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Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus

Objective Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by autoantibody production and multi-system involvement, but the etiology is largely unclear. This study aimed to elucidate candidate genes and pathways involved in SLE. Methods Three original datasets GSE7250...

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Published in:Clinical rheumatology 2020-02, Vol.39 (2), p.425-434
Main Authors: Yang, Fangyuan, Zhai, Zeqing, Luo, Xiaoqing, Luo, Guihu, Zhuang, Lili, Zhang, Yanan, Li, Yehao, Sun, Erwei, He, Yi
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container_title Clinical rheumatology
container_volume 39
creator Yang, Fangyuan
Zhai, Zeqing
Luo, Xiaoqing
Luo, Guihu
Zhuang, Lili
Zhang, Yanan
Li, Yehao
Sun, Erwei
He, Yi
description Objective Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by autoantibody production and multi-system involvement, but the etiology is largely unclear. This study aimed to elucidate candidate genes and pathways involved in SLE. Methods Three original datasets GSE72509, GSE20864, and GSE39088 were downloaded from Gene Expression Omnibus (GEO) and the data were further integrated and analyzed. Subsequently, differentially expressed genes (DEGs) between SLE patients and healthy people were identified. And then we performed gene ontology (GO) function and pathway enrichment analyses of common DEGs, and constructed a protein-protein interaction (PPI) network with STRING database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to validate the expression levels of candidate genes in blood samples from SLE patients and healthy controls. Results In total, 321 common DEGs were identified in SLE patients compared with healthy controls, including 231 upregulated and 90 downregulated genes. GO function analysis revealed that 321 common DEGs were mainly enriched in innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, and I-kappaB kinase/NF-kappaB signaling. Additionally, pathway enrichment analysis indicated that DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. The expression levels of candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 were validated by RT-qPCR analysis. Conclusions The four hub genes including RPL26L1, FBXW11, FOXO1, and SMAD7 may play key roles in the pathogenesis and development of SLE. RIG-I-like receptor signaling pathway, antigen processing and presentation pathway, and p53 signaling pathway may be closely implicated in SLE pathogenesis. Collectively, these results may provide valuable novel markers or targets for the diagnosis and treatment of SLE. Key Points • Integrated bioinformatics analysis of three profile datasets based on SLE patients and healthy controls was performed and 321 common DEGs were identified. • The 321 common DEGs were mainly enriched in biological processes related to immune responses and inflammatory responses, including innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, I-kappaB
doi_str_mv 10.1007/s10067-019-04751-7
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This study aimed to elucidate candidate genes and pathways involved in SLE. Methods Three original datasets GSE72509, GSE20864, and GSE39088 were downloaded from Gene Expression Omnibus (GEO) and the data were further integrated and analyzed. Subsequently, differentially expressed genes (DEGs) between SLE patients and healthy people were identified. And then we performed gene ontology (GO) function and pathway enrichment analyses of common DEGs, and constructed a protein-protein interaction (PPI) network with STRING database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to validate the expression levels of candidate genes in blood samples from SLE patients and healthy controls. Results In total, 321 common DEGs were identified in SLE patients compared with healthy controls, including 231 upregulated and 90 downregulated genes. GO function analysis revealed that 321 common DEGs were mainly enriched in innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, and I-kappaB kinase/NF-kappaB signaling. Additionally, pathway enrichment analysis indicated that DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. The expression levels of candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 were validated by RT-qPCR analysis. Conclusions The four hub genes including RPL26L1, FBXW11, FOXO1, and SMAD7 may play key roles in the pathogenesis and development of SLE. RIG-I-like receptor signaling pathway, antigen processing and presentation