AUTHOR=Deng Yi-Xuan , Liu Kun , Qiu Qun-Xiang , Tang Zhi-Yao , Que Rui-Man , Li Dian-Ke , Gu Xu-Rui , Zhou Guang-Liang , Wu Yi-Feng , Zhou Ling-Yun , Yin Wen-Jun , Zuo Xiao-Cong TITLE=Identification and validation of hub genes in drug induced acute kidney injury basing on integrated transcriptomic analysis JOURNAL=Frontiers in Immunology VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1126348 DOI=10.3389/fimmu.2023.1126348 ISSN=1664-3224 ABSTRACT=Background

Drug-induced acute kidney damage (DI-AKI) is a clinical phenomenon of rapid loss of kidney function over a brief period of time as a consequence of the using of medicines. The lack of a specialized treatment and the instability of traditional kidney injury markers to detect DI-AKI frequently result in the development of chronic kidney disease. Thus, it is crucial to continue screening for DI-AKI hub genes and specific biomarkers.

Methods

Differentially expressed genes (DEGs) of group iohexol, cisplatin, and vancomycin’s were analyzed using Limma package, and the intersection was calculated. DEGs were then put into String database to create a network of protein-protein interactions (PPI). Ten algorithms are used in the Cytohubba plugin to find the common hub genes. Three DI-AKI models’ hub gene expression was verified in vivo and in vitro using PCR and western blot. To investigate the hub gene’s potential as a biomarker, protein levels of mouse serum and urine were measured by ELISA kits. The UUO, IRI and aristolochic acid I-induced nephrotoxicity (AAN) datasets in the GEO database were utilized for external data verification by WGCNA and Limma package. Finally, the Elisa kit was used to identify DI-AKI patient samples.

Results

95 up-regulated common DEGs and 32 down-regulated common DEGs were obtained using Limma package. A PPI network with 84 nodes and 24 edges was built with confidence >0.4. Four hub genes were obtained by Algorithms of Cytohubba plugin, including TLR4, AOC3, IRF4 and TNFAIP6. Then, we discovered that the protein and mRNA levels of four hub genes were significantly changed in the DI-AKI model in vivo and in vitro. External data validation revealed that only the AAN model, which also belonged to DI-AKI model, had significant difference in these hub genes, whereas IRI and UUO did not. Finally, we found that plasma TLR4 levels were higher in patients with DI-AKI, especially in vancomycin-induced AKI.

Conclusion

The immune system and inflammation are key factors in DI-AKI. We discovered the immunological and inflammatory-related genes TLR4, AOC3, IRF4, and TNFAIP6, which may be promising specific biomarkers and essential hub genes for the prevention and identification of DI-AKI.