Dataset Information

DNA methylation-based age estimation in pediatric healthy tissues and brain tumors.

ABSTRACT: Several DNA methylation clocks have been developed to reflect chronological age of human tissues, but most clocks have been trained on adult samples. The rapid methylome changes in children and the role of epigenetics in pediatric tumors calls for tools accurately estimating methylation age in children. We aimed to evaluate seven methylation clocks in multiple tissues from healthy children to inform future studies on the optimal clock for pediatric cohorts, and analyzed the methylation age in brain tumors. We found that clocks trained on pediatric samples were the best in all tested tissues, highlighting the need for dedicated clocks. For blood samples, the Skin and blood clock had the best correlation with chronological age, while PedBE was the most accurate for saliva and buccal samples, and Horvath for brain tissue. Horvath methylation age was accelerated in pediatric brain tumors and the acceleration was subtype-specific for atypical teratoid rhabdoid tumor (ATRT), ependymoma, medulloblastoma and glioma. The subtypes with the highest acceleration corresponded to the worst prognostic categories in ATRT, ependymoma and glioma, whereas the relationship was reversed in medulloblastoma. This suggests that methylation age has potential as a prognostic biomarker in pediatric brain tumors and should be further explored.

SUBMITTER: Kling T

PROVIDER: S-EPMC7695434 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

DNA methylation-based age estimation in pediatric healthy tissues and brain tumors.

Kling Teresia T Wenger Anna A Carén Helena H

Aging 20201109 21

Several DNA methylation clocks have been developed to reflect chronological age of human tissues, but most clocks have been trained on adult samples. The rapid methylome changes in children and the role of epigenetics in pediatric tumors calls for tools accurately estimating methylation age in children. We aimed to evaluate seven methylation clocks in multiple tissues from healthy children to inform future studies on the optimal clock for pediatric cohorts, and analyzed the methylation age in br ...[more]

PMID: 33168783

Similar Datasets

Project description:DNA methylation (DNAm) plays diverse roles in human biology, but this dynamic epigenetic mark remains far from fully characterized. Although earlier studies uncovered loci that undergo age-associated DNAm changes in adults, little is known about such changes during childhood. Despite profound DNAm plasticity during embryogenesis and early development, monozygotic twins show indistinguishable childhood methylation, suggesting DNAm is highly coordinated during the pediatric period. Here we examine the methylation of 27,578 CpG dinucleotides in peripheral blood DNA from 398 boys, aged 3 to 17 years, and find significant age-associated changes in DNAm at 2,078 loci. We report a deficit of such loci on the X chromosome, a preference for specific nucleotides immediately surrounding the interrogated CpG dinucleotide, and a primary association with developmental and immune ontological functions. These pediatric age-associated loci overlap significantly with those previously identified in adults (p < 0.001) but most of the pediatric loci are unique, suggesting many are childhood-specific. Meta-analysis (n = 1080) with two adult studies reveals that the methylation changes in 29.5% of the age-associated pediatric loci follow a linear pattern from childhood into adulthood; however, we also find a three-fold higher rate of change in children compared with adults and that a higher proportion of lifelong changes are more accurately modeled as a function of logarithmic age. We therefore conclude that DNAm changes occur more rapidly during childhood and are imperfectly accounted for by statistical corrections that are linear in age, further suggesting that future DNAm studies are matched closely for age. Age associated DNA methylation was evaluated at each CpG locus using a fixed-effects linear regression model adjusting for BeadChip as a covariate to account for batch effects. Analysis of variance (ANOVA) was conducted for each CpG locus to assess the age affect at each CpG locus which was subsequently corrected for multiple hypotheses using a Benjamini-Hochberg FDR. SUPPLEMENTARY FILES: * Matrix_AllSampleDetection.txt: Detection P-values for each sample and each loci * Matrix_AllSampleSignal.txt: Signal for Probe A and Probe B for each sample and each loci * Matrix_Non-Normalized_AllSampleBeta.txt: Beta values calculated using GenomeStudio v2010.3 Methylation Module 1.8.5 as Signal of Probe B / (Signal of Probe A + Signal of Probe B + 100) * Matrix_Normalized_AllSampleBetaPrime.txt: Beta Prime values used for analysis calculated from the Probe B and Probe A signals as Beta Prime = Signal of Probe B / (Signal of Probe A + Signal of Probe A)

Dataset Information

DNA methylation-based age estimation in pediatric healthy tissues and brain tumors.

Publications

DNA methylation-based age estimation in pediatric healthy tissues and brain tumors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets