Shift work, DNA methylation and epigenetic age

Association between maternal prenatal depressive symptoms and offspring epigenetic aging at 3-5 weeks

Epigenetic clocks are emerging as tools for assessing acceleration and deceleration of biological age during childhood. Maternal depression during pregnancy may affect the biological aging of offspring and related development. In a low-income cohort of mother-child dyads, we investigated the relationship between prenatal maternal depressive symptoms and infant epigenetic age residuals, which represent the deviation (acceleration or deceleration) that exists between predicted biological age and chronological age. The epigenetic age residuals were derived from a pediatric-specific buccal epithelial clock. We hypothesized that maternal depressive symptoms, both sub-clinical and elevated (clinical level), would be associated with estimated biological age deceleration in offspring during early infancy. We analyzed data from 94 mother-child dyads using the Edinburgh Postnatal Depression Scale (EPDS) and DNA methylation derived from offspring buccal cells collected at 3-5 weeks of age. There was a significant non-linear association between the EPDS score and epigenetic age residual (β = -0.017, 95% confidence interval: -0.03,-0.01, P = <0.01). The results indicated that infants of mothers with sub-clinical depressive symptoms had the lowest infant epigenetic age residuals while infants of mothers with no-to-low depressive symptoms had the highest and experienced biological age acceleration. Maternal depressive symptoms may influence the biological aging of offspring living in poverty.

Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation

Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.

Exploration of genome-wide DNA methylation profiles in night shift workers

The past decades, studies indicated that night shift work is associated with adverse health effects, however, molecular mechanisms underlying these effects are poorly understood. A few previous studies have hypothesized a role for DNA-methylation (DNAm) in this relationship. We performed a cross-sectional epigenome-wide association study, to investigate if night shift work is associated with genome-wide DNAm changes and DNAm-based biological age acceleration, based on previously developed so-called 'epigenetic clocks.' Short term (2-6 years) and intermediate term (10-16 years) night shift workers, along with age and sex matched dayworkers (non-shift workers) were selected from the Lifelines Cohort Study. For genome-wide methylation analysis the Infinium Methylation EPIC array (Ilumina) was used. Linear regression analyses were used to detect differences in methylation at individual CpG-sites associated with night shift work. Pathway analysis was performed based on KEGG pathways and predictions of age acceleration in night shift workers were performed based on four previously developed epigenetic age calculators. Only in women, differences in methylation at individual CpG-sites were observed between night shift workers and non-shift workers. Most of these differentially methylated positions (DMPs) were observed in intermediate term night shift workers. Pathway analysis shows involvement of pathways related to circadian rhythm and cellular senescence. Increased age acceleration was observed only in short-term night shift workers (men and women). This might be indicative of adaptation to night shift work or a so-called healthy worker effect. In conclusion, these results show that DNA methylation changes are associated with night shift work, specifically in women.

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.

Changes in methylation-based aging in women who do and do not develop breast cancer

BACKGROUND

Breast cancer survivors have increased incidence of age-related diseases, suggesting that some survivors may experience faster biological aging.

METHODS

Among 417 women enrolled in the prospective Sister Study cohort, DNA methylation data were generated on paired blood samples collected an average of 7.7 years apart and used to calculate 3 epigenetic metrics of biological aging (PhenoAgeAccel, GrimAgeAccel, and Dunedin Pace of Aging Calculated from the Epigenome [DunedinPACE]). Approximately half (n = 190) the women sampled were diagnosed and treated for breast cancer between blood draws, whereas the other half (n = 227) remained breast cancer-free. Breast tumor characteristics and treatment information were abstracted from medical records.

RESULTS

Among women who developed breast cancer, diagnoses occurred an average of 3.5 years after the initial blood draw and 4 years before the second draw. After accounting for covariates and biological aging metrics measured at baseline, women diagnosed and treated for breast cancer had higher biological aging at the second blood draw than women who remained cancer-free as measured by PhenoAgeAccel (standardized mean difference [β] = 0.13, 95% confidence interval [CI) = 0.00 to 0.26), GrimAgeAccel (β = 0.14, 95% CI = 0.03 to 0.25), and DunedinPACE (β = 0.37, 95% CI = 0.24 to 0.50). In case-only analyses assessing associations with different breast cancer therapies, radiation had strong positive associations with biological aging (PhenoAgeAccel: β = 0.39, 95% CI = 0.19 to 0.59; GrimAgeAccel: β = 0.29, 95% CI = 0.10 to 0.47; DunedinPACE: β = 0.25, 95% CI = 0.02 to 0.48).

CONCLUSIONS

Biological aging is accelerated following a breast cancer diagnosis and treatment. Breast cancer treatment modalities appear to differentially contribute to biological aging.

Objective and subjective measures of sleep initiation are differentially associated with DNA methylation in adolescents

INTRODUCTION

The onset of puberty is associated with a shift in the circadian timing of sleep, leading to delayed sleep initiation [i.e., later sleep onset time (SOT)] due to later bedtimes and/or longer sleep onset latency (SOL). Several genome-wide association studies (GWAS) have identified genes that may be involved in the etiology of sleep phenotypes. However, circadian rhythms are also epigenetically regulated; therefore, epigenetic biomarkers may provide insight into the physiology of the pubertal sleep onset shift and the pathophysiology of prolonged or delayed sleep initiation.

RESULTS

The gene-wide analysis indicated differential methylation within or around 1818 unique genes across the sleep initiation measurements using self-report, actigraphy (ACT), and polysomnography (PSG), while GWAS-informed analysis yielded 67 genes. Gene hits were identified for bedtime (PSG), SOL (subjective, ACT and PSG) and SOT (subjective and PSG). DNA methylation within 12 genes was associated with both subjective and PSG-measured SOL, 31 with both ACT- and PSG-measured SOL, 19 with both subjective and ACT-measured SOL, and one gene (SMG1P2) had methylation sites associated with subjective, ACT- and PSG-measured SOL.

CONCLUSIONS

Objective and subjective sleep initiation in adolescents is associated with altered DNA methylation in genes previously identified in adult GWAS of sleep and circadian phenotypes. Additionally, our data provide evidence for a potential epigenetic link between habitual (subjective and ACT) SOL and in-lab SOT and DNA methylation in and around genes involved in circadian regulation (i.e., RASD1, RAI1), cardiometabolic disorders (i.e., FADS1, WNK1, SLC5A6), and neuropsychiatric disorders (i.e., PRR7, SDK1, FAM172A). If validated, these sites may provide valuable targets for early detection and prevention of disorders involving prolonged or delayed SOT, such as insomnia, delayed sleep phase, and their comorbidity.

BPIFB4 and its longevity-associated haplotype protect from cardiac ischemia in humans and mice

Long-living individuals (LLIs) escape age-related cardiovascular complications until the very last stage of life. Previous studies have shown that a Longevity-Associated Variant (LAV) of the BPI Fold Containing Family B Member 4 (BPIFB4) gene correlates with an extraordinarily prolonged life span. Moreover, delivery of the LAV-BPIFB4 gene exerted therapeutic action in murine models of atherosclerosis, limb ischemia, diabetic cardiomyopathy, and aging. We hypothesize that downregulation of BPIFB4 expression marks the severity of coronary artery disease (CAD) in human subjects, and supplementation of the LAV-BPIFB4 protects the heart from ischemia. In an elderly cohort with acute myocardial infarction (MI), patients with three-vessel CAD were characterized by lower levels of the natural logarithm (Ln) of peripheral blood BPIFB4 (p = 0.0077). The inverse association between Ln BPIFB4 and three-vessel CAD was confirmed by logistic regression adjusting for confounders (Odds Ratio = 0.81, p = 0.0054). Moreover, in infarcted mice, a single administration of LAV-BPIFB4 rescued cardiac function and vascularization. In vitro studies showed that LAV-BPIFB4 protein supplementation exerted chronotropic and inotropic actions on induced pluripotent stem cell (iPSC)-derived cardiomyocytes. In addition, LAV-BPIFB4 inhibited the pro-fibrotic phenotype in human cardiac fibroblasts. These findings provide a strong rationale and proof of concept evidence for treating CAD with the longevity BPIFB4 gene/protein.

Methylation-Based Biological Age and Hypertension Prevalence and Incidence

BACKGROUND

Hypertension is common in older individuals and is a major risk factor for cardiovascular disease. Blood DNA methylation profiles have been used to derive metrics of biological age that capture age-related physiological change, disease risk, and mortality. The relationships between hypertension and DNA methylation-based biological age metrics have yet to be carefully described.

METHODS

Among 4419 women enrolled in the prospective Sister Study cohort, DNA methylation data generated from whole blood samples collected at baseline were used to calculate 3 biological age metrics (PhenoAgeAccel, GrimAgeAccel, DunedinPACE). Women were classified as hypertensive at baseline if they had high blood pressure (systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg) or reported current use of antihypertensive medication. New incident cases of hypertension during follow-up were identified via self-report on annual health questionnaires.

