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Conceptual graph showing the relation between chronological and biological age across individuals (depicted as circles). Although age predicted with biological measures, such as DNA methylation, generally correlates well with chronological age at the population level (dotted black line), the two can substantially differ for certain individuals, who can thus follow trajectories with either accelerated (biological age > chronological age; orange continuous line) or decelerated biological aging (biological age < chronological age; blue continuous line). Such interindividual variance in biological aging may be explained by genetic factors that confer risk or resilience, environmental factors such as psychosocial stress, and their complex interplay. For illustrative purposes, the figure highlights two individuals with the same chronological age and either accelerated (orange circle) or decelerated biological aging (blue circle)
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Psychosocial stress—especially when chronic, excessive, or occurring early in life—has been associated with accelerated aging and increased disease risk. With rapid aging of the world population, the need to elucidate the underlying mechanisms is pressing, now more so than ever. Among molecular mechanisms linking stress and aging, the present artic...
Citations
... The accumulation of socioeconomic disadvantages across the life course is a robust predictor of the risk for CKD [19,29]. Finally, the new epigenetic indices for analyzing DNA methylation provide robust tools to capture the accumulation of physiological wear-and-tear across the life course, including stressors associated with socioeconomic disadvantages [20,29,30]. Prior analyses showed accelerated epigenetic aging may also capture socioeconomic disadvantages across generations [31]. ...
Epigenetic aging measures are novel molecular indicators of biological aging that predict age-related chronic disease. We examined whether several established indices of epigenetic aging mediated the association between life course socioeconomic status (SES) and decrements in kidney function across a decade. Biomarker data were from 252 non-Hispanic (NH) Black and white participants who had consented to genetic analyses in Wave 2 (2004–2009) and 3 (2014–2021) of the Midlife in the United States study (MIDUS). Life course SES included parental education, a proxy of early life SES, and a composite score of adult SES based on the highest education level, household income to poverty line ratio, health insurance coverage, perception of the availability of money to meet needs, and difficulty level paying monthly bills. We included five measures of epigenetic age accelerations (EAA), based on the residuals after each epigenetic clock was regressed on chronological age (Horvath, Horvath blood and skin, Hannum, PhenoAge, and GrimAge) and one measure of the pace of aging (DunedinPACE) obtained during MIDUS 2. Kidney function was based on serum creatinine–based estimated glomerular filtration rate (eGFR), calculated using the CKD-EPI formula (without race adjustment). We calculated absolute decrements in eGFR across 11 years between MIDUS waves 2 and 3. Analyses were adjusted for age, sex, and health-related covariates (currently smoking, obese, hypertension, and insulin resistance). Lower adult SES and accelerated epigenetic aging, especially accelerated GrimAge and faster DunedinPACE pace of aging, mediated the association between lower parental education and larger decrements in eGFR. Accelerated epigenetic aging is associated with larger decrements in kidney function across a decade and may be one of the critical explanatory pathways for the higher burden of chronic kidney disease (CKD) among lower SES individuals.
... Th e last several decades of stress research have produced new data that changed our understanding of the stress process, the mechanisms by which psychosocial stress aff ects health and how the stress works to instigate pathology. Integrating the results from biological and medical sciences into sociological research on stress and disease has helped shift ing our conceptualization of the role of social factors in patterns of aging, immunity, disease, and mortality (associations between chronic stress and hypertension (Bautista et al., 2019); links between loneliness, stress and disease (Berkman, Glymour, & Kawachi, 2014); diff erential eff ects of objective stress exposure and subjective (perceived) stress severity on health (Christensen et al., 2019); formulating mechanisms leading from stress to disease (McEwen & Stellar, 1993;Pearlin, 1989); exploring co-evolutionary pathways between social stress and social behavior (Rubenstein et al., 2019); highlighting connections between stress, aging, and senescence (Zannas, 2019). Th e impact of childhood adversity (scarce resources, parental neglect, abuse etc. in early years of life which can be associated with low SES) on health has been acknowledged. ...
