Profile of urinary exosomal microRNAs and their contribution to diabetic kidney disease through a predictive classification model

Abstract

Aim Evaluate the expression of exomiRs‐126, ‐146, and ‐155 in urinary exosomes of patients with T2DM and diabetic kidney disease to establish a predictive classification model with exomiRs and clinical variables in order to determine their contribution to DKD. Methods The study group included 92 subjects: 64 patients diagnosed with T2DM subclassified into two groups with albuminuria (T2DM with albuminuria, n = 30) and without albuminuria (TD2M, n = 34) as well as 28 healthy, non‐diabetic participants. Exosomes were isolated from urine and identified by TEM and flow cytometry. Profile expression of exomiRs‐126, ‐146 and ‐155 was evaluated by RT‐qPCR. Data were analysed by permutational multivariate analysis of variance (PERMANOVA), similarity percentage (SIMPER), principal coordinate analysis (PCO), and canonical analysis of principal coordinates (CAP). Results T2DM patients with and without albuminuria showed higher levels of miR‐155 and miR‐146 compared with controls. In addition, T2DM patients with albuminuria presented a significant increase in miR‐126 contrasted to controls and patients without albuminuria. PCO analysis explained 34.6% of the total variability of the data (PERMANOVA; p < .0001). Subsequently, SIMPER analysis showed that miR‐146, miR‐155, and miR‐126 together, with some clinical parameters, contributed to 50% of the between‐group significance. Finally, the CAP analysis developed showed a correct classification of 89.01% with the analysed parameters. Conclusion A platform using a combination of clinical variables and exomiRs could be used to classify individuals with T2D as risk for developing DKD.

Urinary microRNA profiling in pregnant women identifies placental microRNAs that are candidate biomarkers for monitoring placental health

“…Only limited medical fields have investigated urinary microRNA profiles. Examples are metabolic diseases, chronic kidney disease, and cancers such as clear cell renal cell carcinoma, and prostate cancer [8,13–16]. The main innovation of this study was to explore urinary microRNAs as a novel resource to be potentially utilized for monitoring the pregnancy course.…”

“…Only limited medical fields have investigated urinary microRNA profiles. Examples are metabolic diseases, chronic kidney disease, and cancers such as clear cell renal cell carcinoma, and prostate cancer [8,[13][14][15][16].…”

Exosomes as biomarkers and therapy in type 2 diabetes mellitus and associated complications

“…The group was able to create various models that predicted the extent of renal fibrosis with high AUCs (i.e., 0.9 and above) (Lv et al, 2013). More recent work focused on DN, was able to create a multivariable model using urine exosomal miR-126, miR-146, miR-155, as well as other paraclinical data, to predict between patients with T2DM with and without DN while maintaining high sensitivity (0.963) and specificity (0.935) (González-Palomo et al, 2022). These findings, as well as those of other studies that identified exosomal miRNA biomarkers for DN are summarized in Table 3 and Figure 2 (Eissa et al, 2016a;Eissa et al, 2016b;Delić et al, 2016;Mohan et al, 2016;Xie et al, 2017;Li et al, 2018;Zang et al, 2019).…”