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Ion Mobility-Mass Spectrometry Techniques for Determining the Structure and Mechanisms of Metal Ion Recognition and Redox Activity of Metal Binding Oligopeptides
Published on: September 7, 2019
Bioinformatics-based exploration of the role of copper metabolism in chronic glomerulonephritis
Lingjun Sun1, Xiaoying Deng2, Beibei Yang3
1Department of Nephrology, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Background:
Chronic glomerulonephritis is a prevalent renal disorder in clinical practice. A metabolic imbalance in copper, a vital trace element in the human body, is potentially linked to a myriad of diseases. Consequently, this study aimed to elucidate the role of copper metabolism in the onset and progression of chronic glomerulonephritis.
Methods:
Public microarray datasets gene expression omnibus series(GSE) 66494, GSE32591, and GSE116626 were procured from the gene expression omnibus database, encompassing clinical information on chronic glomerulonephritis and normal kidney tissues. Differential gene expression analysis was conducted, followed by the intersection of the differentially expressed genes from the 3 datasets with those related to copper metabolism. Furthermore, STRING and Cytoscape were used to construct a protein-protein interaction (PPI) network; PPI hub genes were identified via the cytoHubba plugin, and gene set enrichment analysis was performed. Tissues were subsequently collected from chronic glomerulonephritis patients at our hospital; hematoxylin and eosin, periodic acid-silver methenamine, and Masson staining were conducted; and transmission electron microscopy was performed. Pivotal genes were selected for real time quantitative polymerase chain reaction (PCR) (RT-qPCR) validation, and serum copper ion levels were measured. Additionally, CIBERSORT analysis was employed to assess immune cell infiltration and its correlation with pivotal genes.
Results:
Differential gene expression analysis revealed 25 differentially expressed copper metabolism-related genes (CMRGs), comprising 11 upregulated genes and 14 downregulated genes. PPI network construction and gene correlation analysis ultimately identified aconitase (ACO1) and superoxide dismutase (SOD2) as pivotal genes for RT-qPCR validation. The results demonstrated that ACO1 was expressed at low levels in lupus nephritis tissues, whereas SOD2 was highly expressed in immunoglobulin A nephropathy and diabetic nephropathy tissues. Moreover, immune infiltration analysis revealed that diverse immune cell types, including T cells, B cells, and macrophages, are intricately associated with the onset and progression of chronic glomerulonephritis in patient tissues. Differential and correlation analyses of CMRGs revealed that T cells, plasma cells, and monocyte-macrophages are involved in the biological processes of copper metabolism.
Conclusion:
This study suggests that the CMRGs ACO1 and SOD2 may modulate the inflammatory response and immune microenvironment in chronic glomerulonephritis by regulating immune cell activation and function, thereby facilitating disease progression.
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