Decoding IBD progression: a dynamic biomarker atlas for personalized disease stratification

作者：Yi Tao, Lin-F Wang, Li Pan, Rui Sun, Yong-J Li, Ming‐Hong Sun, Li-J Zhang, Li-H Yang, Jia-J Jin, Xiaoni Zhong · 发表于：Journal of Translational Medicine · 年份：2025 · DOI：10.1186/s12967-025-07024-x · 被引用次数：6 · 研究领域：Gut microbiota and health、Inflammatory Bowel Disease、Gastrointestinal motility and disorders

BACKGROUND: Accurate staging is pivotal for tailoring treatment intensity, optimizing resource allocation, and improving long-term patient outcomes in IBD. The intestinal microbiota and transcriptional profiles emerge as critical determinants in IBD staging, demonstrating promise as non-invasive biomarkers for predicting disease progression and informing personalized therapeutic strategies. METHODS: We recruited 97 participants (IBD patients and healthy controls) at the First Affiliated Hospital of Chongqing Medical University, collecting fecal and serum samples for integrated multi-omics analysis. Microbial community profiling was performed via 16S rRNA sequencing, and host transcriptomic landscapes were characterized using RNA-seq. Stage-specific microbial signatures were identified using NetMoss, a network-based microbial community analysis tool, while differential gene expression across IBD stages was determined by Boruta feature selection coupled with a recursive SVM classifier (REF-SVM). Cross-omics correlations between gut microbiota abundances and host gene expression were evaluated to map microbiota-host interactions. For predictive modeling, seven machine learning algorithms were trained on microbial and transcriptomic features, with a Stacking Classifier meta-ensemble employed to integrate predictions and optimize classification accuracy for IBD staging. This pipeline enabled the discovery of microbial biomarkers, stage-specific transcriptional markers, and robust ...