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Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus

BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disease with strong heterogeneity, leading to variable clinical symptoms, which makes diagnosis and activity evaluation difficult. METHODS: The original dataset of GSE88884 was analyzed to screen differentially expressed genes (DEGs) of...

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Autores principales: Chen, Wu, Li, Zhi-Yu, Huang, Lin, Zhou, Dong-Hai, Luo, Wen-Qing, Zhang, Xu-Feng, Li, Lin, Wen, Cheng-Ping, Wang, Qiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842429/
https://www.ncbi.nlm.nih.gov/pubmed/36655136
http://dx.doi.org/10.1155/2023/8564650
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author Chen, Wu
Li, Zhi-Yu
Huang, Lin
Zhou, Dong-Hai
Luo, Wen-Qing
Zhang, Xu-Feng
Li, Lin
Wen, Cheng-Ping
Wang, Qiao
author_facet Chen, Wu
Li, Zhi-Yu
Huang, Lin
Zhou, Dong-Hai
Luo, Wen-Qing
Zhang, Xu-Feng
Li, Lin
Wen, Cheng-Ping
Wang, Qiao
author_sort Chen, Wu
collection PubMed
description BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disease with strong heterogeneity, leading to variable clinical symptoms, which makes diagnosis and activity evaluation difficult. METHODS: The original dataset of GSE88884 was analyzed to screen differentially expressed genes (DEGs) of SLE and the correlation between DEGs and clinical parameters (SLEDAI, anti-dsDNA, C3, and C4). The result was validated by microarray GSE121239 and SLE patients with RT-qPCR. Next, receiver operator characteristic (ROC) analysis, correlation analysis, and ordinal logistic regression were applied, respectively, to evaluate the capability of diagnosis and prediction of the candidate biomarker. Subsequently, the biological functions of the candidate biomarker were investigated through KEGG and GO enrichment, protein–protein interaction network, and the correlation matrix. RESULTS: A total of 283 DEGs were screened, and seven of them were overlapped with SLE-related genes. DDX60 was identified as the candidate biomarker. Analyses of GSE88884, GSE121239, and SLE patients with RT-qPCR indicated that DDX60 expression level is significantly higher in patients with high disease activity. ROC analysis and the area under the ROC curve (AUC = 0.8818) suggested that DDX60 has good diagnostic performance. DDX60 expression level was positively correlated with SLEDAI scores (r = 0.24). For every 1-unit increase in DDX60 expression value, the odds of a higher stage of activity of SLE disease are multiplied by 1.47. The function of DDX60 mainly focuses on IFN-I-induced antiviral activities, RIG-I signaling, and innate immune. Moreover, DDX60 plays a synergistic role with DDX58, IFIH1, OASL, IFIT1, and other related genes in the SLE pathogenesis. Conclusions. DDX60 is differently expressed in SLE, and it is significantly related to both serological indicators and the disease activity of SLE. We suggested that DDX60 might be a potential biomarker for SLE diagnosis and management.
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spelling pubmed-98424292023-01-17 Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus Chen, Wu Li, Zhi-Yu Huang, Lin Zhou, Dong-Hai Luo, Wen-Qing Zhang, Xu-Feng Li, Lin Wen, Cheng-Ping Wang, Qiao Dis Markers Research Article BACKGROUND: Systemic lupus erythematosus (SLE) is an autoimmune disease with strong heterogeneity, leading to variable clinical symptoms, which makes diagnosis and activity evaluation difficult. METHODS: The original dataset of GSE88884 was analyzed to screen differentially expressed genes (DEGs) of SLE and the correlation between DEGs and clinical parameters (SLEDAI, anti-dsDNA, C3, and C4). The result was validated by microarray GSE121239 and SLE patients with RT-qPCR. Next, receiver operator characteristic (ROC) analysis, correlation analysis, and ordinal logistic regression were applied, respectively, to evaluate the capability of diagnosis and prediction of the candidate biomarker. Subsequently, the biological functions of the candidate biomarker were investigated through KEGG and GO enrichment, protein–protein interaction network, and the correlation matrix. RESULTS: A total of 283 DEGs were screened, and seven of them were overlapped with SLE-related genes. DDX60 was identified as the candidate biomarker. Analyses of GSE88884, GSE121239, and SLE patients with RT-qPCR indicated that DDX60 expression level is significantly higher in patients with high disease activity. ROC analysis and the area under the ROC curve (AUC = 0.8818) suggested that DDX60 has good diagnostic performance. DDX60 expression level was positively correlated with SLEDAI scores (r = 0.24). For every 1-unit increase in DDX60 expression value, the odds of a higher stage of activity of SLE disease are multiplied by 1.47. The function of DDX60 mainly focuses on IFN-I-induced antiviral activities, RIG-I signaling, and innate immune. Moreover, DDX60 plays a synergistic role with DDX58, IFIH1, OASL, IFIT1, and other related genes in the SLE pathogenesis. Conclusions. DDX60 is differently expressed in SLE, and it is significantly related to both serological indicators and the disease activity of SLE. We suggested that DDX60 might be a potential biomarker for SLE diagnosis and management. Hindawi 2023-01-09 /pmc/articles/PMC9842429/ /pubmed/36655136 http://dx.doi.org/10.1155/2023/8564650 Text en Copyright © 2023 Wu Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Wu
Li, Zhi-Yu
Huang, Lin
Zhou, Dong-Hai
Luo, Wen-Qing
Zhang, Xu-Feng
Li, Lin
Wen, Cheng-Ping
Wang, Qiao
Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus
title Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus
title_full Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus
title_fullStr Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus
title_full_unstemmed Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus
title_short Integrative Bioinformatics Analysis Identifies DDX60 as a Potential Biomarker for Systemic Lupus Erythematosus
title_sort integrative bioinformatics analysis identifies ddx60 as a potential biomarker for systemic lupus erythematosus
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9842429/
https://www.ncbi.nlm.nih.gov/pubmed/36655136
http://dx.doi.org/10.1155/2023/8564650
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