Novel type 2 diabetes prediction score based on traditional risk factors and circulating metabolites: model derivation and validation in two large cohort studies.

ABSTRACT:

Background

We aimed to evaluate the incremental predictive value of metabolomic biomarkers for assessing the 10-year risk of type 2 diabetes when added to the clinical Cambridge Diabetes Risk Score (CDRS).

Methods

We utilized 86,232 UK Biobank (UKB) participants (recruited between 13 March 2006 and 1 October 2010) for model derivation and internal validation. Additionally, we included 4383 participants from the German ESTHER cohort (recruited between 1 July 2000 and 30 June 2002 for external validation). Participants were followed up for 10 years to assess the incidence of type 2 diabetes. A total of 249 NMR-derived metabolites were quantified using nuclear magnetic resonance (NMR) spectroscopy. Metabolites were selected with LASSO regression and model performance was evalua

SUBMITTER: Xie R 

PROVIDER: S-EPMC11667638 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature