Immune Cell Differences Must Be Considered in Epigenetic Age
Epigenetic age is most commonly measured via blood sample, assessing the epigenetic markers of immune cells in that sample. Unfortunately the present mainstream epigenetic clocks will provide different ages for different immune cell populations. This leads to meaningful variation in assessments of the same individual, because different cell populations might be present in somewhat different proportions in each blood sample. We might also question which of the cell populations provide the most useful epigenetic age when it comes to responsiveness to interventions that might slow or reverse aspects of aging. This is a well known problem at this point in the continued development of epigenetic clocks, but there is as yet little consensus on what to do about it.
Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA.
We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from more than 10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis.
Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research.