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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-12-20
DOI
https://doi.org/10.1038/s41598-025-27363-5
Citations
1
Primary Topic
Autophagy in Disease and Therapy
Type
article
Field-Weighted Citation Impact
1.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Hong Shen, Min Su, Seung‐Kee Min, Zhaofeng Shen et al.
1 citations
Scientific Reports
Autophagy in Disease and Therapy
1.35
article

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

Hong Shen, Min Su, Seung‐Kee Min, Zhaofeng Shen, Laurence Huang, Xiaojun Chen, Mengyuan Zhang, Lei Zhu
article en
1 citations

Abstract

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.

Scientific ReportsVol. 15(1)
Nanjing University of Chinese Medicine (CN)
Openalex Percentile: Top 13%
Autophagy in Disease and Therapy
1.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.