Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis
Abstract Background Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-01-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-020-02698-x |
| _version_ | 1818961533434068992 |
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| author | Xingwang Zhao Longlong Zhang Juan Wang Min Zhang Zhiqiang Song Bing Ni Yi You |
| author_facet | Xingwang Zhao Longlong Zhang Juan Wang Min Zhang Zhiqiang Song Bing Ni Yi You |
| author_sort | Xingwang Zhao |
| collection | DOAJ |
| description | Abstract Background Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved. Methods The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis. Results In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE. Conclusion IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE. |
| first_indexed | 2024-12-20T12:14:56Z |
| format | Article |
| id | doaj.art-66beaebc6af3496f882c6e45d2aa76c4 |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-12-20T12:14:56Z |
| publishDate | 2021-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-66beaebc6af3496f882c6e45d2aa76c42022-12-21T19:41:09ZengBMCJournal of Translational Medicine1479-58762021-01-0119111710.1186/s12967-020-02698-xIdentification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysisXingwang Zhao0Longlong Zhang1Juan Wang2Min Zhang3Zhiqiang Song4Bing Ni5Yi You6Department of Dermatology, Southwest Hospital, Army Medical University, (Third Military Medical University)State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of SciencesDepartment of Dermatology, Southwest Hospital, Army Medical University, (Third Military Medical University)Department of Dermatology, Southwest Hospital, Army Medical University, (Third Military Medical University)Department of Dermatology, Southwest Hospital, Army Medical University, (Third Military Medical University)Department of Pathophysiology, College of High Altitude Military Medicine, Army Medical University, (Third Military Medical University)Department of Dermatology, Southwest Hospital, Army Medical University, (Third Military Medical University)Abstract Background Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved. Methods The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis. Results In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE. Conclusion IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE.https://doi.org/10.1186/s12967-020-02698-xSystemic lupus erythematosusImmune infiltrationIntegrated bioinformaticsIFI27Biomarkers |
| spellingShingle | Xingwang Zhao Longlong Zhang Juan Wang Min Zhang Zhiqiang Song Bing Ni Yi You Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis Journal of Translational Medicine Systemic lupus erythematosus Immune infiltration Integrated bioinformatics IFI27 Biomarkers |
| title | Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis |
| title_full | Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis |
| title_fullStr | Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis |
| title_full_unstemmed | Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis |
| title_short | Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis |
| title_sort | identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis |
| topic | Systemic lupus erythematosus Immune infiltration Integrated bioinformatics IFI27 Biomarkers |
| url | https://doi.org/10.1186/s12967-020-02698-x |
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