Age-Associated Genetic and Environmental Contributions to Epigenetic Aging Across Adolescence and Emerging Adulthood DOI Creative Commons
Dmitry V. Kuznetsov, Yixuan Liu, Alicia M. Schowe

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 12, 2024

Background Epigenetic aging estimators commonly track chronological and biological aging, quantifying its accumulation (i.e., epigenetic age acceleration) or speed pace). Their scores reflect a combination of inherent programming the impact environmental factors, which are suggested to vary at different life stages. The transition from adolescence adulthood is an important period in this regard, marked by increasing and, then, stabilizing variance. Whether pattern arises influences genetic factors still uncertain. This study delves into understanding contributions variance across these developmental Using twin modeling, we analyzed four namely Horvath Acceleration, PedBE GrimAge DunedinPACE, based on saliva samples collected two timepoints approximately 2.5 years apart 976 twins birth cohorts (aged about 9.5, 15.5, 21.5, 27.5 first 12, 18, 24, 30 second measurement occasion). Results Half two-thirds (50-68%) differences were due unique indicating role experiences drift, besides error. remaining was explained (Horvath Acceleration: 24%; 32%; DunedinPACE: 47%) shared 26%; 47%). represented primary sources stable corresponding over years. Age moderation analyses revealed that individually-unique smaller younger than older trained 47% 49%; 33% 68%). contributions, turn, potentially increased groups for adult 18% 39%; 24% 43%; 42% 57%). Conclusions Transition aging. Both contribute trend. degree can be partially design estimators.

Language: Английский

Applying blood-derived epigenetic algorithms to saliva: cross-tissue similarity of DNA-methylation indices of aging, physiology, and cognition DOI Creative Commons

Sepideh Zarandooz,

Laurel Raffington

Clinical Epigenetics, Journal Year: 2025, Volume and Issue: 17(1)

Published: April 23, 2025

Abstract Background Epigenetic algorithms of aging, health, and cognition, based on DNA-methylation (DNAm) patterns, are prominent tools for measuring biological age have been linked to age-related diseases, cognitive decline, mortality. While most these methylation profile scores (MPSs) developed in blood tissue, there is growing interest using less invasive tissues like saliva. The aim the current study probe cross-tissue intraclass correlation coefficients (ICCs) MPSs applied saliva DNAm from same people. our primary focus that were previously found be robustly correlated with social determinants including second- third-generation clocks physiology we also report ICC values first-generation enable comparison across metrics. We pooled three publicly available datasets had both individuals (total n = 107, aged 5–74 years), corrected cell composition within each computed ICCs. Results after correcting composition, saliva–blood ICCs moderate indices aging cognition. Specifically, PCGrimAge highest (0.76), followed by PCPhenoAge (0.72), a measure performance (Epigenetic- g , 0.69), DunedinPACE (0.68), Acceleration (0.67), (0.66), an MPS hs-CRP (0.58), BMI (0.54). These appear lower than previous reports within-tissue (saliva range 0.67 0.85, 0.73 0.93). Cross-tissue acceleration measures poor, ranging 0.19 0.25. Conclusions Our findings suggest applying related phenotypes results similarity precise correspondence differs measure. degree several may suffice some research settings, it not suitable clinical or commercial applications. Collection samples necessary validate existing customize DNAm.

Language: Английский

Citations

0
Genetic and environmental contributions to epigenetic aging across adolescence and young adulthood DOI Creative Commons
Dmitry V. Kuznetsov, Yixuan Liu, Alicia M. Schowe

et al.