pathway, and p53 signaling pathway may be closely implicated in SLE pathogenesis. Collectively, these results may provide valuable novel markers or targets for the diagnosis and treatment of SLE. Key Points • Integrated bioinformatics analysis of three profile datasets based on SLE patients and healthy controls was performed and 321 common DEGs were identified. • The 321 common DEGs were mainly enriched in biological processes related to immune responses and inflammatory responses, including innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, I-kappaB kinase/NF-kappaB signaling, whereas the three most significant cellular components were oxidoreductase complex, AIM2 inflammasome complex, and ubiquitin ligase complex. • KEGG pathway enrichment analysis indicated that common DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. • Candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 may be closely involved in the pathogenesis and development of SLE and may provide valuable novel markers or targets for the diagnosis and treatment of SLE.</description><identifier>ISSN: 0770-3198</identifier><identifier>EISSN: 1434-9949</identifier><identifier>DOI: 10.1007/s10067-019-04751-7</identifier><identifier>PMID: 31673979</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>Antigen presentation ; Antigen processing ; Antigens ; Apoptosis ; Autoantibodies ; Autoimmune diseases ; Bioinformatics ; Case-Control Studies ; Computational Biology ; Cytokines ; Diagnosis ; Etiology ; FOXO1 protein ; Gene expression ; Humans ; Immune response ; Immune system ; Inflammasomes ; Inflammation ; Information processing ; Innate immunity ; Kinases ; Lupus ; Lupus Erythematosus, Systemic - genetics ; Lupus Erythematosus, Systemic - metabolism ; Medical diagnosis ; Medicine ; Medicine &amp; Public Health ; NF-κB protein ; Original Article ; Oxidoreductase ; p53 Protein ; Pathogenesis ; Polymerase chain reaction ; Protein interaction ; Protein Interaction Maps ; Reverse transcription ; Rheumatology ; Signal transduction ; Signal Transduction - genetics ; Smad7 protein ; Systemic lupus erythematosus ; Transcriptome ; Ubiquitin-protein ligase ; α-Interferon</subject><ispartof>Clinical rheumatology, 2020-02, Vol.39 (2), p.425-434</ispartof><rights>International League of Associations for Rheumatology (ILAR) 2019</rights><rights>Clinical Rheumatology is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-7ef34f1b801db2266aa0675b4d5e033db4fe80baa52bed9ee6c57129a7dcec473</citedby><cites>FETCH-LOGICAL-c375t-7ef34f1b801db2266aa0675b4d5e033db4fe80baa52bed9ee6c57129a7dcec473</cites><orcidid>0000-0002-9367-6186</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31673979$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Fangyuan</creatorcontrib><creatorcontrib>Zhai, Zeqing</creatorcontrib><creatorcontrib>Luo, Xiaoqing</creatorcontrib><creatorcontrib>Luo, Guihu</creatorcontrib><creatorcontrib>Zhuang, Lili</creatorcontrib><creatorcontrib>Zhang, Yanan</creatorcontrib><creatorcontrib>Li, Yehao</creatorcontrib><creatorcontrib>Sun, Erwei</creatorcontrib><creatorcontrib>He, Yi</creatorcontrib><title>Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus</title><title>Clinical rheumatology</title><addtitle>Clin Rheumatol</addtitle><addtitle>Clin Rheumatol</addtitle><description>Objective Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by autoantibody production and multi-system involvement, but the etiology is largely unclear. This study aimed to elucidate candidate genes and pathways involved in SLE. Methods Three original datasets GSE72509, GSE20864, and GSE39088 were downloaded from Gene Expression Omnibus (GEO) and the data were further integrated and analyzed. Subsequently, differentially expressed genes (DEGs) between SLE patients and healthy people were identified. And then we performed gene ontology (GO) function and pathway enrichment analyses of common DEGs, and constructed a protein-protein interaction (PPI) network with STRING database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to validate the expression levels of candidate genes in blood samples from SLE patients and healthy controls. Results In total, 321 common DEGs were identified in SLE patients compared with healthy controls, including 231 upregulated and 90 downregulated genes. GO function analysis revealed that 321 common DEGs were mainly enriched in innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, and I-kappaB kinase/NF-kappaB signaling. Additionally, pathway enrichment analysis indicated that DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. The expression levels of candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 were validated by RT-qPCR analysis. Conclusions The four hub genes including RPL26L1, FBXW11, FOXO1, and SMAD7 may play key roles in the pathogenesis and development of SLE. RIG-I-like receptor signaling pathway, antigen processing and presentation pathway, and p53 signaling pathway may be closely implicated in SLE pathogenesis. Collectively, these results may provide valuable novel markers or targets for the diagnosis and treatment of SLE. Key Points • Integrated bioinformatics analysis of three profile datasets based on SLE patients and healthy controls was performed and 321 common DEGs were identified. • The 321 common DEGs were mainly enriched in biological processes related to immune responses and inflammatory responses, including innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, I-kappaB kinase/NF-kappaB signaling, whereas the three most significant cellular components were oxidoreductase complex, AIM2 inflammasome complex, and ubiquitin ligase complex. • KEGG pathway enrichment analysis indicated that common DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. • Candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 may be closely involved in the pathogenesis and development of SLE and may provide valuable novel markers or targets for the diagnosis and treatment of SLE.</description><subject>Antigen presentation</subject><subject>Antigen processing</subject><subject>Antigens</subject><subject>Apoptosis</subject><subject>Autoantibodies</subject><subject>Autoimmune diseases</subject><subject>Bioinformatics</subject><subject>Case-Control Studies</subject><subject>Computational Biology</subject><subject>Cytokines</subject><subject>Diagnosis</subject><subject>Etiology</subject><subject>FOXO1 protein</subject><subject>Gene expression</subject><subject>Humans</subject><subject>Immune response</subject><subject>Immune system</subject><subject>Inflammasomes</subject><subject>Inflammation</subject><subject>Information processing</subject><subject>Innate immunity</subject><subject>Kinases</subject><subject>Lupus</subject><subject>Lupus Erythematosus, Systemic - genetics</subject><subject>Lupus Erythematosus, Systemic - metabolism</subject><subject>Medical diagnosis</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>NF-κB protein</subject><subject>Original Article</subject><subject>Oxidoreductase</subject><subject>p53 Protein</subject><subject>Pathogenesis</subject><subject>Polymerase chain reaction</subject><subject>Protein interaction</subject><subject>Protein Interaction Maps</subject><subject>Reverse transcription</subject><subject>Rheumatology</subject><subject>Signal transduction</subject><subject>Signal Transduction - genetics</subject><subject>Smad7 protein</subject><subject>Systemic lupus erythematosus</subject><subject>Transcriptome</subject><subject>Ubiquitin-protein ligase</subject><subject>α-Interferon</subject><issn>0770-3198</issn><issn>1434-9949</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kU2PFCEQhonRuOPqH_BgSLx4aeWrm-aoG7-STbzomdBQvcM6DSNFZ9P_XsZZNfHghcqbengL6iXkOWevOWP6DbZz0B3jpmNK97zTD8iOK6k6Y5R5SHZMa9ZJbsYL8gTxljEmRsMfkwvJBy2NNjuS3sUc05zL4mr0SGOAVOMcfZM50TzT77BR71KIwVWgN5AAaZP06Or-zm1NIGYfWzPQu1j3FDessERPD-txRQplq3to9hlXfEoeze6A8Oy-XpJvH95_vfrUXX_5-Pnq7XXnpe5rp2GWaubTyHiYhBgG59pP-0mFHpiUYVIzjGxyrhcTBAMw-F5zYZwOHrzS8pK8OvseS_6xAla7RPRwOLgEeUUrJOdDP8rhhL78B73Na0ntdY1Sph_VKESjxJnyJSMWmO2xxMWVzXJmT2nYcxq2pWF_pWFP1i_urddpgfDnyu_1N0CeAWytdAPl7-z_2P4EVYOX_g</recordid><startdate>20200201</startdate><enddate>20200201</enddate><creator>Yang, Fangyuan</creator><creator>Zhai, Zeqing</creator><creator>Luo, Xiaoqing</creator><creator>Luo, Guihu</creator><creator>Zhuang, Lili</creator><creator>Zhang, Yanan</creator><creator>Li, Yehao</creator><creator>Sun, Erwei</creator><creator>He, Yi</creator><general>Springer London</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9367-6186</orcidid></search><sort><creationdate>20200201</creationdate><title>Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus</title><author>Yang, Fangyuan ; Zhai, Zeqing ; Luo, Xiaoqing ; Luo, Guihu ; Zhuang, Lili ; Zhang, Yanan ; Li, Yehao ; Sun, Erwei ; He, Yi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-7ef34f1b801db2266aa0675b4d5e033db4fe80baa52bed9ee6c57129a7dcec473</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Antigen presentation</topic><topic>Antigen processing</topic><topic>Antigens</topic><topic>Apoptosis</topic><topic>Autoantibodies</topic><topic>Autoimmune diseases</topic><topic>Bioinformatics</topic><topic>Case-Control