Background: Membranous nephropathy (MN) is one of the most common pathologies of the nephrotic syndrome. MN is closely associated with the autoimmune response but its molecular mechanism remains unclear. Bioinformatic network analysis can be used to identify disease-related hub genes.
Methods: The microarray data set GSE47183 of patients with MN containing 21 MN samples and 13 control samples that were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package. Thereafter, gene ontology (GO) enrichment was performed for DEGs using the clusterProfiler package. The protein-protein interaction (PPI) network was established through the Search Tool for the Retrieval of Interacting Genes database and visualized using Cytoscape. Finally, the hub genes were identified through the maximal clique centrality method.
Result: A total of 642 DEGs were recognized, consisting of 458 upregulated genes and 184 downregulated genes. GO enrichment analysis indicates that DEGs for MN are mainly related to antigen processing and presentation. For the PPI network, we identified approximately nine hub genes. Considering data from the literature, we ultimately identified PSMB8 as a novel hub gene, which could play a significant role in the occurrence and development of MN.
Conclusion: This study is the first to identify novel hub genes with transcriptome microarray data in MN using bioinformatics. The newly discovered hypothetical hub genes should be functionally tested to determine if they truly play an etiologic role in MN.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1089/gtmb.2018.0137 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Identification of Anoikis-Related Genes in Chronic Kidney Disease Based on Bioinformatics Analysis Combined with Experimental Validation.
J Inflamm Res
January 2025
Department of Pharmacology, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.
Background: Chronic kidney disease (CKD) is a progressive condition that arises from diverse etiological factors, resulting in structural alterations and functional impairment of the kidneys. We aimed to establish the Anoikis-related gene signature in CKD by bioinformatics analysis.
Methods: We retrieved 3 datasets from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) of them, which were intersected with Anoikis-related genes (ARGs) to derive Anoikis-related differentially expressed genes (ARDEGs).
Identification of hub genes and immune-related pathways in acute myeloid leukemia: insights from bioinformatics and experimental validation.
Front Immunol
January 2025
Postdoctoral Workstation, Liaocheng People's Hospital, Liaocheng, China.
Background: This study aims to identify the hub genes and immune-related pathways in acute myeloid leukemia (AML) to provide new theories for immunotherapy.
Methods: We use bioinformatics methods to find and verify the hub gene. At the same time, we use the results of GSEA enrichment analysis to find immune-related mediators.
Comprehensive analysis of ferroptosis-related genes reveals potential therapeutic targets in osteoporosis patients: a computational analysis and experiments.
Front Genet
January 2025
Department of Orthopedics, First Hospital of Jiaxing, Jiaxing, China.
Background: Ferroptosis-related genes have been reported to play important roles in many diseases, but their molecular mechanisms in osteoporosis have not been elucidated.
Methods: Based on two independent GEO datasets (GSE35956 and GSE35958), and GSE35959 as the validation dataset, we comprehensively elucidated the pathological mechanism of ferroptosis-related genes in osteoporosis by GO analyses, KEGG analyses and a PPI network. Then, We used Western Blot (WB) and Quantitative real-time polymerase chain reaction (qPCR) to verify the expression level of KMT2D, a ferroptosis-related hub gene, in clinical samples.
Identification of Ferroptosis-related Genes for Diabetic Nephropathy by Bioinformatics and Experimental Validation.
Curr Pharm Des
January 2025
Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, Jiangsu Province, China.
Objective: The present study delves into the exploration of diagnostic biomarkers linked with ferroptosis in the context of diabetic nephropathy, unraveling their underlying molecular mechanisms.
Methods: In this study, we retrieved datasets GSE96804 and GSE30529 as the training cohort, followed by screening for Differentially Expressed Genes (DEGs). By intersecting these DEGs with known ferroptosisrelated genes, we obtained the differentially expressed genes related to ferroptosis (DEFGs).
CDKN3 as a key regulator of G2M phase in triple-negative breast cancer: Insights from multi-transcriptomic analysis.
IUBMB Life
January 2025
Precision Medicine Laboratory, School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
Triple-negative breast cancer (TNBC) remains a significant global health challenge, emphasizing the need for precise identification of patients with specific therapeutic targets and those at high risk of metastasis. This study aimed to identify novel therapeutic targets for personalized treatment of TNBC patients by elucidating their roles in cell cycle regulation. Using weighted gene co-expression network analysis (WGCNA), we identified 83 hub genes by integrating gene expression profiles with clinical pathological grades.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!