ArticleFrontiers in immunology2023
Identification of biomarkers related to immune and inflammation in membranous nephropathy: comprehensive bioinformatic analysis and validation.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Serum PLA2R-IgG4/PLA2R-IgG ratio dynamics reveal pathogenic autoantibody subclass switch during progression of PLA2R-associated membranous nephropathy.Annals of medicine · 2026Article
- Gut and Glomerular Barriers Determine Nanoplastic Fate and Systemic Impact.ACS environmental Au · 2026Article
- Integrative single-cell and bulk transcriptomic analysis identifies lesion-associated gene signatures for prognostic stratification and therapeutic guidance in head and neck squamous cell carcinoma.Biochemistry and biophysics reports · 2026Article
- Integrated Transcriptomic and Machine Learning Analyses Identify KCNN3 and TLR10 as Candidate Cell-Type-Associated Molecules in Idiopathic Membranous Nephropathy.International journal of general medicine · 2026Article
- Elevated SLC1A5 links to inflamed endothelial cells and proteinuria in membranous nephropathy patients.PeerJ · 2025Article
- Identification of key genes in membranous nephropathy and non-alcoholic fatty liver disease by bioinformatics and machine learning.Frontiers in immunology · 2025Article
- SPDYC serves as a prognostic biomarker related to lipid metabolism and the immune microenvironment in breast cancer.Immunologic research · 2024Article
- Identification and validation of biomarkers in membranous nephropathy and pan-cancer analysis.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Membranous nephropathy (MN) is an autoimmune glomerular disease that is predominantly mediated by immune complex deposition and complement activation. The aim of this study was to identify key biomarkers of MN and investigate their association with immune-related mechanisms, inflammatory cytokines, chemokines and chemokine receptors (CCRs). Methods: MN cohort microarray expression data were downloaded from the GEO database. Differentially expressed genes (DEGs) in MN were identified, and hub genes were determined using a protein-protein interaction (PPI) network. The relationships between immune-related hub genes, immune cells, CCRs, and inflammatory cytokines were examined using immune infiltration analysis, gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA). Finally, the immune-related hub genes in MN were validated using ELISA. Results: In total, 501 DEGs were identified. Enrichment analysis revealed the involvement of immune- and cytokine-related pathways in MN progression. Using WGCNA and immune infiltration analysis, 2 immune-related hub genes ( Conclusion: Our study identified
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.