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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |