Bioinformatics analysis of pathways of renal infiltrating macrophages in different renal disease models

Yin Celeste Cheuk; Pingbao Zhang; Shihao Xu; Jiyan Wang; Tian Chen; Yongxin Mao; Yamei Jiang; Yongsheng Luo; Jingjing Guo; Weixi Wang; Ruiming Rong

doi:10.21037/tau-21-761

Bioinformatics analysis of pathways of renal infiltrating macrophages in different renal disease models

Transl Androl Urol. 2021 Dec;10(12):4333-4343. doi: 10.21037/tau-21-761.

Authors

Yin Celeste Cheuk^#^{1

2}, Pingbao Zhang^#^{1

2}, Shihao Xu^{1

2}, Jiyan Wang^{1

2}, Tian Chen^{1

2}, Yongxin Mao³, Yamei Jiang^{1

2}, Yongsheng Luo^{1

2}, Jingjing Guo^{1

2}, Weixi Wang⁴, Ruiming Rong^{1

2}

Affiliations

¹ Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China.
² Shanghai Key Laboratory of Organ Transplantation, Shanghai, China.
³ Department of Urology, Huadong Hospital, Fudan University, Shanghai, China.
⁴ Department of Geriatrics, Zhongshan Hospital, Fudan University, Shanghai, China.

^# Contributed equally.

Abstract

Background: Recent studies have suggested that macrophages are significantly involved in different renal diseases. However, the role of these renal infiltrating macrophages has not been entirely uncovered. To further clarify the underlying mechanism and identify therapeutic targets, a bioinformatic analysis based on transcriptome profiles was performed.

Methods: Three transcription profiling datasets, GSE27045, GSE51466 and GSE75808, were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were assessed by Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA).

Results: The classic signaling pathways and metabolic pathways of macrophages infiltrating the kidney in different pathophysiological processes, including lupus nephritis (LN), renal crystal formation and renal ischemia-reperfusion injury (IRI), were analysed. Furthermore, the common classical pathways significantly altered in the three renal disorders were the oxidative phosphorylation, VEGF signaling and JAK/STAT signaling pathways, while the renin-angiotensin system was uniquely altered in LN, the glycolysis and gluconeogenesis pathways were uniquely altered in models of renal crystal formation, and the calcium signaling pathway was specific to renal IRI.

Conclusions: Via bioinformatics analysis, this study revealed the transcriptional features of macrophages in murine LN, renal crystal formation and IRI models, which may serve as promising targets for mechanistic research and the clinical treatment of multiple renal diseases.

Keywords: Macrophage; bioinformatics analysis; renal disease; signaling pathways.