEGs, and a total of 272 genes were obtained (Fig. 1C). To reveal the potential functions of those DEGs, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. For enrichment of GO terms, the shared DEGs were mainly involved in the immune system process, multi-organism pathway, immune response, and transcription factor binding and related to cytosol and mitochondrion (Fig. 1D). For KEGG pathway enrichment analysis, the top five significant pathways were Cytokine-cytokine receptor interaction, influenza A, Th17 cell differentiation, Epstein-Barr virus infection, and ribosome (Fig. 1E). To further identify key genes affecting the interactions between severe COVID-19 and SLE, we used STRING (https://string-db.org/) and Cytoscape to screen the top 20 hub genes using six topological algorithms of the plugin CytoHubba and obtained their intersection (Fig. 2A). The final 17 hub genes included IFIT3, RSAD2, IFIT1, IFI44L, IFI44, OAS3, OAS1, OAS2, IFIT2, IFI35, OASL, IFI27, IFIT5, XAF1, USP18, HERC5, and EIF2AK2. GO enrichment analysis showed that these genes functioned in the defense response, innate immune response, biotic stimulus response, and infection response, and were mainly related to the cytosol and RNA binding (Fig. 2B). KEGG pathway enrichment analysis revealed that these genes were mainly involved in immune- and infection-related pathways such as Hepatitis C and NOD-like receptor signaling pathways (Fig. 2C). In addition, we verified the expression of these 17 DEGs in the severe COVID-19 and SLE datasets. Interestingly, all these key genes were significantly highly expressed in both the severe COVID-19 cohorts and the SLE cohort compared to those in healthy individuals (Fig. 2D and E). Furthermore, we constructed a transcription factor (TF)-miRNA-hub gene network to present potential regulatory mechanisms by NetworkAnalyst.7Zhou G. Soufan O. Ewald J. Hancock R.E.W. Basu N. Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis.Nucleic Acids Res. 2019; 47: W234-W241Crossref PubMed Scopus (732) Google Scholar The network consists of 72 nodes and 78 edges, including 41 TFs, 21 miRNAs, and 10 key genes (Fig. 2F). Our work identified some key genes and presented molecular mechanisms of the correlation between severe COVID-19 and SLE. Notably, most selected genes belong to interferon-induced proteins with tetratricopeptide repeats (IFITs) or oligoadenylate synthetase (OAS) gene families. IFITs and OAS gene families are both induced by Interferons (IFNs), participate in regulating innate immune response, and play antiviral functions.8Hornung V. Hartmann R. Ablasser A. Hopfner K.-P. OAS proteins and cGAS: unifying concepts in sensing and responding to cytosolic nucleic acids.Nat Rev Immunol. 2014; 14: 521-528Crossref PubMed Scopus (188) Google Scholar, 9Zhou X. Michal J.J. Zhang L. Ding B. Lunney J.K. Liu B. et al.Interferon induced IFIT family genes in host antiviral defense.Int J Biol Sci. 2013; 9: 200-208Crossref PubMed Scopus (155) Google Scholar Previous research has proven that IFNs and the innate immune response are involved in the progression of COVID-19 and SLE. The dysregulation of IFNs and perturbations in adaptive immune systems, which is prevalent in SLE, may lead to severe COVID-19.10Thanou A. Sawalha A.H. SARS-CoV-2 and systemic lupus erythematosus.Curr Rheumatol Rep. 2021; 23: 8Crossref PubMed Scopus (13) Google Scholar In short, our results revealed potential mechanisms and key biomarkers that contribute to the crosstalk between severe COVID-19 and SLE, which provides new insight into COVID-19 and SLE and contributes to precise diagnosis and treatment. This work was funded by the National College Students’ Innovation and Entrepreneurship Training Program (No. 202210366002) and the College Students’ Innovation and Entrepreneurship Training Program of Anhui Province (No. S202210366021 and S202210366017).

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
2秒前
2秒前
科研豆包完成签到 ,获得积分10
2秒前
qwe完成签到,获得积分10
2秒前
科研通AI6.4的应助被匍匐前进采纳,获得10
3秒前
sky发布了新的文献求助10
3秒前
楠楠多多完成签到,获得积分10
5秒前
我居然要写两篇小论文完成签到 ,获得积分10
6秒前
7秒前
今后的应助被qq采纳,获得10
7秒前
斯文败类的应助被lars采纳,获得10
8秒前
博纳清完成签到 ,获得积分10
8秒前
keyanren的应助被能干妙松采纳,获得20
8秒前
Bruce完成签到,获得积分10
12秒前
sghsh发布了新的文献求助10
12秒前
六道完成签到,获得积分10
13秒前
科研通AI6.2的应助被sky采纳,获得10
13秒前
Rui_Rui的应助被烦烦烦采纳,获得10
13秒前
jsy关闭了jsy的文献求助
14秒前
神勇的青旋发布了新的文献求助200
14秒前
Snow发布了新的文献求助10
14秒前
NepTune发布了新的文献求助20
14秒前
感动雪糕完成签到,获得积分10
14秒前
15秒前
蒋50完成签到,获得积分0
16秒前
16秒前
16秒前
ding的应助被咩咩咩咩吗采纳,获得10
16秒前
科研通AI6.2的应助被啤啤采纳,获得10
17秒前
Ming的应助被六道采纳,获得20
18秒前
keke完成签到 ,获得积分10
18秒前
ff999完成签到,获得积分0
18秒前
糖葫芦傻乎乎关注了科研通微信公众号
18秒前
19秒前
okiya完成签到,获得积分10
20秒前
超级铅笔发布了新的文献求助10
20秒前
云卷云舒发布了新的文献求助10
20秒前
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Energie-Contracting 1500
Spec 401: Standards for Jet Fuel Facility and Equipment Commissioning and Flushing at Airports, 2026.1 (Original Issue) 1000
Spec 103: Standard for Jet Fuel Quality Control at Airports, Revision 2026.1 1000
Mathematical models in hydrology 1000
Klimaschutzrecht durch den Energiesektor im Mehrebenensystem – Ein Rechtsvergleich 1000
Introduction to Industrial/Organizational Psychology 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8092854
求助须知:如何正确求助?哪些是违规求助? 9505109
关于积分的说明 21445771
捐赠科研通 7665852
什么是DOI,文献DOI怎么找? 3405381
关于科研通互助平台的介绍 2533689
邀请新用户注册赠送积分活动 2444501