What question did this study set out to answer?

The study aims to evaluate multi-omics factors associated with ulcerative colitis and identify biomarkers for diagnosis.

July 9, 2026

Multi‐Omics Framework Integrating Genetics, Microbiome, Metabolism, and Immunity for Deciphering Ulcerative Colitis Pathogenesis and Diagnostic Biomarker Discovery

Key Points

The study aims to evaluate multi-omics factors associated with ulcerative colitis and identify biomarkers for diagnosis.
Utilized a two-sample Mendelian randomization framework for causal assessment.
Integrated transcriptomic datasets to find differentially expressed genes.
Used machine learning modeling and external validation for diagnostic performance.
Identified potential causal associations between gut microbiome, metabolites, and immune cell phenotypes with UC susceptibility.
Achieved an AUC of 0.964 for a four-gene signature diagnostic model.
Localized IFITM2 upregulation to myeloid cells, particularly in neutrophils.

Abstract

Ulcerative colitis (UC) is an inflammatory bowel disease involving complex interactions between genetics, gut microbiota, metabolism, and immunity. This study aimed to systematically evaluate multi-omics factors potentially associated with UC susceptibility and identify reliable diagnostic biomarkers. A two-sample Mendelian randomization (MR) framework assessed potential causal associations between gut microbiome, circulating metabolites, immune cell phenotypes, and UC susceptibility. Significant MR findings were integrated with multiple transcriptomic datasets to identify differentially expressed candidate genes. Immune infiltration analysis, machine learning modeling, and external validation were subsequently performed. Single-cell and spatial transcriptomics were used to localize key genes and to explore their potential cell type-specific functions within the tissue microenvironment, followed by qRT-PCR validation in independent clinical tissues and siRNA-mediated IFITM2 knockdown in THP-1-derived macrophages. MR analyses identified potential causal associations for specific microbiota, sphingomyelin-related metabolites, and immune cell phenotypes with UC susceptibility. Integrative analysis prioritized four core signature genes: SAG, WDR48, IFITM2, and SIRPA. A random forest model achieved an AUC of 0. 964 and identified a four-gene signature with strong diagnostic performance. Single-cell and spatial transcriptomics localized IFITM2 upregulation mainly to myeloid cells, particularly NeutrophilIFITM2. CellChat suggested a potential CD4TemIL7R-ANXA1-FPR1-NeutrophilIFITM2 axis. qRT-PCR supported the expression directions of the four genes, and IFITM2 knockdown in THP-1-derived macrophages reduced TNF-α, IL-6, and IL-1β mRNA expression. This multi-omics framework supports the potential roles of specific microbiota, sphingolipid metabolism, and immune phenotypes in UC pathogenesis. The four-gene signature and characterization of NeutrophilIFITM2, supported by independent qRT-PCR validation and preliminary IFITM2 knockdown experiments, may provide a framework for precision diagnosis and future mechanistic studies in UC.

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