How DNA methylation and cells of the innate immune system affect ageing and related health outcomes

By Josie Robertson

As a PhD student in the Marioni group here at the IGC, I recently had the opportunity to contribute to an international study seeking to understand associations between DNA methylation and cells of the innate immune system on ageing and related health outcomes.

DNA methylation patterns (called Epigenetic clocks) measured across our DNA, demonstrate promise in quantifying biological age and associate with age-related ill-health and mortality.

We know that these clocks are affected by the proportions of different immune cells in the blood samples from which they are measured. Studies exploring this have mostly focussed on changes in adaptive immune system cell types, such as T-cells.

Our study – ‘Variations in innate immune cell subtypes correlate with epigenetic clocks, inflammaging and health outcomes’ – published in the journal Advanced Science, used a newly developed 19 immune-cell type DNA methylation reference panel (UniLIFE) which allows estimates of ‘young’ or ‘old’ innate immune cell type proportions in blood samples.

The study demonstrated that shifts from young to old fractions of certain innate immune cells are correlated with age-related inflammation (‘inflammaging’) and all-cause mortality, independently of major disease-risk factors.

It also identifies that the estimated fraction of a rare cell-type, which may indicate nucleated red blood cells (nRBC), increases with age, though remaining a small fraction of the overall cells, and is associated with increased mortality (independent of age or other risk factors) and markers of dysfunctional red blood cell synthesis.

This work enhances our understanding of epigenetic clocks – which are leading biomarkers helping research into ageing and age-related morbidity.

I worked with Anne Richmond (GS bioinformatics analyst) and Professor Riccardo Marioni, in collaboration with the study leads from the Shanghai Institute for Nutrition and Health, to contribute analyses using the Generation Scotland (GS) cohort.

We applied the UniLIFE DNA methylation reference panel to estimate fractions for 19 immune cell types for the almost 19,000 GS volunteers with methylation data. These results were then used to assess the association of the immune cell types with disease outcomes, all-cause mortality and epigenetic clocks. The GS contribution to this work was valuable due to its large sample size and health record linkage allowing follow up for over 10 years.

Work in my PhD has focused on using epigenetic proxies (similar to epigenetic clocks) of proteins to compare protein and epigenetic data as potential disease biomarkers. Participating in this study was a fantastic opportunity to enhance my understanding of factors influencing the interpretation of epigenetic data and their potential as valuable biomarkers for a range of applications.