{"title":"Inhibition of complement system-related gene ITGB2 attenuates epithelial-mesenchymal transition and inflammation in diabetic nephropathy.","authors":"Jun Peng, Wenqi Zhao, Lu Zhou, Kun Ding","doi":"10.1186/s40001-025-02323-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Emerging evidences have indicated a role of the complement system in the pathogenesis of diabetic nephropathy (DN). Thus, this study was conducted to explore the complement system-related key biomarkers for patients with DN.</p><p><strong>Methods: </strong>DN microarray datasets were downloaded from the GEO database, followed by differentially expressed genes (DEGs) screening. Complement system-related genes (CSRGs) were searched from various databases. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to screen the DN-related genes, then the differential CSRGs (DCSRGs) were identified, followed by protein-protein interaction (PPI) network construction. In addition, key biomarkers were acquired by two machine learning algorithms, then immune infiltration analysis, Gene Set Enrichment Analysis (GSEA), and potential drugs screening were conducted. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and western blotting were utilized to detect the ITGB2 expression. Then the cell viability, inflammatory factors, and the expression of epithelial-mesenchymal transition (EMT) and fibrosis markers were determined by using Cell Counting Kit-8 (CCK-8) assay, enzyme linked immunosorbent assay (ELISA), western blotting assays, respectively.</p><p><strong>Results: </strong>In total, 1012 DEGs and 974 DN-related genes were screened, and intersection analysis of the three (DN-related genes, DEGs and CSRGs) yielded 13 intersection genes, which were considered as the DCSRGs. Subsequently, 2 key biomarkers were identified by machine learning, namely VWF and ITGB2. The VWF and ITGB2 were both enriched in the pathways of chemokine signaling pathway, CAMs, focal adhesion and natural killer cell-mediated cytotoxicity, and significantly correlated with the activated mast cells, resting NK cells, and macrophages. Also, VWF and ITGB2 were significantly related to the clinical features, including age, serum creatinine level, and GFR (MDRD). Besides, mRNA and protein expression levels of ITGB2 in HG-treated HK-2 cells were remarkably elevated. Moreover, the viability of HK-2 cells, expression of TNF-α, IL-6, IL-12, α-SMA, E-cadherin and vimentin in HK-2 cells changed by HG administration were reversed by ITGB2-silence.</p><p><strong>Conclusion: </strong>Complement system-related gene ITGB2 was overexpressed in DN, and inhibition of ITGB2 attenuated EMT and inflammation in DN.</p>","PeriodicalId":11949,"journal":{"name":"European Journal of Medical Research","volume":"30 1","pages":"87"},"PeriodicalIF":2.8000,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11806615/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Medical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40001-025-02323-x","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: Emerging evidences have indicated a role of the complement system in the pathogenesis of diabetic nephropathy (DN). Thus, this study was conducted to explore the complement system-related key biomarkers for patients with DN.
Methods: DN microarray datasets were downloaded from the GEO database, followed by differentially expressed genes (DEGs) screening. Complement system-related genes (CSRGs) were searched from various databases. Weighted Gene Co-expression Network Analysis (WGCNA) was employed to screen the DN-related genes, then the differential CSRGs (DCSRGs) were identified, followed by protein-protein interaction (PPI) network construction. In addition, key biomarkers were acquired by two machine learning algorithms, then immune infiltration analysis, Gene Set Enrichment Analysis (GSEA), and potential drugs screening were conducted. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and western blotting were utilized to detect the ITGB2 expression. Then the cell viability, inflammatory factors, and the expression of epithelial-mesenchymal transition (EMT) and fibrosis markers were determined by using Cell Counting Kit-8 (CCK-8) assay, enzyme linked immunosorbent assay (ELISA), western blotting assays, respectively.
Results: In total, 1012 DEGs and 974 DN-related genes were screened, and intersection analysis of the three (DN-related genes, DEGs and CSRGs) yielded 13 intersection genes, which were considered as the DCSRGs. Subsequently, 2 key biomarkers were identified by machine learning, namely VWF and ITGB2. The VWF and ITGB2 were both enriched in the pathways of chemokine signaling pathway, CAMs, focal adhesion and natural killer cell-mediated cytotoxicity, and significantly correlated with the activated mast cells, resting NK cells, and macrophages. Also, VWF and ITGB2 were significantly related to the clinical features, including age, serum creatinine level, and GFR (MDRD). Besides, mRNA and protein expression levels of ITGB2 in HG-treated HK-2 cells were remarkably elevated. Moreover, the viability of HK-2 cells, expression of TNF-α, IL-6, IL-12, α-SMA, E-cadherin and vimentin in HK-2 cells changed by HG administration were reversed by ITGB2-silence.
Conclusion: Complement system-related gene ITGB2 was overexpressed in DN, and inhibition of ITGB2 attenuated EMT and inflammation in DN.
期刊介绍:
European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.