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Neighborhood Exposome at Birth and Trajectories of Epigenetic Age Acceleration Across Childhood

Yuan, Q. E.; Bozack, A. K.; Paquin, V.; Abrishamcar, S.; Arrant, E. J.; Xu, Y.; Rifas-Shiman, S. L.; Chen, Y.; Dimitrov, L. V.; Risk, B. B.; Hivert, M.-F.; Oken, E.; Cardenas, A.; Huels, A.; Ku, B. S.

2026-08-25 psychiatry and clinical psychology
10.64898/2026.08.21.26361042 medRxiv
Show abstract

Importance: Epigenetic age acceleration (EAA) has been linked to increased disease risk in adults, yet its developmental trajectories and early-life neighborhood determinants remain poorly understood. Objective: To examine associations between the neighborhood exposome at birth and EAA trajectories from early childhood through adolescence. Design, Setting, and Participants: Longitudinal cohort study using data from Project Viva, a pre-birth cohort that enrolled pregnant women in eastern Massachusetts (1999-2002). Participants included 570 children with available peripheral blood DNA methylation data, complete neighborhood characteristics, and complete covariates. Data were analyzed from 2024 to 2026. Exposures: Neighborhood exposome profiles at birth derived from 22 census tract-level characteristics across four domains (area deprivation, social fragmentation, population density, and environmental quality) using self-organizing maps. Main Outcomes and Measures: EAA was calculated at ages 3 (n=84), 8 (n=301), and 13 (n=434) years using Horvath, Skin & Blood, and Wu epigenetic clocks. Trajectories were identified using latent class linear mixed models. Associations between neighborhood profiles and EAA trajectories were estimated using multinomial mixed models. Results: Among 570 children (mean [SD] age at early childhood, 3.2 [0.4] years; 265 [46.5%] female), three EAA trajectory groups (stable, increasing, and decreasing for the Horvath and Skin & Blood clocks or low-baseline for the Wu clock) and three neighborhood profiles were identified. Compared with Profile 1 (suburban, lowest adverse exposures; n=278), children born into Profile 2 (urban, high residential instability and single-person households, and highway proximity; n=168) had greater odds of increasing EAA for Wu clock (aOR, 1.67; 95% CI, 1.03-2.69). Profile 3 (urban, high socioeconomic deprivation; n=124) showed no significant associations. Conclusions and Relevance: In this longitudinal cohort study, birth into neighborhoods characterized by high residential instability and single- person households, and highway proximity was associated with increasing Wu EAA trajectories across childhood. These findings suggest that early-life neighborhood conditions, encompassing both social and physical environmental factors, may represent targets for interventions aimed at reducing long-term disease risk. Further research is needed to clarify the implications of these findings for later health and prevention.

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