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Research Paper|Volume 17, Issue 7|pp 1702—1720

Second generation DNA methylation age predicts cognitive change in midlife: the moderating role of childhood socioeconomic status

Sophie A. Bell1, Christopher R. Beam2,3, Ebrahim Zandi4, Alyssa Kam2, Emily Andrews1, Jonathan Becker5, Deborah Finkel6,7, Deborah W. Davis8,9, Eric Turkheimer1
  • 1Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA
  • 2Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA
  • 3Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
  • 4Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
  • 5Department of Family and Geriatric Medicine, University of Louisville School of Medicine, Louisville, KY 40202, USA
  • 6Institute for Gerontology, Jönköping University, Jönköping, Sweden
  • 7Center for Economic and Social Research, University of Southern California, Los Angeles, CA 90089, USA
  • 8Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY 40202, USA
  • 9Norton Children’s Research Institute Affiliated with The University of Louisville School of Medicine, Louisville, KY 40202, USA
Received: April 14, 2025Accepted: July 8, 2025Published: July 23, 2025
https://doi.org/10.18632/aging.206284

Copyright: © 2025 Bell et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

DNA methylation age (DNAmAge) surpasses chronological age in its ability to predict age-related morbidities and mortality. This study analyzed data from 287 middle-aged twins in the Louisville Twin Study (mean age 51.9 years ± 7.03) to investigate the effect of DNAmAge acceleration on change in IQ (ΔIQ) between childhood and midlife, while testing childhood socioeconomic status (SES) as a moderator of the relationship. DNAmAge was estimated with five commonly used algorithms, or epigenetic clocks (Horvath, Horvath Skin and Blood, GrimAge, and PhenoAge). A factor analysis of these measures produced a two-factor structure which we identified as first generation and second generation measures. Results of genetically informed, quasi-causal regression models indicated that accelerated second generation DNAmAge predicted more negative ΔIQ from childhood to midlife, after accounting for genetic and environmental confounds shared by twins. The relationship between DNAmAge and ΔIQ was moderated by childhood SES, with a stronger effect observed among twins from low SES backgrounds. Second generation DNAmAge measures trained to estimate phenotypic biological age show promise in their predictive value for cognitive decline in midlife. Our genetically informed twin design suggested that epigenetic aging may represent a pathway through which early-life socioeconomic disadvantage impacts midlife cognitive health.