Role of Aging in Ulcerative Colitis Pathogenesis: A Focus on ETS1 as a Promising Biomarker
Man Ni,1,2 Weilong Peng,1,2 Xiaoguang Wang,1,2 Jingui Li1,2 1School of Veterinary Medicine, Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, 225009, People’s Republic of China; 2Joint International Research L...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2025-02-01
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| Series: | Journal of Inflammation Research |
| Subjects: | |
| Online Access: | https://www.dovepress.com/role-of-aging-in-ulcerative-colitis-pathogenesis-a-focus-on-ets1-as-a--peer-reviewed-fulltext-article-JIR |
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| Summary: | Man Ni,1,2 Weilong Peng,1,2 Xiaoguang Wang,1,2 Jingui Li1,2 1School of Veterinary Medicine, Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, 225009, People’s Republic of China; 2Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Yangzhou University, Yangzhou, Jiangsu, 225009, People’s Republic of ChinaCorrespondence: Jingui Li, School of Veterinary Medicine, Yangzhou University, No. 48, Daxue North Road, Hanjiang District, Yangzhou City, Jiangsu, 225009, People’s Republic of China, Email jgli@yzu.edu.cnPurpose: An increasing proportion of the aging population has led to a rapid increase in the number of elderly patients with ulcerative colitis (UC). However, the molecular mechanisms by which aging causes UC remain unclear. In this study, we explored the role of aging-related genes (ARGs) in UC pathogenesis and diagnosis prediction.Methods: Gene expression data were obtained from four independent datasets (GSE75214, GSE87466, GSE94648, and GSE169568) in the GEO database, and ARGs were derived from multiple public databases. After identifying UC-related ARGs, consistent clustering was performed to screen aging-related molecular subtypes, followed by the exploration of differences in the immune microenvironment and pathways between distinct subtypes. Next, core module genes were screened using WGCNA and then the hub genes were characterized using LASSO and random forest methods. Besides, the associations between hub genes, immune cells, and key pathways were explored. Finally, the expression levels of key genes were determined in a dextran sulfate sodium (DSS)-induced UC mouse model by qRT-PCR.Results: UC samples were classified into two subtypes (1 and 2), which displayed significant differences in the immune landscape and JAK/STAT signaling pathways. A series of machine learning algorithms was used to screen two feature genes (ETS1 and IL7R) to establish the diagnostic model, which exhibited satisfactory diagnostic efficiency. In addition, these hub genes were closely associated with the infiltration of specific immune cells (such as neutrophils, memory B cells, and M2 macrophages) as well as with the JAK/STAT pathway. Later, experimental validation confirmed that ETS1 expression was markedly increased in a mouse model of UC.Conclusion: Overall, aging, immune dysregulation, and UC process are closely associated. The identified feature genes, particularly ETS1, could serve as novel diagnostic biomarkers for UC. These findings have the potential to enhance the understanding of the age-related mechanisms of UC. Keywords: ulcerative colitis, aging, machine learning, immune microenvironment, biomarker |
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| ISSN: | 1178-7031 |