Title:CD163 in Macrophages: A Potential Biomarker for Predicting the Progression
of Diabetic Nephropathy based on Bioinformatics Analysis
Volume: 23
Issue: 3
Author(s): Xiaoxia Wang, Rui Li, Ting Liu, Yanyan Jia, Xingxing Gao and Xiaodong Zhang*
Affiliation:
- Department of Nephrology, The First Hospital of Shanxi
Medicinal University, Taiyuan, China
Keywords:
Weight gene co-expression network analysis, diabetic nephropathy, key genes, CD163, biomarkers, immune cell.
Abstract:
Objective: This study aimed to identify the potential biomarkers in DN.
Methods: DN datasets GSE30528 and GSE47183 were downloaded from the Gene Expression Omnibus
database. Immune cell infiltration was analyzed using CIBERSORT. Weighted gene co-expression
network analysis (WGCNA) was performed to obtain the module genes specific to DN.
The relevant genes were identified intersecting the module genes and differentially expressed genes
(DEGs). The core genes were identified using the MCC algorithm in Cytoscape software. ROC and
Pearson analyses alongside gene set enrichment analysis (GSEA) were performed to identify the
key gene for the core genes. Finally, we performed the Spearman to analyze the correlation between
key gene and glomerular filtration rate (GFR), serum creatinine (Scr), age and sex in DN.
Results: CIBERSORT analysis revealed the immune cell infiltration in the DN renal tissue and
Venn identified 12 relevant genes. Among these, 5 core genes, namely TYROBP, C1QA, C1QB,
CD163 and MS4A6A, were identified. Pearson analyses revealed that immune cell infiltration and
expression of core genes are related. The key genes with high diagnostic values for DN were identified
to be CD163 via ROC analyses. After Spearman correlation analysis, the expression level of
CD163 was correlated with GFR (r =0.27), a difference that nearly reached statistical significance
(P =0.058). However, there was no correlation between the level of CD163 and age (r =-0.24, P
=0.09), sex (r =-0.11, P=0.32) and Scr (r=0.15, P=0.4).
Conclusion: We found that CD163 in macrophages may be a potential biomarker in predicting and
treating DN.