ExomiRs-126, -146, and -155 expression in urine exosomes of patients with T2DM and diabetic kidney disease will be evaluated to construct a predictive classification model with exomiRs and clinical factors to identify their contribution to DKD.
The study group comprised 92 subjects: 64 T2DM patients divided into two groups: those with albuminuria (T2DM with albuminuria, n=30) and those without (TD2M, n=34), and 28 healthy, non-diabetic people. TEM and flow cytometry was used to identify exosomes extracted from urine. RT-qPCR was used to assess the expression profiles of exomiRs-126, -146, and -155. Permutational multivariate analysis of variance (PERMANOVA), similarity percentage (SIMPER), principal coordinate analysis (PCO), and canonical analysis of principal coordinates (CAP) were used to analyze the data.
T2DM patients with and without albuminuria had greater levels of miR-155 and miR-146 than controls. Furthermore, compared to controls and patients without albuminuria, T2DM patients with albuminuria had a substantial increase in miR-126. PCO analysis explained 34.6% of the overall data variability (PERMANOVA; P<.0001). Following that, SIMPER analysis revealed that miR-146, miR-155, and miR-126, together with several clinical factors, contributed to 50% of the between-group significance. Finally, the constructed CAP analysis revealed an accurate classification rate of 89.01% using the examined parameters.
A platform based on clinical factors and exomiRs might be utilized to identify persons with T2D who are at risk of developing DKD.