Project 460613

Aging is a complex process characterized by the progressive, irreversible loss of functional capacity across tissues. Over the last two decades, global life expectancy has increased rapidly - from 66.20 in 2000 to 72.6 years in 2019. However, the quality of life in later years remains variable. For example, some people experience physiological frailty and cognitive decline earlier than others. Chronological age- the number of years since birth- does not account for this inter-personal variability. This has led to an increased interest in the development of aging biomarkers to study healthy aging. Aging biomarkers aim to predict functional capacity, in the absence of disease, more accurately than chronological age. The epigenetic clock is a promising aging biomarker which has been repeatedly independently validated and shown to have good predictive power for outcomes such as all cause mortality. The epigenetic clock relies on an epigenetic modifications known as DNA methylation. This consists of the placement of a CH3 functional group on the DNA bases Cytosine. In humans, this modification occurs at Cytosine-phosphate-Guanine (CpG) dinucleotides and changes over time. The epigenetic clock consists of a set of CpG sites and a mathematic algorithm which can accurately predict epigenetic age. Epigenetic age acceleration (EAA, epigenetic age > chronological age) has been associated with many age-related diseases. The most used epigenetic clock, the Horvath clock, has been developed using data from methylation arrays and linear mathematical models. Novel methylation sequencing methods assay methylation at significantly more CpG sites than the arrays (~3.3million vs 850,000). In this study, there are two main objectives cities: 1) develop a novel more accurate algorithm using 915 methylation sequencing samples from three Canadian studies and novel non-linear models and 2) use this novel clock to study the effect of diseases on epigenetic age and healthy aging.