Application of spatial omics, multi-omics, and artificial intelligence in inflammatory bowel disease: Current applications and emerging opportunities

Abstract

Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, is a complex and heterogeneous disorder driven by dynamic interactions between genetic susceptibility, immune dysregulation, epithelial barrier dysfunction, and the intestinal microbiome. Despite significant therapeutic advances, durable remission remains elusive for many patients, reflecting an incomplete understanding of disease mechanisms within the spatially organized intestinal mucosa. Recent advances in multi-omics and spatial-omics technologies have transformed IBD research by enabling high-resolution molecular profiling while preserving tissue architecture, discovering disease-defining cellular niches and host-microbiome interactions. Simultaneously, artificial intelligence (AI) has emerged as an essential framework for integrating high-dimensional omics datasets, uncovering non-linear relationships, and translating molecular complexity into clinical applications. This review has discussed current applications of multi-omics, spatial omics, and AI-driven analyses that are reshaping disease management. Also, we discussed challenges and emerging opportunities at the intersection of omics and AI, including the development of next-generation non-animal disease models and the discovery of spatial biomarkers for disease progression and cancer risk. Therefore, integration of multi-omics, spatial omics, and AI creates a transformative approach that enhances our understanding and facilitates precision medicine in IBD.

Keywords: Inflammatory bowel disease; Multi-omics; Crohn’s disease; Artificial intelligence; Spatial-omics; Ulcerative colitis; Microbiota

Core Tip: Inflammatory bowel disease (IBD), including Crohn’s disease and ulcerative colitis, arises from complex, spatially organized interactions between host genetics, immune responses, epithelial integrity, and the intestinal microbiota. Emerging multi-omics and spatial-omics technologies now enable high-resolution, tissue-context-preserved profiling of these processes, revealing disease-defining cellular niches and host-microbiome interactions. Artificial intelligence (AI) provides a critical framework for integrating high-dimensional datasets, uncovering non-linear relationships, and translating molecular complexity into clinically actionable insights. The convergence of multi-omics, spatial-omics, and AI holds strong promise for precision medicine in IBD, enabling improved disease stratification, identification of spatial biomarkers for progression and cancer risk, and the development of next-generation, non-animal disease models.