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CCL2、FOS和JUN的表达可能有助于区分IgA肾病患者与健康对照者。

Expression of CCL2, FOS, and JUN May Help to Distinguish Patients With IgA Nephropathy From Healthy Controls.

作者信息

Zhou Xue, Wang Ning, Zhang Yuefeng, Yu Pei

机构信息

NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.

Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University, Tianjin, China.

出版信息

Front Physiol. 2022 Apr 7;13:840890. doi: 10.3389/fphys.2022.840890. eCollection 2022.

Abstract

BACKGROUND

IgA nephropathy (IgAN), the most common type of glomerulonephritis worldwide, can only be diagnosed mainly by renal biopsy owing to lack of effective biomarkers. It is urgent to explore and identify the potential diagnostic biomarkers through assessing the gene expression profiles of patients with IgAN.

METHODS

Two datasets were obtained from the Gene Expression Omnibus (GEO) database, including GSE115857 (55 IgAN, 7 living healthy donors) and GSE35487 (25 IgAN, 6 living healthy donors), then underwent differentially expressed genes (DEGs) and function enrichment analyses utilizing R packages. The common gene list was screened out between DEGs and immune-associated genes by Venn diagram, then performed gene-gene interaction, protein-protein interaction (PPI) and function enrichment analyses. Top three immune-associated hub genes were selected by Maximal Clique Centrality (MCC) method, then the expression and diagnostic value of these hub genes were determined. Consensus clustering algorithm was applied to conduct the unsupervised cluster analysis of the immune-associated hub gene list in IgAN. Finally, the Nephroseq V5 tool was applied to identify the expression level of CCL2, FOS, JUN in kidney diseases, as well as the correlation between CCL2, FOS, JUN expression and renal function in the patients with IgAN.

RESULTS

A total of 129 DEGs were obtained through comparing IgAN with healthy controls the GSE115857 and GSE35487 datasets. Then, we screened out 24 immune-associated IgAN DEGs. CCL2, JUN, and FOS were identified as the top three hub genes, and they were all remarkably downregulated in IgAN. More importantly, CCL2, JUN, and FOS had a high accuracy [area under the curve (AUC) reached almost 1] in predicting IgAN, which could easily distinguish between IgAN patients and healthy individuals. Three distinct subgroups of IgAN were determined based on 24 immune-associated DEGs, with significant differences in the expression of CCL2, JUN, and FOS genes. Finally, CCL2, FOS, JUN were manifested a meaningful association with proteinuria, glomerular filtration rate (GFR), and serum creatinine level.

CONCLUSION

In summary, our study comprehensively uncovers that CCL2, JUN, and FOS may function as promising biomarkers for diagnosis of IgAN.

摘要

背景

IgA肾病(IgAN)是全球最常见的肾小球肾炎类型,由于缺乏有效的生物标志物,目前主要只能通过肾活检来诊断。因此,迫切需要通过评估IgAN患者的基因表达谱来探索和识别潜在的诊断生物标志物。

方法

从基因表达综合数据库(GEO)中获取了两个数据集,分别为GSE115857(55例IgAN患者,7例健康活体供者)和GSE35487(25例IgAN患者,6例健康活体供者),然后使用R包进行差异表达基因(DEG)和功能富集分析。通过维恩图在DEG和免疫相关基因之间筛选出共同基因列表,然后进行基因-基因相互作用、蛋白质-蛋白质相互作用(PPI)和功能富集分析。采用最大团中心性(MCC)方法选择前三个免疫相关的枢纽基因,然后确定这些枢纽基因的表达和诊断价值。应用共识聚类算法对IgAN中免疫相关枢纽基因列表进行无监督聚类分析。最后,使用Nephroseq V5工具确定CCL2、FOS、JUN在肾脏疾病中的表达水平,以及IgAN患者中CCL2、FOS、JUN表达与肾功能之间的相关性。

结果

通过比较GSE115857和GSE35487数据集中的IgAN患者与健康对照,共获得129个DEG。然后,我们筛选出24个与免疫相关的IgAN DEG。CCL2、JUN和FOS被确定为前三个枢纽基因,它们在IgAN中均显著下调。更重要的是,CCL2、JUN和FOS在预测IgAN方面具有较高的准确性[曲线下面积(AUC)几乎达到1],能够轻松区分IgAN患者和健康个体。基于24个与免疫相关的DEG确定了IgAN的三个不同亚组,CCL2, JUN和FOS基因的表达存在显著差异。最后,CCL2、FOS、JUN与蛋白尿、肾小球滤过率(GFR)和血清肌酐水平表现出有意义的关联。

结论

总之,我们的研究全面揭示了CCL2、JUN和FOS可能作为IgAN诊断的有前景的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c78/9021889/05b79c24d34b/fphys-13-840890-g001.jpg

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