High-Resolution Spatial Multi-Omics for Unraveling Immune Heterogeneity in Inflammatory Bowel Disease 9111

Abstract Description Inflammatory bowel disease (IBD) encompasses chronic, lifelong intestinal disorders marked by immune dysregulation. The intestinal microenvironment exhibits pronounced spatial heterogeneity, with intricate immune and metabolic landscapes that remain poorly understood. Effectively leveraging single-cell resolution spatial multi-omics technologies is critical to elucidate the metabolic, transcriptional, and spatial complexities of immune cells within the IBD intestinal microenvironment. However, the lack of comprehensive high-resolution spatial multi-omics technologies and novel algorithms for cross-modality integration limits our ability to accurately characterize immune features. Here, we developed and applied advanced high-resolution (500 nm) spatial multi-omics methods, including transcriptomics, proteomics, TCR profiling, and metabolomics, along with H&E and DAPI imaging on adjacent colon sections from IBD patients. We further introduced a novel deep learning-based method for integrating spatial multi-omics data to identify distinct spatial clusters. This enabled a multimodal characterization of immune cells in IBD-affected regions, allowing for precise profiling of T-cell clonal expansion, metabolic states, and transcriptional landscapes. Our approach holds significant promise for identifying key biomarkers, offering potential diagnostic and therapeutic insights into the pathogenesis of IBD. Funding Sources None declared. Topic Categories Computational and Systems Immunology (COMP)