Metabolic profiling reveals circulating biomarkers associated with incident and prevalent Parkinson's disease.

ABSTRACT: The metabolic profile predating the onset of Parkinson's disease (PD) remains unclear. We aim to investigate the metabolites associated with incident and prevalent PD and their predictive values in the UK Biobank participants with metabolomics and genetic data at the baseline. A panel of 249 metabolites was quantified using a nuclear magnetic resonance analytical platform. PD was ascertained by self-reported history, hospital admission records and death registers. Cox proportional hazard models and logistic regression models were used to investigate the associations between metabolites and incident and prevalent PD, respectively. Area under receiver operating characteristics curves (AUC) were used to estimate the predictive values of models for future PD. Among 109,790 participants without

SUBMITTER: Hu W 

PROVIDER: S-EPMC11233508 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature