Computational and Structural Biotechnology Journal (Jan 2023)
Network-based identification and prioritization of key transcriptional factors of diabetic kidney disease
Abstract
Diabetic nephropathy (DN) is one of the most established microvascular complications of diabetes and a key cause of end-stage renal disease. It is well established that gene susceptibility to DN plays a critical role in disease pathophysiology. Therefore, many genetic studies have been performed to categorize candidate genes in prominent diabetic cohorts, aiming to investigate DN pathogenesis and etiology. In this study, we performed a meta-analysis on the expression profiles of GSE1009, GSE30122, GSE96804, GSE99340, GSE104948, GSE104954, and GSE111154 to identify critical transcriptional factors associated with DN progression. The analysis was conducted for all individual datasets for each kidney tissue (glomerulus, tubules, and kidney cortex). We identified distinct clusters of susceptibility genes that were dysregulated in a renal compartment-specific pattern. Further, we recognized a small but a closely connected set of these susceptibility genes enriched for podocyte differentiation, several of which were characterized as genes encoding critical transcriptional factors (TFs) involved in DN development and podocyte function. To validate the role of identified TFs in DN progression, we functionally validated the three main TFs (DACH1, LMX1B, and WT1) identified through differential gene expression and network analysis using the hyperglycemic zebrafish model. We report that hyperglycemia-induced altered gene expression of the key TF genes leads to morphological abnormalities in zebrafish glomeruli, pronephric tubules, proximal and distal ducts. This study demonstrated that altered expression of these TF genes could be associated with hyperglycemia-induced nephropathy and, thus, aids in understanding the molecular drivers, essential genes, and pathways that trigger DN initiation and development.
