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
Towards early risk biomarkers : serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood
|Author:||Ojanen, Xiaowei1,2,3; Cheng, Runtan1,2; Törmäkangas, Timo3;|
1Key Laboratory of Systems Biomedicine (Ministry of Education), School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
2Exercise Translational Medicine Center, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
3Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
4Institute for Systems Biology, Seattle, WA, USA
5CARE Programme, Lui Che Woo Institute of Innovative Medicine, CUHK Hong Kong Hub of Paediatric Excellence, Hong Kong Children’s Hospital, Hong Kong SAR, China
6Laboratory for Heart Failure + Circulation Research, Li Ka Shing Institute of Health Sciences; Gerald Choa Cardiac Research Centre, Department of Medicine and Therapeutics; Centre for Cardiovascular Genomics and Medicine, Faculty of Medicine, The Chinese University of Hong Kong and Prince of Wales Hospital, Hong Kong SAR, China
7Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom
8Centre for Life-Course Health Research, Faculty of Medicine, University of Oulu, Finland
9Children’s Health and Exercise Research Centre, Sport and Health Sciences, University of Exeter, Exeter, United Kingdom
10Department of Physical Education, Shanghai Jiao Tong University, Shanghai, China
|Online Access:||PDF Full Text (PDF, 3.4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021121660974
|Publish Date:|| 2021-12-16
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.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
318 Medical biotechnology
This study was financially supported by the Academy of Finland, Ministry of Education of Finland and University of Jyväskylä, the National Nature Science Foundation of China (Grant 31571219), the 111 Project (B17029), the Shanghai Jiao Tong University Zhiyuan Foundation (Grant CP2014013), China Postdoc Scholarship Council (201806230001), the Food and Health Bureau of Hong Kong SAR's Health and Medical Research Fund (HMRF grants 15162161 and 07181036) and the CUHK Direct Grants for Research (2016¢033 and 2018¢034), and a postdoctoral fellowship from K. Carole Ellison (to T.W.). The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. NFBC1966 received financial support from University of Oulu Grant no. 24000692, Oulu University Hospital Grant no. 24301140, ERDF European Regional Development Fund Grant no. 539/2010 A31592. This work was supported by European Union's Horizon 2020 research and innovation programme LongITools 874739.
|EU Grant Number:||
(874739) LONGITOOLS - Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases
© 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/)