Work-related stress and well-being in association with epigenetic age acceleration: A Northern Finland Birth Cohort 1966 Study

An overview of work-related stress assessment

OBJECTIVE

Work-related stress (WRS) is associated with the development of various health issues and long-term absence from the workplace. Adequate measurement of WRS is essential to assess its prevalence, risks, and effectiveness of preventive interventions. The aim of this review was to provide an overview of different categories of WRS assessment: 1) self-assessment, 2) external assessment, and 3) biomarkers.

METHODS

The databases MEDLINE, PsycINFO, EMBASE, CINAHL, and Web of Science have been searched until July 2024 for studies comprising self-assessment or external assessment of WRS, and WRS biomarkers. The self-assessment studies were further evaluated following the COSMIN guidelines.

RESULTS

In this review, a total of 15,749 articles were screened. The final analysis included 53 studies on self-assessment of WRS, 33 articles on external assessment of WRS and 167 articles on stress biomarkers. Within self-assessment studies, four instruments were included in the analysis: Job Content Questionnaire, Effort Reward Imbalance Questionnaire, Copenhagen Psychosocial Questionnaire II and the Demand-Control-Support Questionnaire. The studies applying external assessment used job-exposure matrices, work register data, ethnography, digital tools, and external observation. The identified WRS biomarkers were associated with the sympathetic adrenal medullary axis, the hypothalamic pituitary adrenal axis, immune response and inflammation, and haemostatic, metabolic and (epi)genetic biomarkers.

CONCLUSION

The available evidence does not support the claim that there is a singular golden standard for assessing WRS. Inclusion of objective parameters and the interaction with subjective parameters and biological markers has to be studied to receive a broader view of WRS.

Quantification of Epigenetic Aging in Public Health

Estimators of biological age hold promise for use in preventive medicine, for early detection of chronic conditions, and for monitoring the effectiveness of interventions aimed at improving population health. Among the promising biomarkers in this field are DNA methylation-based biomarkers, commonly referred to as epigenetic clocks. This review provides a survey of these clocks, with an emphasis on second-generation clocks that predict human morbidity and mortality. It explores the validity of epigenetic clocks when considering factors such as race, sex differences, lifestyle, and environmental influences. Furthermore, the review addresses the current challenges and limitations in this research area.

Correlation analysis of occupational stress and metabolic syndrome among employees of a power grid enterprise in China

BACKGROUND

Being in a state of high occupational stress may disrupt the metabolic balance of the body, thus increasing the risk of metabolic diseases. However, the evidence about the relationship between occupational stress and metabolic syndrome was limited.

OBJECTIVES

To explore the association between occupational stress and metabolic syndrome (MetS) in employees of a power grid enterprise.

METHODS

A total of 1091 employees were recruited from a power grid enterprise in China. Excluding those who failed to complete the questionnaire and those who had incomplete health check-ups, 945 subjects were included in the study. Assessment of occupational stress was used by job demand-control (JDC) and effort-reward imbalance (ERI) questionnaires, respectively. The information on body mass index (BMI), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were collected. The levels of high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and fasting blood glucose (FBG) in the fasting venous blood samples were measured. Logistic regression analysis and multiple linear regression methods were used to analyze the correlation between JDC and ERI models of occupational stress, metabolic syndrome, and its components, respectively.

RESULTS

The prevalence of MetS was 8.4% and 9.9% in JDC and ERI model high occupational stress employees, respectively. ERI model occupational stress and smoking are significantly associated with the risk of MetS. ERI ratio was significantly associated with lower HDL-C levels. Gender, age, marital status, smoking, high-temperature and high-altitude work were significantly associated with metabolic component levels.

CONCLUSION

Our study revealed a high detection rate of occupational stress in both JDC and ERI models among employees of a power grid enterprise. ERI model occupational stress, demanding more attention, was associated with the risk of MetS as well as its components such as HDL-C.

Epigenetic Mechanisms in Aging: Extrinsic Factors and Gut Microbiome

BACKGROUND/OBJECTIVES

Aging is a natural physiological process involving biological and genetic pathways. Growing evidence suggests that alterations in the epigenome during aging result in transcriptional changes, which play a significant role in the onset of age-related diseases, including cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. For this reason, the epigenetic alterations in aging and age-related diseases have been reviewed, and the major extrinsic factors influencing these epigenetic alterations have been identified. In addition, the role of the gut microbiome and its metabolites as epigenetic modifiers has been addressed.

RESULTS

Long-term exposure to extrinsic factors such as air pollution, diet, drug use, environmental chemicals, microbial infections, physical activity, radiation, and stress provoke epigenetic changes in the host through several endocrine and immune pathways, potentially accelerating the aging process. Diverse studies have reported that the gut microbiome plays a critical role in regulating brain cell functions through DNA methylation and histone modifications. The interaction between genes and the gut microbiome serves as a source of adaptive variation, contributing to phenotypic plasticity. However, the molecular mechanisms and signaling pathways driving this process are still not fully understood.

