Cargando…

Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation

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 ad...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Chunxiao, Gao, Wenjing, Gao, Ying, Yu, Canqing, Lv, Jun, Lv, Ruoran, Duan, Jiali, Sun, Ying, Guo, Xianghui, Cao, Weihua, Li, Liming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5990383/
https://www.ncbi.nlm.nih.gov/pubmed/29754148
http://dx.doi.org/10.18632/aging.101445
_version_ 1783329570636693504
author Li, Chunxiao
Gao, Wenjing
Gao, Ying
Yu, Canqing
Lv, Jun
Lv, Ruoran
Duan, Jiali
Sun, Ying
Guo, Xianghui
Cao, Weihua
Li, Liming
author_facet Li, Chunxiao
Gao, Wenjing
Gao, Ying
Yu, Canqing
Lv, Jun
Lv, Ruoran
Duan, Jiali
Sun, Ying
Guo, Xianghui
Cao, Weihua
Li, Liming
author_sort Li, Chunxiao
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5990383
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Impact Journals
record_format MEDLINE/PubMed
spelling pubmed-59903832018-06-07 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 Aging (Albany NY) Research Paper 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. Impact Journals 2018-05-12 /pmc/articles/PMC5990383/ /pubmed/29754148 http://dx.doi.org/10.18632/aging.101445 Text en Copyright © 2018 Li et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Li, Chunxiao
Gao, Wenjing
Gao, Ying
Yu, Canqing
Lv, Jun
Lv, Ruoran
Duan, Jiali
Sun, Ying
Guo, Xianghui
Cao, Weihua
Li, Liming
Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
title Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
title_full Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
title_fullStr Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
title_full_unstemmed Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
title_short Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
title_sort age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of dna methylation
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5990383/
https://www.ncbi.nlm.nih.gov/pubmed/29754148
http://dx.doi.org/10.18632/aging.101445
work_keys_str_mv AT lichunxiao agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT gaowenjing agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT gaoying agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT yucanqing agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT lvjun agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT lvruoran agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT duanjiali agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT sunying agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT guoxianghui agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT caoweihua agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation
AT liliming agepredictionofchildrenandadolescentsaged617yearsanepigenomewideanalysisofdnamethylation