Abstract

BACKGROUND: Diabetic kidney disease (DKD) can result in end-stage kidney disease and renal failure. This study aimed to examine the expression of serum microRNAs (miRNAs), miR-20a, miR-99b, miR-122-5p, and miR-486-5p, and to use bioinformatics data to investigate the pathways involved in DKD.

MATERIAL AND METHODS: Serum miRNAs were obtained from 25 healthy volunteers, 50 patients with non-complicated type 2 diabetes mellitus (T2DM), and 42 patients with T2DM and DKD. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression of serum miRNAs. Specificity and sensitivity of the association between serum miRNAs in DKD were evaluated by analysis of the receiver operating characteristic (ROC) area under the curve (AUC). Serum miRNAs and clinical parameters of the patients were compared. Bioinformatics data analysis accessed the miRNA targets involved in the pathways related to the pathogenesis of DKD.

RESULTS: Serum levels of miR-99b and miR-122 significantly increased, and mir-20a and miR-486 decreased in the DKD group compared with healthy controls. Serum levels of miR-20a, miR-99b, miR-486-5p, and miR-122-5p were significantly correlated with albuminuria, estimated glomerular filtration rate (eGFR), blood glucose and lipid profiles. ROC curve analysis showed that diagnostic accuracy of serum levels of miR-99b for DKD was superior to miR-486-5p, miR-122-5p, and miR-20a, resulting in AUCs of 0.895, 0.853, 0.80, and 0.697, respectively. These four miRNAs regulate several genes affecting oxidative stress, inflammation, and apoptosis.

CONCLUSIONS: Serum miR-99b, miR-486-5p, miR-122-5p, and miR-20a were differentially expressed in patients with T2DM and DKD and should be evaluated further as potential biomarkers for DKD.

Keywords: Biological Markers, MicroRNAs, Adult, Albuminuria, Area Under Curve, Blood Glucose, Case-Control Studies, Computational Biology, Diabetes Mellitus, Type 2, Gene Expression Profiling, Glomerular Filtration Rate, Lipids, Middle Aged, ROC Curve