Background: Acute kidney injury (AKI) represents a diverse range of conditions characterized by high incidence and mortality rates, and it is mainly associated with immune-mediated mechanisms and mitochondrial metabolism dysfunction. Cuproptosis, a recently identified form of programmed cell death dependent on copper, is closely linked to mitochondrial respiration and contributes to various diseases. Our study aimed to investigate the involvement of cuproptosis-related genes (CRGs) in AKI.
Methods: Identification of CRGs was conducted using differential expression analysis, and subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using human sequencing profiles. Utilizing CIBERSORT algorithm, receiver operating characteristic (ROC) curve analysis, nomogram development, and decision curve analysis (DCA), the association among immune scores, CRGs, and the diagnostic value of these genes was explored.
Results: Notably, six CRGs (FDX1, DLD, DLAT, DBT, PDHA1, and ATP7A) were identified as significant differentiators between AKI and non-AKI groups. The ROC curve, based on these six genes, demonstrated an AUC value of 0.917, which was further validated using an additional dataset with an AUC value of 0.902. Nomogram and DCA further confirmed the accuracy of the model in predicting the risk of AKI.
Conclusion: This study elucidated the role of cuproptosis in AKI and revealed the association between CRGs and infiltrated immune cells through comprehensive bioinformatic techniques. The six-gene cuproptosis-related signature exhibited remarkable predictive efficiency for AKI.
Keywords: CIBERSORT; acute kidney injury; cuproptosis; gene signature; immune infiltration.