Association of Adverse Childhood Experiences With Accelerated Epigenetic Aging in Midlife

Mendelian randomization identifies causal effects of major depressive disorder on accelerated aging

BACKGROUND

Evidence links major depressive disorder (MDD) with aging, but it's unclear if MDD accelerates aging and what factors mediate this transition.

METHODS

Two-sample Mendelian randomization (MR) analyses were applied to estimate the causal association between MDD and frailty index (FI), telomere length (TL), and appendicular lean mass (ALM) from available genome-wide association studies in populations of European ancestry. Furthermore, we conducted mediation MR analyses to assess the mediating effects of 31 lifestyle factors or diseases on the causal relationship between MDD and aging.

RESULTS

MDD was significantly causally associated with increased FI (βIVW = 0.23, 95 % CI = 0.18 to 0.28, p = 1.20 × 10-17), shorter TL (βIVW = -0.04, 95 % CI = -0.07 to -0.01, p = 0.01), and decreased ALM (βIVW = -0.07, 95 % CI = -0.11 to -0.03, p = 3.54 × 10-4). The mediation analysis through two-step MR revealed smoking initiation (9.09 %), hypertension (6.67 %) and heart failure (5.36 %) mediated the causal effect of MDD on FI. Additionally, alcohol use disorders and alcohol dependence on the causal relationship between MDD and TL were found to be 17.52 % and 17.13 % respectively.

LIMITATIONS

Confounding, statistical power, and Euro-centric focus limit generalization.

CONCLUSION

Overall, individuals with MDD may be at a higher risk of experiencing premature aging, and this risk is partially influenced by the pathways involving smoking, alcohol use, and cardiovascular health. It underscores the importance of early intervention and comprehensive health management in individuals with MDD to promote healthy aging and overall well-being.

From premature birth to premature kidney disease: does accelerated aging play a role?

As the limits of fetal viability have increased over the past 30 years, there has been a growing body of evidence supporting the idea that chronic disease should be taken into greater consideration in addition to survival after preterm birth. Accumulating evidence also suggests there is early onset of biologic aging after preterm birth. Similarly, chronic kidney disease (CKD) is also associated with a phenotype of advanced biologic age which exceeds chronologic age. Yet, significant knowledge gaps remain regarding the link between premature biologic age after preterm birth and kidney disease. This review summarizes the four broad pillars of aging, the evidence of premature aging following preterm birth, and in the setting of CKD. The aim is to provide additional plausible biologic mechanisms to explore the link between preterm birth and CKD. There is a need for more research to further elucidate the biologic mechanisms of the premature aging paradigm and kidney disease after preterm birth. Given the emerging research on therapies for premature aging, this paradigm could create pathways for prevention of advanced CKD.

Associations between epigenetic age acceleration and longitudinal measures of psychosocioeconomic stress and status

Relationships between epigenetic aging markers and psychosocial variables such as socioeconomic status and stress have been well-documented, but are often examined cross-sectionally or retrospectively, and have tended to focus on objective markers of SES or major life events. Here, we examined associations between psychosocial variables, including measures of socioeconomic status and social stress, and epigenetic aging markers in adulthood, using longitudinal data spanning three decades from the Midlife in the United States (MIDUS) study. The largest effects were observed for epigenetic markers of change in health, such as DunedinPACE and GrimAge, and for associations involving education, income, net assets, general social stress, inequality-related stress, and financial stress. Analyses of polygenic indices suggests that at least in the case of education, the link to epigenetic aging cannot be accounted for by common genetic variants.

Better Life's Essential 8 contributes to slowing the biological aging process: a cross-sectional study based on NHANES 2007-2010 data

Objective

To investigate the relationship between Life's Essential 8 (LE8) and Phenotypic Age Acceleration (PhenoAgeAccel) in United States adults and to explore the impact of LE8 on phenotypic biological aging, thereby providing references for public health policies and health education.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2010, this cross-sectional study analyzed 7,339 adults aged 20 and above. Comprehensive assessments of LE8, PhenoAgeAccel, and research covariates were achieved through the integration of Demographics Data, Dietary Data, Laboratory Data, and Questionnaire Data derived from NHANES. Weighted generalized linear regression models and restricted cubic spline plots were employed to analyze the linear and non-linear associations between LE8 and PhenoAgeAccel, along with gender subgroup analysis and interaction effect testing.

Results

(1) Dividing the 2007-2010 NHANES cohort into quartiles based on LE8 unveiled significant disparities in age, gender, race, body mass index, education level, marital status, poverty-income ratio, smoking and drinking statuses, diabetes, hypertension, hyperlipidemia, phenotypic age, PhenoAgeAccel, and various biological markers (p < 0.05). Mean cell volume demonstrated no intergroup differences (p > 0.05). (2) The generalized linear regression weighted models revealed a more pronounced negative correlation between higher quartiles of LE8 (Q2, Q3, and Q4) and PhenoAgeAccel compared to the lowest LE8 quartile in both crude and fully adjusted models (p < 0.05). This trend was statistically significant (p < 0.001) in the full adjustment model. Gender subgroup analysis within the fully adjusted models exhibited a significant negative relationship between LE8 and PhenoAgeAccel in both male and female participants, with trend tests demonstrating significant results (p < 0.001 for males and p = 0.001 for females). (3) Restricted cubic spline (RCS) plots elucidated no significant non-linear trends between LE8 and PhenoAgeAccel overall and in gender subgroups (p for non-linear > 0.05). (4) Interaction effect tests denoted no interaction effects between the studied stratified variables such as age, gender, race, education level, and marital status on the relationship between LE8 and PhenoAgeAccel (p for interaction > 0.05). However, body mass index and diabetes manifested interaction effects (p for interaction < 0.05), suggesting that the influence of LE8 on PhenoAgeAccel might vary depending on an individual's BMI and diabetes status.

Conclusion

This study, based on NHANES data from 2007-2010, has revealed a significant negative correlation between LE8 and PhenoAgeAccel, emphasizing the importance of maintaining a healthy lifestyle in slowing down the biological aging process. Despite the limitations posed by the study's design and geographical constraints, these findings provide a scientific basis for the development of public health policies focused on healthy lifestyle practices. Future research should further investigate the causal mechanisms underlying the relationship between LE8 and PhenoAgeAccel and consider cross-cultural comparisons to enhance our understanding of healthy aging.

Educational Mobility, Pace of Aging, and Lifespan Among Participants in the Framingham Heart Study

Importance

People who complete more education live longer lives with better health. New evidence suggests that these benefits operate through a slowed pace of biological aging. If so, measurements of the pace of biological aging could offer intermediate end points for studies of how interventions to promote education will affect healthy longevity.

Objective

To test the hypothesis that upward educational mobility is associated with a slower pace of biological aging and increased longevity.

Design, Setting, and Participants

This prospective cohort study analyzed data from 3 generations of participants in the Framingham Heart Study: (1) the original cohort, enrolled beginning in 1948; (2) the Offspring cohort, enrolled beginning in 1971; and (3) the Gen3 cohort, enrolled beginning in 2002. A 3-generation database was constructed to quantify intergenerational educational mobility. Mobility data were linked with blood DNA-methylation data collected from the Offspring cohort in 2005 to 2008 (n = 1652) and the Gen3 cohort in 2009 to 2011 (n = 1449). Follow-up is ongoing. Data analysis was conducted from June 2022 to November 2023 using data obtained from the National Institutes of Health database of Genotypes and Phenotypes (dbGaP).

Exposure

Educational mobility was measured by comparing participants' educational outcomes with those of their parents.

Main Outcomes and Measures

The pace of biological aging was measured from whole-blood DNA-methylation data using the DunedinPACE epigenetic clock. For comparison purposes, the analysis was repeated using 4 other epigenetic clocks. Survival follow-up was conducted through 2019.

Results

This study analyzed data from 3101 participants from the Framingham Heart Study; 1652 were in the Offspring cohort (mean [SD] age, 65.57 [9.22] years; 764 [46.2%] male) and 1449 were in the Gen3 cohort (mean [SD] age, 45.38 [7.83] years; 691 [47.7%] male). Participants who were upwardly mobile in educational terms tended to have slower pace of aging in later life (r = -0.18 [95% CI, -0.23 to -0.13]; P < .001). This pattern of association was similar across generations and held in within-family sibling comparisons. There were 402 Offspring cohort participants who died over the follow-up period. Upward educational mobility was associated with lower mortality risk (hazard ratio, 0.89 [95% CI, 0.81 to 0.98]; P = .01). Slower pace of aging accounted for approximately half of this association.

Conclusions and Relevance

This cohort study's findings support the hypothesis that interventions to promote educational attainment may slow the pace of biological aging and promote longevity. Epigenetic clocks have potential as near-term outcome measures of intervention effects on healthy aging. Experimental evidence is needed to confirm findings.

Understanding the role of childhood nurture, abuse, and stability on gestational diabetes in the Coronary Artery Risk Development in Young Adults study (CARDIA)

BACKGROUND

To estimate associations between facets of the maternal childhood family environment with gestational diabetes (GDM) and to test mediation by pre-pregnancy waist circumference.

METHODS

We used data from CARDIA, a cohort of individuals aged 18-30 years at baseline (1985-86), followed over 30 years (2016). We included participants with one or more pregnancies ≥ 20 weeks after baseline, without pre-pregnancy diabetes. The primary exposure was the Childhood Family Environment Scale (assessed year 15), including the total score and abuse, nurture, and stability subscales as continuous, separate exposures. The outcome was GDM (self-reported at each visit for each pregnancy). We fit log binomial models with generalized estimating equations to calculate risk ratios (RR) and 95% confidence intervals (CI), adjusting for age at delivery, parity, race (Black or White), and parental education. We used regression models with bootstrapped CIs to test mediation and effect modification by excess abdominal adiposity at the last preconception CARDIA visit (waist circumference ≥ 88 cm).

RESULTS

We included 1033 individuals (46% Black) with 1836 pregnancies. 130 pregnancies (7.1%) were complicated by GDM. For each 1 point increase on the abuse subscale (e.g., from "rarely or never" to "some or little of the time") there was a 30% increased risk of GDM (RR: 1.3, 95% CI: 1.0, 1.7). There was evidence of effect modification but not mediation by preconception abdominal adiposity.

CONCLUSIONS

A more adverse childhood family environment was associated with increased risk of GDM, with a stronger association among individuals with preconception waist circumference ≥ 88 cm.

Stress, epigenetics, and aging: Unraveling the intricate crosstalk

Aging, as a complex process involving multiple cellular and molecular pathways, is known to be exacerbated by various stresses. Because responses to these stresses, such as oxidative stress and genotoxic stress, are known to interplay with the epigenome and thereby contribute to the development of age-related diseases, investigations into how such epigenetic mechanisms alter gene expression and maintenance of cellular homeostasis is an active research area. In this review, we highlight recent studies investigating the intricate relationship between stress and aging, including its underlying epigenetic basis; describe different types of stresses that originate from both internal and external stimuli; and discuss potential interventions aimed at alleviating stress and restoring epigenetic patterns to combat aging or age-related diseases. Additionally, we address the challenges currently limiting advancement in this burgeoning field.

Does biological age mediate the relationship between childhood adversity and depression? Insights from the Detroit Neighborhood Health Study

The link between childhood adversity and adulthood depression is well-established; however, the underlying mechanisms are still being explored. Recent research suggests biological age may mediate the relationship between childhood adversity and depression in later life. This study examines if biological age mediates the relationship between childhood adversity and depression symptoms using an expanded set of biological age measures in an urban population-based cohort. Data from waves 1-3 of the Detroit Neighborhood Health Study (DNHS) were used in this analysis. Questions about abuse during childhood were coded to form a childhood adversity score similar to the Adverse Childhood Experience measure. Multiple dimensions of biological age, defined as latent variables, were considered, including systemic biological age (GrimAge, PhenoAge), epigenetic age (Horvath, SkinBlood), and immune age (cytomegalovirus, herpes simplex virus type 1, C-reactive protein, interleukin-6). Depression symptoms, modeled as a latent variable, were captured through the Patient Health Questionnaire-9 (PHQ-9). Models were adjusted for age, gender, race, parent education, and past depressive symptoms. Total and direct effects of childhood adversity on depression symptoms and indirect effects mediated by biological age were estimated. For total and direct effects, we observed a dose-dependent relationship between cumulative childhood adversity and depression symptoms, with emotional abuse being particularly influential. However, contrary to prior studies, in this sample, we found few direct effects of childhood adversity on biological age or biological age on depression symptoms and no evidence of mediation through the measures of biological age considered in this study. Further research is needed to understand how childhood maltreatment experiences are embodied to influence health and wellness.