Studies</topic><topic>Computational Biology</topic><topic>Cytokines</topic><topic>Diagnosis</topic><topic>Etiology</topic><topic>FOXO1 protein</topic><topic>Gene expression</topic><topic>Humans</topic><topic>Immune response</topic><topic>Immune system</topic><topic>Inflammasomes</topic><topic>Inflammation</topic><topic>Information processing</topic><topic>Innate immunity</topic><topic>Kinases</topic><topic>Lupus</topic><topic>Lupus Erythematosus, Systemic - genetics</topic><topic>Lupus Erythematosus, Systemic - metabolism</topic><topic>Medical diagnosis</topic><topic>Medicine</topic><topic>Medicine &amp; 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This study aimed to elucidate candidate genes and pathways involved in SLE. Methods Three original datasets GSE72509, GSE20864, and GSE39088 were downloaded from Gene Expression Omnibus (GEO) and the data were further integrated and analyzed. Subsequently, differentially expressed genes (DEGs) between SLE patients and healthy people were identified. And then we performed gene ontology (GO) function and pathway enrichment analyses of common DEGs, and constructed a protein-protein interaction (PPI) network with STRING database. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to validate the expression levels of candidate genes in blood samples from SLE patients and healthy controls. Results In total, 321 common DEGs were identified in SLE patients compared with healthy controls, including 231 upregulated and 90 downregulated genes. GO function analysis revealed that 321 common DEGs were mainly enriched in innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, and I-kappaB kinase/NF-kappaB signaling. Additionally, pathway enrichment analysis indicated that DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. The expression levels of candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 were validated by RT-qPCR analysis. Conclusions The four hub genes including RPL26L1, FBXW11, FOXO1, and SMAD7 may play key roles in the pathogenesis and development of SLE. RIG-I-like receptor signaling pathway, antigen processing and presentation pathway, and p53 signaling pathway may be closely implicated in SLE pathogenesis. Collectively, these results may provide valuable novel markers or targets for the diagnosis and treatment of SLE. Key Points • Integrated bioinformatics analysis of three profile datasets based on SLE patients and healthy controls was performed and 321 common DEGs were identified. • The 321 common DEGs were mainly enriched in biological processes related to immune responses and inflammatory responses, including innate immune response, defense response, cytokine-mediated signaling pathway, response to interferon-alpha, I-kappaB kinase/NF-kappaB signaling, whereas the three most significant cellular components were oxidoreductase complex, AIM2 inflammasome complex, and ubiquitin ligase complex. • KEGG pathway enrichment analysis indicated that common DEGs were mainly enriched in several signaling pathways associated with immune system and apoptosis, including RIG-I-like receptor signaling pathway, antigen processing and presentation, and p53 signaling pathway. • Candidate genes RPL26L1, FBXW11, FOXO1, and SMAD7 may be closely involved in the pathogenesis and development of SLE and may provide valuable novel markers or targets for the diagnosis and treatment of SLE.</abstract><cop>London</cop><pub>Springer London</pub><pmid>31673979</pmid><doi>10.1007/s10067-019-04751-7</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-9367-6186</orcidid></addata></record>
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subjects Antigen presentation
Antigen processing
Antigens
Apoptosis
Autoantibodies
Autoimmune diseases
Bioinformatics
Case-Control Studies
Computational Biology
Cytokines
Diagnosis
Etiology
FOXO1 protein
Gene expression
Humans
Immune response
Immune system
Inflammasomes
Inflammation
Information processing
Innate immunity
Kinases
Lupus
Lupus Erythematosus, Systemic - genetics
Lupus Erythematosus, Systemic - metabolism
Medical diagnosis
Medicine
Medicine & Public Health
NF-κB protein
Original Article
Oxidoreductase
p53 Protein
Pathogenesis
Polymerase chain reaction
Protein interaction
Protein Interaction Maps
Reverse transcription
Rheumatology
Signal transduction
Signal Transduction - genetics
Smad7 protein
Systemic lupus erythematosus
Transcriptome
Ubiquitin-protein ligase
α-Interferon
title Bioinformatics identification of key candidate genes and pathways associated with systemic lupus erythematosus
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