Neighborhood environment, social cohesion, and epigenetic aging

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

Risk of dementia due to Co-exposure to air pollution and neighborhood disadvantage

BACKGROUND

Co-exposure to air pollution and neighborhood disadvantage may influence cognition decline. We tested these associations in the context of dementia risk.

METHODS

We leveraged a cohort of adults ≥65 years (n = 5397) enrolled from 2011 to 2018 in the National Health and Aging Trends Study (NHATS). Particulate matter (PM) ≤ 10 μm in diameter, PM ≤ 2.5 μm in diameter, carbon monoxide, nitric oxide, and nitrogen dioxide - and neighborhood disadvantage were tested for joint associations with dementia risk. Pollutant concentrations at the 2010 census tract level were assigned using the US Environmental Protection Agency's Community Multiscale Air Quality Modeling System. Neighborhood disadvantage was defined using the tract Social Deprivation Index (SDI). Dementia was determined through self- or proxy-report or scores indicative of "probable dementia" according to NHATS screening tools. Joint effects of air pollutants and SDI were tested using quantile g-computation Cox proportional hazards models. We also stratified joint air pollution effects across SDI tertiles. Analyses adjusted for age at enrollment, sex, education, partner status, urbanicity, income, race and ethnicity, years at residence, census segregation, and census region.

RESULTS

SDI score (aHR = 1.08; 95% CI 0.96, 1.22), joint air pollution (aHR = 1.03, 95% CI 0.92, 1.16) and joint SDI with air pollution (aHR = 1.04, 95% CI 0.89, 1.22) were not associated with dementia risk. After accounting for competing risk of death, joint SDI with air pollution was not associated with dementia risk (aHR = 1.06; 95% CI 0.87, 1.29). In stratified models, joint air pollution was associated with greater risk of dementia at high (aHR = 1.19; 95% CI 0.87, 1.63), but not at medium or low SDI.

CONCLUSION

Air pollution was associated with greater dementia risk in disadvantaged areas after accounting for competing risks. Air pollution associations with dementia incidence may be attenuated when other risk factors are more prominent in disadvantaged neighborhoods.

Neighborhood Disadvantage and Parenting in Early Adolescence Predict Epigenetic Aging and Mortality Risk in Adulthood

Youth who grow up in disadvantaged neighborhoods experience poorer health later in life, but little is known about the biological mechanisms underlying these effects and socioenvironmental factors that may protect youth from the biological embedding of neighborhood adversity. This study tests whether supportive and consistent parenting buffers associations between neighborhood disadvantage in early adolescence and epigenetic aging in adulthood. A community sample from Birmingham, Alabama, USA (N = 343; 57% female; 81% Black, 19% White) was assessed in early adolescence (T1; ages 11 and 13) and adulthood (T2; age 27). At T1, neighborhood poverty was derived from census data and neighborhood disorder was reported by caregivers. Both youth and parents reported on parental discipline and nurturance. At T2, methylation of salivary DNA was used to derive a mortality risk index and Hannum, Horvath, PhenoAge, and GrimAge epigenetic age estimators. Regression analyses revealed that neighborhood disadvantage was associated with accelerated epigenetic aging and/or mortality risk only when combined with high levels of harsh and inconsistent discipline and low child-reported parental nurturance. These findings identify epigenetic aging and mortality risk as relevant mechanisms through which neighborhood adversity experienced in adolescence may affect later health; they also point to the importance of supportive and consistent parenting for reducing the biological embedding of neighborhood adversity in early adolescence.

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.

Hidalgo B, Aroke EN. Neighborhood Environment and Epigenetic Age: A Scoping Review

BACKGROUND

Interest in how the neighborhood environment impacts age-related health conditions has been increasing for decades. Epigenetic changes are environmentally derived modifications to the genome that alter the way genes function-thus altering health status. Epigenetic age, a biomarker for biological age, has been shown to be a useful predictor of several age-related health conditions. Consequently, its relation to the neighborhood environment has been the focus of a growing body of literature.

OBJECTIVE

We aimed to describe the scope of the evidence on the relationship between neighborhood environmental characteristics and epigenetic age.

METHODS

Using scoping review following methods established by Arksey and O'Malley, we first defined our research questions and searched the literature in PubMed, PsycINFO, and EMBASE. Next, we selected the literature to be included, and finally, we analyzed and summarized the information.

