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dc.contributor.authorOjanen, Xiaowei
dc.contributor.authorCheng, Runtan
dc.contributor.authorTörmäkangas, Timo
dc.contributor.authorRappaport, Noa
dc.contributor.authorWilmanski, Tomasz
dc.contributor.authorWu, Na
dc.contributor.authorFung, Erik
dc.contributor.authorNedelec, Rozenn
dc.contributor.authorSebert, Sylvain
dc.contributor.authorVlachopoulos, Dimitris
dc.contributor.authorYan, Wei
dc.contributor.authorPrice, Nathan D.
dc.contributor.authorCheng, Sulin
dc.contributor.authorWiklund, Petri
dc.date.accessioned2021-10-18T10:41:56Z
dc.date.available2021-10-18T10:41:56Z
dc.date.issued2021
dc.identifier.citationOjanen, 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. <i>EBioMedicine</i>, <i>72</i>, Article 103611. <a href="https://doi.org/10.1016/j.ebiom.2021.103611" target="_blank">https://doi.org/10.1016/j.ebiom.2021.103611</a>
dc.identifier.otherCONVID_101482519
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/78240
dc.description.abstractBackground 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.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesEBioMedicine
dc.rightsCC BY-NC-ND 4.0
dc.subject.othermetabolomics
dc.subject.othercardio-metabolic risk
dc.subject.otherchildren
dc.subject.otherlongitudinal-study
dc.subject.otherALSPAC
dc.titleTowards early risk biomarkers : serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202110185269
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.contributor.oppiaineLiikuntalääketiedefi
dc.contributor.oppiaineSports and Exercise Medicineen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.description.reviewstatuspeerReviewed
dc.relation.issn2352-3964
dc.relation.volume72
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 The Authors. Published by Elsevier B.V.
dc.rights.accesslevelopenAccessfi
dc.subject.ysosydän- ja verisuonitaudit
dc.subject.ysomarkkerit
dc.subject.ysoaineenvaihduntatuotteet
dc.subject.ysolapsuus
dc.subject.ysoriskitekijät
dc.subject.ysoaikuisuus
dc.subject.ysopitkittäistutkimus
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p9886
jyx.subject.urihttp://www.yso.fi/onto/yso/p12288
jyx.subject.urihttp://www.yso.fi/onto/yso/p24583
jyx.subject.urihttp://www.yso.fi/onto/yso/p13735
jyx.subject.urihttp://www.yso.fi/onto/yso/p13277
jyx.subject.urihttp://www.yso.fi/onto/yso/p15515
jyx.subject.urihttp://www.yso.fi/onto/yso/p14610
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.ebiom.2021.103611
jyx.fundinginformationThis 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.


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