The trajectory of the blood DNA methylome ageing rate is largely set before adulthood: evidence from two longitudinal studies

• Published in: AGE Vol. 38; no. 3; p. 65
• Main Authors: Kananen, L., Marttila, S., Nevalainen, T., Kummola, L., Junttila, I., Mononen, N., Kähönen, M., Raitakari, O. T., Hervonen, A., Jylhä, M., Lehtimäki, T., Hurme, M., Jylhävä, J.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2016; Springer Nature B.V
• Subjects: Adolescent; Adult; Age; Aged; Aged, 80 and over; Aging; Aging - genetics; Algorithms; Biomarkers; Biomarkers - blood; Biomedical and Life Sciences; Blood; Calendars; Cell Biology; DNA - blood; DNA Damage; DNA Methylation; Epigenesis, Genetic; Epigenetics; Female; Follow-Up Studies; Geriatrics/Gerontology; Humans; Life Sciences; Longitudinal studies; Male; Medicin och hälsovetenskap; Medicine; Middle Aged; Molecular Medicine; Physiology; Principal components analysis; Time Factors; Young Adult; DNA methylation; DNAmAge; Immunosenescence; Epigenetic clock; Follow-up
• ISSN: 0161-9152; 2509-2715; 1574-4647; 1574-4647; 2509-2723
• DOI: 10.1007/s11357-016-9927-9

The epigenetic clock, defined as the DNA methylome age (DNAmAge), is a candidate biomarker of ageing. In this study, we aimed to characterize the behaviour of this marker during the human lifespan in more detail using two follow-up cohorts (the Young Finns study, calendar age i.e. cAge range at baseline 15–24 years, 25-year-follow-up, N  = 183; The Vitality 90+ study, cAge range at baseline 19–90 years, 4-year-follow-up, N  = 48). We also aimed to assess the relationship between DNAmAge estimate and the blood cell distributions, as both of these measures are known to change as a function of age. The subjects’ DNAmAges were determined using Horvath’s calculator of epigenetic cAge. The estimate of the DNA methylome age acceleration (Δ-cAge-DNAmAge) demonstrated remarkable stability in both cohorts: the individual rank orders of the DNAmAges remained largely unchanged during the follow-ups. The blood cell distributions also demonstrated significant intra-individual correlation between the baseline and follow-up time points. Interestingly, the immunosenescence-associated features (CD8+CD28− and CD4+CD28− cell proportions and the CD4/CD8 cell ratio) were tightly associated with the estimate of the DNA methylome age. In summary, our data demonstrate that the general level of Δ-cAge-DNAmAge is fixed before adulthood and appears to be quite stationary thereafter, even in the oldest-old ages. Moreover, the blood DNAmAge estimate seems to be tightly associated with ageing-associated shifts in blood cell composition, especially with those that are the hallmarks of immunosenescence. Overall, these observations contribute to the understanding of the longitudinal aspects of the DNAmAge estimate.