Comprehensive analysis of diabetic nephropathy expression profile based on weighted gene co-expression network analysis algorithm

Abstract

Background Diabetic nephropathy (DN) is the major complication of diabetes mellitus, and leading cause of end-stage renal disease. The underlying molecular mechanism of DN is not yet completely clear. The aim of this study was to analyze a DN microarray dataset using weighted gene co-expression network analysis (WGCNA) algorithm for better understanding of DN pathogenesis and exploring key genes in the disease progression. Methods The identified differentially expressed genes (DEGs) in DN dataset GSE47183 were introduced to WGCNA algorithm to construct co-expression modules. STRING database was used for construction of Protein-protein interaction (PPI) networks of the genes in all modules and the hub genes were identified considering both the degree centrality in the PPI networks and the ranked lists of weighted networks. Gene ontology and Reactome pathway enrichment analyses were performed on each module to understand their involvement in the biological processes and pathways. Following validation of the hub genes in another DN dataset (GSE96804), their up-stream regulators, including microRNAs and transcription factors were predicted and a regulatory network comprising of all these molecules was constructed. Results After normalization and analysis of the dataset, 2475 significant DEGs were identified and clustered into six different co-expression modules by WGCNA algorithm. Then, DEGs of each module were subjected to functional enrichment analyses and PPI network constructions. Metabolic processes, cell cycle control, and apoptosis were among the top enriched terms. In the next step, 23 hub genes were identified among the modules in genes and five of them, including FN1, SLC2A2, FABP1, EHHADH and PIPOX were validated in another DN dataset. In the regulatory network, FN1 was the most affected hub gene and mir-27a and REAL were recognized as two main upstream-regulators of the hub genes. Conclusions The identified hub genes from the hearts of co-expression modules could widen our understanding of the DN development and might be of targets of future investigations, exploring their therapeutic potentials for treatment of this complicated disease.

Proteomic Analysis of Mouse Kidney Tissue Associates Peroxisomal Dysfunction with Early Diabetic Kidney Disease

“…EHHADH (enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase) [ 63 ] was recently shown to oxidize medium- and long-chain fatty acids [ 64 , 65 ]. In line with our findings, decreased mRNA levels of EHHADH were detected in human DKD glomeruli tissues [ 66 ].…”

“…In line with our findings, previous studies detected increased levels of pipecolate in T1D mice compared to healthy controls [ 61 ]. Further, decreased mRNA levels of PIPOX were also reported in human DKD glomerular tissues [ 66 ].…”

Upregulation of T Cell Receptor Signaling Pathway Components in Gestational Diabetes Mellitus Patients: Joint Analysis of mRNA and circRNA Expression Profiles

“…Gene expression microarrays have been widely used in diabetic studies because alterations in transcriptional profiles provide a robust and sensitive way to better understand the pathogenesis of the disease. mRNA and ncRNA microarray analyses have previously been used to investigate the mechanisms underlying diabetic neuropathy (24), diabetic nephropathy (25), diabetic cardiomyopathy (26), and diabetic periodontitis (27). Similarly, microarray analyses have also been conducted in GDM.…”

Metabolic Variation Dictates Cardiac Pathogenesis in Patients With Tetralogy of Fallot

“…Xu et al found that the high expression level of the gene encoding EHHADH may be closely related to heart damage caused by exposure to hexafluoropropylene oxide dimer acid (33). Gholaminejad et al suggested that the gene encoding EHHADH plays an important role in the development of diabetic nephropathy in end-stage renal disease (34). In addition, Chen et al illustrated that EHHADH expression was significantly upregulated in the left atrial biopsy specimens of patients with mitral regurgitation compared with those with aortic valve disease (35).…”