Artificial intelligence driven definition of food preference endotypes in UK Biobank volunteers is associated with distinctive health outcomes and blood based metabolomic and proteomic profiles.

ABSTRACT:

Background

Specific food preferences can determine an individual's dietary patterns and therefore, may be associated with certain health risks and benefits.

Methods

Using food preference questionnaire (FPQ) data from a subset comprising over 180,000 UK Biobank participants, we employed Latent Profile Analysis (LPA) approach to identify the main patterns or profiles among participants. blood biochemistry across groups/profiles was compared using the non-parametric Kruskal-Wallis test. We applied the Limma algorithm for differential abundance analysis on 168 metabolites and 2923 proteins, and utilized the Database for Annotation, Visualization and Integrated Discovery (DAVID) to identify enriched biological processes and pathways. Relative risks (RR) were calculated for chroni

SUBMITTER: Navratilova HF 

PROVIDER: S-EPMC11443809 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature