What question did this study set out to answer?

To characterize prediagnostic metabolic changes associated with inflammatory bowel disease (IBD).

January 23, 2026

P0034Pre-diagnostic changes in the metabolome of inflammatory bowel disease

Key Points

To characterize prediagnostic metabolic changes associated with inflammatory bowel disease (IBD).
Analyzed 169 pre-diagnostic serum samples from patients with IBD and matched controls.
Conducted untargeted metabolomics using liquid chromatography-mass spectrometry.
Applied conditional logistic regression models to assess associations with future IBD.
Performed metabolite class enrichment analysis and sPLS-DA for predictive capability.
Identified 1,206 significantly altered metabolites prior to IBD diagnosis, mostly in Crohn's disease cases.
Eicosanoids, fatty acids, and glycerophosphocholines were prominently enriched.
The model predicted future onset of Crohn's disease (AUC=0.78), ulcerative colitis (AUC=0.62), and IBD (AUC=0.67).

Abstract

Abstract Background The pre-clinical phase of IBD involves rising subclinical inflammation, increased epithelial permeability, and gut dysbiosis1. Serum metabolomics, shaped by genetics, environment, and the microbiome2, captures much of these early shifts. Yet our understanding of prediagnostic IBD remains limited, largely because biological samples from this period are scarce. An initial study of prediagnostic serum samples indicated alterations in steroid hormone synthesis, gut dysbiosis and oxidative stress3. However, the limited sample size hampers a wider characterization of the metabolic processes. Methods The PREDICT cohort was established by cross-linking nationwide health registries with the Danish National Biobank to identify patients with pre-diagnostic serum samples. We retrieved 169 samples collected 2–14 years before IBD diagnosis (72 Crohn’s disease, 97 ulcerative colitis) and matched them to 169 controls matched on age, sex and sampling time. Untargeted metabolomics was performed using liquid chromatography-mass spectrometry to measure 4,899 metabolites. Associations with future IBD were assessed using conditional logistic regression models. Metabolite class enrichment analysis was performed using Fisher’s exact test. Sparse partial least squares discriminant analysis (sPLS-DA) evaluated the ability of the metabolome to predict future IBD development in hold-out datasets, as assessed using the area under the receiver operating characteristic curve (AUC). Results A total of 1,206 metabolites were significantly altered prior to IBD diagnosis (padj0.05). For CD, 882 metabolites were significantly altered, with significant enrichment of eicosanoids, fatty acids, and glycerophosphocholines, including bioactive lipids linked to inflammation. While no metabolites were significantly associated with UC, 570 metabolites out of the 882 CD associated metabolites (65%) were also nominally associated with UC, with consistent directionality (Fig 1). In general, the association with CD was stronger for individuals with samples drawn 5 years prior to diagnosis. Using sPLS-DA, the metabolome could predict future onset of CD (AUC=0.78), UC (AUC=0.62) and IBD (AUC=0.67). Conclusion We observed associations in 1000 metabolites up to 14 years prior to IBD diagnosis, most pronounced in individuals with later CD. Findings support a prolonged pre-clinical phase of IBD, compatible with mucosal dysfunction and altered inflammation-modulating lipids. References: 1)Rudbaek JJ, Agrawal M, Torres J, Mehandru S, Colombel JF, Jess T. Deciphering the different phases of preclinical inflammatory bowel disease. Nat Rev Gastroenterol Hepatol. 2024;21(2):86-100. doi:10.1038/s41575-023-00854-4 2)Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016;17(7):451-459. doi:10.1038/nrm.2016.25 3)Hua X, Ungaro RC, Petrick LM, et al. Inflammatory bowel disease is associated with prediagnostic perturbances in metabolic pathways. Gastroenterology. 2023;164(1):147-150.e2. doi:10.1053/j.gastro.2022.09.007 Conflict of interest: Engel Lemser, Camilla: No conflict of interest Koziol, Adam Leslie: No conflict of interest Grundvad Boelt, Sanne: No conflict of interest MacSween, Nadia: No conflict of interest Ernst, Madeleine: None declared. Jess, Tine: Personal Fees: Consultancy for Ferring, Pfizer, Johnson & Johnson Dr. Ottosson, Filip: No conflict of interest

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