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Promoting adaptive repair (AR) in acute kidney injury (AKI) is an effective strategy to preventprogression from AKI to chronic kidney disease (CKD). However, the mechanisms involved in renal repair after AKI remain unclear. In this study, we investigated the role of hypoxia-inducible factor (HIF), an important regulator of ischemic and hypoxic injury, in AKI during the repair phase. We established mouse models of ischemia-reperfusion injury (IRI)-induced AKI with AR or maladaptive repair (MAR). We found that after injury, the activation of HIF in the AR group was rapid, while in the MAR group, HIF activation was relatively delayed, and its expression was significantly lower than that in the AR group during the early repair phase. To further investigate the mechanism of HIF, we regulated the expression of HIF-1α and HIF-2α in HK-2 cells and EA.hy926 cells, respectively. Silencing HIF expression reduced proliferation and increased apoptosis in cells injured by hypoxia/reoxygenation (H/R). Self-healing ability was further reduced due to the downregulation of HIF. Moreover, HIF overexpression had the opposite effect. HIF increased the expression of β-catenin and its downstream target genes. Activation of Wnt/β-catenin by the small molecule activator SKL2001 mitigated the damaging effect of HIF knockdown, while blocking β-catenin with the inhibitor IWR-1-endo reduced the protective effects of HIF. In conclusion, HIF, which is highly expressed in the early stage after AKI, promotes renal repair by interacting with the Wnt/β-catenin signaling pathway.

Since urine samples more directly reflect kidney alterations and damage than blood samples, we investigated whether urine anti-PLA2R antibody (uPLA2R-Ab) could be utilized similarly to serum anti-PLA2R antibody (sPLA2R-Ab) as a noninvasive biomarker of idiopathic membranous nephropathy (IMN). In this study, we performed a qualitative analysis using an indirect immunofluorescence test (IIFT) and measured uPLA2R-Ab and sPLA2R-Ab concentrations using an enzyme-linked immunosorbent assay (ELISA) in 28 patients with biopsy-proven IMN and 12 patients with secondary membranous nephropathy (SMN). Overall, 64.3% (n=18) of patients with IMN had IIFT-positive sPLA2R-Ab, 67.9% (n=19) of patients with IMN had IIFT-positive uPLA2R-Ab, and none of the SMN patients had IIFT-positive sPLA2R-Ab or uPLA2R-Ab. The titers of the anti-PLA2R antibody from the IMN patients in the urine (10.72±22.24 RU/μmol, presented as uPLA2R-Ab/urine creatinine) and serum (107.36±140.93 RU/ml) were higher than those from the SMN patients (0.51±0.46 RU/μmol, 0.008±0.029 RU/ml, respectively, p<0.05). Statistical analyses indicated that there were positive correlations between uPLA2R-Ab and gPLA2R, sPLA2R-Ab or urinary protein and negative correlations between uPLA2R-Ab and serum albumin in patients with IMN. In conclusion, uPLA2R-Ab is a novel biomarker of IMN. sPLA2R-Ab combined with uPLA2R-Ab might be more helpful for diagnosis and activity in PLA2R associated MN.

Background: Focal segmental glomerulosclerosis (FSGS) is a type of nephrotic syndrome leading to end-stage renal disease, and this study aimed to explore the hub genes and pathways associated with FSGS to identify potential diagnostic and therapeutic targets.Methods: We downloaded the microarray datasets GSE121233 and GSE129973 from the Gene Expression Omnibus (GEO) database. The datasets comprise 25 FSGS samples and 25 normal samples. The differential expression genes (DEGs) were identified using the R package “limma”. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID) to identify the pathways and functional annotation of the DEGs. The protein–protein interaction (PPI) was constructed based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized using Cytoscape software. The hub genes of the DEGs were then evaluated using the cytoHubba plugin of Cytoscape. The expression of the hub genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) using the FSGS rat model, and receiver operating characteristic (ROC) curve analysis was performed to validate the accuracy of these hub genes.Results: A total of 45 DEGs including 18 upregulated and 27 downregulated DEGs, were identified in the two GSE datasets (GSE121233 and GSE129973). Among them, five hub genes with a high degree of connectivity were selected. From the PPI network, of the top five hub genes, FN1 was upregulated, while ALB, EGF, TTR, and KNG1 were downregulated. The qRT-PCR analysis of FSGS rats confirmed that the expression of FN1 was upregulated and that of EGF and TTR was downregulated. The ROC analysis indicated that FN1, EGF, and TTR showed considerable diagnostic efficiency for FSGS.Conclusion: Three novel FSGS-specific genes were identified through bioinformatic analysis combined with experimental validation, which may promote our understanding of the molecular underpinning of FSGS and provide potential therapeutic targets for the clinical management.

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