0000000000018632
AUTHOR
Noa Rappaport
Towards early risk biomarkers: serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood
Summary: Background: Cardiovascular diseases may originate in childhood. Biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimise prevention strategies. Methods: In this prospective study, by applying a machine learning to high throughput NMR-based metabolomics data, we identified circulating childhood metabolic predictors of adult cardiovascular disease risk (MetS score) in a cohort of 396 females, followed from childhood (mean age 11·2 years) to early adulthood (mean age 18·1 years). The results obtained from the discovery cohort were validated in a large longitudinal birth cohort of females and males followed from puberty to…
Towards early risk biomarkers: serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood
AbstractCardiovascular diseases have their origin in childhood. Early biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimize prevention strategies. By applying machine learning approach on high throughput NMR-based metabolomics data, we identified metabolic predictors of cardiovascular risk in circulation in a cohort of 396 females, followed from childhood (mean age 11.2 years) to early adulthood (mean age 18.1 years). The identified childhood metabolic signature included three circulating biomarkers robustly associating with increased cardiovascular risk in early adulthood (AUC = 0.641 to 0.802, all p<0.01). These associa…