RESULTS

Nine articles met the inclusion criteria. Most studies examined deprivation as the neighborhood characteristic of interest. While all studies were observational in design, the articles included diverse participants, including men and women, adults and children, and multiple ethnicities. Results demonstrated a relationship between the neighborhood environment and epigenetic age, whether the characteristic of interest is socioeconomic or physical.

CONCLUSIONS

Overall, studies concluded there was a relationship between neighborhood characteristics and epigenetic age, whether the characteristic of interest was socioeconomic or physical. However, findings varied based on how the neighborhood characteristic and/or epigenetic age was measured. Furthermore, a paucity of investigations on physical characteristics was noticeable and warrants increased attention.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

The role of community cohesion in elderly people during the COVID-19 epidemic: a cross-sectional study

BACKGROUND

Elderly people were regarded as the most impacted and most vulnerable social group during the COVID-19 epidemic. The community environment is vital for their health. The elderly people had to stay home during the implementation of the management and control of the COVID-19 epidemic. They lack resources and suffer from anxiety. Thus, determining environmental factors beneficial for their physical and mental health is very important.

OBJECTIVE

This study aims to assess the association between community cohesion and physical and mental health among elderly people and to identify the related community service and environmental factors that may promote community cohesion.

METHODS

This community-based cross-sectional study was designed during the COVID-19 epidemic. A multistage sampling method is applied to this study. A total of 2,036 participants aged ≥ 60 years were sampled from 27 locations in China. Data were collected through face-to-face interviews. The neighborhood cohesion instrument consisting of three-dimensional scales was used to assess community cohesion. Self-efficacy and life satisfaction, cognitive function and depression, and community service and environmental factors were also measured using standard instruments. Statistical analyses were restricted to 2,017 participants. Separate logistic regression analysis was conducted to assess the association between community cohesion and physical and mental health factors, as well as related community service and environmental factors, among elderly people.

RESULTS

The results showed that high levels of community cohesion were associated with good self-perceived health status and life satisfaction and high levels of self-efficacy and psychological resilience, and their odds ratios (ORs) were 1.27 (95% CI, 1.01-1.59) and 1.20 (95% CI, 1.15-1.27) and 1.09 (95% CI, 1.05-1.13) and 1.05 (95% CI, 1.03-1.06), respectively. The length of stay in the community and the level of physical activity were positively associated with community cohesion scores, whereas the educational level was negatively associated with the community cohesion scores (P < .05). Community cohesion was also associated with low level of depression and high level of cognitive function. The community cohesion was significantly associated with community services and environmental factors from four dimensions. High levels of community cohesion were associated with transportation service, rental of rehabilitation equipment, high levels of satisfaction for community doctors' technical level and community waste disposal, and their ORs were 3.14 (95% CI, 1.87-5.28), 3.62 (95% CI, 2.38-5.52), 1.37 (95% CI, 1.08-1.73), and 1.23 (95% CI, 1.01-1.50), respectively.

CONCLUSIONS

Community cohesion was associated with the physical and mental health of elderly people. Our research suggests that enhancing community services and environmental management may be an effective strategy to increase community cohesion during the epidemic period of major infectious diseases.

CLINICALTRIAL

Objectively measured external building quality, Census housing vacancies and age, and serum metals in an adult cohort in Detroit, Michigan

BACKGROUND

Residentially derived lead pollution remains a significant problem in urban areas across the country and globe. The risks of childhood residence in housing contaminated with lead-based paint are well-established, but less is known about the effects of housing quality on adult lead exposure.

OBJECTIVE

To evaluate the effects of residential-area housing age, vacancy status, and building quality on adult lead exposures.

METHODS

We evaluated the effect of Census block group housing vacancy proportion, block group housing age, and in-person survey evaluated neighborhood building quality on serum levels of lead, mercury, manganese, and copper among a representative cohort of adults in Detroit, Michigan, from 2008-2013 using generalized estimating equations.

RESULTS

Participants in Census block groups with higher proportions of vacant and aged housing had non-significantly elevated serum lead levels. We identified similar positive associations between residence in neighborhoods with poorer objectively measured building quality and serum lead. Associations between Census vacancies, housing age, objectively measured building quality, and serum lead were stronger among participants with a more stable residential history.

