Epigenetic Clocks in the Pediatric Population: When and Why They Tick?
Introduction
DNA methylation (DNAm) is the most extensively studied and mechanistically understood epigenetic modification, involving the addition of a methyl group to the fifth position of cytosine. It plays a crucial role in development and growth. In utero, DNAm is involved in vital processes such as cell differentiation, X-chromosome inactivation, and fetal growth. Postnatally, DNAm maintains cell-type identity, ensures genome stability, responds to external exposures, and is involved in neural and immune development.
The epigenetic clock, also known as the DNAm clock, estimates the age of any DNA source (cells, tissues, or organs) based on a relatively small set of cytosine-guanine dinucleotide (CpG) sites. Since its inception in 2011, the epigenetic clock has been regarded as a promising marker for studying development, cancer, and aging. However, its role in the pediatric population is only beginning to be understood. Early life and childhood are critical susceptibility windows during which epigenetic programming is sensitive to external influences. Epigenetic age is not linear throughout the lifespan, and changes in DNAm early in life differ from those later in life. Influenced by both genetic and environmental factors, DNAm has emerged as a key mechanism for understanding the gene-environment interplay in normal development and related diseases.
Epigenetic Clocks for the Pediatric Population
The development of epigenetic clocks initially focused on adult-specific or all-age clocks, which sacrificed precision in predicting pediatric chronological age to serve a wider population. To better understand age-related DNAm changes in pediatrics, clocks for neonates and children have been introduced. Over the past five years, several pediatric estimators using different sets of CpGs from various age spectra and tissues have been developed. These clocks cover both preterm and term infants for neonates and children younger than 20 years.
Epigenetic clocks for gestational age (GA) estimation
Even before the development of the epigenetic GA clock, GA itself has been associated with methylation changes at various CpG sites. In 2016, two epigenetic GA clocks, Knight and Bohlin, were developed to predict DNAm age in neonates. The Knight clock, based on cord blood and blood spot samples from 1434 neonates, uses 148 CpG sites uniformly distributed across the genome. The Bohlin clock, developed using cord blood samples from 1753 newborns, uses 96 CpG sites. Both clocks showed that ultrasound-based regression models outperform last menstrual period (LMP)-based models in terms of model fit and standard error.
Epigenetic clocks for pediatric chronological age
In 2013, Horvath developed the first pan-tissue epigenetic clock, using 353 CpGs in almost all human cell types and tissues. Another wide-spectra DNAm age estimator, the skin and blood clock, was introduced to capture aging acceleration in Hutchinson-Gilford Progeria Syndrome (HGPS). However, these clocks sacrifice accuracy in the pediatric population to serve all ages. Therefore, pediatric-specific clocks were developed. In 2019 and 2020, Wu et al and McEwen et al designed two children-specific epigenetic clocks. Wu’s clock, based on blood samples from 716 children, uses 111 CpG sites. The Pediatric Buccal Epigenetic (PedBE) clock, based on buccal epithelial cells from 1032 subjects, uses 94 CpGs and achieves high accuracy in estimating DNAm age.
Epigenetic Age Deviation (EAD) in the Pediatric Population
The application of epigenetic clocks reveals individuals whose chronological and epigenetic ages diverge. Positive epigenetic age acceleration (PEAA) occurs when the epigenetic age is older than expected, while negative epigenetic age acceleration (NEAA) occurs when it is younger. In the pediatric population, EADs may reflect developmental trajectories, developmental diseases, and environmental conditions.
Biomarkers of developmental trajectories
Epigenetic age deviations are associated with developmental characteristics such as weight, body mass index (BMI), height, fat mass, bone density, and pubertal timing. For instance, a 5-year PEAA on average is related to a significant decrease in time to menarche in girls. Higher age acceleration at birth is associated with faster growth in weight and BMI during childhood and adolescence.
Deviations under environmental exposure
Environmental factors, including physical and social exposures, can influence pediatric DNAm. Prenatal exposures such as air pollution, maternal alcohol consumption, and maternal nutrition affect newborns through maternal-fetal communications. Childhood exposures to violence, sexual abuse, and low socioeconomic status are also associated with EADs. Animal studies have identified the developmental programming of the hypothalamic-pituitary-adrenal stress axis as a target in epigenetics for pediatric health research.
Indicators for developmental diseases
Epigenetic age deviations are linked to developmental diseases such as allergies, asthma, and autism spectrum disorder (ASD). For example, a 1-year increase in EAA is associated with greater levels of total serum immunoglobulin E and greater odds of asthma and atopic sensitization. In ASD, increased PedBE age deviation is consistent with altered developmentally related phenotypes such as increased body growth and head growth.
Understanding the Mechanism Behind Pediatric Epigenetic Clocks
The use of machine learning methods to analyze large sets of methylated CpGs has generated powerful epigenetic clocks. However, this data-driven approach poses challenges in understanding the underlying mechanism. The limited overlap between clocks for pediatrics and adults was initially interpreted as the difference in biological processes between development and aging. However, the desolation of overlap is due to the algorithm behind it, which selects a relatively small number of CpGs to construct clocks.
Single CpG and cluster analyses help unravel the function of clock CpGs and related genes. Clock CpGs located in gene bodies are more likely to have decreasing DNAm, while those in promoter regions and enhancers tend to have increasing DNAm. Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses suggest links between epigenetic clocks and cell and tissue development. The ticking of epigenetic clocks reflects a general progression of high- and low-methylated CpGs to an intermediate level near 50%, indicating a smoothening of the epigenetic landscape.
DNAm captured by epigenetic clocks may also be secondary to other chromatin modifications. Histone modification affects DNAm, and DNA hypomethylation causes a redistribution of polycomb and histone modifications. The epigenetic clock may be secondary to other parts of the wider epigenetic networks, consisting of other epigenetic changes.
Concluding Remarks and Future Perspectives
Epigenetic clocks have emerged as valuable tools for understanding development, growth, and diseases in early life. Future studies should focus on generating tissue-specific clocks, developing pediatric animal models, understanding the molecular mechanisms underlying epigenetic clocks, and determining the consequences of epigenetic clocks. A deeper understanding of the molecular mechanism behind the clocks can help identify potential therapeutic targets for epigenetic modifications.
doi.org/10.1097/CM9.0000000000001723
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