The mRNA landscape profiling reveals potential biomarkers associated with acute kidney injury AKI after kidney transplantation.

BACKGROUND

This study aims to identify potential biomarkers associated with acute kidney injury (AKI) post kidney transplantation.

MATERIAL AND METHODS

Two mRNA expression profiles from Gene Expression Omnibus repertory were downloaded, including 20 delayed graft function (DGF) and 68 immediate graft function (IGF) samples. Differentially expressed genes (DEGs) were identified between DGF and IGF group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis of DEGs were performed. Then, a protein-protein interaction analysis was performed to extract hub genes. The key genes were searched by literature retrieval and cross-validated based on the training dataset. An external dataset was used to validate the expression levels of key genes. Receiver operating characteristic curve analyses were performed to evaluate diagnostic performance of key genes for AKI.

RESULTS

A total of 330 DEGs were identified between DGF and IGF samples, including 179 up-regulated and 151 down-regulated genes. Of these, , and were transcription factor genes. Moreover, , , , , , and served as hub genes in PPI network. EBF3 was significantly up-regulated in validation GSE139061 dataset, which was consistently with our initial gene differential expression analysis. Finally, we found that had a great diagnostic value for AKI (AUC = 0.740).

CONCLUSION

may be associated with the development of AKI following kidney transplantation. Furthermore, had a good diagnostic value for AKI. These findings provide deeper insights into the diagnosis and management of AKI post renal transplantation.