Childhood adversity predicts black young adults' DNA methylation-based accelerated aging: A dual pathway model

Abstract

We expand upon prior work (Gibbons et al., ) relating childhood stressor effects, particularly harsh childhood environments, to risky behavior and ultimately physical health by adding longer-term outcomes - deoxyribonucleic acid (DNA) methylation-based measures of accelerated aging (DNA_m-aging). Further, following work on the effects of early exposure to danger (McLaughlin et al., ), we also identify an additional pathway from harsh childhood environments to DNA_m-aging that we label the danger/FKBP5 pathway, which includes early exposure to dangerous community conditions that are thought to impact glucocorticoid regulation and pro-inflammatory mechanisms. Because different DNA_m-aging indices provide different windows on accelerated aging, we contrast effects on early indices of DNA_m-aging based on chronological age with later indices that focused on predicting biological outcomes. We utilize data from Family and Community Health Study participants (N = 449) from age 10 to 29. We find that harshness influences parenting, which, in turn, influences accelerated DNA_m-aging through the risky cognitions and substance use (i.e., behavioral) pathway outlined by Gibbons et al. (). Harshness is also associated with increased exposure to threat/danger, which, in turn, leads to accelerated DNA_m-aging through effects on FKBP5 activity and enhanced pro-inflammatory tendencies (i.e., the danger/FKBP5 pathway).

Keywords: DNAm-aging; FKBP5; Life History; discrimination.

Figure 1.

Pathways from harshness (SES) decreased parental investments leading to adult health and weathering through the behavioral pathway.

Figure 2:

Pathway from Harshness (SES) to Childhood exposure to Danger leading to adult health and weathering via the Danger/FkBP5 pathway.

Figure 3a.

Two pathways to young adult health from childhood exposure to Harshness via decreased parental investment and increased exposure to danger

Figure 3b.

Two pathways to young adult health from childhood exposure to Harshness via decreased parental investment and increased exposure to danger – with dotted lines illustrating potential cross-pathway effects.

Figure 4a.

The unconditional indirect effects model showing the prediction of Epigenetic aging (Chronological Age) from childhood exposure to harshness, decreased parental investment, discrimination, and danger. Chi-square = 6.948, df = 10, p =.7304; RMSEA = .000; CFI = 1.000. Values are standardized parameter estimates and standard errors are in parentheses. Gender and age are controlled in these analyses. **p ≤ .01, *p ≤ .05 (two-tailed tests), n = 449. DNA_m-CA = Epigenetic aging - Chronological Age; LHS Cognition = fast life history strategies reflected in Cognition; and LHS Behavior = fast life history strategies reflected in substance use behavior.

Figure 4b.

The unconditional indirect effects model showing the prediction of Epigenetic aging (Biomarker Age) from childhood exposure to harshness, decreased parental investment, discrimination, and danger. Chi-square = 6.984_: df = 10, p = 7270; RMSEA = .000; CFI = 1.000. Values are standardized parameter estimates and standard errors are in parentheses. Gender and age are controlled in these analyses. **p ≤ .01, *p ≤ .05 (two-tailed tests), N = 449. DNA_m-Bio = Epigenetic aging -Biomarker Age; LHS Cognition = fast life history strategies reflected in Cognition; and LHS Behavior = fast life history strategies reflected in substance use behavior.