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DOI 10.1038/s41598-025-27363-5

Медицинская библиотека · Scientific reports · 2025

Autophagy related biomarkers in ulcerative colitis revealed by bioinformatics analysis and immune correlation.

Chen Xinyi Xue, Min Shichen, Shen Zhaofeng, Zhang Mengyuan, Huang Lejuan, Su Mengran, Shen Hong, Zhu Lei

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

Ulcerative colitis (UC) is a chronic inflammatory bowel disease of unknown etiology characterized by abnormal mucosal immune responses and persistent intestinal inflammation. UC significantly reduces quality of life and imposes a substantial economic burden. Early diagnosis and personalized treatment are crucial for improving outcomes; however, significant challenges remain. This study aimed to identify novel molecular targets for UC treatment. Gene expression data related to UC were obtained from the Gene Expression Omnibus, and differentially expressed genes (DEGs) were identified based on the criteria P < 0.05 and |logFC| > 0.5. The DEGs were intersected with autophagy-related genes (ARGs) to explore the relationship between UC pathogenesis and autophagy. LASSO regression, random forest regression, and support vector machine-recursive feature elimination were employed to screen for differentially expressed ARGs. The robustness and generalizability of the intersected genes were validated in external datasets and mouse models, and immune infiltration was analyzed to assess the interaction between UC and the immune system. PEA15 was identified as a potential UC diagnostic marker, and the diagnostic value of SERPINA1, CASP4, and CASP1 was reconfirmed. Our findings provide new insights into the pathogenesis of UC, facilitating early diagnosis and the development of personalized therapeutic strategies.

Для цитирования: Chen Xinyi Xue, Min Shichen, Shen Zhaofeng, Zhang Mengyuan, Huang Lejuan, Su Mengran, Shen Hong, Zhu Lei. Autophagy related biomarkers in ulcerative colitis revealed by bioinformatics analysis and immune correlation.. Scientific reports. 2025. DOI: 10.1038/s41598-025-27363-5.

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