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

Xue Zhou; Ning Wang; Yuefeng Zhang; Pei Yu

doi:10.3389/fphys.2022.840890

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

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

Authors

Xue Zhou^{1

2

3}, Ning Wang⁴, Yuefeng Zhang³, Pei Yu^{1

2}

Affiliations

¹ NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
² Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University, Tianjin, China.
³ Department of Nephrology, Tianjin Haihe Hospital, Tianjin, China.
⁴ Tianjin Third Central Hospital, Tianjin, China.

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 via 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.

Keywords: IgA nephropathy; bioinformatics analysis; biomarker; diagnosis; immune.