Protein-Predicted Obesity Phenotypes and Cardiovascular Events: A Secondary Analysis of UK Biobank Proteomics Data.

ABSTRACT:

Background

Proteomic profiling may improve the understanding of obesity and cardiovascular risk prediction. This study explores the use of protein-predicted scores for body mass index (PPS_BMI), body fat percentage (PPS_BFP), and waist-hip ratio (PPS_WHR) to estimate risk for major adverse cardiovascular events (MACEs).

Methods

We used data from the UK Biobank with proteome profiling. PPS_BMI, PPS_BFP, and PPS_WHR were derived using the LASSO algorithm. The association between these protein scores and incident MACEs was evaluated using a competing risk model.

Results

Strong to moderate correlations were observed between protein-predicted obesity phenotypes and their measured counterparts (R²: BMI =

SUBMITTER: Liu C 

PROVIDER: S-EPMC12551110 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature