Abstract
DNA methylation changes within the genome can be used to predict human age. However, the existing biological age prediction models based on DNA methylation are predominantly adult-oriented. We established a methylation-based age prediction model for children (9-212 months old) using data from 716 blood samples in 11 DNA methylation datasets. Our elastic net model includes 111 CpG sites, mostly in genes associated with development and aging. The model performed well and exhibited high precision, yielding a 98% correlation between the DNA methylation age and the chronological age, with an error of only 6.7 months. When we used the model to assess age acceleration in children based on their methylation data, we observed the following: first, the aging rate appears to be fastest in mid-childhood, and this acceleration is more pronounced in autistic children; second, lead exposure early in life increases the aging rate in boys, but not in girls; third, short-term recombinant human growth hormone treatment has little effect on the aging rate of children. Our child-specific methylation-based age prediction model can effectively detect epigenetic changes and health imbalances early in life. This may thus be a useful model for future studies of epigenetic interventions for age-related diseases.
Highlights
Due to the declining fertility rate and the increasing life expectancy, the world is on the brink of a demographic milestone: adults above the age of 65 will soon outnumber children under the age of 5 [1,2,3]
We found that the acceleration difference (AAD) and apparent methylation aging rate (AMAR) were significantly greater in mid-childhood than in toddlerhood, and were significantly lower in adolescence than in midchildhood (AAD: P = 7.2×10-14, AMAR: P = 4.5×10-6, analysis of variance (ANOVA); Figure 4B and C)
We found no significant difference in the AAD or AMAR between these three types of autistic children and their unaffected siblings (AAD: P = 0.47, AMAR: P = 0.098, ANOVA; Supplementary Figure 4B and 4C)
Summary
Due to the declining fertility rate and the increasing life expectancy, the world is on the brink of a demographic milestone: adults above the age of 65 will soon outnumber children under the age of 5 [1,2,3]. Noncommunicable diseases that more commonly occur in adults and older people are imposing the greatest burden on global health. Extending the period of life free of disability and disease is the key to limiting health and social costs. Most elderly study participants already suffer from age-related diseases. The theory of the fetal origins of adult disorders [10,11,12,13] proposes that many health problems in adults or the elderly are rooted in early life experiences and living conditions. The lack of tools to quantify aging in children is a significant obstacle to this goal
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