Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis
Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees f...
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| Veröffentlicht in: | Immunogenetics (New York) 2021-12, Vol.73 (6), p.435-448 |
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| creator | Fang, Sheng Xu, Xin Zhong, Lin Wang, An-quan Gao, Wei-lu Lu, Ming Yin, Zong-Sheng |
| description | Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein–protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes:
Ccr1
,
Ccr2
,
Ccr5
,
Ccr7
,
Cxcl5
,
Cxcl6
,
Cxcl13
,
Ccl13
,
Adcy2
, and
Pnoc
. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis.
Adcy2
,
Cxcl13
, and
Ccr5
are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that
Adcy2
,
Cxcl13
, and
Ccr5
have the potential to be biomarkers for RA treatment. |
| doi_str_mv | 10.1007/s00251-021-01224-7 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2569381808</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2593747561</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-36ef90690b89587f48c0e8e46f1462c26ad0da30a980212df662e2dcf47194f83</originalsourceid><addsrcrecordid>eNp9kc9uFSEUxonR2NvqC7gwJG7coPwbGJbaqDVp4kbXhBkOvdQZqMAs7oP0feV6qyYuXBASzu_7zjl8CL1g9A2jVL-tlPKBEcr7YZxLoh-hHZOCE8YZe4x2lBpBtGbsDJ3XekspGwxXT9GZkFJrI9QO3b-POaaQy-panCuZXAWPa9v8AbeMo4fUYjjguK5bAtzRuLTS2ZywS_74sLi1i3M5kAKLa12-3yZ8AwkqdhVPMa-ufIdScW-D2x5wK-Da2p1xDrjsYTvqo8eutH2JLdZn6ElwS4XnD_cF-vbxw9fLK3L95dPny3fXZBZ6aEQoCIYqQ6fRDKMOcpwpjCBVYFLxmSvnqXeCOjP2T-I-KMWB-zlIzYwMo7hAr0--dyX_2KA2u8Y6w7K4BHmrlg_KiJGN9Ii--ge9zVtJfbpOGaGlHhTrFD9Rc8m1Fgj2rsS-_sEyao-h2VNots9jf4VmdRe9fLDephX8H8nvlDogTkDtpXQD5W_v_9j-BNnGpNY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2593747561</pqid></control><display><type>article</type><title>Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Fang, Sheng ; Xu, Xin ; Zhong, Lin ; Wang, An-quan ; Gao, Wei-lu ; Lu, Ming ; Yin, Zong-Sheng</creator><creatorcontrib>Fang, Sheng ; Xu, Xin ; Zhong, Lin ; Wang, An-quan ; Gao, Wei-lu ; Lu, Ming ; Yin, Zong-Sheng</creatorcontrib><description>Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein–protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes:
Ccr1
,
Ccr2
,
Ccr5
,
Ccr7
,
Cxcl5
,
Cxcl6
,
Cxcl13
,
Ccl13
,
Adcy2
, and
Pnoc
. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis.
