Epigenetic Clock Trajectories and Brain Health in Midlife

Age norms for DunedinPACE: An epigenetic pace of aging biomarker

Linking Epigenetic Age Acceleration to Self-Reported Daily Memory Lapses: Evidence from the National Study of Daily Experiences.

Biological Age Associates with Longitudinal Frailty-Related Functional Decline: The Health and Retirement Study.

Epigenetic clocks have emerged as markers of biological aging. Understanding their association with age-related functional decline may provide insights into DNA-mediated mechanisms underlying frailty-related functional decline and reveal which clocks best associate with accelerated functional decline. We therefore examined associations between established epigenetic clock measures and longitudinal trajectories of cognitive function, grip strength, and walking speed. We analyzed data from 4,018 participants in the Health and Retirement Study with available DNA methylation data and up to 12 years of follow-up data. Using linear mixed-effects models, we examined retrospective associations between twelve epigenetic clocks and longitudinal trajectories of frailty-related functional decline, modeling interactions between each epigenetic clock and time, adjusting for chronological age and sociodemographic covariates. In longitudinal analyses controlling for chronological age, older epigenetic age was associated with faster cognitive decline for Hannum (β = -0.0054, 95% CI: -0.0095, -0.0014, p = 0.009) and DNAmGrimAge (β = -0.0141, 95% CI: -0.0174, -0.0107, p < 0.001). Higher DNAmGrimAge was associated with accelerated decline in grip strength (β = -0.024, 95% CI: -0.033, -0.015, p < 0.001) and decline in walking speed (β = -0.0008, 95% CI: -0.0013, -0.0004, p < 0.001). Higher epigenetic clock biological age estimates, particularly DNAmGrimAge, are retrospectively associated with accelerated frailty-related functional decline across multiple functional domains. Systematic comparison of clock derivations may reveal specific epigenetic patterns underlying age-related functional deterioration.

Adolescent weight gain trajectories and their associations with biological aging: a genetically informed study.

BACKGROUND High body mass index (BMI) in adolescence is associated with accelerated biological aging, which might predict the onset of obesity-related diseases before they develop. Genetic factors may shape both adolescent BMI and weight trajectories. METHODS Participants were from the Young Finns Study (n = 3 596, ages 3-18 at baseline), followed from 1980 to 2018-2020. Biological aging was estimated using DNA methylation based epigenetic clocks DunedinPACE (years/calendar year) and PC-GrimAge (years) at three follow-ups (ages 15-56, n = 2045). Genetic predispositions to BMI and childhood body size were quantified using polygenic risk scores (PRSs) (941 and 286 genetic variants). BMI trajectories were modelled from BMI measured at ages 9, 12, 15 and 18 using latent growth curve modelling. Path analysis was used to examine whether genetic liability to BMI is associated with biological aging and if BMI trajectories in adolescence mediate this association. The causal effect of genetically predicted adolescent BMI on biological aging in adulthood was examined with Mendelian randomisation (MR) using individual-level data. RESULTS Higher level of adolescent BMI partly mediated the association between higher BMI-PRS and accelerated biological aging from late adolescence to middle adulthood. MR analyses supported a positive causal effect from genetically predicted adolescent BMI on biological aging, and the causal effect was more consistent when DunedinPACE was used to measure biological aging in 2011 (causal estimate = 0.020 [95% CI = 0.008, 0.031]) and 2018 (0.019 [0.003, 0.035]). CONCLUSIONS Our findings indicate that high BMI in adolescence may accelerate biological aging, especially in individuals with a genetic predisposition to high BMI. Adolescents with a genetic susceptibility to high BMI and elevated BMI might be prone to obesity-related health risks, highlighting early prevention strategies' importance.

Epigenetic and brain age across development: Performance and associations in the MIND consortium

Understanding how biological age measures perform across development lays the groundwork for investigations into lifespan trajectories of healthy aging. We provide the most comprehensive assessment of epigenetic and brain age models across development (birth to 24 years; ≤20,917 observations across 15 cohorts), evaluating how these models associate with chronological age and with each other, and how these associations change across development. Chronological age-prediction accuracy of epigenetic and brain age models was modest and varied substantially. Accuracy improved with age and stabilized by middle childhood. Few brain and fewer epigenetic clocks performed stably and well across all developmental stages. Performance was better when age range and tissue corresponded between training and testing data. Associations between epigenetic-brain age residuals were small, and changed little across development, tissues or clock generation. Given this developmentally dynamic system of epigenetic-brain age performances and associations, we give key recommendations to improve developmental research in this field.

Accelerated Epigenetic Aging in Diabetes: Socio-Biological Pathways of Health Inequity.

The results warrant validation studies to better understand socio-glucometabolic pathways shared by epigenetic aging processes and to inform early risk stratification among at-risk older women for disease prevention and reduced racial health inequity.