Research Paper Volume 16, Issue 3 pp 2123—2140

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

Xinghua Lv1, *, , Qian Fan3, *, , Xuanjie Li1, *, , Peng Li1, , Zhanhai Wan1, , Xuena Han1,2, , Hao Wang1,2, , Xiaoxia Wang1, , Lin Wu1, , Bin Huo1, , Li Yang5, , Gen Chen4, , Yan Zhang1,2, ,

  • 1 Department of Anesthesiology, First Hospital of Lanzhou University, Lanzhou, Gansu, China
  • 2 The First Clinical Medical College of Lanzhou University, Lanzhou, Gansu Province, China
  • 3 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
  • 4 Department of Microbiology, School of Basic Medical Sciences, Guilin Medical University, Guilin, Guangxi Zhuang Autonomous Region, China
  • 5 Lanzhou First People's Hospital, Lanzhou, Gansu, China
* Co-first author

Received: September 22, 2023       Accepted: December 15, 2023       Published: February 6, 2024
How to Cite

Copyright: © 2024 Lv et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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.


IRI: ischemia reperfusion injury; DEGs: differentially expressed genes; GSVA: gene set variation analysis; WGCNA: weighted gene coexpression network analysis; qRT-PCR: quantitative real-time polymerase chain reaction; AKI: acute kidney injury; GEO: Gene Expression Omnibus; ATF3: activating transcription factor 3; HBEGF: heparin binding EGF-like growth factor; ERS: endoplasmic reticulum stress; TRIP13: thyroid receptor interacting protein 13.