SIGNIFICANCE

Vacant, aged, and poorly maintained housing may contribute to widespread, low-level lead exposure among adult residents of older cities like Detroit, Michigan. US Census and neighborhood quality data may be a useful tool to identify population-level lead exposures among US adults.

IMPACT

Using longitudinal data from a representative cohort of adults in Detroit, Michigan, we demonstrate that Census data regarding housing vacancies and age and neighborhood survey data regarding housing quality are associated with increasing serum lead levels. Previous research has primarily focused on housing quality and lead exposures among children. Here, we demonstrate that area-level metrics of housing quality are associated with lead exposures among adults.

Maternal depression and adverse neighbourhood conditions during pregnancy are associated with gestational epigenetic age deceleration

Gestational epigenetic age (GEA) acceleration and deceleration can indicate developmental risk and may help elucidate how prenatal exposures lead to offspring outcomes. Depression and neighbourhood conditions during pregnancy are well-established determinants of birth and child outcomes. Emerging research suggests that maternal depression may contribute to GEA deceleration. It is unknown whether prenatal neighbourhood adversity would likewise influence GEA deceleration. This study examined whether maternal depression and neighbourhood conditions independently or jointly contributed to GEA deceleration, and which social and environmental neighbourhood conditions were associated with GEA. Participants were from the Albany Infant and Mother Study (n = 204), a prospective non-probability sampled cohort of higher risk racial/ethnic diverse mother/infant dyads. GEA was estimated from cord blood. Depressive symptoms and census-tract level neighbourhood conditions were assessed during pregnancy. Maternal depression (β = -0.03, SE = 0.01, p = 0.008) and neighbourhood adversity (β = -0.32, SE = 0.14, p = 0.02) were independently associated with GEA deceleration, controlling for all covariates including antidepressant use and cell type proportions. Neighbourhood adversity did not modify the association of maternal depression and GEA (β = 0.003, SE = 0.03, p = 0.92). igher levels of neighbourhood poverty, public assistance, and lack of healthy food access were each associated with GEA deceleration; higher elementary school test scores (an indicator of community tax base) were associated with GEA acceleration (all p < 0.001). The results of this study indicated that maternal depression and neighbourhood conditions were independently and cumulatively associated GEA in this diverse population.

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health.

Understanding Health Inequalities Through the Lens of Social Epigenetics

Longstanding racial/ethnic inequalities in morbidity and mortality persist in the United States. Although the determinants of health inequalities are complex, social and structural factors produced by inequitable and racialized systems are recognized as contributing sources. Social epigenetics is an emerging area of research that aims to uncover biological pathways through which social experiences affect health outcomes. A growing body of literature links adverse social exposures to epigenetic mechanisms, namely DNA methylation, offering a plausible pathway through which health inequalities may arise. This review provides an overview of social epigenetics and highlights existing literature linking social exposures—i.e., psychosocial stressors, racism, discrimination, socioeconomic position, and neighborhood social environment—to DNA methylation in humans.We conclude with a discussion of social epigenetics as a mechanistic link to health inequalities and provide suggestions for future social epigenetics research on health inequalities.

Integrating Environment and Aging Research: Opportunities for Synergy and Acceleration

Despite significant overlaps in mission, the fields of environmental health sciences and aging biology are just beginning to intersect. It is increasingly clear that genetics alone does not predict an individual’s neurological aging and sensitivity to disease. Accordingly, aging neuroscience is a growing area of mutual interest within environmental health sciences. The impetus for this review came from a workshop hosted by the National Academies of Sciences, Engineering, and Medicine in June of 2020, which focused on integrating the science of aging and environmental health research. It is critical to bridge disciplines with multidisciplinary collaborations across toxicology, comparative biology, epidemiology to understand the impacts of environmental toxicant exposures and age-related outcomes. This scoping review aims to highlight overlaps and gaps in existing knowledge and identify essential research initiatives. It begins with an overview of aging biology and biomarkers, followed by examples of synergy with environmental health sciences. New areas for synergistic research and policy development are also discussed. Technological advances including next-generation sequencing and other-omics tools now offer new opportunities, including exposomic research, to integrate aging biomarkers into environmental health assessments and bridge disciplinary gaps. This is necessary to advance a more complete mechanistic understanding of how life-time exposures to toxicants and other physical and social stressors alter biological aging. New cumulative risk frameworks in environmental health sciences acknowledge that exposures and other external stressors can accumulate across the life course and the advancement of new biomarkers of exposure and response grounded in aging biology can support increased understanding of population vulnerability. Identifying the role of environmental stressors, broadly defined, on aging biology and neuroscience can similarly advance opportunities for intervention and translational research. Several areas of growing research interest include expanding exposomics and use of multi-omics, the microbiome as a mediator of environmental stressors, toxicant mixtures and neurobiology, and the role of structural and historical marginalization and racism in shaping persistent disparities in population aging and outcomes. Integrated foundational and translational aging biology research in environmental health sciences is needed to improve policy, reduce disparities, and enhance the quality of life for older individuals.

