An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks
Objective The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA–miRNA-lncRNA/circRNA network.Methods The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expres...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Renal Failure |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2023.2284212 |
| _version_ | 1827233688026349568 |
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| author | Yun Xia Zhang Jun Yuan Bai XiaoWei Pu Juan Lv En Lai Dai |
| author_facet | Yun Xia Zhang Jun Yuan Bai XiaoWei Pu Juan Lv En Lai Dai |
| author_sort | Yun Xia Zhang |
| collection | DOAJ |
| description | Objective The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA–miRNA-lncRNA/circRNA network.Methods The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Identification and enrichment analysis of differentially expressed genes (DEGs) were performed. the PPI networks of the DEGs were constructed and classified using the Cytoscape molecular complex detection (MCODE) plugin. Weighted gene coexpression network analysis (WGCNA) was used to identify critical gene modules. Least absolute shrinkage and selection operator regression analysis were used to screen for key biomarkers of the tubulointerstitium in FSGS, and the receiver operating characteristic curve was used to determine their diagnostic accuracy. The screening results were verified by quantitative real-time-PCR (qRT–PCR) and Western blot. The transcription factors (TFs) affecting the hub genes were identified by Cytoscape iRegulon. The mRNA–miRNA-lncRNA/circRNA network for identifying potential biomarkers was based on the starBase database.Results A total of 535 DEGs were identified. MCODE obtained eight modules. The green module of WGCNA had the greatest association with the tubulointerstitium in FSGS. PPARG coactivator 1 alpha (PPARGC1A) was screened as a potential tubulointerstitial biomarker for FSGS and verified by qRT–PCR and Western blot. The TFs FOXO4 and FOXO1 had a regulatory effect on PPARGC1A. The ceRNA network yielded 17 miRNAs, 32 lncRNAs, and 50 circRNAs.Conclusions PPARGC1A may be a potential biomarker in the tubulointerstitium of FSGS. The ceRNA network contributes to the comprehensive elucidation of the mechanisms of tubulointerstitial lesions in FSGS. |
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| id | doaj.art-2c5d996c05be4964a59a5514d37c8cc5 |
| institution | Directory Open Access Journal |
| issn | 0886-022X 1525-6049 |
| language | English |
| last_indexed | 2025-03-21T19:37:18Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj.art-2c5d996c05be4964a59a5514d37c8cc52024-06-03T10:02:15ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492023-12-0145210.1080/0886022X.2023.2284212An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networksYun Xia Zhang0Jun Yuan Bai1XiaoWei Pu2Juan Lv3En Lai Dai4College of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, ChinaCollege of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, ChinaCollege of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, ChinaCollege of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, ChinaCollege of Integrated Traditional and Western Medicine, Gansu University of Traditional Chinese Medicine, Lanzhou, ChinaObjective The purpose of this study was to identify potential biomarkers in the tubulointerstitium of focal segmental glomerulosclerosis (FSGS) and comprehensively analyze its mRNA–miRNA-lncRNA/circRNA network.Methods The expression data (GSE108112 and GSE200818) were downloaded from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Identification and enrichment analysis of differentially expressed genes (DEGs) were performed. the PPI networks of the DEGs were constructed and classified using the Cytoscape molecular complex detection (MCODE) plugin. Weighted gene coexpression network analysis (WGCNA) was used to identify critical gene modules. Least absolute shrinkage and selection operator regression analysis were used to screen for key biomarkers of the tubulointerstitium in FSGS, and the receiver operating characteristic curve was used to determine their diagnostic accuracy. The screening results were verified by quantitative real-time-PCR (qRT–PCR) and Western blot. The transcription factors (TFs) affecting the hub genes were identified by Cytoscape iRegulon. The mRNA–miRNA-lncRNA/circRNA network for identifying potential biomarkers was based on the starBase database.Results A total of 535 DEGs were identified. MCODE obtained eight modules. The green module of WGCNA had the greatest association with the tubulointerstitium in FSGS. PPARG coactivator 1 alpha (PPARGC1A) was screened as a potential tubulointerstitial biomarker for FSGS and verified by qRT–PCR and Western blot. The TFs FOXO4 and FOXO1 had a regulatory effect on PPARGC1A. The ceRNA network yielded 17 miRNAs, 32 lncRNAs, and 50 circRNAs.Conclusions PPARGC1A may be a potential biomarker in the tubulointerstitium of FSGS. The ceRNA network contributes to the comprehensive elucidation of the mechanisms of tubulointerstitial lesions in FSGS.https://www.tandfonline.com/doi/10.1080/0886022X.2023.2284212Focal segmental glomerulosclerosistubulointerstitiumweighted gene coexpression network analysisleast absolute shrinkage and selection operatorPPARGC1AmRNA–miRNA-lncRNA/circRNA network |
| spellingShingle | Yun Xia Zhang Jun Yuan Bai XiaoWei Pu Juan Lv En Lai Dai An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks Renal Failure Focal segmental glomerulosclerosis tubulointerstitium weighted gene coexpression network analysis least absolute shrinkage and selection operator PPARGC1A mRNA–miRNA-lncRNA/circRNA network |
| title | An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks |
| title_full | An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks |
| title_fullStr | An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks |
| title_full_unstemmed | An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks |
| title_short | An integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mRNA–miRNA-lncRNA/circRNA networks |
| title_sort | integrated bioinformatics approach to identify key biomarkers in the tubulointerstitium of patients with focal segmental glomerulosclerosis and construction of mrna mirna lncrna circrna networks |
| topic | Focal segmental glomerulosclerosis tubulointerstitium weighted gene coexpression network analysis least absolute shrinkage and selection operator PPARGC1A mRNA–miRNA-lncRNA/circRNA network |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2023.2284212 |
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