Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis

Geng, Xiaodong; Wang, Wei‐wei; Feng, Zhe; Liu, Ran; Cheng, Xinhua; Shen, Weisong; Dong, Zheyi; Cai, Guangyan; Chen, Xiangmei; Hong, Quan; Wu, Di

doi:10.1111/jdi.12986

Cited by 63 publications

(49 citation statements)

References 27 publications

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“…In lupus, bioinformatics analysis revealed that CD38 and CCL2 are hub macrophage-related genes [8]. Additionally, EST1 may be a drug target for diabetic nephropathy treatment [9]. Currently, only a few bioinformatics analyses have been performed on IgAN; its critical associated genes and interactions have not been thoroughly investigated.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

Xue

et al. 2020

Eur J Med Res

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Background Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulopathy worldwide. However, the molecular events underlying IgAN remain to be fully elucidated. This study aimed to identify novel biomarkers of IgAN through bioinformatics analysis and elucidate the possible molecular mechanism. Methods Based on the microarray datasets GSE93798 and GSE37460 downloaded from the Gene Expression Omnibus database, the differentially expressed genes (DEGs) between IgAN samples and normal controls were identified. Using the DEGs, we further performed a series of functional enrichment analyses. Protein–protein interaction (PPI) networks of the DEGs were constructed using the STRING online search tool and were visualized using Cytoscape. Next, hub genes were identified and the most important module among the DEGs, Biological Networks Gene Ontology tool (BiNGO), was used to elucidate the molecular mechanism of IgAN. Results In total, 148 DEGs were identified, comprising 53 upregulated genes and 95 downregulated genes. Gene Ontology (GO) analysis indicated that the DEGs for IgAN were mainly enriched in extracellular exosome, region and space, fibroblast growth factor stimulus, inflammatory response, and innate immunity. Module analysis showed that genes in the top 1 significant module of the PPI network were mainly associated with innate immune response, integrin-mediated signaling pathway and inflammatory response. The top 10 hub genes were constructed in the PPI network, which could well distinguish the IgAN and control group in monocyte and tissue samples. We finally identified the integrin subunit beta 2 (ITGB2) and Fc fragment of IgE receptor Ig (FCER1G) genes that may play important roles in the development of IgAN. Conclusions We identified key genes along with the pathways that were most closely related to IgAN initiation and progression. Our results provide a more detailed molecular mechanism for the development of IgAN and novel candidate gene targets of IgAN.

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Section: Introductionmentioning

confidence: 99%

Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

Xue

et al. 2020

Eur J Med Res

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“…WGCNA was performed in an independent study of large number of samples of multiple kidney diseases, avoiding the heterogeneity among different studies caused by a comprehensive analysis of multiple GEO datasets. Different from the analysis of DEGs [14][15][16], the genome-wide transcriptional co-expression network analysis has provided an unbiased description of gene expression network in DN. A gene module speci c for DN was identi ed re ecting the unique pathogenesis of DN.…”

Section: Discussionmentioning

confidence: 99%

Identification of hub genes associated with accumulation of extracellular matrix as biomarkers of diabetic nephropathy

Feng

Gao

Yin

et al. 2020

Preprint

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Abstract Background Diabetic nephropathy (DN) remains a major cause of end stage renal disease (ESRD). The development of novel biomarkers and early diagnosis of DN are of great clinical importance. The goal of this study was to identify hub genes with diagnostic potential for DN by weighted gene co-expression network analysis (WGCNA). Methods Gene Expression Omnibus (GEO) database was searched for microarray data including distinct types of chronic kidney diseases (CKD). Gene co-expression network was constructed and modules specific for DN were identified by WGCNA. Gene Ontology (GO) analysis was performed and the hub genes were screened out within the selected gene modules. Furthermore, receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic values of hub genes. In addition, an external validation was performed in an independent dataset. Results Dataset GSE99339 was selected and a total of 179 microdissected glomeruli samples were analyzed, including DN, normal control and 7 groups of other glomerular diseases. 23 modules of the total 10947 genes were grouped by WGCNA and a module was specifically correlated with DN (r = 0.54, 9e-15). GO analysis showed that module genes were mainly enriched in the accumulation of extracellular matrix (ECM). LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD were identified as hub genes. Furthermore, levels of hub genes were the highest in DN compared to other groups, which could differentially diagnose DN (AUC, 0.67 ~ 0.95). External verification showed hub genes were higher in DN group and were negatively correlated with eGFR. Conclusions By using WGCNA approach, we identified 6 hub genes, LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD, related to ECM accumulation and were specific for DN. These genes may represent potential candidate diagnostic biomarkers of DN.

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“…Recently, VSIG4-related EMT was reported in renal cells as well as cancer metastasis [ 8 , 9 ]. Moreover, VSIG4 is upregulated in diabetic kidney disease, as indicated by bioinformatics analysis [ 10 ]. However, the precise role of VSIG4 in the diabetic milieu is still unclear.…”

Section: Introductionmentioning

confidence: 99%

VSIG4 Induces Epithelial-Mesenchymal Transition of Renal Tubular Cells under High-Glucose Conditions

Gong

Park

et al. 2020

Life

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High glucose-mediated tubular injury contributes to the development and progression of diabetic nephropathy through renal tubulointerstitial fibrosis. V-set immunoglobulin-domain-containing 4 (VSIG4), a B7 family-related protein, is a complement receptor. Although the role of epithelial–mesenchymal transition (EMT) has been reported in several diseases, little is known about its relationship with VSIG4 under diabetic conditions. This study aimed to investigate the role of VSIG4 in human tubule cells stimulated by high glucose (HG, 55 mM). HG upregulated both mRNA and protein levels of VSIG4 in proximal tubule cells (HK-2 cells) and Madin Darby Canine Kidney cells. These upregulations were accompanied by increased expression of mesenchymal markers such as fibronectin, N-cadherin, matrix metalloproteinase 9, and vimentin, and by decreased expression of the epithelial marker, E-cadherin. The siRNA-mediated inhibition of VSIG4 in HK-2 cells restored the dysregulation of EMT in cells. Interestingly, VSIG4 inhibition did not affect the expression of transforming growth factor (TGF)-β, whereas inhibition of TGF-β reduced VSIG4 expression, subsequently suppressing fibrosis markers. These findings suggest that VSIG4 plays an important role in mediating renal tubular EMT through the downstream action of HG-induced TGF-β activation.

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Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis

Cited by 63 publications

References 27 publications

Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

Identification of hub genes associated with accumulation of extracellular matrix as biomarkers of diabetic nephropathy

VSIG4 Induces Epithelial-Mesenchymal Transition of Renal Tubular Cells under High-Glucose Conditions

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