The Frailty Puzzle: Searching for Immortality or for Knowledge Survival?

What is the value of assessing the biological age and frailty and predicting residual lifespan and health status? The benefit is obvious if we have means to alter the pace of aging and the development of frailty. So far, limited but increasing examples of interventions altering the predicted status indicate that, at least in some cases, this is possible through interventions spanning from the economic-social through drug treatments. Thus, why searching for biological markers, when some clinical and socio-economic indicators do already provide sufficiently accurate predictions? Indeed, the search of frailty biomarkers and of their biological clocks helps to build up a mechanistic frame that may orientate the design of interventions and the time window of their efficacy. Among the candidate biomarkers identified, several studies converge to indicate epigenetic clocks as a promising sensitive biomarker of the aging process. Moreover, it will help to establish the relationship between personal aging and health trajectories and to individuate the check points beyond which biological changes are irreversible.

The accelerated aging phenotype: The role of race and social determinants of health on aging

The pursuit to discover the fundamental biology and mechanisms of aging within the context of the physical and social environment is critical to designing interventions to prevent and treat its complex phenotypes. Aging research is critically linked to understanding health disparities because these inequities shape minority aging, which may proceed on a different trajectory than the overall population. Health disparities are characteristically seen in commonly occurring age-associated diseases such as cardiovascular and cerebrovascular disease as well as diabetes mellitus and cancer. The early appearance and increased severity of age-associated disease among African American and low socioeconomic status (SES) individuals suggests that the factors contributing to the emergence of health disparities may also induce a phenotype of 'premature aging' or 'accelerated aging' or 'weathering'. In marginalized and low SES populations with high rates of early onset age-associated disease the interaction of biologic, psychosocial, socioeconomic and environmental factors may result in a phenotype of accelerated aging biologically similar to premature aging syndromes with increased susceptibility to oxidative stress, premature accumulation of oxidative DNA damage, defects in DNA repair and higher levels of biomarkers of oxidative stress and inflammation. Health disparities, therefore, may be the end product of this complex interaction in populations at high risk. This review will examine the factors that drive both health disparities and the accelerated aging phenotype that ultimately contributes to premature mortality.

Neighborhood structural disadvantage and biological aging in a sample of Black middle age and young adults

OBJECTIVES

Research on the social determinants of health has suggested that neighborhood disadvantage may undermine healthy aging and is particularly relevant for understanding health disparities. Recently, this work has examined deoxyribonucleic acid methylation (DNAm)-based measures of biological aging to understand the risk factors for morbidity and mortality. However, it is unknown whether neighborhood disadvantage is related to different indices of DNAm-based aging among Black Americans and whether such neighborhood effects vary as a function of age or gender.

METHODS

Our analyses of a Black American sample included 448 young adults and 493 middle-aged adults. We measured neighborhood disadvantage using the Area Deprivation Index at the census block group level. DNAm-based accelerated aging indices were measured using established procedures. Regressions with clustered standard errors were used for the analysis.

RESULTS

Neighborhood disadvantage was independently associated with acceleration in PhenoAge, GrimAge, and DunedinPoAm, among young and middle-aged adults. Further, there was no evidence that gender conditioned the effects of neighborhood disadvantage on the aging indices.

CONCLUSIONS

Regardless of age groups or gender, accelerated biological aging among Black Americans is partly rooted in differences in neighborhood disadvantage. From a policy standpoint, our findings suggest that programs that decrease neighborhood disadvantage are likely to increase healthy aging, especially among Black Americans.