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The genetic background of metabolic trait clusters in children and adolescents

2017Journal article Open access
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dc.contributor.authorSilventoinen, Karri
dc.contributor.authorGouveia, Élvio
dc.contributor.authorJelenkovic, Aline
dc.contributor.authorMaia, José
dc.contributor.authorAntunes, António M.
dc.contributor.authorCarvalho, Miguel Â. A. Pinheiro de
dc.contributor.authorBrehm, António M.
dc.contributor.authorThomis, Martine
dc.contributor.authorLefevre, Johan
dc.contributor.authorKaprio, Jaakko
dc.contributor.authorFreitas, Duarte
dc.date.accessioned2020-11-13T14:07:30Z
dc.date.available2020-11-13T14:07:30Z
dc.date.issued2017
dc.description.abstractBackground: It is well known that the metabolic risk factors of cardiovascular diseases are correlated, but the background of this clustering in children is more poorly known than in adults. Thus, we studied the contribution of genetic and environmental factors to the clustering of metabolic traits in childhood and adolescence. Methods: Nine metabolic traits were measured in 214 complete twin pairs aged 3 to 18 years in the Autonomous Region of Madeira, Portugal, in 2007 and 2008. The variation of and covariations between the traits were decomposed into genetic and environmental components by using classical genetic twin modeling. Results: A model including additive genetic and environmental factors unique for each twin individual explained the variation of the metabolic factors well. Under this model, the heritability estimates varied from 0.47 (systolic blood pressure in children under 12 years of age) to 0.91 (HDL cholesterol in adolescents 12 years of age or older). The most systematic correlations were found between adiposity (body mass index and waist circumference) and blood lipids (HDL cholesterol, LDL cholesterol and triglycerides), as well as blood pressure. These correlations were mainly explained by common genetic factors. Conclusions: Our results suggest that obesity, in particular, is behind the clustering of metabolic factors in children and adolescents. Both general and abdominal obesity partly share the same genetic background as blood lipids and blood pressure. Obesity prevention already in childhood is important in reducing the risk of metabolic diseases in adulthood.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSilventoinen, K., Gouveia, E., Jelenkovic, A., Maia, J., Antunes, A. M., Pinheiro de Carvalho, M. A., ... & Freitas, D. (2017). The genetic background of metabolic trait clusters in children and adolescents. Metabolic Syndrome and Related Disorders, 15(7), 329-336.pt_PT
dc.identifier.doi10.1089/met.2017.0013pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/2977
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMary Ann Liebertpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectMetabolic syndromept_PT
dc.subjectGeneticspt_PT
dc.subjectTwinspt_PT
dc.subjectChildrenpt_PT
dc.subjectAdolescentspt_PT
dc.subjectPortugalpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências da Vidapt_PT
dc.titleThe genetic background of metabolic trait clusters in children and adolescentspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POCI/POCI%2FDES%2F56834%2F2004/PT
oaire.citation.endPage336pt_PT
oaire.citation.startPage329pt_PT
oaire.citation.titleMetabolic Syndrome and Related Disorderspt_PT
oaire.citation.volume15(7)pt_PT
oaire.fundingStreamPOCI
person.familyNameGouveia
person.familyNameMaia
person.familyNameAntunes
person.familyNameAlmeida Pinheiro de Carvalho
person.familyNameBrehm
person.familyNameThomis
person.familyNameLefevre
person.familyNameKaprio
person.familyNameFreitas
person.givenNameÉlvio Rúbio
person.givenNameJosé
person.givenNameAntónio Manuel
person.givenNameMiguel Angelo
person.givenNameAntonio
person.givenNameMartine
person.givenNameJohan
person.givenNameJaakko
person.givenNameDuarte
person.identifier1218558
person.identifier.ciencia-id3B10-8BDF-0D67
person.identifier.ciencia-id7C1E-A4CD-64EA
person.identifier.ciencia-id4610-6741-6816
person.identifier.ciencia-id3613-8D1F-0EDF
person.identifier.ciencia-idAA13-1821-A447
person.identifier.orcid0000-0003-0927-692X
person.identifier.orcid0000-0002-3273-0046
person.identifier.orcid0000-0002-7532-3053
person.identifier.orcid0000-0002-5084-870X
person.identifier.orcid0000-0003-3168-5340
person.identifier.orcid0000-0001-9093-2191
person.identifier.orcid0000-0003-0659-2388
person.identifier.orcid0000-0002-3716-2455
person.identifier.orcid0000-0001-6642-3370
person.identifier.ridAEE-0913-2022
person.identifier.scopus-author-id7006248142
person.identifier.scopus-author-id8758577600
person.identifier.scopus-author-idAuthor ID 7006085833
person.identifier.scopus-author-id35379599600
person.identifier.scopus-author-id37096975400
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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