| Autor: |
ZHAO Sheng, LI Wenchuan, DONG Lan, LIAN Rong, LI Yuejiao, HE Feng |
| Jazyk: |
čínština |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Xin yixue, Vol 55, Iss 5, Pp 321-327 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
0253-9802 |
| DOI: |
10.3969/j.issn.0253-9802.2024.05.001 |
| Popis: |
Objective To identify hub genes associated with ferroptosis in the progression of diabetic nephropathy （DN） through bioinformatics analysis， offering novel insights into DN treatment. Methods Differentially expressed genes （DEGs） in DN were screened using RNA sequencing dataset GSE142025， and Gene Ontology （GO） and Gene Set Enrichment Analysis （GSEA） were utilized for functional annotation. Subsequently， the Weighted Gene Co-expression Network Analysis （WGCNA）was conducted to pinpoint key genes. Venn diagrams aided in identifying hub genes among ferroptosis-related genes （FRGs） common to DEGs and key genes. ROC curves were employed to assess the clinical diagnostic potential of these hub genes. Immunohistochemistry （IHC）was conducted to detect the expression levels of hub genes in DN patients and normal kidney tissues. Results 1 916 DEGs were identified between the DN and control （NC） groups. GO enrichment analysis revealed that DEGs were mainly involved in inflammation-related biological processes. GSEA analysis found significant enrichment in processes related to iron ion binding. Among 12 co-expression modules constructed by WGCNA， grey60， turquoise， and grey modules showed the highest correlation with DN. 188 key genes were selected from 3 modules based on the screening criteria， among which 2 were FRGs shared by DEGs， namely ceruloplasmin （CP） gene and lipocalin-2 （LCN2） gene. ROC curves confirmed high clinical diagnostic value of these two genes. IHC results showed upregulated expression of both two genes in DN patient samples （both P < 0.05）， consistent with the findings of bioinformatics analysis. Conclusion CP and LCN2 could be involved in the progression of DN by inhibiting ferroptosis， serving as promising biomarkers and treatment targets for DN. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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