Adcy2
,
Cxcl13
, and
Ccr5
are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that
Adcy2
,
Cxcl13
, and
Ccr5
have the potential to be biomarkers for RA treatment.</description><identifier>ISSN: 0093-7711</identifier><identifier>EISSN: 1432-1211</identifier><identifier>DOI: 10.1007/s00251-021-01224-7</identifier><identifier>PMID: 34477936</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Adenylyl Cyclases - genetics ; Adenylyl Cyclases - immunology ; Adenylyl Cyclases - metabolism ; Algorithms ; Allergology ; Arthritis ; Arthritis, Rheumatoid - genetics ; Arthritis, Rheumatoid - immunology ; Arthritis, Rheumatoid - metabolism ; Arthritis, Rheumatoid - therapy ; Autoimmune diseases ; Bioinformatics ; Biological activity ; Biomarkers ; Biomedical and Life Sciences ; Biomedicine ; CCR1 protein ; CCR2 protein ; CCR5 protein ; CCR7 protein ; Cell Biology ; Chemokine CXCL13 - genetics ; Chemokine CXCL13 - immunology ; Chemokine CXCL13 - metabolism ; Computational Biology ; CXCL13 protein ; Etiology ; Gene expression ; Gene Expression Regulation ; Gene Function ; Genes ; Genetic Predisposition to Disease ; Human Genetics ; Humans ; Immune system ; Immunology ; Infiltration ; Inflammation ; Knee ; Monocyte chemoattractant protein 1 ; Original Article ; Pathogenesis ; Protein Interaction Maps ; Proteins ; Receptors, CCR5 - genetics ; Receptors, CCR5 - immunology ; Receptors, CCR5 - metabolism ; Rheumatoid arthritis ; Signal Transduction ; Signaling ; Synovial Membrane - metabolism ; Transcriptome</subject><ispartof>Immunogenetics (New York), 2021-12, Vol.73 (6), p.435-448</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-36ef90690b89587f48c0e8e46f1462c26ad0da30a980212df662e2dcf47194f83</citedby><cites>FETCH-LOGICAL-c375t-36ef90690b89587f48c0e8e46f1462c26ad0da30a980212df662e2dcf47194f83</cites><orcidid>0000-0001-7632-5088</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00251-021-01224-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00251-021-01224-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51298</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34477936$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fang, Sheng</creatorcontrib><creatorcontrib>Xu, Xin</creatorcontrib><creatorcontrib>Zhong, Lin</creatorcontrib><creatorcontrib>Wang, An-quan</creatorcontrib><creatorcontrib>Gao, Wei-lu</creatorcontrib><creatorcontrib>Lu, Ming</creatorcontrib><creatorcontrib>Yin, Zong-Sheng</creatorcontrib><title>Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis</title><title>Immunogenetics (New York)</title><addtitle>Immunogenetics</addtitle><addtitle>Immunogenetics</addtitle><description>Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein–protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes:
Ccr1
,
Ccr2
,
Ccr5
,
Ccr7
,
Cxcl5
,
Cxcl6
,
Cxcl13
,
Ccl13
,
Adcy2
, and
Pnoc
. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis.
Adcy2
,
Cxcl13
, and
Ccr5
are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that
Adcy2
,
Cxcl13
, and
Ccr5
have the potential to be biomarkers for RA treatment.</description><subject>Adenylyl Cyclases - genetics</subject><subject>Adenylyl Cyclases - immunology</subject><subject>Adenylyl Cyclases - metabolism</subject><subject>Algorithms</subject><subject>Allergology</subject><subject>Arthritis</subject><subject>Arthritis, Rheumatoid - genetics</subject><subject>Arthritis, Rheumatoid - immunology</subject><subject>Arthritis, Rheumatoid - metabolism</subject><subject>Arthritis, Rheumatoid - therapy</subject><subject>Autoimmune diseases</subject><subject>Bioinformatics</subject><subject>Biological activity</subject><subject>Biomarkers</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>CCR1 protein</subject><subject>CCR2 protein</subject><subject>CCR5 protein</subject><subject>CCR7 protein</subject><subject>Cell Biology</subject><subject>Chemokine CXCL13 - genetics</subject><subject>Chemokine CXCL13 - immunology</subject><subject>Chemokine CXCL13 - metabolism</subject><subject>Computational Biology</subject><subject>CXCL13 protein</subject><subject>Etiology</subject><subject>Gene