Dataset Information

Urinary miR-3137 and miR-4270 as potential biomarkers for diabetic kidney disease.

ABSTRACT:

Background

As one of the most prevalent diagnostic indicators of diabetic kidney disease (DKD), albumin-to-creatinine ratio (ACR) shows considerably limited predictive power in clinical application. We analyzed microarray expression profiling of urine to seek for differentially expressed miRNAs for potential biomarkers of DKD.

Methods

Urine samples from type 2 diabetes mellitus (T2DM) patients with (30 mg/g < ACR < 300 mg/g, DKD group) or without DKD (ACR < 30 mg/g, DM group) were collected for miRNA microarray analysis. The differentially expressed miRNAs were screened by bioinformatics analysis and validated by quantitative real-time PCR. Target genes of differentially expressed miRNAs were predicted in miRDB, Targetscan, and microRNA.org databases. We also conducted the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways analysis to explore for potential mechanisms in DKD.

Results

Nine miRNAs were down-regulated and seventeen miRNAs were up-regulated in DKD group, compared to DM group. The levels of miR-3137 and miR-4270 in DKD group were 0.670 ± 0.505 and 2.116 ± 1.762 times than those in DM group, respectively, showing great significance. A total of 1076 target genes were simultaneously predicted by miRDB, Targetscan, and microRNA.org databases. According to the GO analysis results, disorders of endomembrane system may be one of the major pathological changes in DKD. In addition, Rap 1 signaling pathway is also altered obviously in DKD, discovered by the KEGG analysis.

Conclusion

MiR-3137 and miR-4270 show the potential for urinary biomarkers of DKD. The pathological changes of DKD may be related to disorders of endomembrane system and alternation of Rap1 signaling pathway.

SUBMITTER: Li X

PROVIDER: S-EPMC7755759 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Urinary miR-3137 and miR-4270 as potential biomarkers for diabetic kidney disease.

Li Xiaoyu X Xu Rong R Liu Xiangyang X Xu Linxin L Xue Mei M Cheng Ying Y Li Ting T Yu Xiaochen X Wang Yue Y Li Chunjun C Sun Bei B Chen Liming L

Journal of clinical laboratory analysis 20200901 12

<h4>Background</h4>As one of the most prevalent diagnostic indicators of diabetic kidney disease (DKD), albumin-to-creatinine ratio (ACR) shows considerably limited predictive power in clinical application. We analyzed microarray expression profiling of urine to seek for differentially expressed miRNAs for potential biomarkers of DKD.<h4>Methods</h4>Urine samples from type 2 diabetes mellitus (T2DM) patients with (30 mg/g < ACR < 300 mg/g, DKD group) or without DKD (ACR < 30 mg/g, DM group) were ...[more]

PMID: 32869917

Similar Datasets

Project description:BackgroundDiabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD) in the world. Emerging evidence has shown that urinary mRNAs may serve as early diagnostic and prognostic biomarkers of DKD. In this article, we aimed to first establish a novel bioinformatics-based methodology for analyzing the "urinary kidney-specific mRNAs" and verify their potential clinical utility in DKD.MethodsTo select candidate mRNAs, a total of 127 Affymetrix microarray datasets of diabetic kidney tissues and other tissues from humans were compiled and analyzed using an integrative bioinformatics approach. Then, the urinary expression of candidate mRNAs in stage 1 study (n?=?82) was verified, and the one with best performance moved on to stage 2 study (n?=?80) for validation. To avoid potential detection bias, a one-step Taqman PCR assay was developed for quantification of the interested mRNA in stage 2 study. Lastly, the in situ expression of the selected mRNA was further confirmed using fluorescent in situ hybridization (FISH) assay and bioinformatics analysis.ResultsOur bioinformatics analysis identified sixteen mRNAs as candidates, of which urinary BBOX1 (uBBOX1) levels were significantly upregulated in the urine of patients with DKD. The expression of uBBOX1 was also increased in normoalbuminuric diabetes subjects, while remained unchanged in patients with urinary tract infection or bladder cancer. Besides, uBBOX1 levels correlated with glycemic control, albuminuria and urinary tubular injury marker levels. Similar results were obtained in stage 2 study. FISH assay further demonstrated that BBOX1 mRNA was predominantly located in renal tubular epithelial cells, while its expression in podocytes and urothelium was weak. Further bioinformatics analysis also suggested that tubular BBOX1 mRNA expression was quite stable in various types of kidney diseases.ConclusionsOur study provided a novel methodology to identify and analyze urinary kidney-specific mRNAs. uBBOX1 might serve as a promising biomarker of DKD. The performance of the selected urinary mRNAs in monitoring disease progression needs further validation.

Dataset Information

Urinary miR-3137 and miR-4270 as potential biomarkers for diabetic kidney disease.

Background

Methods

Results

Conclusion

Publications

Urinary miR-3137 and miR-4270 as potential biomarkers for diabetic kidney disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets