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Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data.

ABSTRACT: Background:Epigenetic clocks based on DNA methylation yield high correlations with chronological age in cross-sectional data. Due to a paucity of longitudinal data, it is not known how ?age (epigenetic age - chronological age) changes over time or if it remains constant from childhood to old age. Here, we investigate this using longitudinal DNA methylation data from five datasets, covering most of the human life course. Methods:Two measures of the epigenetic clock (Hannum and Horvath) are used to calculate ?age in the following cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) offspring (n = 986, total age-range 7-19 years, 2 waves), ALSPAC mothers (n = 982, 16-60 years, 2 waves), InCHIANTI (n = 460, 21-100 years, 2 waves), SATSA (n = 373, 48-99 years, 5 waves), Lothian Birth Cohort 1936 (n = 1,054, 70-76 years, 3 waves), and Lothian Birth Cohort 1921 (n = 476, 79-90 years, 3 waves). Linear mixed models were used to track longitudinal change in ?age within each cohort. Results:For both epigenetic age measures, ?age showed a declining trend in almost all of the cohorts. The correlation between ?age across waves ranged from 0.22 to 0.82 for Horvath and 0.25 to 0.71 for Hannum, with stronger associations in samples collected closer in time. Conclusions:Epigenetic age increases at a slower rate than chronological age across the life course, especially in the oldest population. Some of the effect is likely driven by survival bias, where healthy individuals are those maintained within a longitudinal study, although other factors like the age distribution of the underlying training population may also have influenced this trend.

SUBMITTER: Marioni RE

PROVIDER: S-EPMC6298183 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data.

Marioni Riccardo E RE Suderman Matthew M Chen Brian H BH Horvath Steve S Bandinelli Stefania S Morris Tiffany T Beck Stephan S Ferrucci Luigi L Pedersen Nancy L NL Relton Caroline L CL Deary Ian J IJ Hägg Sara S

The journals of gerontology. Series A, Biological sciences and medical sciences 20190101 1

<h4>Background</h4>Epigenetic clocks based on DNA methylation yield high correlations with chronological age in cross-sectional data. Due to a paucity of longitudinal data, it is not known how Δage (epigenetic age - chronological age) changes over time or if it remains constant from childhood to old age. Here, we investigate this using longitudinal DNA methylation data from five datasets, covering most of the human life course.<h4>Methods</h4>Two measures of the epigenetic clock (Hannum and Horv ...[more]

PMID: 29718110

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Project description:Prior research shows that individuals who have exhibited antisocial behavior are in poorer health than their same-aged peers. A major driver of poor health is aging itself, yet research has not investigated relationships between offending trajectories and biological aging. We tested the hypothesis that individuals following a life-course persistent (LCP) antisocial trajectory show accelerated aging in midlife. Trajectories of antisocial behavior from age 7 to 26 years were studied in the Dunedin Multidisciplinary Health and Development Study, a population-representative birth cohort (N = 1037). Signs of aging were assessed at age 45 years using previously validated measures including biomarkers, clinical tests, and self-reports. First, we tested whether the association between antisocial behavior trajectories and midlife signs of faster aging represented a decline from initial childhood health. We then tested whether decline was attributable to tobacco smoking, antipsychotic medication use, debilitating illnesses in adulthood, adverse exposures in childhood (maltreatment, socioeconomic disadvantage) and adulthood (incarceration), and to childhood self-control difficulties. Study members with a history of antisocial behavior had a significantly faster pace of biological aging by midlife, and this was most evident among individuals following the LCP trajectory (β, 0.22, 95%CI, 0.14, 0.28, p ≤ 0.001). This amounted to 4.3 extra years of biological aging between ages 25-45 years for Study members following the LCP trajectory compared to low-antisocial trajectory individuals. LCP offenders also experienced more midlife difficulties with hearing (β, -0.14, 95%CI, -0.21, -0.08, p ≤ 0.001), balance (β, -0.13, 95%CI, -0.18, -0.06, p ≤ 0.001), gait speed (β, -0.18, 95%CI, -0.24, -0.10, p ≤ 0.001), and cognitive functioning (β, -0.25, 95%CI, -0.31, -0.18, p ≤ 0.001). Associations represented a decline from childhood health. Associations persisted after controlling individually for tobacco smoking, antipsychotic medication use, midlife illnesses, maltreatment, socioeconomic status, incarceration, and childhood self-control difficulties. However, the cumulative effect of these lifestyle characteristics together explained why LCP offenders have a faster Pace of Aging than their peers. While older adults typically age-out of crime, LCP offenders will likely age-into the healthcare system earlier than their chronologically same-aged peers. Preventing young people from offending is likely to have substantial benefits for health, and people engaging in a LCP trajectory of antisocial behaviors might be the most in need of health promotion programs. We offer prevention and intervention strategies to reduce the financial burden of offenders on healthcare systems and improve their wellbeing.

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Dataset Information

Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data.

Publications

Tracking the Epigenetic Clock Across the Human Life Course: A Meta-analysis of Longitudinal Cohort Data.

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