Towards early risk biomarkers : serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood
Ojanen, Xiaowei; Cheng, Runtan; Törmäkangas, Timo; Rappaport, Noa; Wilmanski, Tomasz; Wu, Na; Fung, Erik; Nedelec, Rozenn; Sebert, Sylvain; Vlachopoulos, Dimitris; Yan, Wei; Price, Nathan D.; Cheng, Sulin; Wiklund, Petri (2021-10-07)
Ojanen, X., Cheng, R., Törmäkangas, T., Rappaport, N., Wilmanski, T., Wu, N., Fung, E., Nedelec, R., Sebert, S., Vlachopoulos, D., Yan, W., Price, N. D., Cheng, S., & Wiklund, P. (2021). Towards early risk biomarkers: serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood. EBioMedicine, 72, 103611. https://doi.org/10.1016/j.ebiom.2021.103611
© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
https://creativecommons.org/licenses/by-nc-nd/4.0/
https://urn.fi/URN:NBN:fi-fe2021121660974
Tiivistelmä
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 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 follow-up could be indicated.
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