Investigation of circulating metabolites associated with breast cancer risk by untargeted metabolomics: a case-control study nested within the French E3N cohort.

ABSTRACT:

Background

Perturbations in circulating metabolites prior to a breast cancer diagnosis are not well characterised. We aimed to gain more detailed knowledge to help understand and prevent the disease.

Methods

Baseline plasma samples from 791 breast cancer cases and 791 matched controls from the E3N (EPIC-France) cohort were profiled by nuclear magnetic resonance (NMR)-based untargeted metabolomics. Partial least-squares discriminant analysis (PLS-DA) models were built from NMR profiles to predict disease outcome, and odds ratios and false discovery rate (FDR)-adjusted CIs were calculated for 43 identified metabolites by conditional logistic regression.

Results

Breast cancer onset was predicted in the premenopausal subgroup with modest accuracy (AUC 0.61, 95% CI: 0.49-0

SUBMITTER: Jobard E 

PROVIDER: S-EPMC8110540 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature