Metabolic profiles to predict long-term cancer and mortality: the use of latent class analysis.

ABSTRACT:

Background

Metabolites are genetically and environmentally determined. Consequently, they can be used to characterize environmental exposures and reveal biochemical mechanisms that link exposure to disease. To explore disease susceptibility and improve population risk stratification, we aimed to identify metabolic profiles linked to carcinogenesis and mortality and their intrinsic associations by characterizing subgroups of individuals based on serum biomarker measurements. We included 13,615 participants from the Swedish Apolipoprotein MOrtality RISk Study who had measurements for 19 biomarkers representative of central metabolic pathways. Latent Class Analysis (LCA) was applied to characterise individuals based on their biomarker values (according to medical cut-offs), which were

SUBMITTER: Santaolalla A 

PROVIDER: S-EPMC6651931 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature