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Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation.
Li, Chunxiao; Gao, Wenjing; Gao, Ying; Yu, Canqing; Lv, Jun; Lv, Ruoran; Duan, Jiali; Sun, Ying; Guo, Xianghui; Cao, Weihua; Li, Liming.
Afiliação
  • Li C; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Gao W; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Gao Y; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Yu C; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Lv J; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Lv R; Beijing Center for Disease Control and Prevention, Beijing 100013, China.
  • Duan J; Beijing Center for Disease Control and Prevention, Beijing 100013, China.
  • Sun Y; Beijing Center for Disease Control and Prevention, Beijing 100013, China.
  • Guo X; Chaoyang District Center for Disease Control and Prevention, Beijing 100021, China.
  • Cao W; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
  • Li L; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
Aging (Albany NY) ; 10(5): 1015-1026, 2018 05 12.
Article em En | MEDLINE | ID: mdl-29754148
ABSTRACT
The DNA methylation age, a good reflection of human aging process, has been used to predict chronological age of adults and newborns. However, the prediction model for children and adolescents was absent. In this study, we aimed to generate a prediction model of chronological age for children and adolescents aged 6-17 years by using age-specific DNA methylation patterns from 180 Chinese twin individuals. We identified 6,350 age-related CpGs from the epigenome-wide association analysis (N=179). 116 known age-related sites in children were confirmed. 83 novel CpGs were selected as predictors from all age-related loci by elastic net regression and they could accurately predict the chronological age of the pediatric population, with a correlation of 0.99 and the error of 0.23 years in the training dataset (N=90). The predictive accuracy in the testing dataset (N=89) was high (correlation=0.93, error=0.62 years). Among the 83 predictors, 49 sites were novel probes not existing on the Illumina 450K BeadChip. The top two predictors of age were on the PRKCB and REG4 genes, which are associated with diabetes and cancer, respectively. Our results suggest that the chronological age can be accurately predicted among children and adolescents aged 6-17 years by 83 newly identified CpG sites.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador / Ilhas de CpG / Metilação de DNA / Estudo de Associação Genômica Ampla Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Child / Female / Humans / Male Idioma: En Revista: Aging (Albany NY) Assunto da revista: GERIATRIA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador / Ilhas de CpG / Metilação de DNA / Estudo de Associação Genômica Ampla Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Child / Female / Humans / Male Idioma: En Revista: Aging (Albany NY) Assunto da revista: GERIATRIA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China