Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy
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 GE...
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BMC
2025-02-01
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| Series: | European Journal of Medical Research |
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| Online Access: | https://doi.org/10.1186/s40001-025-02323-x |
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| author | Jun Peng Wenqi Zhao Lu Zhou Kun Ding |
| author_facet | Jun Peng Wenqi Zhao Lu Zhou Kun Ding |
| author_sort | Jun Peng |
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| description | 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. |
| format | Article |
| id | doaj-art-b35deb0602c84461a5bd0ea4b6e0a10e |
| institution | Kabale University |
| issn | 2047-783X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
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| series | European Journal of Medical Research |
| spelling | doaj-art-b35deb0602c84461a5bd0ea4b6e0a10e2025-02-09T12:26:33ZengBMCEuropean Journal of Medical Research2047-783X2025-02-0130111210.1186/s40001-025-02323-xInhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathyJun Peng0Wenqi Zhao1Lu Zhou2Kun Ding3Nephrology Department, Central Theater Command General Hospital of the Chinese People’s Liberation ArmyNephrology Department, Central Theater Command General Hospital of the Chinese People’s Liberation ArmyNephrology Department, Central Theater Command General Hospital of the Chinese People’s Liberation ArmyNephrology Department, Central Theater Command General Hospital of the Chinese People’s Liberation ArmyAbstract 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.https://doi.org/10.1186/s40001-025-02323-xDiabetic nephropathyComplement systemImmune infiltrationWeighted correlation network analysisMachine learning |
| spellingShingle | Jun Peng Wenqi Zhao Lu Zhou Kun Ding Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy European Journal of Medical Research Diabetic nephropathy Complement system Immune infiltration Weighted correlation network analysis Machine learning |
| title | Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy |
| title_full | Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy |
| title_fullStr | Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy |
| title_full_unstemmed | Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy |
| title_short | Inhibition of complement system-related gene ITGB2 attenuates epithelial–mesenchymal transition and inflammation in diabetic nephropathy |
| title_sort | inhibition of complement system related gene itgb2 attenuates epithelial mesenchymal transition and inflammation in diabetic nephropathy |
| topic | Diabetic nephropathy Complement system Immune infiltration Weighted correlation network analysis Machine learning |
| url | https://doi.org/10.1186/s40001-025-02323-x |
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