A single blood or saliva sample can now reveal whether someone is ageing faster than their calendar years suggest, and this project will work out which parts of the body are ageing fastest and whether changing your lifestyle can slow that process down. The problem is that most ageing research has only looked at blood, even though saliva is easier to collect and may better reflect how the mouth and throat respond to smoking, diet, and the environment. This project will compare DNA methylation patterns—chemical switches that turn genes on or off—in blood and saliva from the largest datasets ever assembled. It will also track the same people over time to see whether biological ageing speeds up or slows down as their habits change. If successful, the work could lead to a simple, non-invasive saliva test that tells a person which of their organs are ageing prematurely and whether quitting smoking, losing weight, or changing their diet is actually reversing that damage. This is fundamental science—it will not produce a commercial test tomorrow—but understanding how lifestyle leaves chemical marks on our DNA is the first step toward personalised health advice that goes beyond generic recommendations.
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Improving healthspan is a key goal for society. Underlying this is a drive to understand why some people appear to age faster than others. If this can be identified and quantified then we can examine if different organs and tissues age at the same rate and test if modifiable lifestyle behaviours and the external environment impact this biological ageing. Over the last decade, we have driven research to show that DNA methylation (DNAm, an epigenetic modification) patterns from blood are leading candidates to assess biological ageing. Our pioneering work has linked DNAm with chronological ageing as well as modifiable lifestyle behaviours and traits linked to healthspan e.g., smoking, alcohol consumption and BMI. In addition to providing a readout of an individual’s environment, we have shown that DNAm, which can be thought of as analogous to a dimmer switch to turn gene expression up/down, is partly regulated by our underlying DNA sequence. Despite these advancements, numerous challenges remain. These include understanding differences in DNAm patterns by tissue/biosample type. Almost all large DNAm studies have focused on blood methylation. Given the proximity of the oral cavity to the external environment and the possibility of remote, inexpensive and non-invasive sampling, saliva has potential as a biomarker of healthy ageing. By understanding the genetic regulation of salivary DNAm, we can identify if differences in patterns are caused by lifestyle and environmental stimuli and test if this is also the case for blood-based DNAm. A second limitation of existing studies is how longitudinal patterns (e.g., DNAm changes with age) are typically inferred from cross-sectional data in studies with wide age ranges. Repeat sampling from the same individuals requires following study participants over many years, which is a costly process. However, within-person trajectories represent the gold-standard and enable us to examine if changes in biology mirror changes in lifestyle behaviours. Finally, while a host of disease-based DNAm studies have been conducted, few have sought to take a complementary approach to identify patterns that characterise healthy ageing. With multimorbidity (the accumulation of multiple disease diagnoses in an individual) being an increasingly observed phenomenon, understanding biological patterns that promote disease-free ageing are crucial. Here, we will address the limitations in previous research by analysing the largest blood- and saliva-based DNAm datasets in the world in tandem with longitudinal blood-based DNAm and concurrently measured blood- and salivary-DNAm. By integrating these data with detailed measures of the social, cognitive and physical environment in an outstanding research environment, we will: 1) determine the genetic patterns that underlie the salivary methylome and compare their similarities to the genetic regulation of the blood methylome. We will use these findings to ascertain if environmental and behavioural patterns cause differential DNAm patterns at overlapping or different genes across blood and saliva; 2) discover which genes and regions of the salivary methylome show differential patterns by age and modifiable lifestyle factors and; 3) identify methylation-based signatures of healthy ageing and investigate in longitudinal samples if these change over time and in tandem with markers of physical and cognitive health. We will develop and apply a suite of novel statistical data analysis tools to address these points. Understanding how the genetic regulation and lifestyle correlates of the methylome vary by tissue will provide fundamental insights into the role of DNAm for tracking both biological and healthy ageing.
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