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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Alloimmunity and Transplantation

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1536800

This article is part of the Research Topic Renal Fibrosis and Renal Transplantation View all 3 articles

Identification of ALDH2 as a novel target for the treatment of acute kidney injury in kidney transplantation based on WGCNA and machine learning algorithms and exploration of its potential mechanism of action using animal experiments

Provisionally accepted
Jinpu Peng Jinpu Peng *Shili Wang Shili Wang *Xingyu Pan Xingyu Pan *Moudong Wu Moudong Wu *Xiong Zhan Xiong Zhan *Dan Wang Dan Wang *Guohua Zhu Guohua Zhu *Wei Wang Wei Wang *Hongyu Tang Hongyu Tang *Nini An Nini An *Jun Pei Jun Pei *
  • Guizhou Provincial People's Hospital, Guiyang, China

The final, formatted version of the article will be published soon.

    Background: Acute kidney injury (AKI) after kidney transplantation is one of the main causes of graft loss and poor patient prognosis, and it is important to explore new targets for treating AKI in kidney transplantation. Methods: Based on the kidney transplantation AKI-related dataset GSE30718, the most relevant modular genes for AKI among them were firstly screened using WGCNA and intersected with the DEGs, and the intersected genes were used as candidate genes for kidney transplantation AKI. Second, machine learning algorithms were utilized to identify the key genes among them, and the HPA database was used to explore the expression landscape. Next, we constructed a rat renal IRI model and explored the role of key genes in renal IRI. Finally, we combined ssGSEA enrichment analysis with animal experiments to further validate the potential mechanism of action of key genes. Results: In total, we identified 98 of the most relevant modular genes for AKI and 417 DEGs, which intersected to yield a total of 24 AKI candidate genes. Next, we intersected the key genes identified by three types of machine learning, namely, Random Forest, LASSO regression analysis and SVM, and obtained a total of 1 intersected gene as ALDH2, which we used as a key gene in kidney transplantation AKI. Using the HPA database, we found that ALDH2 has a high expression level in renal tissues and is mainly located in renal tubular epithelial cells. Next, we found in a rat renal IRI model that increasing the expression of ALDH2 alleviated the impairment of renal function and decreased the expression of NGAL, a marker of tubular injury, and BAX, an apoptotic protein, as well as reducing the expression of the inflammatory factors IL1β and IL6. Finally, using ssGSEA enrichment analysis and animal experiments, we further found that ALDH2 was able to inhibit the activation of the MAPK signaling pathway. Conclusion: ALDH2 may serve as a novel target for the treatment of kidney transplantation AKI, and increasing the expression level of ALDH2 has a protective effect on renal IRI, and this protective effect may be achieved by inhibiting the MAPK signaling pathway.

    Keywords: Kidney Transplantation, Acute Kidney Injury, renal ischemia-reperfusion injury, ALDH2, machine learning

    Received: 29 Nov 2024; Accepted: 13 Feb 2025.

    Copyright: © 2025 Peng, Wang, Pan, Wu, Zhan, Wang, Zhu, Wang, Tang, An and Pei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jinpu Peng, Guizhou Provincial People's Hospital, Guiyang, China
    Shili Wang, Guizhou Provincial People's Hospital, Guiyang, China
    Xingyu Pan, Guizhou Provincial People's Hospital, Guiyang, China
    Moudong Wu, Guizhou Provincial People's Hospital, Guiyang, China
    Xiong Zhan, Guizhou Provincial People's Hospital, Guiyang, China
    Dan Wang, Guizhou Provincial People's Hospital, Guiyang, China
    Guohua Zhu, Guizhou Provincial People's Hospital, Guiyang, China
    Wei Wang, Guizhou Provincial People's Hospital, Guiyang, China
    Hongyu Tang, Guizhou Provincial People's Hospital, Guiyang, China
    Nini An, Guizhou Provincial People's Hospital, Guiyang, China
    Jun Pei, Guizhou Provincial People's Hospital, Guiyang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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