ABSTRACT
Objective:To investigate the correlation between Piwi-interacting RNA (piRNA) and diabetic nephropathy (DN).Methods:The differential expression profiles of piRNAs in renal tissues of patients with DN (experimental group) and renal tissues adjacent to tumors of patients with renal tumors (control group) were detected by high-throughput sequencing. The biological function of differentially expressed piRNAs was described by gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis. Real-time fluorescence quantitative PCR was used to detect the serum expression level of target piRNAs in patients with DN. Spearman correlation analysis was used to analyze the correlation between serum target piRNAs and clinical indexes of patients with DN.Results:The results of high throughput sequencing showed that there were 127 differentially expressed piRNAs between DN group and control group, with screening condition of |log 2(fold changes)|≥2 and P<0.05. Among them, there were 99 up-regulated piRNAs and 28 down-regulated piRNAs. The top 5 up-regulated piRNAs were piRNA-hsa-161686, piRNA-hsa-349255, piRNA-hsa-355720, piRNA-hsa-151229 and piRNA-hsa-154959, respectively. The top 5 down-regulated piRNAs were piRNA-hsa-1929960, piRNA-hsa-174194, piRNA-hsa- 148658, piRNA-hsa-172594 and piRNA-hsa-172421, respectively. The PCR verification results of 3 up-regulated genes and 3 down-regulated genes with low P values and high expression levels showed that serum expression level of piRNA-hsa-77976 was significantly down-regulated in patients with DN ( P=0.028), which was consistent with that of sequencing, while the expression levels of other genes were inconsistent with the sequencing results or had no statistical significance. Bioinformatics analysis results predicted that significantly differentially expressed piRNAs might participate in the regulation of DN through Rap1, Ras, PI3K-Akt and axon guiding pathways. The results of correlation analysis showed that the expression level of piRNA-hsa-77976 was negatively correlated with blood urea nitrogen ( r=-0.584, P=0.028), serum creatinine ( r=-0.637, P=0.014), cystatin C ( r=-0.738, P=0.003) and β2 microglobulin ( r=-0.822, P<0.001), and positively correlated with estimated glomerular filtration rate ( r=0.661, P=0.010). Conclusion:The differential expression of piRNA is closely related to DN, and may be used as a new biomarker for the diagnosis and prognosis of DN.