Evidence map›Paper›PMID 41718908›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2026

Plasma metabolomic signatures of all and cause-specific cancers: a multi-platform population-based study.

Yu Shuai, Rikje Ruiter, Bruno H Stricker, M Arfan Ikram, Mohsen Ghanbari

Abstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Yu ShuaiDepartment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Rikje RuiterDepartment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Bruno H StrickerDepartment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
M Arfan IkramDepartment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Mohsen GhanbariDepartment of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands. m.ghanbari@erasmusmc.nl.

Funding

Erasmus MC Fellowship grant EMCF20213
6 · The paper itself

Abstract

introductionEarly diagnosis of cancer is essential for improving patient outcomes. Metabolomics analysis has shown promise in detecting cancer and distinguishing its metastatic burdens in previous studies.

objectivesWe hypothesized that metabolomics data can differentiate between people with and without cancer at a population level, uncovering new biomarkers and deepening our understanding of cancer metabolism.

methodsA total of 1,386 metabolites were measured by two commonly used metabolomics platforms: Nightingale and Metabolon, in baseline plasma samples from participants in the population-based Rotterdam Study, with sample sizes of 2,538 and 5,057, respectively. Logistic regression and competing risk Cox proportional hazards models were employed to examine associations between these metabolites and both baseline prevalent and incident during follow-up of all and cause-specific cancers. Statistical significance was defined by a false discovery rate (FDR) < 0.05.

resultsThere were 654 cancer cases at baseline, and 618 new cases also occurred during follow-up of nearly 10 years. In the cross-sectional study, 68, 7, and 10 metabolites were significantly associated with prevalent blood, colorectal, and all cancer, after multivariate adjustment. In the longitudinal study, 19, 11, 2, 3, and 1 metabolites were significantly associated with incident blood, colorectal, lung, prostate, and all cancer, respectively. Among these, 17 and 2 metabolites were associated with both prevalent and incident blood and colorectal cancer.

conclusionsThis study indicates several circulating metabolites that are associated with different cancers. These metabolites may contribute to better understanding of the metabolic pathways of cancer and serve as biomarkers for early cancer diagnosis.

Indexed as

Biomarkers, TumorMetabolomicsNeoplasmsAgedCross-Sectional StudiesFemaleHumansMaleMetabolomeMiddle AgedBiomarkers, TumorAll cancersBiomarkerCause-specific cancersCirculating metabolitesMetabolomic signaturesPopulation-based study

Identifiers

PMID41718908
PMCPMC12923424

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.