Untargeted plasma metabolomics and risk of colorectal cancer-an analysis nested within a large-scale prospective cohort
Journal article, 2023

BackgroundColorectal 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.MethodsThis 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.ResultsIn 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).ConclusionsThese 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.

Early detection

Colorectal cancer

Untargeted metabolomics

Author

Linda Vidman

Umeå University

Rui Zheng

Uppsala University

Stina Boden

Umeå University

Anton Ribbenstedt

Chalmers, Life Sciences, Systems and Synthetic Biology

Marc J. Gunter

WHO

Imperial College London

Richard Palmqvist

Umeå University

Sophia Harlid

Umeå University

Carl Brunius

Chalmers, Life Sciences, Food and Nutrition Science

Bethany Van Guelpen

Umeå University

CANCER & METABOLISM

2049-3002 (eISSN)

Vol. 11 1 17

Riskprediktion och tidig upptäckt av tjock- och ändtarmscancer, en integrativ molekylärepidemiologisk approach

Swedish Research Council (VR) (2017-01737), 2018-01-01 -- 2020-12-31.

Subject Categories

Cancer and Oncology

DOI

10.1186/s40170-023-00319-x

PubMed

37849011

More information

Latest update

11/24/2023