CONCLUSIONS

Extrinsic factors are potential inducers of epigenetic alterations, which may have important implications for longevity. The gut microbiome serves as an epigenetic effector influencing host gene expression through histone and DNA modifications, while bidirectional interactions with the host and the underexplored roles of microbial metabolites and non-bacterial microorganisms such as fungi and viruses highlight the need for further research.

Using non-invasive behavioral and physiological data to measure biological age in wild baboons

Biological aging is near-ubiquitous in the animal kingdom, but its timing and pace vary between individuals and over lifespans. Prospective, individual-based studies of wild animals-especially non-human primates-help identify the social and environmental drivers of this variation by indicating the conditions and exposure windows that affect aging processes. However, measuring individual biological age in wild primates is challenging because several of the most promising methods require invasive sampling. Here, we leverage observational data on behavior and physiology, collected non-invasively from 319 wild female baboons across 2402 female-years of study, to develop a composite predictor of age: the non-invasive physiology and behavior (NPB) clock. We found that age predictions from the NPB clock explained 51% of the variation in females' known ages. Further, deviations from the clock's age predictions predicted female survival: females predicted to be older than their known ages had higher adult mortality. Finally, females who experienced harsh early-life conditions were predicted to be about 6 months older than those who grew up in more benign conditions. While the relationship between early adversity and NPB age is noisy, this estimate translates to a predicted 2-3 year reduction in mean adult lifespan in our model. A constraint of our clock is that it is tailored to data collection approaches implemented in our study population. However, many of the clock's components have analogs in other populations, suggesting that non-invasive data can provide broadly applicable insight into heterogeneity in biological age in natural populations.

Associations between cardiorespiratory fitness and lifestyle-related factors with DNA methylation-based ageing clocks in older men: WASEDA'S Health Study

DNA methylation-based age estimators (DNAm ageing clocks) are currently one of the most promising biomarkers for predicting biological age. However, the relationships between cardiorespiratory fitness (CRF), measured directly by expiratory gas analysis, and DNAm ageing clocks are largely unknown. We investigated the relationships between CRF and the age-adjusted value from the residuals of the regression of DNAm ageing clock to chronological age (DNAmAgeAcceleration: DNAmAgeAccel) and attempted to determine the relative contribution of CRF to DNAmAgeAccel in the presence of other lifestyle factors. DNA samples from 144 Japanese men aged 65-72 years were used to appraise first- (i.e., DNAmHorvath and DNAmHannum) and second- (i.e., DNAmPhenoAge, DNAmGrimAge, and DNAmFitAge) generation DNAm ageing clocks. Various surveys and measurements were conducted, including physical fitness, body composition, blood biochemical parameters, nutrient intake, smoking, alcohol consumption, disease status, sleep status, and chronotype. Both oxygen uptake at ventilatory threshold (VO2 /kg at VT) and peak oxygen uptake (VO2 /kg at Peak) showed a significant negative correlation with GrimAgeAccel, even after adjustments for chronological age and smoking and drinking status. Notably, VO2 /kg at VT and VO2 /kg at Peak above the reference value were also associated with delayed GrimAgeAccel. Multiple regression analysis showed that calf circumference, serum triglyceride, carbohydrate intake, and smoking status, rather than CRF, contributed more to GrimAgeAccel and FitAgeAccel. In conclusion, although the contribution of CRF to GrimAgeAccel and FitAgeAccel is relatively low compared to lifestyle-related factors such as smoking, the results suggest that the maintenance of CRF is associated with delayed biological ageing in older men.

Occupational characteristics and epigenetic aging among older adults in the United States

Occupational characteristics have been studied as risk factors for several age-related diseases and are thought to impact the ageing process, although there has been limited empirical work demonstrating an association between adverse occupational characteristics and accelerated ageing and this prior work has yielded mixed results. We used the 2010 and 2016 waves of the Health and Retirement Study (n = 1,251) to examine the association between occupation categories and self-reported working conditions of American adults at midlife and their subsequent epigenetic ageing as measured through five epigenetic clocks: PCHorvath, PCHannum, PCPhenoAge, PCGrimAge, and DunedinPACE. We found that individuals working in sales/clerical, service, and manual work show evidence of epigenetic age acceleration compared to those working in managerial/professional jobs and that the associations were stronger with second- and third-generation clocks. Individuals reporting high stress and high physical effort at work showed evidence of epigenetic age acceleration only on PCGrimAge and DunedinPACE. Most of these associations were attenuated after adjustment for race/ethnicity, educational attainment, and lifestyle-related risk factors. Sales/clerical work remained significantly associated with PCHorvath and PCHannum, while service work remained significantly associated with PCGrimAge. The results suggest that manual work and occupational physical activity may appear to be risk factors for epigenetic age acceleration through their associations with socioeconomic status, while stress at work may be a risk factor for epigenetic age acceleration through its associations with health behaviours outside of work. Additional work is needed to understand when in the life course and the specific mechanisms through which these associations occur.

