糖尿病肾病(DN)代表主要的慢性肾病和终末期肾病(ESRD)的主要原因。小RNA已经显示出作为诊断标记和药物靶标的巨大前景。识别失调的微小RNA(miRNA)可以帮助识别疾病生物标志物和下游相互作用的研究。阐明DN的分子病理生理学。在这项研究中,我们使用小RNA下一代测序分析了DN患者的人尿细胞外囊泡(ECV)中的小RNA.
■在这项横断面研究中,从88名参与者中收集尿液样本,这些参与者分为3组:2型糖尿病(T2D)合并DN(T2D+DN,n=20),不带DN的T2D(T2D-DN,n=40),和健康个体(n=28)。该研究集中于分离尿ECV以提取和测序小RNA。差异表达的小RNA被鉴定,并进行了功能富集分析。
■该研究揭示了13个miRNA和10个Piwi相互作用的RNA的不同子集,与其他组相比,它们在DN组的尿ECV中明显失调。值得注意的是,miR-151a-3p和miR-182-5p表现出独特的表达模式,在T2D-DN组中下调,并在T2D+DN组中上调,从而证明了它们在区分两组患者方面的有效性。八个驱动基因被鉴定为PTEN,SMAD2,SMAD4,VEGFA,CCND2,CDK6,LIN28B,和CHD1。
■我们的发现为DN的发病机制提供了宝贵的见解,发现新的生物标志物,并确定可能有助于控制和减缓疾病进展的潜在治疗靶点。
UNASSIGNED: Diabetic nephropathy (DN) represents a major chronic kidney disorder and a leading cause of end-stage renal disease (ESRD). Small RNAs have been showing great promise as diagnostic markers as well as drug targets. Identifying dysregulated micro RNAs (miRNAs) could help in identifying disease biomarkers and investigation of downstream interactions, shedding light on the molecular pathophysiology of DN. In this study, we analyzed small RNAs within human urinary extracellular vesicles (ECVs) from DN patients using small RNA next-generation sequencing.
UNASSIGNED: In this cross-sectional study, urine samples were collected from 88 participants who were divided into 3 groups: type 2 diabetes (T2D) with DN (T2D + DN, n = 20), T2D without DN (T2D - DN, n = 40), and healthy individuals (n = 28). The study focused on isolating urinary ECVs to extract and sequence small RNAs. Differentially expressed small RNAs were identified, and a functional enrichment analysis was conducted.
UNASSIGNED: The study revealed a distinct subset of 13 miRNAs and 10 Piwi-interacting RNAs that were significantly dysregulated in urinary ECVs of the DN group when compared to other groups. Notably, miR-151a-3p and miR-182-5p exhibited a unique expression pattern, being downregulated in the T2D - DN group, and upregulated in the T2D + DN group, thus demonstrating their effectiveness in distinguishing patients between the 2 groups. Eight driver genes were identified PTEN, SMAD2, SMAD4, VEGFA, CCND2, CDK6, LIN28B, and CHD1.
UNASSIGNED: Our findings contribute valuable insights into the pathogenesis of DN, uncovering novel biomarkers and identifying potential therapeutic targets that may aid in managing and potentially decelerating the progression of the disease.