Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis
BackgroundRheumatoid arthritis (RA) is a chronic autoimmune disease in which autophagy is pivotal in its pathogenesis. This study aims to identify autophagy-related genes associated with RA and investigate their functional roles.MethodsWe performed mRNA sequencing to identify differentially expresse...
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2025.1563911/full |
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| author | Runrun Zhang Runrun Zhang Wenhan Huang Wenhan Huang Ting Zhao Ting Zhao Jintao Fang Jintao Fang Cen Chang Cen Chang Dongyi He Dongyi He Xinchang Wang Xinchang Wang |
| author_facet | Runrun Zhang Runrun Zhang Wenhan Huang Wenhan Huang Ting Zhao Ting Zhao Jintao Fang Jintao Fang Cen Chang Cen Chang Dongyi He Dongyi He Xinchang Wang Xinchang Wang |
| author_sort | Runrun Zhang |
| collection | DOAJ |
| description | BackgroundRheumatoid arthritis (RA) is a chronic autoimmune disease in which autophagy is pivotal in its pathogenesis. This study aims to identify autophagy-related genes associated with RA and investigate their functional roles.MethodsWe performed mRNA sequencing to identify differentially expressed genes (DEGs) between RA and osteoarthritis (OA) and intersected these with autophagy-related genes to obtain autophagy-related DEGs (ARDEGs) in RA. Bioinformatics and machine learning approaches were used to identify key biomarkers. Functional experiments, including real-time cellular analysis (RTCA), scratch healing, and flow cytometry, were conducted to examine the effects of gene silencing on the proliferation and migration of MH7A cells.ResultsA total of 37 ARDEGs were identified in RA. Through bioinformatics analysis, interferon regulatory factor 4 (IRF4) emerged as a key hub gene, with its high expression confirmed in RA synovial tissues and RA FLS cells. IRF4 knockdown inhibited the proliferation and migration and promoted the death of MH7A cells.ConclusionIRF4 is an autophagy-related diagnostic biomarker for RA. Targeting IRF4 could serve as a potential diagnostic and therapeutic strategy for RA, although further clinical studies are required to validate its effectiveness. |
| format | Article |
| id | doaj-art-3dd8200bf565476c9304d1b96c8167cd |
| institution | Kabale University |
| issn | 2296-634X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj-art-3dd8200bf565476c9304d1b96c8167cd2025-08-20T03:42:53ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2025-03-011310.3389/fcell.2025.15639111563911Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritisRunrun Zhang0Runrun Zhang1Wenhan Huang2Wenhan Huang3Ting Zhao4Ting Zhao5Jintao Fang6Jintao Fang7Cen Chang8Cen Chang9Dongyi He10Dongyi He11Xinchang Wang12Xinchang Wang13The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaGuanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaInstitute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, ChinaGuanghua Clinical Medical College, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaInstitute of Arthritis Research in Integrative Medicine, Shanghai Academy of Traditional Chinese Medicine, Shanghai, ChinaThe Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaBackgroundRheumatoid arthritis (RA) is a chronic autoimmune disease in which autophagy is pivotal in its pathogenesis. This study aims to identify autophagy-related genes associated with RA and investigate their functional roles.MethodsWe performed mRNA sequencing to identify differentially expressed genes (DEGs) between RA and osteoarthritis (OA) and intersected these with autophagy-related genes to obtain autophagy-related DEGs (ARDEGs) in RA. Bioinformatics and machine learning approaches were used to identify key biomarkers. Functional experiments, including real-time cellular analysis (RTCA), scratch healing, and flow cytometry, were conducted to examine the effects of gene silencing on the proliferation and migration of MH7A cells.ResultsA total of 37 ARDEGs were identified in RA. Through bioinformatics analysis, interferon regulatory factor 4 (IRF4) emerged as a key hub gene, with its high expression confirmed in RA synovial tissues and RA FLS cells. IRF4 knockdown inhibited the proliferation and migration and promoted the death of MH7A cells.ConclusionIRF4 is an autophagy-related diagnostic biomarker for RA. Targeting IRF4 could serve as a potential diagnostic and therapeutic strategy for RA, although further clinical studies are required to validate its effectiveness.https://www.frontiersin.org/articles/10.3389/fcell.2025.1563911/fullrheumatoid arthritisIRF4autophagybioinformaticsmachine learning |
| spellingShingle | Runrun Zhang Runrun Zhang Wenhan Huang Wenhan Huang Ting Zhao Ting Zhao Jintao Fang Jintao Fang Cen Chang Cen Chang Dongyi He Dongyi He Xinchang Wang Xinchang Wang Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis Frontiers in Cell and Developmental Biology rheumatoid arthritis IRF4 autophagy bioinformatics machine learning |
| title | Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis |
| title_full | Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis |
| title_fullStr | Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis |
| title_full_unstemmed | Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis |
| title_short | Comprehensive analysis and validation of autophagy-related gene in rheumatoid arthritis |
| title_sort | comprehensive analysis and validation of autophagy related gene in rheumatoid arthritis |
| topic | rheumatoid arthritis IRF4 autophagy bioinformatics machine learning |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2025.1563911/full |
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