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综合生物信息学分析鉴定 DDX60 为系统性红斑狼疮的潜在生物标志物。

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

机构信息

Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.

The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.

出版信息

Dis Markers. 2023 Jan 9;2023:8564650. doi: 10.1155/2023/8564650. eCollection 2023.

DOI:10.1155/2023/8564650
PMID:36655136
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9842429/
Abstract

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 ( = 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. 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.

摘要

背景

系统性红斑狼疮(SLE)是一种异质性很强的自身免疫性疾病,导致临床表现多样,给诊断和病情活动评估带来困难。

方法

分析 GSE88884 原始数据集,筛选 SLE 的差异表达基因(DEGs),并分析 DEGs 与临床参数(SLEDAI、抗 dsDNA、C3 和 C4)的相关性。结果经微阵列 GSE121239 和 SLE 患者的 RT-qPCR 验证。然后,分别采用受试者工作特征(ROC)分析、相关性分析和有序逻辑回归评估候选生物标志物的诊断和预测能力。接着,通过 KEGG 和 GO 富集、蛋白质-蛋白质相互作用网络和相关矩阵分析候选生物标志物的生物学功能。

结果

筛选出 283 个差异表达基因,其中 7 个与 SLE 相关基因重叠。DDX60 被确定为候选生物标志物。GSE88884、GSE121239 和 SLE 患者的 RT-qPCR 分析表明,高疾病活动患者的 DDX60 表达水平显著升高。ROC 分析和 ROC 曲线下面积(AUC=0.8818)表明 DDX60 具有良好的诊断性能。DDX60 表达水平与 SLEDAI 评分呈正相关( = 0.24)。DDX60 表达值每增加 1 个单位,SLE 疾病活动度更高的几率增加 1.47 倍。DDX60 的功能主要集中在 IFN-I 诱导的抗病毒活性、RIG-I 信号和固有免疫。此外,DDX60 在 SLE 发病机制中与 DDX58、IFIH1、OASL、IFIT1 和其他相关基因发挥协同作用。DDX60 在 SLE 中表达差异显著,与血清学指标和 SLE 疾病活动度均显著相关。我们认为 DDX60 可能是 SLE 诊断和治疗的潜在生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/e72d0f1de785/DM2023-8564650.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/5cdadc577cb3/DM2023-8564650.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/7be84ea184ea/DM2023-8564650.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/d551168b1da5/DM2023-8564650.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/18689973aa07/DM2023-8564650.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/28faed8fbf85/DM2023-8564650.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/f4a8b68dab60/DM2023-8564650.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/e72d0f1de785/DM2023-8564650.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/5cdadc577cb3/DM2023-8564650.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/7be84ea184ea/DM2023-8564650.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/d551168b1da5/DM2023-8564650.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/18689973aa07/DM2023-8564650.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/28faed8fbf85/DM2023-8564650.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/f4a8b68dab60/DM2023-8564650.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8090/9842429/e72d0f1de785/DM2023-8564650.007.jpg

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