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Tracking age-correlated DNA methylation markers in the young.
Freire-Aradas, Ana; Phillips, Christopher; Girón-Santamaría, Lorena; Mosquera-Miguel, Ana; Gómez-Tato, Antonio; Casares de Cal, M Ángeles; Álvarez-Dios, Jose; Lareu, Maria Victoria.
Afiliação
  • Freire-Aradas A; Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain. Electronic address: ana.freire@usc.es.
  • Phillips C; Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain.
  • Girón-Santamaría L; Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain.
  • Mosquera-Miguel A; Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain.
  • Gómez-Tato A; Faculty of Mathematics, University of Santiago de Compostela, Spain.
  • Casares de Cal MÁ; Faculty of Mathematics, University of Santiago de Compostela, Spain.
  • Álvarez-Dios J; Faculty of Mathematics, University of Santiago de Compostela, Spain.
  • Lareu MV; Faculty of Mathematics, University of Santiago de Compostela, Spain.
Forensic Sci Int Genet ; 36: 50-59, 2018 09.
Article em En | MEDLINE | ID: mdl-29933125
DNA methylation is the most extensively studied epigenetic signature, with a large number of studies reporting age-correlated CpG sites in overlapping genes. However, most of these studies lack sample coverage of individuals under 18 years old and therefore little is known about the progression of DNA methylation patterns in children and adolescents. In the present study we aimed to select candidate age-correlated DNA methylation markers based on public datasets from Illumina BeadChip arrays and previous publications, then to explore the resulting markers in 209 blood samples from donors aged between 2 to 18 years old using the EpiTYPER® DNA methylation analysis system. Results from our analyses identified six genes highly correlated with age in the young, in particular the gene KCNAB3, which indicates its potential as a highly informative and specific age biomarker for childhood and adolescence. We outline a preliminary age prediction model based on quantile regression that uses data from the six CpG sites most strongly correlated with age ranges extended to include children and adolescents.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Envelhecimento / Marcadores Genéticos / Metilação de DNA / Genética Forense Tipo de estudo: Prognostic_studies Limite: Adolescent / Child / Child, preschool / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Envelhecimento / Marcadores Genéticos / Metilação de DNA / Genética Forense Tipo de estudo: Prognostic_studies Limite: Adolescent / Child / Child, preschool / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article