... Th e impact of childhood adversity (scarce resources, parental neglect, abuse etc. in early years of life which can be associated with low SES) on health has been acknowledged. While the existing theoretical models diff er in the details of their causal arguments, childhood stress has been shown by multiple researchers to produce a cascade of negative symptoms in health in later life (Epel et al., 2018;Fogelman & Canli, 2019 for scoping reviews); adverse childhood experiences and incidents of abuse (Felitti, 2009); stress in early years of life and risks of chronic disease, especially cardiovascular disease (Friedman, Karlamangla, Gruenewald, Koretz, & Seeman, 2015;Friedman, Montez, Sheehan, Gruenewald, & Seeman, 2015); a life-course approach to stress emphasizing the impact of stress 'baggage' accumulated with years of life (Yang, Gerken, Schorpp, Boen, & Harris, 2017;Slavich, 2016); the link between distressing experiences and the speed of aging (Zannas, 2019). ...
Health is biocultural. Some of the challenges the social scientists are traditionally facing include understanding, measuring, and explaining the effects of culture on human condition. While the effects of culture in cognition, emotion, behavior, and health are not disputed, the casual relationships between them and their specific mechanisms are still not clearly understood. Current biocultural research explores multiple themes and subsumes several diverse intellectual positions. Although this set of approaches is highly suitable to explore the critical junctures within health research, it is a relatively new research trajectory. In terms of data, biocultural research builds on interdisciplinary evidence. As the interdisciplinary communication between the social and life sciences has expanded and intensified, during the last few decades we have witnessed an incremental interest in the ways various forms of social organization affect health. It is understood that health is shaped by many factors. Social determinants of health theory is a framework offering important insights into how exactly human society can affect and mold human health and disease. Socio-epidemiological research offers ample insights into the risk factors associated with these determinants, as well as the pathways linking social conditions to the important health outcomes. One of the major ways social factors of such nature can affect human physiology and shape the patterns of health and illness is by generating stress. Being present in one’s life from birth through maturation to senescence, social determinants of health are conceptualized as exercising systematic pressure in daily lives of individuals. SES is considered the most potent among social determinants of stress. While social determinants of health are conceptualized as the most modifiable among the health-determining conditions and therefore highly actionable to improve health and the quality of life, many questions still require solutions. One of the possible avenues for both improving our understanding of how social determinants of health work and painting a complete picture of what the social gradient in health is, is by way of inclusion of the ethnographically diverse settings, to glean more data from non-Western societies in order to explore how the social gradient in health emerges.
... Together, a low MAE and high R-squared or age correlation are characteristics of an accurate clock ( Figure 2). When chronological age estimates are reasonably accurate and precise, the residual difference between the chronological and epigenetic ages of an animal, as predicted by the clock, reflects its epigenetic age acceleration (Horvath and Raj 2018), which is a measure of biological age acceleration associated with mortality (Chen et al. 2016;Marioni et al. 2015), disease (Lu et al. 2019) and lifetime stress (Zannas 2019). ...
... Recent research has also identified connections between ecologically relevant environmental stressors and epigenetic age acceleration (Anderson et al. 2021;Newediuk et al. 2024), mirroring biomedical findings and suggesting that epigenetic age acceleration can serve as a useful measure of lifetime stress in wildlife. Unlike traditional wildlife stress biomarkers, such as glucocorticoid hormone levels, which are highly variable and lack a clear reference point for an 'unstressed' animal (Romero and Beattie 2022), epigenetic age acceleration is relatively stable and has been consistently associated with stress and health across lifetimes (Lu et al. 2019;Perna et al. 2016;Zannas 2019). However, it should be noted that epigenetic clocks can estimate age acceleration only when applied to known-age samples, the availability of which can be limited in wildlife studies. ...
