Univariate- and machine learning-based plasma metabolite signature differentiates PSC-IBD from IBD and is predicted to be driven by gut microbial changes
These results demonstrate the potential of DI-MS-based metabolomics with machine learning to create diagnostic models and generate hypotheses on the metabolomic-metagenomic level. Sharing our dataset of patients will enrich future human IBD metabolomics research possibilities.
Authors
- Saskia W. C. van Mil (ORCID: https://orcid.org/0000-0002-7850-5012)
- Edwin C.A. Stigter (ORCID: https://orcid.org/0000-0001-5970-4668)
- J Schultheiss (ORCID: https://orcid.org/0000-0001-6111-0893)
- Stefanía Magnúsdóttir (ORCID: https://orcid.org/0000-0001-6506-8696)
- Joanna C. Wolthuis (ORCID: https://orcid.org/0000-0001-9282-9518)
- Judith Jans (ORCID: https://orcid.org/0000-0003-0960-6263)
- Yuen Fung Tang
- J. C. M. de Ridder
- Bas Oldenburg
Institutions
- Utrecht University (NL)
- University Medical Center Utrecht (NL)
- Oncode Institute (NL)
Publication Details
- Journal
- Metabolomics
- Published
- 2026-03-28
- DOI
- https://doi.org/10.1007/s11306-026-02420-w
- Primary Topic
- Inflammatory Bowel Disease
- Type
- article
- Field-Weighted Citation Impact
- 0.00