Abstract
Aging research is essential to identifying factors that influence healthy aging, with improved well-being and increased longevity for contemporary humans. Importantly, the rate of biological aging varies considerably between people, therefore it is critical to develop a maker of biological age that accurately reflects this variation.
The aims of this thesis were to 1) develop new epigenetic biomarkers of aging and growth with high precision, and 2) conduct an epigenome-wide association study of leukocyte telomere length (LTL) – a cellular replicative aging biomarker.
Three blood-based epigenetic clocks were developed for the precise estimation of adults’chronological age using EPIC-derived DNA methylation (DNAm) data. The clocks achieved high precision of age prediction in independent cohorts. This highly precise age prediction was not explained by the broader genomic coverage of the EPIC array but rather by the large training set used and its wide age-span.
Three placenta-based epigenetic clocks were subsequently developed to estimate fetal gestational age using a mixture of publicly available DNAm data. These placental clocks were highly accurate estimators of GA based on placental tissue regardless of pregnancy conditions.
The EWAS of LTL identified 823 CpG sites significantly associated (P<10-7) with LTL after adjustment for age, sex, ethnicity, and imputed white blood cell counts. Functional enrichment analyses revealed that these CpG sites were near genes that play a role in circadian rhythm, blood coagulation, and wound healing. Importantly, this study revealed significant relationships between the two recognized hallmarks of aging: TL and DNAm.