Global analysis of urinary extracellular vesicle small RNAs in autosomal dominant polycystic kidney disease

Background Autosomal dominant polycystic kidney disease (ADPKD) is the most prevalent monogenic renal disease progressing to end‐stage renal disease. There is a pressing need for the identification of early ADPKD biomarkers to enable timely intervention and the development of effective therapeutic approaches. Here, we profiled human urinary extracellular vesicles small RNAs by small RNA sequencing in patients with ADPKD and compared their differential expression considering healthy control individuals to identify dysregulated small RNAs and analyze downstream interaction to gain insight about molecular pathophysiology. Methods This is a cross‐sectional study where urine samples were collected from a total of 23 PKD1‐ADPKD patients and 28 healthy individuals. Urinary extracellular vesicles were purified, and small RNA was isolated and sequenced. Differentially expressed Small RNA were identified and functional enrichment analysis of the critical miRNAs was performed to identify driver genes and affected pathways. Results miR‐320b, miR‐320c, miR‐146a‐5p, miR‐199b‐3p, miR‐671‐5p, miR‐1246, miR‐8485, miR‐3656, has_piR_020497, has_piR_020496 and has_piR_016271 were significantly upregulated in ADPKD patient urine extracellular vesicles and miRNA‐29c was significantly downregulated. Five ‘driver’ target genes (FBRS, EDC3, FMNL3, CTNNBIP1 and KMT2A) were identified. Conclusions The findings of the present study make significant contributions to the understanding of ADPKD pathogenesis and to the identification of novel biomarkers and potential drug targets aimed at slowing disease progression in ADPKD. Urine samples were collected from autosomal dominant polycystic kidney disease (ADPKD) patients and urinary extracellular vesicles were purified. Then, small RNA fraction was sequenced, and data were analyzed and compared to healthy controls. Significantly dysregulated miRNAs were identified, and functional enrichment analysis was performed to identify driver's genes and affected biological pathways. Our findings contribute to the understanding of ADPKD pathogenesis and to the identification of novel biomarkers and potential drug targets aimed at slowing disease progression in ADPKD.