The applications of epigenetic clocks – statistical models that predict an individual's age based on DNA methylation patterns – are expanding in wildlife conservation and management. This growing interest highlights the need for field‐specific design best practices. Here, we provide recommendations for two main applications of wildlife epigenetic clocks: estimating the unknown ages of individuals and assessing their biological ageing rates. Epigenetic clocks were originally developed to measure biological ageing rates of human tissues, which presents challenges for their adoption in wildlife research. Most notably, the estimated chronological ages of sampled wildlife can be unreliable, and sampling restrictions limit the number and variety of tissues with which epigenetic clocks can be constructed, reducing their accuracy. To address these challenges, we present a detailed workflow for designing, validating applying accurate wildlife epigenetic clocks. Using simulations and analyses applied to an extensive polar bear dataset from across the Canadian Arctic, we demonstrate that accurate epigenetic clocks for wildlife can be constructed and validated using a limited number of samples, accommodating projects with small budgets and sampling constraints. The concerns we address are critical for clock design, whether researchers or third‐party service providers perform the bioinformatics. With our workflow and examples, we hope to support the accessible and widespread use of epigenetic clocks in wildlife conservation and management.
... It is important to acknowledge the significant role that epigenetic mechanisms play in the impact of stress on aging processes and the development of stressrelated diseases [45]. ...
... The Horvath clock also showed advanced epigenetic aging that was particularly pronounced in TM but remained stable over the study period. A potential explanation for the higher accelerated aging detected especially by the Horvath clock is the known eroding effect that negative social experiences have on the epigenome [56,57] . Previous studies have shown that epigenetic clocks, including the Horvath and Hannum, are accelerated by psychosocial stress, adversity, and discrimination [41,[58][59][60][61] . ...
Gender-affirming hormone therapy (GAHT) is a necessary treatment for many transgender people, and there is a critical need to further improve treatment experience and mitigate possible risks. Here we investigated whether DNA methylation (DNAm) biomarkers of health and aging are modified during the first year of GAHT and whether these vary by treatment type. Cohort consisted of 13 trans women and 13 trans men. Sampling occurred at baseline (pre-GAHT), and at 6- and 12-month follow-up. We tracked the longitudinal dynamics of three epigenetic clocks (Horvath, Hannum, PhenoAge), DNA methylation-based telomere length (DNAmTL), and DunedinPACE. At baseline, the Horvath and Hannum showed accelerated epigenetic aging, particularly pronounced among trans men, while the PhenoAge and DunedinPACE showed lower pace of aging in both groups. This discrepancy may reflect possible effects of minority stress in an otherwise healthy cohort. While GAHT did not affect the three clocks, DNAmTL and DunedinPACE showed treatment-specific patterns but with notable inter-individual variability in trajectories. Trans women had increased DunedinPACE (estimate = 0.057, p=0.002) and slight DNAmTL gains (estimate = 0.024, ns); trans men exhibited stable to slight decline in DunedinPACE (estimate = -0.013, ns), and reduction in DNAmTL (estimate = -0.057, p=0.037). The marked heterogeneity is indicative of an individualized response to treatment and highlights the potential value of incorporating such biomarkers in comprehensive health monitoring. Our findings emphasize the need for larger, long-term studies to optimize personalized strategies for gender-affirming healthcare.
... Epigenetic clocks assess biological age acceleration as the residual difference between an 118 animal's known chronological age and its epigenetic age as predicted by the clock. Positive age 119 acceleration has been linked to environmental stress (Zannas, 2019), disease 120 Perna et al., 2016), and early death (Marioni et al., 2015) in humans. As in humans, epigenetic 121 clocks for wildlife can only estimate age acceleration when applied to known-age samples. ...
... which are highly variable and lack a clear reference point for an "unstressed" animal (Romero & 137 Beattie, 2022)-epigenetic age acceleration is relatively stable and has been consistently 138 associated with stress and health Perna et al., 2016;Zannas, 2019). 139 ...
