Abstract

BackgroundDiabetic 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.MethodsThe 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.ResultsAfter 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.ConclusionsThe 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.

Highlights

  • Diabetic nephropathy (DN) is the major complication of diabetes mellitus, and leading cause of endstage renal disease

  • Inflammatory processes, oxidative stress, overactive renin-angiotensin-aldosterone system (RAAS) and renal fibrosis are among the wellknown pathogenesis features of DN [2]

  • The present study revealed the downregulation of Glucose transporter 2 (GLUT2) in DN samples and introduced this transporter as a hub gene

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Summary

Introduction

Diabetic nephropathy (DN) is the major complication of diabetes mellitus, and leading cause of endstage renal disease. 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. Podocyte autophagy, mitochondria dysfunction, as well as some genetic and epigenetic modulations are among recently identified features of DN pathogenesis [3]. Despite such findings, current knowledge about the DN pathogenesis is not sufficient and treatment of this enigmatic disease is principally based on controlling the blood pressure, lowering the blood glucose, blocking the reninangiotensin system and application of sodium/glucose cotransporter 2 inhibitors [4, 5]. Construction of gene coexpression modules, and identifying hub genes based on their correlations with a trait are valuable features of this algorithm [8, 9]

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