Identification of Transcription Regulatory Relationships in Diabetic Nephropathy.
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ABSTRACT:
SUBMITTER: Shi JS
PROVIDER: S-EPMC6278184 | biostudies-literature | 2018 Dec
REPOSITORIES: biostudies-literature
Publications
Identification of Transcription Regulatory Relationships in Diabetic Nephropathy.
Shi Jing-Song JS Qiu Dan-Dan DD Le Wei-Bo WB Wang Hui H Li Shen S Lu Yin-Hui YH Jiang Song S
Chinese medical journal 20181201 23
Similar Datasets
Project description:MicroRNAs (miRNAs) play a great contribution to the development of diabetic nephropathy (DN). The aim of this study was to explore potential miRNAs-genes regulatory network and biomarkers for the pathogenesis of DN using bioinformatics methods.Gene expression profiling data related to DN (GSE1009) was obtained from the Gene Expression Omnibus (GEO) database, and then differentially expressed genes (DEGs) between DN patients and normal individuals were screened using GEO2R, followed by a series of bioinformatics analyses, including identifying key genes, conducting pathway enrichment analysis, predicting and identifying key miRNAs, and establishing regulatory relationships between key miRNAs and their target genes.A total of 600 DEGs associated with DN were identified. An additional 7 key DEGs, including 6 downregulated genes, such as vascular endothelial growth factor α (VEGFA) and COL4A5, and 1 upregulated gene (CCL19), were identified in another dataset (GSE30528) from glomeruli samples. Pathway analysis showed that the down- and upregulated DEGs were enriched in 14 and 6 pathways, respectively, with 7 key genes mainly involved in extracellular matrix-receptor interaction, PI3K/Akt signaling, focal adhesion, and Rap1 signaling. The relationships between miRNAs and target genes were constructed, showing that miR-29 targeted COL4A and VEGFA, miR-200 targeted VEGFA, miR-25 targeted ITGAV, and miR-27 targeted EGFR.MiR-29 and miR-200 may play important roles in DN. VEGFA and COL4A5 were targeted by miR-29 and VEGFA by miR-200, which may mediate multiple signaling pathways leading to the pathogenesis and development of DN.
| S-EPMC6635158 | biostudies-literature
Project description:The pathogenesis of diabetic nephropathy (DN) is accompanied by alterations in biological function and signaling pathways regulated through complex molecular mechanisms. A number of regulatory factors, including transcription factors (TFs) and non-coding RNAs (ncRNAs, including lncRNAs and miRNAs), have been implicated in DN; however, it is unclear how the interactions among these regulatory factors contribute to the development of DN pathogenesis. In this study, we developed a network-based analysis to decipher interplays between TFs and ncRNAs regulating progression of DN by combining omics data with regulatory factor-target information. To accomplish this, we identified differential expression programs of mRNAs and miRNAs during early DN (EDN) and established DN. We then uncovered putative interactive connections among miRNA-mRNA, lncRNA-miRNA, and lncRNA-mRNA implicated in transcriptional control. This led to the identification of two lncRNAs (MALAT1 and NEAT1) and the three TFs (NF-κB, NFE2L2, and PPARG) that likely cooperate with a set of miRNAs to modulate EDN and DN target genes. The results highlight how crosstalk among TFs, lncRNAs, and miRNAs regulate the expression of genes both transcriptionally and post-transcriptionally, and our findings provide new insights into the molecular basis and pathogenesis of progressive DN.
| S-EPMC7490338 | biostudies-literature
Project description:Gene expression profiling in glomeruli from human kidneys with diabetic nephropathy Keywords = Diabetes Keywords = kidney Keywords = glomeruli Keywords: other
2004-04-01 | GSE1009 | GEO
Project description:Diabetic nephropathy (DN) is one of the leading causes of end-stage renal disease and lacks effective clinical treatment for its complicated pathogenesis. In this study, the gene expression profiles downloaded from the GEO database were used to identify the key regulatory gene through bioinformatics analyses, and the potential mechanism in regulating DN was revealed via the gene set enrichment analysis, pathway analysis, and in vitro phenotype detection. The effect of the screened drug on DN was analyzed through in vitro and in vivo model experiments. Interferon regulatory factor 4 (IRF4) in DN was identified to be upregulated compared with that in normal control tissues. Further results revealed that IRF4 promoted the DN progression through inflammation, immunity, and extracellular matrix remodeling. The screening results of the TCM library showed that aloe-emodin (Ae) should be a potentially active target drug, and the in vitro and in vivo experiment results demonstrated that Ae could ameliorate DN by targeting IRF4. In conclusion, this study revealed the mechanism of the DN progression and demonstrated that Ae could be a potential target drug in ameliorating DN, providing ideas for the clinical treatments for DN.