expression</subject><subject>Gene Expression Regulation</subject><subject>Gene Function</subject><subject>Genes</subject><subject>Genetic Predisposition to Disease</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Immune system</subject><subject>Immunology</subject><subject>Infiltration</subject><subject>Inflammation</subject><subject>Knee</subject><subject>Monocyte chemoattractant protein 1</subject><subject>Original Article</subject><subject>Pathogenesis</subject><subject>Protein Interaction Maps</subject><subject>Proteins</subject><subject>Receptors, CCR5 - genetics</subject><subject>Receptors, CCR5 - immunology</subject><subject>Receptors, CCR5 - metabolism</subject><subject>Rheumatoid arthritis</subject><subject>Signal Transduction</subject><subject>Signaling</subject><subject>Synovial Membrane - metabolism</subject><subject>Transcriptome</subject><issn>0093-7711</issn><issn>1432-1211</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kc9uFSEUxonR2NvqC7gwJG7coPwbGJbaqDVp4kbXhBkOvdQZqMAs7oP0feV6qyYuXBASzu_7zjl8CL1g9A2jVL-tlPKBEcr7YZxLoh-hHZOCE8YZe4x2lBpBtGbsDJ3XekspGwxXT9GZkFJrI9QO3b-POaaQy-panCuZXAWPa9v8AbeMo4fUYjjguK5bAtzRuLTS2ZywS_74sLi1i3M5kAKLa12-3yZ8AwkqdhVPMa-ufIdScW-D2x5wK-Da2p1xDrjsYTvqo8eutH2JLdZn6ElwS4XnD_cF-vbxw9fLK3L95dPny3fXZBZ6aEQoCIYqQ6fRDKMOcpwpjCBVYFLxmSvnqXeCOjP2T-I-KMWB-zlIzYwMo7hAr0--dyX_2KA2u8Y6w7K4BHmrlg_KiJGN9Ii--ge9zVtJfbpOGaGlHhTrFD9Rc8m1Fgj2rsS-_sEyao-h2VNots9jf4VmdRe9fLDephX8H8nvlDogTkDtpXQD5W_v_9j-BNnGpNY</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Fang, Sheng</creator><creator>Xu, Xin</creator><creator>Zhong, Lin</creator><creator>Wang, An-quan</creator><creator>Gao, Wei-lu</creator><creator>Lu, Ming</creator><creator>Yin, Zong-Sheng</creator><general>Springer Berlin Heidelberg</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>7QL</scope><scope>7T5</scope><scope>7T7</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-7632-5088</orcidid></search><sort><creationdate>20211201</creationdate><title>Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis</title><author>Fang, Sheng ; Xu, Xin ; Zhong, Lin ; Wang, An-quan ; Gao, Wei-lu ; Lu, Ming ; Yin, Zong-Sheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-36ef90690b89587f48c0e8e46f1462c26ad0da30a980212df662e2dcf47194f83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adenylyl Cyclases - genetics</topic><topic>Adenylyl Cyclases - immunology</topic><topic>Adenylyl Cyclases - metabolism</topic><topic>Algorithms</topic><topic>Allergology</topic><topic>Arthritis</topic><topic>Arthritis, Rheumatoid - genetics</topic><topic>Arthritis, Rheumatoid - immunology</topic><topic>Arthritis, Rheumatoid - metabolism</topic><topic>Arthritis, Rheumatoid - therapy</topic><topic>Autoimmune diseases</topic><topic>Bioinformatics</topic><topic>Biological activity</topic><topic>Biomarkers</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>CCR1 protein</topic><topic>CCR2 protein</topic><topic>CCR5 protein</topic><topic>CCR7 protein</topic><topic>Cell Biology</topic><topic>Chemokine CXCL13 - genetics</topic><topic>Chemokine CXCL13 - immunology</topic><topic>Chemokine CXCL13 - metabolism</topic><topic>Computational Biology</topic><topic>CXCL13 protein</topic><topic>Etiology</topic><topic>Gene expression</topic><topic>Gene Expression Regulation</topic><topic>Gene Function</topic><topic>Genes</topic><topic>Genetic Predisposition to Disease</topic><topic>Human Genetics</topic><topic>Humans</topic><topic>Immune system</topic><topic>Immunology</topic><topic>Infiltration</topic><topic>Inflammation</topic><topic>Knee</topic><topic>Monocyte chemoattractant protein 1</topic><topic>Original Article</topic><topic>Pathogenesis</topic><topic>Protein Interaction Maps</topic><topic>Proteins</topic><topic>Receptors, CCR5 - genetics</topic><topic>Receptors, CCR5 - immunology</topic><topic>Receptors, CCR5 - metabolism</topic><topic>Rheumatoid arthritis</topic><topic>Signal Transduction</topic><topic>Signaling</topic><topic>Synovial Membrane - metabolism</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fang, Sheng</creatorcontrib><creatorcontrib>Xu, Xin</creatorcontrib><creatorcontrib>Zhong, Lin</creatorcontrib><creatorcontrib>Wang, An-quan</creatorcontrib><creatorcontrib>Gao, Wei-lu</creatorcontrib><creatorcontrib>Lu, Ming</creatorcontrib><creatorcontrib>Yin, Zong-Sheng</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Immunology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Immunogenetics (New York)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fang, Sheng</au><au>Xu, Xin</au><au>Zhong, Lin</au><au>Wang, An-quan</au><au>Gao, Wei-lu</au><au>Lu, Ming</au><au>Yin, Zong-Sheng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis</atitle><jtitle>Immunogenetics (New York)</jtitle><stitle>Immunogenetics</stitle><addtitle>Immunogenetics</addtitle><date>2021-12-01</date><risdate>2021</risdate><volume>73</volume><issue>6</issue><spage>435</spage><epage>448</epage><pages>435-448</pages><issn>0093-7711</issn><eissn>1432-1211</eissn><abstract>Rheumatoid arthritis (RA) is a systemic autoimmune disease whose principal pathological change is aggressive chronic synovial inflammation; however, the specific etiology and pathogenesis have not been fully elucidated. We downloaded the synovial tissue gene expression profiles of four human knees from the Gene Expression Omnibus database, analyzed the differentially expressed genes in the normal and RA groups, and assessed their enrichment in functions and pathways using bioinformatics methods and the STRING online database to establish protein–protein interaction networks. Cytoscape software was used to obtain 10 hub genes; receiver operating characteristic (ROC) curves were calculated for each hub gene and differential expression analysis of the two groups of hub genes. The CIBERSORT algorithm was used to impute immune infiltration. We identified the signaling pathways that play important roles in RA and 10 hub genes:
Ccr1
,
Ccr2
,
Ccr5
,
Ccr7
,
Cxcl5
,
Cxcl6
,
Cxcl13
,
Ccl13
,
Adcy2
, and
Pnoc
. The diagnostic value of these 10 hub genes for RA was confirmed using ROC curves and expression analysis.
Adcy2
,
Cxcl13
, and
Ccr5
are strongly associated with RA development. The study also revealed that the differential infiltration profile of different inflammatory immune cells in the synovial tissue of RA is an extremely critical factor in RA progression. This study may contribute to the understanding of signaling pathways and biological processes associated with RA and the role of inflammatory immune infiltration in the pathogenesis of RA. In addition, this study shows that
Adcy2
,
Cxcl13
, and
Ccr5
have the potential to be biomarkers for RA treatment.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>34477936</pmid><doi>10.1007/s00251-021-01224-7</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-7632-5088</orcidid></addata></record> |
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| subjects | Adenylyl Cyclases - genetics Adenylyl Cyclases - immunology Adenylyl Cyclases - metabolism Algorithms Allergology Arthritis Arthritis, Rheumatoid - genetics Arthritis, Rheumatoid - immunology Arthritis, Rheumatoid - metabolism Arthritis, Rheumatoid - therapy Autoimmune diseases Bioinformatics Biological activity Biomarkers Biomedical and Life Sciences Biomedicine CCR1 protein CCR2 protein CCR5 protein CCR7 protein Cell Biology Chemokine CXCL13 - genetics Chemokine CXCL13 - immunology Chemokine CXCL13 - metabolism Computational Biology CXCL13 protein Etiology Gene expression Gene Expression Regulation Gene Function Genes Genetic Predisposition to Disease Human Genetics Humans Immune system Immunology Infiltration Inflammation Knee Monocyte chemoattractant protein 1 Original Article Pathogenesis Protein Interaction Maps Proteins Receptors, CCR5 - genetics Receptors, CCR5 - immunology Receptors, CCR5 - metabolism Rheumatoid arthritis Signal Transduction Signaling Synovial Membrane - metabolism Transcriptome |
| title | Bioinformatics-based study to identify immune infiltration and inflammatory-related hub genes as biomarkers for the treatment of rheumatoid arthritis |
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