Bioinformatics and systems biology to identify underlying common pathogenesis of diabetic kidney disease and stenosis of arteriovenous fistula.

BACKGROUND

Diabetic nephropathy is an important cause of end-stage renal disease. Arteriovenous fistula (AVF) stenosis is closely associated with hyperglycemia. However, studies exploring biomarkers linking these two diseases are lacking, which may provide insight into the mechanisms underlying Diabetic kidney disease (DKD) comorbid AVF stenosis.

OBJECTIVE

This study investigated the common pathogenesis of DKD and AVF stenosis.

METHODS

Biomarkers were screened by identifying key genes common between DKD and AVF stenosis through differential gene analysis. GO, KEGG and GSEA enrichment analysis of DEGs were performed by cluster profiler. Immuno-infiltration analysis was performed by CIBERSORT. The predictive value of HPGD to distinguish DKD comorbid AVF stenosis was determined by ROC curves. Upstream miRNAs and transcription factors (TFs) of HPGD were predicted using hTFtarget and mirtarbase databases. After specifically knockdown six upstream miRNAs of HPGD in vascular smooth muscle cells (VSMCs), the expression levels of HPGD in each group were analyzed by quantitative reverse transcription PCR (qRT-PCR), and the empty vector was used as the control group. Clinical patient samples were collected to validate HPGD expression in DKD patients with AVF stenosis via qRT-PCR and immunofluorescence. Subsequently, the proliferation ability and the release level of inflammatory cytokines of VSMCs under high glucose culture conditions were evaluated by regulating the expression of HPGD.

RESULTS

Eleven shared DEGs were identified between DKD and AVF stenosis. Diagnostic efficacy of four hub genes (INHBA, PCK1, ALB, HPGD) was validated through receiver operating characteristic (ROC) curve analysis. qRT-PCR and immunofluorescence analyses showed that HPGD expression in the veins of patients with DKD combined with AVF stenosis was significantly decreased compared to the control group. Regulatory network analysis identified 691 TFs and 72 miRNAs modulating hub gene expression. Specific knockdown of six predicted upstream miRNAs of HPGD resulted in a significant increase in HPGD expression, with the hsa-miR-486-5p knockdown group showing the most pronounced effect. Overexpression of HPGD inhibited the proliferation of VSMCs and the release of inflammatory factors under high-glucose culture conditions. Significantly reduced infiltration of memory activated CD4 T cells was observed in AVF stenosis compared to normal veins. Pearson correlation analysis indicated that HPGD is positively correlated with resting mast cells, M1 macrophages, and M2 macrophages, while it is negatively correlated with naïve B cells and resting CD4 memory T cells.

CONCLUSION

HPGD may be a biomarker of DKD comorbid AVF stenosis. The targeted therapy of HPGD may prevent the occurrence of AVF stenosis in DKD patients, which is worthy of further study.