Diagnostic PANoptosis-related genes in acute kidney injury: bioinformatics, machine learning, and validation.

BACKGROUND: Acute kidney injury (AKI) is a prevalent and life-threatening condition characterized by abrupt renal function decline and subsequent inflammatory cascades. PANoptosis has emerged as a significant contributor to the pathophysiology of AKI. This research aimed to explore the diagnostic and therapeutic implications of PANoptosis-related genes in AKI. METHODS: Kidney biopsy transcriptomic expression data were obtained from the GEO database. Differentially expressed genes (DEGs) associated with PANoptosis were identified between AKI and controls. WGCNA identified hub PANoptosis-related genes. PANoptosis scores and immune cell infiltration were calculated by ssGSEA. Machine learning algorithms was used to select feature genes. ROC analysis evaluated their diagnostic performance. Drug-gene interactions were explored. RESULTS: We identified 3460 DEGs between AKI and controls (61 upregulated and 11 downregulated) related to PANoptosis, mainly enriched in cytokine signaling and apoptosis. Eight hub PANoptosis genes were identified. PANoptosis scores were significantly higher in AKI patients (p < 0.001). CASP8, CASP4, SFN, FAS, and CASP1 were selected as feature genes, with CASP8 having the highest AUC at 0.850 in the training set. A nomogram combining these genes demonstrated strong predictive power. Furthermore, these genes were related to immune cell infiltration positively and had potential drug associations. Validation in a renal ischemia-reperfusion injury rat model confirmed the upregulation of CASP8 (p < 0.01), CASP4 (p < 0.001), SFN (p < 0.0001), FAS (p < 0.01), and CASP1 (p < 0.01). CONCLUSIONS: Our study identifies PANoptosis-related genes as potential diagnostic markers and therapeutic targets in AKI, highlighting their role in immune dysregulation in AKI.