Identification of core genes in acute kidney injury: evidence from multi-omics human transcriptomic data and in vivo models.

Abstract

Background: Acute kidney injury (AKI) affects up to 23.2% of hospitalized patients, but its complex pathophysiology hinders diagnosis and treatment. Bioinformatics-driven identification of core genes from large-scale omics data offers a promising approach for uncovering diagnostic and therapeutic targets. This study aims to integrate multi-omics data with experimental validation to identify core genes involved in AKI and explore their mechanisms.

Methods: We analyzed renal transcriptomic data from 67 AKI patients and 20 controls, integrating differential expression, weighted gene co-expression network analysis (WGCNA), and clinical correlations to identify key genes. A nomogram model was used to assess diagnostic performance, and immune microenvironment characteristics were analyzed using CIBERSORT. AKI was induced in mice by ischemia-reperfusion and cisplatin, with gene expression validated by reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry. SUGCT expression and function were further examined in proximal tubules (PT) using human single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics.

Results: Three core genes, epidermal growth factor (EGF), vascular cell adhesion molecule 1 (VCAM1), and SUGCT, were identified, showing significant associations with AKI phenotypes and clinical renal parameters. Combined, these genes provided a robust diagnostic model for AKI. CIBERSORT associated VCAM1 with monocytes, SUGCT with monocytes and M2 macrophages, and EGF with monocytes and T cells. Both mouse models showed downregulation of Sugct and Egf, and upregulation of Vcam1, consistent with human data. Single-nucleus RNA sequencing revealed that SUGCT was highly expressed in healthy PT but downregulated in severely injured PT. Low SUGCT expression correlated with suppressed mitochondrial functions and activated immune responses. Spatial transcriptomics confirmed that regions of high SUGCT expression co-localized with areas of oxidative phosphorylation activity in PT.

Conclusions: This study highlights three core genes of AKI, especially SUGCT, which is related to mitochondrial metabolism and immune balance in PT during AKI, offering potential diagnostic and therapeutic targets.