Identification of renal ischemia reperfusion injury-characteristic genes, pathways and immunological micro-environment features through bioinformatics approaches

Xinghua Lv; Qian Fan; Xuanjie Li; Peng Li; Zhanhai Wan; Xuena Han; Hao Wang; Xiaoxia Wang; Lin Wu; Bin Huo; Li Yang; Gen Chen; Yan Zhang

doi:10.18632/aging.205471

Identification of renal ischemia reperfusion injury-characteristic genes, pathways and immunological micro-environment features through bioinformatics approaches

Aging (Albany NY). 2024 Feb 6;16(3):2123-2140. doi: 10.18632/aging.205471. Epub 2024 Feb 6.

Authors

Xinghua Lv¹, Qian Fan², Xuanjie Li¹, Peng Li¹, Zhanhai Wan¹, Xuena Han^{1

3}, Hao Wang^{1

3}, Xiaoxia Wang¹, Lin Wu¹, Bin Huo¹, Li Yang⁴, Gen Chen⁵, Yan Zhang^{1

3}

Affiliations

¹ Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China.
² Tianjin Eye Hospital, Tianjin Key Lab of Ophthalmology and Visual Science, Tianjin Eye Institute, Nankai University Affiliated Eye Hospital, Nankai University Eye Institute, Nankai University, Clinical College of Ophthalmology, Tianjin Medical University, Tianjin, China.
³ The First Clinical Medical College of Lanzhou University, Lanzhou, Gansu Province, China.
⁴ Lanzhou First People's Hospital, Lanzhou, Gansu, China.
⁵ Department of Microbiology, School of Basic Medical Sciences, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China.

Abstract

Background: Biomarkers and pathways associated with renal ischemia reperfusion injury (IRI) had not been well unveiled. This study was intended to investigate and summarize the regulatory networks for related hub genes. Besides, the immunological micro-environment features were evaluated and the correlations between immune cells and hub genes were also explored.

Methods: GSE98622 containing mouse samples with multiple IRI stages and controls was collected from the GEO database. Differentially expressed genes (DEGs) were recognized by the R package limma, and the GO and KEGG analyses were conducted by DAVID. Gene set variation analysis (GSVA) and weighted gene coexpression network analysis (WGCNA) had been implemented to uncover changed pathways and gene modules related to IRI. Besides the known pathways such as apoptosis pathway, metabolic pathway, and cell cycle pathways, some novel pathways were also discovered to be critical in IRI. A series of novel genes associated with IRI was also dug out. An IRI mouse model was constructed to validate the results.

Results: The well-known IRI marker genes (Kim1 and Lcn2) and novel hub genes (Hbegf, Serpine2, Apbb1ip, Trip13, Atf3, and Ncaph) had been proved by the quantitative real-time polymerase chain reaction (qRT-PCR). Thereafter, miRNAs targeted to the dysregulated genes were predicted and the miRNA-target network was constructed. Furthermore, the immune infiltration for these samples was predicted and the results showed that macrophages infiltrated to the injured kidney to affect the tissue repair or fibrosis. Hub genes were significantly positively or negatively correlated with the macrophage abundance indicating they played a crucial role in macrophage infiltration.

Conclusions: Consequently, the pathways, hub genes, miRNAs, and the immune microenvironment may explain the mechanism of IRI and might be the potential targets for IRI treatments.

Keywords: MiRNAs; gene set variation analysis; ischemia reperfusion injury; macrophage; weighted gene coexpression network analysis.

MeSH terms

Animals
Cell Cycle
Computational Biology
Kidney
Mice
MicroRNAs* / genetics
Serpin E2*

Substances

Serpin E2
MicroRNAs