Monitoring Social Determinants of Health Assessing Patients and Communities

Because of the devastating health effects of social determinants of health (SDoH), it is important for the primary care provider to assess and monitor these types of stressors. This can be done via surveys, geomapping, or various biomarkers. To date, however, each of these methods is fraught with obstacles. There are currently are no validated "best" SDoH screening tools for use in clinical practice. Nor is geomapping, a perfect solution. Although mapping can collect location specific factors, it does not account for the fact that patients may live in one area, work in another and travel frequently to a third.

The multiple roles of life stress in metabolic disorders

The activation of stress-related neuroendocrine systems helps to maintain homeostasis, but excessive stress can damage body functions. We review current evidence from basic sciences and epidemiology linking stress to the development and progression of metabolic disorders throughout life. Findings from rodents demonstrate that stress can affect features of metabolic dysfunction, such as insulin resistance, glucose and lipid homeostasis, as well as ageing processes such as cellular senescence and telomere length shortening. In human studies, stressors in the home, workplace and neighbourhood are associated with accelerated ageing and metabolic and immune alterations, both directly and indirectly via behavioural risks. The likelihood of developing clinical conditions, such as diabetes mellitus and hepatic steatosis is increased in individuals with adverse childhood experiences or long-term (years) or severe stress at work or in private life. The increased risk of metabolic disorders is often associated with other stress-related conditions, such as mental health disorders, cardiovascular disease and increased susceptibility to infections. Equally, stress can worsen prognosis in metabolic diseases. As favourable modifications in stressors are associated with reductions in incidence of metabolic disorders, further investigation of the therapeutic value of targeting stress in personalized medicine is warranted.

Association between work characteristics and epigenetic age acceleration: cross-sectional results from UK - Understanding Society study

Occupation-related stress and work characteristics are possible determinants of social inequalities in epigenetic aging but have been little investigated. Here, we investigate the association of several work characteristics with epigenetic age acceleration (AA) biomarkers. The study population included employed and unemployed men and women (n = 631) from the UK Understanding Society study. We evaluated the association of employment and work characteristics related to job type, job stability; job schedule; autonomy and influence at work; occupational physical activity; and feelings regarding the job with four epigenetic age acceleration biomarkers (Hannum, Horvath, PhenoAge, GrimAge) and pace of aging (DunedinPoAm, DunedinPACE). We fitted linear regression models, unadjusted and adjusted for established risk factors, and found the following associations for unemployment (years of acceleration): HorvathAA (1.51, 95% CI 0.08, 2.95), GrimAgeAA (1.53, 95% CI 0.16, 2.90) and 3.21 years for PhenoAA (95% CI 0.89, 5.33). Job insecurity increased PhenoAA (1.83, 95% CI 0.003, 3.67), while working at night was associated with an increase of 2.12 years in GrimAgeAA (95% CI 0.69, 3.55). We found effects of unemployment to be stronger in men and effects of night shift work to be stronger in women. These results provide evidence of associations between unemployment with accelerated ageing and suggest that insecure employment and night work may also increase age acceleration. Our findings have implications for policies relating to current changes in working conditions and highlight the utility of biological age biomarkers in studies in younger populations without long-term health information.

A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events

BACKGROUND

Recent evidence highlights the epidemiological value of blood DNA methylation (DNAm) as surrogate biomarker for exposure to risk factors for non-communicable diseases (NCD). DNAm surrogate of exposures predicts diseases and longevity better than self-reported or measured exposures in many cases. Consequently, disease prediction models based on blood DNAm surrogates may outperform current state-of-the-art prediction models. This study aims to develop novel DNAm surrogates for cardiovascular diseases (CVD) risk factors and develop a composite biomarker predictive of CVD risk. We compared the prediction performance of our newly developed risk score with the state-of-the-art DNAm risk scores for cardiovascular diseases, the 'next-generation' epigenetic clock DNAmGrimAge, and the prediction model based on traditional risk factors SCORE2.

RESULTS

Using data from the EPIC Italy cohort, we derived novel DNAm surrogates for BMI, blood pressure, fasting glucose and insulin, cholesterol, triglycerides, and coagulation biomarkers. We validated them in four independent data sets from Europe and the USA. Further, we derived a DNAmCVDscore predictive of the time-to-CVD event as a combination of several DNAm surrogates. ROC curve analyses show that DNAmCVDscore outperforms previously developed DNAm scores for CVD risk and SCORE2 for short-term CVD risk. Interestingly, the performance of DNAmGrimAge and DNAmCVDscore was comparable (slightly lower for DNAmGrimAge, although the differences were not statistically significant).

CONCLUSIONS

We described novel DNAm surrogates for CVD risk factors useful for future molecular epidemiology research, and we described a blood DNAm-based composite biomarker, DNAmCVDscore, predictive of short-term cardiovascular events. Our results highlight the usefulness of DNAm surrogate biomarkers of risk factors in epigenetic epidemiology to identify high-risk populations. In addition, we provide further evidence on the effectiveness of prediction models based on DNAm surrogates and discuss methodological aspects for further improvements. Finally, our results encourage testing this approach for other NCD diseases by training and developing DNAm surrogates for disease-specific risk factors and exposures.