Epigenetic clocks are highly accurate DNA methylation-based biomarkers of biological aging. DNA methylation clocks predict chronological age and have recently emerged as the most accurate molecular marker of biological age in comparison to telomere length, transcriptomic, and proteomic based estimators. Differences between epigenetic age estimates and chronological age, called epigenetic age acceleration, are biologically relevant and have been associated with all-cause mortality, morbidity and longevity. There are several epigenetic clocks which use different sets of CpG sites known to differ by age in a specific tissue (most often blood, but some apply to multiple tissue types) in combination with mathematical algorithms to compute an aggregate measure of epigenetic or DNA methylation age. These findings suggest that epigenetic age is a useful predictive marker of aging and age-associated conditions like cancer and obesity. Given that epigenetic clocks and their role in aging is a relatively young field of research, many data gaps remain. Some studies suggest that environmental and social factors may affect epigenetic clock ticking rates, potentially affecting aging and developmental processes yet data remain somewhat limited. Furthermore, few studies have been conducted in children, and while there is suggestive evidence that maternal metabolic and sociodemographic factors may influence DNA methylation age, findings have not been consistent between studies. Also, newer epigenetic clocks incorporating additional clinical parameters and improving on sensitivity and accuracy have recently been developed but not tested in children. Previously, we assessed DNA methylation profiles in children followed by the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) study, a longitudinal birth cohort of farmworker families. We found significant associations of regional and site-specific DNA methylation in blood with sex, age and environmental exposures. In this proposal, we will leverage our existing DNA methylation data to examine associations of early life factors with epigenetic age acceleration in CHAMACOS children. We will calculate four different epigenetic clock estimates in blood collected from CHAMACOS children at three stages of childhood (birth, mid-childhood - 9y, and adolescence -14y). We will assess their correlation with chronological age and determine rates of epigenetic age acceleration. We will examine associations of epigenetic age acceleration with maternal factors during pregnancy like metabolic parameters, parity, age, and SES factors and child birth outcomes (gestational age and birthweight) and sex to identify early life factors that influence epigenetic age acceleration. Findings from this study will be used as the basis for an R01 proposal expanding our research on molecular mechanisms of epigenetic aging in CHAMACOS children. Understanding factors that might accelerate or slow ticking rates may strengthen our understanding of the molecular mechanisms involved in age-related conditions and help to identify early targets for prevention.

Public Health Relevance

Age acceleration, the difference between one?s biological age determined by their epigenetic clock, and one?s chronological age has been associated with age-related conditions like pubertal development, obesity, and cancer. In this proposal, we will use state of the art methodologies to estimate epigenetic clocks in Mexican- American children participating in the CHAMACOS study and identify early life factors during pregnancy and at birth (gestational age and birthweight) that may affect epigenetic age acceleration during childhood. Understanding the factors that impact age acceleration will help us elucidate the biological and developmental processes that influence age-related phenotypes.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Small Research Grants (R03)
Project #
5R03AG067064-02
Application #
10152487
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Guo, Max
Project Start
2020-05-01
Project End
2022-01-31
Budget Start
2021-02-01
Budget End
2022-01-31
Support Year
2
Fiscal Year
2021
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94710