Abstract
Background MicroRNA (miRNA) has been confirmed to be involved in the occurrence, development, and prevention of diabetic nephropathy (DN), but its mechanism of action is still unclear. Objective With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Methods The DN-related miRNA microarray dataset (GSE51674) and mRNA expression dataset (GSE30122) are downloaded through the GEO database, online analysis tool GEO2R is used for data differential expression analysis, TargetScan, miRTarBase, and miRDB databases are used to predict potential downstream target genes regulated by differentially expressed miRNAs, and intersection with differential genes is used to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair is clarified, and the miRNA-mRNA regulatory network is constructed using Cytoscape. DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. By GeneMANIA prediction of miRNA target genes and coexpressed genes, the protein interaction network is constructed. Results and Conclusions. A total of 67 differentially expressed miRNAs were screened in the experiment, of which 42 were upregulated and 25 were downregulated; a total of 448 differentially expressed mRNAs were screened, of which 93 were upregulated and 355 were downregulated. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. Finally, 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway.
Highlights
In recent years, impaired glucose tolerance and diabetes incidence was on the rise every year, in 2017, about 425 million people worldwide suffer from diabetes, and the prevalence rate is about 8.4%
Download the miRNA expression data set GSE51674 and mRNA expression data set GSE30122 that meet the requirements. e dataset GSE51674 is based on the platform GPL10656 and contains 16 kidney tissue samples, including 6 diabetic nephropathy (DN) patients, 4 males and 2 females, with an average age of 59 years. e average age of 4 patients in the healthy group was 38 years, 3 males and 1 female; the dataset GSE30122 was based on the platform GPL571 and contained 69 kidney tissue samples. 26 healthy glomerular samples were selected as the control group and 9 DN glomerular sample cases as the disease group
In 2015, diabetes-related chronic kidney disease patients in China accounted for 1.10% of the total hospitalized population, surpassing primary glomerulonephritis-related chronic kidney disease patients (0.75%), becoming one of the main causes of chronic kidney disease [12]
Summary
In recent years, impaired glucose tolerance and diabetes incidence was on the rise every year, in 2017, about 425 million people worldwide suffer from diabetes, and the prevalence rate is about 8.4%. Diabetic nephropathy (DN) is the main cause of end-stage renal disease. With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway
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