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Lee, Seokjun, Park, Jaesub, Lee, Hyun Chang, Xu, Xingze, Slater, Ellie, Gasparetto, Marco 
ORCID: https://orcid.org/0000-0002-3882-3606, Han, Namshik and Zilbauer, Matthias
(2026)
Epigenetic biomarkers in inflammatory bowel diseases - computational challenges and opportunities.
Journal of Crohn's & Colitis, 20 (5).
pp. 1-17.
ISSN 1873-9946
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Abstract
Inflammatory bowel diseases (IBD) remain a therapeutic challenge due to their heterogeneous nature and the absence of clinically actionable biomarkers to guide precision treatment. While multi-omics studies have advanced our understanding of the disease, meaningful translation into practice has been hindered by lack of validation and a need to move from association to a more generalizable signal. Epigenetics, particularly DNA methylation, offers a promising lens to capture disease-relevant regulatory states that reflect both genetic predisposition and environmental influences. However, the path to clinical adoption has been limited by persistent computational hurdles. Here we synthesize the current landscape of IBD biomarker discovery and highlight the conceptual advantages of epigenetic signatures. We outline the main obstacles that have limited clinical translation to date, including data heterogeneity, batch effects, and the challenge of distinguishing functional "driver" from non-functional "passenger" epigenetic changes. We then discuss how recent advances in computational methodology-spanning data harmonization, integrative modeling, and interpretable machine learning-can help bridge the gap between complex datasets and reliable, deployable biomarkers. Finally, we propose a forward-looking roadmap for study design and validation aimed at moving the field toward routine clinical implementation, thereby realizing the full potential of epigenetics in IBD.
| Item Type: | Article |
|---|---|
| Additional Information: | Publisher Copyright: © The Author(s) 2026. Published by Oxford University Press on behalf of European Crohn’s and Colitis Organisation. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Uncontrolled Keywords: | machine learning,precision medicine,multi-omics integration,dna methylation,epigenetic biomarkers,inflammatory bowel disease |
| Faculty \ School: | Faculty of Medicine and Health Sciences > Norwich Medical School |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 16 Jun 2026 09:17 |
| Last Modified: | 18 Jun 2026 21:00 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/103406 |
| DOI: | 10.1093/ecco-jcc/jjag022 |
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