Cargando…

Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort

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 pros...

Descripción completa

Detalles Bibliográficos
Autores principales: Vidman, Linda, Zheng, Rui, Bodén, Stina, Ribbenstedt, Anton, Gunter, Marc J., Palmqvist, Richard, Harlid, Sophia, Brunius, Carl, Van Guelpen, Bethany
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583301/
https://www.ncbi.nlm.nih.gov/pubmed/37849011
http://dx.doi.org/10.1186/s40170-023-00319-x
_version_ 1785122520195661824
author Vidman, Linda
Zheng, Rui
Bodén, Stina
Ribbenstedt, Anton
Gunter, Marc J.
Palmqvist, Richard
Harlid, Sophia
Brunius, Carl
Van Guelpen, Bethany
author_facet Vidman, Linda
Zheng, Rui
Bodén, Stina
Ribbenstedt, Anton
Gunter, Marc J.
Palmqvist, Richard
Harlid, Sophia
Brunius, Carl
Van Guelpen, Bethany
author_sort Vidman, Linda
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40170-023-00319-x.
format Online
Article
Text
id pubmed-10583301
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-105833012023-10-19 Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort Vidman, Linda Zheng, Rui Bodén, Stina Ribbenstedt, Anton Gunter, Marc J. Palmqvist, Richard Harlid, Sophia Brunius, Carl Van Guelpen, Bethany Cancer Metab Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40170-023-00319-x. BioMed Central 2023-10-17 /pmc/articles/PMC10583301/ /pubmed/37849011 http://dx.doi.org/10.1186/s40170-023-00319-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Vidman, Linda
Zheng, Rui
Bodén, Stina
Ribbenstedt, Anton
Gunter, Marc J.
Palmqvist, Richard
Harlid, Sophia
Brunius, Carl
Van Guelpen, Bethany
Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
title Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
title_full Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
title_fullStr Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
title_full_unstemmed Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
title_short Untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
title_sort untargeted plasma metabolomics and risk of colorectal cancer—an analysis nested within a large-scale prospective cohort
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583301/
https://www.ncbi.nlm.nih.gov/pubmed/37849011
http://dx.doi.org/10.1186/s40170-023-00319-x
work_keys_str_mv AT vidmanlinda untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT zhengrui untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT bodenstina untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT ribbenstedtanton untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT guntermarcj untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT palmqvistrichard untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT harlidsophia untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT bruniuscarl untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort
AT vanguelpenbethany untargetedplasmametabolomicsandriskofcolorectalcancerananalysisnestedwithinalargescaleprospectivecohort