Department of Rheumatology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Hainan, China.
Front Immunol. 2022 Jun 9;13:844025. doi: 10.3389/fimmu.2022.844025. eCollection 2022.
This study was conducted to identify the biomarkers and mechanisms associated with systemic lupus erythematosus(SLE) at a transcriptome level.
Microarray datasets were downloaded, and differentially expressed genes (DEGs) were identified. Enrichment and protein-protein interaction networks were analyzed, and hub genes were discovered. The levels of top 10 hub genes were validated by another dataset. The diagnostic accuracy of the hub genes was evaluated with the area under the curve of the receiver operating characteristic curve (ROC-AUC). The odds ratios (OR) and 95% confidence intervals (CI) of the relationship between clinical manifestations and hub genes were estimated with multivariable logistic regression. The relationships between the expression levels of the 10 identified hub genes and SLEDAI scores were subjected to linear correlation analysis. Changes in the expression levels of the hub genes during patient follow-up were examined through one-way repeated measures ANOVA.
A total of 136 DEGs were identified. Enrichment analysis indicated that DEGs were primarily enriched in type I interferon-associated pathways. The identified hub genes were verified by the GSE65391 dataset. The 10 hub genes had good diagnostic performances. Seven (except IFI6, OAS1 and IFIT3) of the 10 hub genes were positively associated with SLEDAI. The combination models of IFIT3, ISG15, MX2, and IFIH1 were effective in diagnosing mucosal ulcers among patients with SLE. The expression levels of IRF7, IFI35, IFIT3, and ISG15 decreased compared with the baseline expression (not significantly).
In this work, the clinical values of the identified hub genes in SLE were demonstrated.
本研究旨在从转录组水平鉴定与系统性红斑狼疮（SLE）相关的生物标志物和机制。
下载微阵列数据集，鉴定差异表达基因（DEGs）。进行富集和蛋白质-蛋白质相互作用网络分析，并发现枢纽基因。通过另一个数据集验证前 10 个枢纽基因的水平。用受试者工作特征曲线（ROC-AUC）下的面积评估枢纽基因的诊断准确性。用多变量逻辑回归估计临床表现与枢纽基因之间关系的优势比（OR）和 95%置信区间（CI）。通过线性相关分析研究 10 个鉴定的枢纽基因的表达水平与 SLEDAI 评分之间的关系。通过单向重复测量方差分析检查枢纽基因表达水平在患者随访期间的变化。
共鉴定出 136 个 DEGs。富集分析表明，DEGs 主要富集在 I 型干扰素相关途径中。通过 GSE65391 数据集验证了鉴定的枢纽基因。这 10 个枢纽基因具有良好的诊断性能。这 10 个枢纽基因中的 7 个（IFI6、OAS1 和 IFIT3 除外）与 SLEDAI 呈正相关。IFIT3、ISG15、MX2 和 IFIH1 的组合模型在诊断 SLE 患者的粘膜溃疡方面是有效的。IRF7、IFI35、IFIT3 和 ISG15 的表达水平与基线表达相比下降（不显著）。
本研究证明了所鉴定的枢纽基因在 SLE 中的临床价值。
