Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

P0971IDENTIFICATION OF HUB GENES ASSOCIATED WITH THE DEPOSITION OF EXTRACELLULAR MATRIX AND SPECIFIC FOR DIABETIC NEPHROPATHY BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS

View through CrossRef
Abstract Background and Aims Diabetic nephropathy (DN) and its most severe manifestation, end-stage renal disease (ESRD), remains one of the leading causes of reduced lifespan in people with diabetes. Identifying novel molecules that are involved in the pathogenesis of DN has both diagnostic and therapeutic implications. The gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology approach that provide the approach of association between gene modules and clinical traits to find the module involvement into the certain phenotypic trait. The goal of this study was to identify hub genes and their roles in DN from the aspect of whole gene transcripts analysis. Method Various types of chronic kidney diseases (CKD), including DN, microarray-based mRNA gene expression data, listed in the Gene Expression Omnibus (GEO) database, were analyzed. Next, we constructed a weighted gene co-expression network and identified modules distinguishing DN from normal or other types of CKD by WGCNA. Functional annotations of the genes in modules specialized for DN were analyzed by Gene Ontology (GO) enrichment analysis. Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes specific for DN were obtained. Furthermore, we drew ROC curves to determine the diagnosis and differential diagnosis value to DN of hub genes. Finally, another study of microarray in the GEO database was selected to verify the expression level of hub genes and in the “Nephroseq” database, the correlation between the gene expression level and eGFR was analyzed. Results “GSE99339”, glomerular tissue microarray in 187 patients with a total of 10947 genes, was selected for analysis. After excluding the inappropriate cases, a total of 179 specimens were analyzed, including 14 cases of DN, 22 cases of focal segmental glomerulosclerosis (FSGS), 15 cases of hypertensive nephropathy (HT), 26 cases of IgA nephropathy (IgAN), 13 cases of minimal change disease (MCD), 21 cases of membranous nephropathy (MGN), 23 cases of rapidly progressive glomerulonephritis (RPGN), 30 cases of lupus nephritis (LN) and 14 cases of kidney tissue adjacent to tumor. Co-expression network analysis by WGCNA identified 23 distinct gene modules of the total 10947 genes and revealed “MEsaddlegreen” module was strongly correlated with DN (r=0,54), but not with other groups. GO functional annotation showed that these 64 genes in the “MEsaddlegreen” module mainly enriched in the deposition of extracellular matrix, which represents the specific and diagnostic pathophysiological process of DN. Further PPI and hub gene screening analysis revealed that LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD can be served as hub genes, which had been proved to play an important role in the deposition of extracellular matrix. Furthermore, we found that the expression of hub genes was the highest in DN group and for the diagnosis value of DN by each gene, the area under the ROC curve is about 0.75∼0.95. The external verification of another study showed that compared with the normal control group, the expression of these hub genes was the highest in the DN group, and their expression level was negatively correlated with eGFR. Conclusion Using WGCNA and further bioinformatics approach, we identified six hub genes that appear to be identical to DN development. As such, they may represent potential diagnostic biomarkers as well as therapeutic targets with clinical utility.
Title: P0971IDENTIFICATION OF HUB GENES ASSOCIATED WITH THE DEPOSITION OF EXTRACELLULAR MATRIX AND SPECIFIC FOR DIABETIC NEPHROPATHY BY WEIGHTED GENE CO-EXPRESSION NETWORK ANALYSIS
Description:
Abstract Background and Aims Diabetic nephropathy (DN) and its most severe manifestation, end-stage renal disease (ESRD), remains one of the leading causes of reduced lifespan in people with diabetes.
Identifying novel molecules that are involved in the pathogenesis of DN has both diagnostic and therapeutic implications.
The gene co-expression network analysis (WGCNA) algorithm represents a novel systems biology approach that provide the approach of association between gene modules and clinical traits to find the module involvement into the certain phenotypic trait.
The goal of this study was to identify hub genes and their roles in DN from the aspect of whole gene transcripts analysis.
Method Various types of chronic kidney diseases (CKD), including DN, microarray-based mRNA gene expression data, listed in the Gene Expression Omnibus (GEO) database, were analyzed.
Next, we constructed a weighted gene co-expression network and identified modules distinguishing DN from normal or other types of CKD by WGCNA.
Functional annotations of the genes in modules specialized for DN were analyzed by Gene Ontology (GO) enrichment analysis.
Through protein-protein interaction (PPI) analysis and hub gene screening, the hub genes specific for DN were obtained.
Furthermore, we drew ROC curves to determine the diagnosis and differential diagnosis value to DN of hub genes.
Finally, another study of microarray in the GEO database was selected to verify the expression level of hub genes and in the “Nephroseq” database, the correlation between the gene expression level and eGFR was analyzed.
Results “GSE99339”, glomerular tissue microarray in 187 patients with a total of 10947 genes, was selected for analysis.
After excluding the inappropriate cases, a total of 179 specimens were analyzed, including 14 cases of DN, 22 cases of focal segmental glomerulosclerosis (FSGS), 15 cases of hypertensive nephropathy (HT), 26 cases of IgA nephropathy (IgAN), 13 cases of minimal change disease (MCD), 21 cases of membranous nephropathy (MGN), 23 cases of rapidly progressive glomerulonephritis (RPGN), 30 cases of lupus nephritis (LN) and 14 cases of kidney tissue adjacent to tumor.
Co-expression network analysis by WGCNA identified 23 distinct gene modules of the total 10947 genes and revealed “MEsaddlegreen” module was strongly correlated with DN (r=0,54), but not with other groups.
GO functional annotation showed that these 64 genes in the “MEsaddlegreen” module mainly enriched in the deposition of extracellular matrix, which represents the specific and diagnostic pathophysiological process of DN.
Further PPI and hub gene screening analysis revealed that LUM, ELN, FBLN1, MMP2, FBLN5 and FMOD can be served as hub genes, which had been proved to play an important role in the deposition of extracellular matrix.
Furthermore, we found that the expression of hub genes was the highest in DN group and for the diagnosis value of DN by each gene, the area under the ROC curve is about 0.
75∼0.
95.
The external verification of another study showed that compared with the normal control group, the expression of these hub genes was the highest in the DN group, and their expression level was negatively correlated with eGFR.
Conclusion Using WGCNA and further bioinformatics approach, we identified six hub genes that appear to be identical to DN development.
As such, they may represent potential diagnostic biomarkers as well as therapeutic targets with clinical utility.