The potential applications of epigenetic clocks are expanding in wildlife conservation and management. The pace at which they are being adopted highlights the need for field-specific design best practices. Epigenetic clocks were originally developed for human studies, presenting challenges for their adoption in wildlife research. Most notably, the estimated ages of sampled wildlife can be unreliable, and sampling restrictions limit the number and variety of available samples, which can reduce the accuracy of epigenetic clocks for wildlife. In this article, we present a detailed workflow for designing, validating, and applying wildlife epigenetic clocks in a way that accounts for sampling constraints. We provide recommendations for two main applications of wildlife epigenetic clocks: estimating unknown ages and assessing cumulative biological aging. Our simulations and analyses, applied to an extensive polar bear dataset from across the Canadian Arctic, demonstrate that accurate epigenetic clocks for wildlife can be constructed and validated with limited samples, accommodating projects with small budgets and sampling constraints. With our workflow and examples, we hope to make epigenetic clock use more accessible and widespread in wildlife conservation and management.
... For example, when a dietary intervention includes caloric restriction [15,19,20] or vitamin D deficiency [17], this could cause a psychological stressor on the subject due to being hungry or malnourished. Psychological stressors on their own create their own effects on the epigenome [99] which are not the focus here and, therefore, function as a confounding variable. Additionally, the biggest challenge to drawing conclusions may be that while epigenetic changes are studied in multiple generations for each study, the number of generations studied varies. ...
Exposure to toxins causes lasting damaging effects on the body. Numerous studies in humans and animals suggest that diet has the potential to modify the epigenome and these modifications can be inherited transgenerationally, but few studies investigate how diet can protect against negative effects of toxins. Potential evidence in the primary literature supports that caloric restriction, high-fat diets, high protein-to-carbohydrate ratios, and dietary supplementation protect against environmental toxins and strengthen these effects on their offspring’s epigenome. Most notably, the timing when dietary interventions are given – during a parent’s early development, pregnancy, and/or lifetime – result in similar transgenerational epigenetic durations. This implies the existence of multiple opportunities to strategically fortify the epigenome. This narrative review explores how to best utilize dietary modifications to modify the epigenome to protect future generations against negative health effects of persistent environmental toxins. Furthermore, by suggesting an ideal diet with specific micronutrients, macronutrients, and food groups, epigenetics can play a key role in the field of preventive medicine. Based on these findings, longitudinal research should be conducted to determine if a high protein, high-fat, and low-carbohydrate diet during a mother’s puberty or pregnancy can epigenetically protect against alcohol, tobacco smoke, and air pollution across multiple generations.
... However, the underlying biological mechanisms remain to be elucidated. DNAm is a potential cellular mechanism through which this association may occur [64]. Thus, there has been a growing interest in examining the impact of perceived discrimination on DNAm, including two EWAS in small cohorts of African American women and African migrants in Europe [27,28]. ...
Perceived discrimination, recognized as a chronic psychosocial stressor, has adverse consequences on health. DNA methylation (DNAm) may be a potential mechanism by which stressors get embedded into the human body at the molecular level and subsequently affect health outcomes. However, relatively little is known about the effects of perceived discrimination on DNAm. To identify the DNAm sites across the epigenome that are associated with discrimination, we conducted epigenome-wide association analyses (EWAS) of three discrimination measures (everyday discrimination, race-related major discrimination, and non-race-related major discrimination) in 1,151 participants, including 565 non-Hispanic White, 221 African American, and 365 Hispanic individuals, from the Multi-Ethnic Study of Atherosclerosis (MESA). We conducted both race/ethnicity-stratified analyses as well as trans-ancestry meta-analyses. At false discovery rate of 10%, 7 CpGs and 4 differentially methylated regions (DMRs) containing 11 CpGs were associated with perceived discrimination exposures in at least one racial/ethnic group or in meta-analysis. Identified CpGs and/or nearby genes have been implicated in cellular development pathways, transcription factor binding, cancer and multiple autoimmune and/or inflammatory diseases. Of the identified CpGs (7 individual CpGs and 11 within DMRs), two CpGs and one CpG within a DMR were associated with expression of cis genes NDUFS5, AK1RIN1, NCF4 and ADSSL1. Our study demonstrated the potential influence of discrimination on DNAm and subsequent gene expression.