Clinical Epigenetics, Journal Year: 2025, Volume and Issue: 17(1)

Published: May 7, 2025

Language: Английский

Citations

0
Social determinants of health and epigenetic clocks: Meta-analysis of 140 studies DOI Creative Commons
Yayouk E. Willems,

A. D. Rezaki,

M. Aikins

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: May 8, 2025

Social determinants of health are social factors that affect and survival. Two the most powerful socioeconomic status (SES) race/ethnicity; people with lower SES or marginalized race/ethnicity tend to experience earlier onset aging-related diseases have shorter lifespans. DNA methylation (DNAm) measures biological aging, often referred as "epigenetic clocks", increasingly used study determination health. However, there several generations epigenetic clocks it remains unclear which sensitive affecting Moreover, is uncertainty about how technical factors, such tissue from derived technology measure may associations clocks. We conducted a pre-registered multi-level meta-analysis 140 studies, including N = 65,919 participants, encompassing 1,065 effect sizes for racial/ethnic identity three found were weakest first generation developed predict age differences between people. Associations stronger second mortality risks. The strongest observed third clocks, sometimes speedometers", pace aging. In studies children, only speedometers showed significant SES. Effects sex minimal was no evidence publication bias.

Language: Английский

Citations

0
Lagged effects of childhood depressive symptoms on adult epigenetic aging DOI Creative Commons
Laura K. M. Han, Moji Aghajani, Brenda W.J.H. Penninx

et al.

Psychological Medicine, Journal Year: 2024, Volume and Issue: 54(12), P. 3398 - 3406

Published: Sept. 1, 2024

Abstract Background Cross-sectional studies have identified health risks associated with epigenetic aging. However, it is unclear whether these make clocks ‘tick faster’ (i.e. accelerate biological aging). The current study examines concurrent and lagged within-person changes of a variety Methods Individuals from the Great Smoky Mountains Study were followed age 9 to 35 years. DNA methylation profiles assessed blood, at multiple timepoints waves) for each individual. Health psychiatric, lifestyle, adversity factors. Concurrent ( N = 539 individuals; 1029 assessments) 380 760 analyses used determine link between Results models showed that BMI r 0.15, P FDR < 0.01) was significantly correlated aging subject-level but not wave-level. Lagged demonstrated depressive symptoms b 1.67 months per symptom, 0.02) in adolescence accelerated adulthood, also when fully adjusted BMI, smoking, cannabis alcohol use. Conclusions Within-persons, unaccompanied by aging, suggesting unlikely immediately ‘accelerate’ time indicated childhood/adolescence predicted adulthood. Together, findings suggest age-related embedding instant provides prognostic opportunities. Repeated measurements longer follow-up times are needed examine stable dynamic contributions childhood experiences across lifespan.

Language: Английский

Citations

1
Age-Associated Genetic and Environmental Contributions to Epigenetic Aging Across Adolescence and Emerging Adulthood DOI Creative Commons
Dmitry V. Kuznetsov, Yixuan Liu, Alicia M. Schowe

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 12, 2024

Background Epigenetic aging estimators commonly track chronological and biological aging, quantifying its accumulation (i.e., epigenetic age acceleration) or speed pace). Their scores reflect a combination of inherent programming the impact environmental factors, which are suggested to vary at different life stages. The transition from adolescence adulthood is an important period in this regard, marked by increasing and, then, stabilizing variance. Whether pattern arises influences genetic factors still uncertain. This study delves into understanding contributions variance across these developmental Using twin modeling, we analyzed four namely Horvath Acceleration, PedBE GrimAge DunedinPACE, based on saliva samples collected two timepoints approximately 2.5 years apart 976 twins birth cohorts (aged about 9.5, 15.5, 21.5, 27.5 first 12, 18, 24, 30 second measurement occasion). Results Half two-thirds (50-68%) differences were due unique indicating role experiences drift, besides error. remaining was explained (Horvath Acceleration: 24%; 32%; DunedinPACE: 47%) shared 26%; 47%). represented primary sources stable corresponding over years. Age moderation analyses revealed that individually-unique smaller younger than older trained 47% 49%; 33% 68%). contributions, turn, potentially increased groups for adult 18% 39%; 24% 43%; 42% 57%). Conclusions Transition aging. Both contribute trend. degree can be partially design estimators.

Language: Английский

Citations

0