Related Results

Diabetic Nephropathy: Advancement in Molecular Mechanism, Pathogenesis, and Management by Pharmacotherapeutics and Natural Compounds
Diabetic Nephropathy: Advancement in Molecular Mechanism, Pathogenesis, and Management by Pharmacotherapeutics and Natural Compounds
The primary cause of End-stage Renal Disease (ESRD) and a possible chronic microvascular consequence of diabetes mellitus is Diabetic Nephropathy (DN). The early stages of diabetic...
The Number of Teeth Is Associated with Diabetic Nephropathy
The Number of Teeth Is Associated with Diabetic Nephropathy
Background: Progression of diabetic nephropathy has serious effects on the life expectancy of diabetic patients. Although diagnoses, lifestyle interventions, and treatment of diabe...
CD4 and CXCR5 in Patients with Diabetic Nephropathy
CD4 and CXCR5 in Patients with Diabetic Nephropathy
Background: Diabetes is a metabolic condition characterized by hyperglycemia caused by defects in insulin secretion, insulin activity, or both. Diabetic nephropathy (DN) is one of ...
Exploring the Diagnosis of Immune-Related Genes in Metabolic Syndrome Based on Three Algorithms
Exploring the Diagnosis of Immune-Related Genes in Metabolic Syndrome Based on Three Algorithms
Abstract Background The pathogenesis of Metabolic Syndrome (MetS) remains largely unexplored. This study aims to explore the immune-related genes in MetS. Methods The mic...
Renal biopsy in diabetic patients: Histopathological and clinical correlations
Renal biopsy in diabetic patients: Histopathological and clinical correlations
Introduction: Diabetes is the leading cause of chronic kidney disease and end-stage kidney disease worldwide. A kidney biopsy in a diabetic patient must be considered when non-diab...
Effect of retinoic acid in experimental diabetic nephropathy
Effect of retinoic acid in experimental diabetic nephropathy
Although the pathogenetic mechanism of diabetic nephropathy has not been elucidated, an inflammatory mechanism has been suggested to contribute to its progression. Monocyte chemoat...
Identification of key genes in DN based on lipid metabolism
Identification of key genes in DN based on lipid metabolism
Abstract Background Diabetic nephropathy (DN), which is one of the most common systemic microvascular complications of diabetes mellitus, is extremely harmful to the patie...

Back to Top