Integrative multi-omics identifies S100A8/IGFBP5/CTSK/S100P as dual diagnostic biomarkers and therapeutic targets in Crohn's disease: from computational discovery to preclinical validation.

Abstract

Crohn's disease (CD) is a chronic inflammatory bowel condition that significantly impairs patients' quality of life. With no cure currently available, the need to discover novel biomarkers and develop effective therapeutic strategies is paramount. This study used a comprehensive machine learning approach to identify key predictive genes for CD, including S100A8, IGFBP5, CTSK, and S100P. The concentrations of these four indicators in the peripheral blood of CD patients were significantly higher than those in the control group, which fully indicates that these four molecules can be used as predictive indicators for clinical CD patients. Additionally, molecular docking studies demonstrated strong binding interactions between S100A8 and CTSK with Cyclosporine, IGFBP5 with Dexamethasone, and S100P with Paclitaxel. DSS-induced mouse model showed paclitaxel and dexamethasone indeed reduced colitis severity. These findings advance precision medicine strategies for CD, offering non-invasive diagnostics and mechanistically grounded therapies, and fully demonstrates the advantages of conducting bench- and bedside-based research using the genomic approach.