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Untargeted plasma metabolomics and risk of colorectal cancer: an analysis nested within a large-scale prospective cohort
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
Department of Surgical Sciences, Medical Epidemiology, Uppsala University, Uppsala, Sweden.
Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology. Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.ORCID iD: 0000-0002-8958-975x
Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden; Chalmers Mass Spectrometry Infrastructure, Chalmers University of Technology, Gothenburg, Sweden.
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2023 (English)In: Cancer & Metabolism, E-ISSN 2049-3002, Vol. 11, no 1, article id 17Article in journal (Refereed) Published
Abstract [en]

Background: Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, but if discovered at an early stage, the survival rate is high. The aim of this study was to identify novel markers predictive of future CRC risk using untargeted metabolomics.

Methods: This study included prospectively collected plasma samples from 902 CRC cases and 902 matched cancer-free control participants from the population-based Northern Sweden Health and Disease Study (NSHDS), which were obtained up to 26 years prior to CRC diagnosis. Using reverse-phase liquid chromatography-mass spectrometry (LC-MS), data comprising 5015 metabolic features were obtained. Conditional logistic regression was applied to identify potentially important metabolic features associated with CRC risk. In addition, we investigated if previously reported metabolite biomarkers of CRC risk could be validated in this study population.

Results: In the univariable analysis, seven metabolic features were associated with CRC risk (using a false discovery rate cutoff of 0.25). Two of these could be annotated, one as pyroglutamic acid (odds ratio per one standard deviation increase = 0.79, 95% confidence interval, 0.70-0.89) and another as hydroxytigecycline (odds ratio per one standard deviation increase = 0.77, 95% confidence interval, 0.67-0.89). Associations with CRC risk were also found for six previously reported metabolic biomarkers of prevalent and/or incident CRC: sebacic acid (inverse association) and L-tryptophan, 3-hydroxybutyric acid, 9,12,13-TriHOME, valine, and 13-OxoODE (positive associations).

Conclusions: These findings suggest that although the circulating metabolome may provide new etiological insights into the underlying causes of CRC development, its potential application for the identification of individuals at higher risk of developing CRC is limited.

Place, publisher, year, edition, pages
BioMed Central (BMC), 2023. Vol. 11, no 1, article id 17
Keywords [en]
Untargeted metabolomics, Colorectal cancer, Early detection
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:umu:diva-218144DOI: 10.1186/s40170-023-00319-xISI: 001088049400001PubMedID: 37849011OAI: oai:DiVA.org:umu-218144DiVA, id: diva2:1821155
Part of project
Risk prediction and early detection of colorectal cancer; an integrative molecular epidemiology approach, Swedish Research Council
Funder
Swedish Cancer Society, CAN 2017/581Swedish Research Council, 2017-01737Region Västerbotten, VLL-833291Region Västerbotten, VLL-841671Knut and Alice Wallenberg FoundationCancerforskningsfonden i NorrlandUmeå UniversityIngaBritt and Arne Lundberg’s Research FoundationAvailable from: 2023-12-19 Created: 2023-12-19 Last updated: 2024-01-05Bibliographically approved

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Vidman, LindaBodén, StinaPalmqvist, RichardHarlid, Sophiavan Guelpen, Bethany

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