| S-EPMC9064522 | biostudies-literature
Project description: Not available
| S-EPMC11337715 | biostudies-literature
Project description:Validation of predicted gene expression of human mesangial cells after 24h Tacrolimus stimulus Objective: To evaluate tacrolimus as therapeutic option for diabetic nephropathy (DN) based on molecular profile and network-based molecular model comparisons. Materials and Methods: We generated molecular models representing pathophysiological mechanisms of DN and tacrolimus mechanism of action (MoA) based on literature derived data and transcriptomics datasets. Shared enriched molecular pathways were identified based on both model datasets. A newly generated transcriptomics dataset studying the effect of tacrolimus on mesangial cells in vitro was added to identify mechanisms in DN pathophysiology. We searched for features in interference between the DN molecular model and the tacrolimus MoA molecular model already holding annotation evidence as diagnostic or prognostic biomarker in the context of DN. Results: Thirty nine molecular features were shared between the DN molecular model, holding 252 molecular features and the tacrolimus MoA molecular model, holding 209 molecular features, with six additional molecular features affected by tacrolimus in mesangial cells. Significantly affected molecular pathways by both molecular model sets included cytokine-cytokine receptor interactions, adherens junctions, TGF-beta signaling, MAPK signaling, and calcium signaling. Molecular features involved in inflammation and immune response contributing to DN progression were significantly downregulated by tacrolimus (e.g. the tumor necrosis factor alpha (TNF), interleukin 4, or interleukin 10). On the other hand, pro-fibrotic stimuli being detrimental to renal function were induced by tacrolimus like the transforming growth factor beta 1 (TGFB1), endothelin 1 (EDN1), or type IV collagen alpha 1 (COL4A1). Conclusion: Patients with DN and elevated TNF levels might benefit from tacrolimus treatment regarding maintaining GFR and reducing inflammation. TGFB1 and EDN1 are proposed as monitoring markers to assess degree of renal damage. Next to this stratification approach, the use of drug combinations consisting of tacrolimus in addition to ACE inhibitors, angiotensin receptor blockers, TGFB1- or EDN1-receptor antagonists might warrant further studies. comparison of gene expression of human mesangial cells after 24h Tacrolimus vs. Ctrl; 4 independent experiments were conducted (4xTacrolimus 24h and 4x ctrl. 24h with Drug solvent (DMSO))
2016-08-01 | E-GEOD-84908 | biostudies-arrayexpress
Project description:Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. After development of DN, patients will progress to end-stage renal disease, which is associated with high morbidity and mortality. Here, we developed early-stage diagnostic biomarkers to detect DN as a strategy for DN intervention. For the DN model, Zucker diabetic fatty rats were used for DN phenotyping. The results revealed that DN rats showed significantly increased blood glucose, blood urea nitrogen (BUN), and serum creatinine levels, accompanied by severe kidney injury, fibrosis and microstructural changes. In addition, DN rats showed significantly increased urinary excretion of kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL). Transcriptome analysis revealed that new DN biomarkers, such as complementary component 4b (C4b), complementary factor D (CFD), C-X-C motif chemokine receptor 6 (CXCR6), and leukemia inhibitory factor (LIF) were identified. Furthermore, they were found in the urine of patients with DN. Since these biomarkers were detected in the urine and kidney of DN rats and urine of diabetic patients, the selected markers could be used as early diagnosis biomarkers for chronic diabetic nephropathy.
| S-EPMC8146473 | biostudies-literature
Project description:Diabetic nephropathy (DN) is a major complication of type 1 and type 2 diabetes and may lead to kidney failure. Understanding how diabetes regulates transcriptome dynamics in DN is important for understanding the biology of the disease and for guiding development of new treatments. In this study, we identified a set of unique biomarkers and canonical pathways that may hold the key to understanding mechanisms of DN pathobiology with value for clinical translation. Our data suggest that mitochondrial dysfunction, genotoxicity and oxidative stress are principal events in DN and that P78-PEDF, an active PEDF peptide, holds promise for its management.
2016-12-09 | GSE87899 | GEO
Project description:Diabetic nephropathy (DN) is one of the most common complications associated with diabetes and characterized by renal microvascular injury along with accelerated synthesis of extracellular matrix proteins causing tubulointerstitial fibrosis. Production of type I collagen, the major component of extracellular matrix, is augmented during renal fibrosis after chronic exposure to hyperglycemia. However, the transcriptional modulator responsible for the epigenetic manipulation leading to induction of type I collagen genes is not clearly defined. We show here that tubulointerstitial fibrosis as a result of DN was diminished in myocardin-related transcription factor A (MRTF-A) -deficient mice. In cultured renal tubular epithelial cells and the kidneys of mice with DN, MRTF-A was induced by glucose and synergized with glucose to activate collagen transcription. Notably, MRTF-A silencing led to the disappearance of prominent histone modifications indicative of transcriptional activation, including acetylated histone H3K18/K27 and trimethylated histone H3K4. Detailed analysis revealed that MRTF-A recruited p300, a histone acetyltransferase, and WD repeat-containing protein 5 (WDR5), a key component of the histone H3K4 methyltransferase complex, to the collagen promoters and engaged these proteins in transcriptional activation. Estradiol suppressed collagen production by dampening the expression and binding activity of MRTF-A and interfering with the interaction between p300 and WDR5 in renal epithelial cells. Therefore, targeting the MRTF-A-associated epigenetic machinery might yield interventional strategies against DN-associated renal fibrosis.
| S-EPMC4483593 | biostudies-literature
Project description:BackgroundMicroRNA (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.ObjectiveWith 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.MethodsThe 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.
| S-EPMC8616647 | biostudies-literature