Abstract
BackgroundImmunoglobulin A nephropathy (IgAN) is one of the most common primary glomerulonephritis and a serious health concern worldwide; though still the underlying molecular mechanisms of IgAN are yet to be known and there is no efficient treatment for this disease. The main goal of this study was to explore the IgAN underlying pathogenic pathways, plus identifying the disease correlated modules and genes using the weighted gene co-expression network analysis (WGCNA) algorithm.ResultsGSE104948 dataset (the expression data from glomerular tissue of IgAN patients) was analyzed and the identified differentially expressed genes (DEGs) were introduced to the WGCNA algorithm for building co-expression modules. Genes were classified into six co-expression modules. Genes of the disease’s most correlated module were mainly enriched in the immune system, cell–cell communication and transmembrane cell signaling pathways. The PPI network was constructed by genes in all the modules and after hub-gene identification and validation steps, 11 genes, mostly transmembrane proteins (CD44, TLR1, TLR2, GNG11, CSF1R, TYROBP, ITGB2, PECAM1), as well as DNMT1, CYBB and PSMB9 were identified as potentially key players in the pathogenesis of IgAN. In the constructed regulatory network, hsa-miR-129-2-3p, hsa-miR-34a-5p and hsa-miR-27a-3p, as well as STAT3 were spotted as top molecules orchestrating the regulation of the hub genes.ConclusionsThe excavated hub genes from the hearts of co-expressed modules and the PPI network were mostly transmembrane signaling molecules. These genes and their upstream regulators could deepen our understanding of IgAN and be considered as potential targets for hindering its progression.
Highlights
IgA nephropathy (IgAN) or Berger’s disease is one of the main causes of kidney failure worldwide [1, 2]
Preprocessing, analysis, and identification of differentially expressed genes (DEGs): 4189 DEGs were identified based on false discovery rate (FDR) cutoff Before the dataset analysis, several preprocessing steps, including principal component analysis (PCA) and normalization procedures were performed to ensure the accuracy of the main analysis
A heatmap and a volcano plot representing top 50 DEGs based on FDR value and the results of the analyzed dataset are depicted in Fig. 2E, F
Summary
IgA nephropathy (IgAN) or Berger’s disease is one of the main causes of kidney failure worldwide [1, 2]. (IgA1)-contained complexes in kidneys will cause local inflammations and subsequently hamper the normal function of kidneys, which is filtering of waste out of the blood. Continuation of this condition results in end-stage renal disease (ESRD) in about 40% of patients [3]. Immunoglobulin A nephropathy (IgAN) is one of the most common primary glomerulonephritis and a serious health concern worldwide; though still the underlying molecular mechanisms of IgAN are yet to be known and there is no efficient treatment for this disease. The main goal of this study was to explore the IgAN underlying pathogenic pathways, plus identifying the disease correlated modules and genes using the weighted gene coexpression network analysis (WGCNA) algorithm
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