... Epigenetics is the study of the effect of all nongenetic factors influencing one or more genetic traits of an individual. The epigenetic factors are generally involved in the regulation of expression of the genes through methylation, phosphorylation, or acetylation of the DNA molecules, but not by altering the sequence of the nucleotides [6,9,27]. Psychological stressors can invite inflammation and different epigenetic activities like oxidative stress (non or improper removal of free radicals), mitochondrial dysfunctions, etc. [28,29]. ...
Psychological stressors can show their negative effects on an individual's mental and physical
states. Following the psycho-neuro-immuno-endocrine axis, they can influence different internal organs and
systems of the body. Such influence can affect the hypothalamus-pituitary-adrenal axis and modify the
secretion of different neuroendocrine mediators. Altered secretions of neurotransmitters, neuropeptides,
and other cytokines and chemokines (including pro-inflammatory cytokines); corticosteroids, catecholamines,
etc. can initiate or potentiate health problems of different types and magnitudes. Psychological stressors
can affect feeding, social behavior, pain sensation, learning, memory, reproduction, etc. They may act as the
root for the development of conditions like epilepsy, hysteria, dementia, melancholia, psychosis, movement
disorders, etc. Anxiety, confusion, depression, memory issues, problems in decision-making, attraction to
negative thoughts, difficulty in focusing, lack of self-confidence, emotional disturbances, sudden changes of
mood, increased irritability, unhappiness, hopelessness, inability to relax, etc. are some common effects of
stress. Physiological conditions like headache, migraine, increased heart rate, sleep disturbances, high blood
pressure, muscle tension, decreased libido, early fatigue, different gastrointestinal disorders, obesity,
diabetes, idiopathic diseases, atopic skin diseases (eczema, acne, etc.), psoriasis, delayed wound healing,
menstruation problems of ladies, etc. are developed due to stress. Developments of various immunityrelated,
allergic, rheumatic, autoimmune, endocrine, neoplastic, and cardiovascular diseases are connected
to different psychological stress components. Development of a self-care attitude, changing the surrounding
environment to a favorable one, modification of lifestyle, practicing mind-controlling exercises like yoga
and meditation, as well as taking assistance from any mental health professionals can be considered to
counter or overcome psychological stress and staying away from different physical and mental health
problems.
... Several studies have identified associations between psychosocial stress and traditional cardiometabolic risk factors including hypertension [12], dyslipidemia [13], dysglycemia [14], and obesity [15], as well as CRP [16]. Additionally, prior research has linked psychosocial stress to epigenetic mechanisms, including DNA methylation, a biochemical modification to DNA and its related proteins that regulates gene expression without altering the underlying genetic sequence [17]. Both candidate gene studies and epigenome-wide association studies (EWAS) have examined the associations between psychosocial stress and DNA methylation [18][19][20][21][22][23]. ...
Background
Exposure to psychosocial stress is linked to a variety of negative health outcomes, including cardiovascular disease and its cardiometabolic risk factors. DNA methylation has been associated with both psychosocial stress and cardiometabolic disease; however, little is known about the mediating role of DNA methylation on the association between stress and cardiometabolic risk. Thus, using the high-dimensional mediation testing method, we conducted an epigenome-wide mediation analysis of the relationship between psychosocial stress and ten cardiometabolic risk factors in a multi-racial/ethnic population of older adults (n = 2668) from the Health and Retirement Study (mean age = 70.4 years).
Results
A total of 50, 46, 7, and 12 CpG sites across the epigenome mediated the total effects of stress on body mass index, waist circumference, high-density lipoprotein cholesterol, and C-reactive protein, respectively. When reducing the dimensionality of the CpG mediators to their top 10 uncorrelated principal components (PC), the cumulative effect of the PCs explained between 35.8 and 46.3% of these associations.
Conclusions
A subset of the mediating CpG sites were associated with the expression of genes enriched in pathways related to cytokine binding and receptor activity, as well as neuron development. Findings from this study help to elucidate the underlying mechanisms through which DNA methylation partially mediates the relationship between psychosocial stress and cardiometabolic risk factors.
