Towards Early Risk Biomarkers: Serum Metabolic Signature in Childhood Predicts Cardio-Metabolic Risk in Adulthood

Abstract

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 adulthood (n = 2664) and in four cross-sectional data sets (n = 6341). Findings: The identified childhood metabolic signature included three circulating biomarkers, glycoprotein acetyls (GlycA), large high-density lipoprotein phospholipids (L-HDL-PL), and the ratio of apolipoprotein B to apolipoprotein A-1 (ApoB/ApoA) that were associated with increased cardio-metabolic risk in early adulthood (AUC = 0¢641-0¢802, all p<0¢01). These associations were confirmed in all validation cohorts with similar effect estimates both in females (AUC = 0¢667-0¢905, all p<0¢01) and males (AUC = 0¢734-0¢889, all p<0¢01) as well as in elderly patients with and without type 2 diabetes (AUC = 0¢517-0¢700, all p<0¢01). We subsequently applied random intercept cross-lagged panel model analysis, which suggested bidirectional causal relationship between metabolic biomarkers and cardio-metabolic risk score from childhood to early adulthood. Interpretation: These results provide evidence for the utility of a circulating metabolomics panel to identify children and adolescents at risk for future cardiovascular disease, to whom preventive measures and followup could be indicated.