RESULTS

All 3 DNA methylation metrics of biological age were positively associated with prevalent hypertension at baseline (per 1-SD increase; PhenoAgeAccel, adjusted odds ratio, 1.16 [95% CI, 1.05-1.28]; GrimAgeAccel, adjusted odds ratio, 1.28 [95% CI, 1.14-1.45]; DunedinPACE, adjusted odds ratio, 1.16 [95% CI, 1.03-1.30]). Among 2610 women who were normotensive at baseline, women with higher biological age were more likely to be diagnosed with incident hypertension (per 1-SD increase; PhenoAgeAccel, adjusted hazard ratio, 1.09 [95% CI, 0.97-1.23]; GrimAgeAccel, adjusted hazard ratio, 1.16 [95% CI, 0.99-1.36]; DunedinPACE, adjusted hazard ratio, 1.16 [95% CI, 1.01-1.33]).

CONCLUSIONS

Methylation-based biological age metrics increase before a hypertension diagnosis and appear to remain elevated in the years after clinical diagnosis and treatment.

Consequences of Shift Work and Night Work: A Literature Review

Nonstandard work schedules such as shift work and night work tend to trigger problems for workers in different areas. To illustrate the diversity of areas affected and the relative interest of the scientific community, we conducted a literature review of the effects of shift work and night work on workers. In particular, we intended to identify the main variables addressed in the field of health, the family sphere, and the organizational context. The literature review was carried out using the Web of Science with the following terms: "shift work", "rotating shifts", and "night work". Inclusion criteria incorporated empirical studies and articles written in Portuguese or English published in 2019. We selected 129 of the 619 articles identified. Regarding the impacts of shift work and night work, there existed a high discrepancy of focus between the three defined areas: health, family life, and organizational context. Specifically, health-related variables were the most studied (83.4%), followed by organizational variables (9.2%), and, lastly, family variables (7.4%). Based on these results, it is essential to extend the study of the two underrepresented impacts to other crucial areas, not only for the worker but also for organizations.

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.

Longitudinal associations of DNA methylation and sleep in children: a meta-analysis

BACKGROUND

Sleep is important for healthy functioning in children. Numerous genetic and environmental factors, from conception onwards, may influence this phenotype. Epigenetic mechanisms such as DNA methylation have been proposed to underlie variation in sleep or may be an early-life marker of sleep disturbances. We examined if DNA methylation at birth or in school age is associated with parent-reported and actigraphy-estimated sleep outcomes in children.

METHODS

We meta-analysed epigenome-wide association study results. DNA methylation was measured from cord blood at birth in 11 cohorts and from peripheral blood in children (4-13 years) in 8 cohorts. Outcomes included parent-reported sleep duration, sleep initiation and fragmentation problems, and actigraphy-estimated sleep duration, sleep onset latency and wake-after-sleep-onset duration.

RESULTS

We found no associations between DNA methylation at birth and parent-reported sleep duration (n = 3658), initiation problems (n = 2504), or fragmentation (n = 1681) (p values above cut-off 4.0 × 10^-8). Lower methylation at cg24815001 and cg02753354 at birth was associated with longer actigraphy-estimated sleep duration (p = 3.31 × 10^-8, n = 577) and sleep onset latency (p = 8.8 × 10^-9, n = 580), respectively. DNA methylation in childhood was not cross-sectionally associated with any sleep outcomes (n = 716-2539).

CONCLUSION

DNA methylation, at birth or in childhood, was not associated with parent-reported sleep. Associations observed with objectively measured sleep outcomes could be studied further if additional data sets become available.

Cardiovascular health and four epigenetic clocks

BACKGROUND

Cardiovascular health (CVH) was defined by the American Heart Association as an integrative idealness of seven clinical or lifestyle factors. Based on populations of European ancestry, recent studies have shown that ideal CVH is associated with a slower aging rate. The aging rate is measured by levels of epigenetic age acceleration (EAA), usually obtained from the residuals of regressing DNA methylation (DNAm) age on chronological age. However, little has been known about the association of CVH with biological aging in Asian populations.

METHODS AND RESULTS

We here analyzed blood DNAm data and clinical/lifestyle factors of 2474 Taiwan Biobank (TWB) participants, to investigate the association of CVH with EAA. CVH was assessed by seven components: smoking status, physical activity, dietary habits, body mass index, total cholesterol, fasting glucose, and blood pressure levels. Four measures of EAA were applied, among which two were based on the first-generation DNAm clocks (HannumEAA and IEAA) and two were based on the second-generation clocks (PhenoEAA and GrimEAA). After excluding 276 individuals with cardiovascular diseases, we regressed EAA on the CVH score (ranging from 0 to 7, integrating the abovementioned seven components) while adjusting for sex, drinking status, and educational attainment. Our results showed that a decrease in one point in the CVH score was associated with a 0.350-year PhenoEAA (p = 4.5E-4) and a 0.499-year GrimEAA (p = 4.2E-15). By contrast, HannumEAA and IEAA were not significantly associated with the CVH score. We have obtained consistent results within each generation of epigenetic clocks.

CONCLUSIONS

This is one of the first studies to comprehensively investigate the associations of CVH with four epigenetic clocks. Our TWB data showed that ideal CVH is associated with lower levels of EAA calculated according to the second-generation epigenetic clocks (PhenoEAA and GrimEAA). Having an ideal CVH status can lower EAA and reduce the risk of aging-related disorders.

The Case for Case-Cohort: An Applied Epidemiologist's Guide to Reframing Case-Cohort Studies to Improve Usability and Flexibility

When research questions require the use of precious samples, expensive assays or equipment, or labor-intensive data collection or analysis, nested case-control or case-cohort sampling of observational cohort study participants can often reduce costs. These study designs have similar statistical precision for addressing a singular research question, but case-cohort studies have broader efficiency and superior flexibility. Despite this, case-cohort designs are comparatively underutilized in the epidemiologic literature. Recent advances in statistical methods and software have made analyses of case-cohort data easier to implement, and advances from casual inference, such as inverse probability of sampling weights, have allowed the case-cohort design to be used with a variety of target parameters and populations. To provide an accessible link to this technical literature, we give a conceptual overview of case-cohort study analysis with inverse probability of sampling weights. We show how this general analytic approach can be leveraged to more efficiently study subgroups of interest or disease subtypes or to examine associations independent of case status. A brief discussion of how this framework could be extended to incorporate other related methodologic applications further demonstrates the broad cost-effectiveness and adaptability of case-cohort methods for a variety of modern epidemiologic applications in resource-limited settings.

A cross‐sectional study of the interaction between night shift frequency and age on hypertension prevalence among female nurses

Night shift is a common work schedule. This study aimed to analyze the interaction between age and frequency of night shift on the hypertension prevalence. A census questionnaire was conducted in 512 medical institutions in 11 cities of Hebei Province. One lakh twenty‐one thousand nine hundred three female nurses were included in this study. Binary Logistic regression analysis was done by SPSS Version 26.0. The youngest age group without night shift was used as the reference group. The odds ratio was calculated by different combinations of interaction items. Interaction coefficients were calculated by an Excel table designed by Andersson. Compared with the 18–25 year old ones without night shift, there existed an additive interaction between the age of 36–45 and more than 5–10 night shifts per month on hypertension prevalence. Odds ratio, the relative excess risk of interaction, the attributable proportion of interaction, and the synergy index and their 95% confidence intervals were 2.923(2.292‐3.727), 0.631(0.309‐0.954), 0.216(0.109‐0.323), 1.488(1.158‐1.913). Additive interaction was also found between the age of 36–45 and more than 10 night shifts per month. OR, RERI, API, SI, and their 95% confidence intervals were 3.430(2.273‐5.175) 1.037(0.061‐2.013), 0.303(0.089‐0.516), and 1.746(1.093‐2.788). There also existed an additive interaction between the age of 46–65 and more than 5–10 night shifts per month on hypertension prevalence. OR, RERI, API, SI, and their 95% confidence intervals were 7.398(5.595‐9.781) 1.809(0.880‐2.739), 0.245(0.148‐0.341), and 1.394(1.199‐1.622).There existed interaction between specific age groups and night shift frequency on the prevalence of hypertension among female nurses.

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

Recent evidence indicates consistent association of low socioeconomic status with epigenetic age acceleration, measured from DNA methylation. As work characteristics and job stressors are crucial components of socioeconomic status, we investigated their association with various measures of epigenetic age acceleration. The study population included employed and unemployed men and women (n=604) from the Northern Finland Birth Cohort 1966. We investigated the association of job strain, effort-reward imbalance and work characteristics with five biomarkers of epigenetic aging (Hannum, Horvath, PhenoAge, GrimAge, and DunedinPoAm). Our results indicate few significant associations between work stress indicators and epigenetic age acceleration, limited to a range of ±2 years, and smoking recording the highest effect on GrimAge age acceleration biomarker between current and no smokers (median difference 4.73 years (IQR 1.18, 8.41). PhenoAgeAA was associated with job strain active work (β=-1.301 95%CI -2.391, -0.212), slowing aging of less than 1.5 years, and working as white-collar slowed aging six months (GrimAgeAA β=-0.683, 95%CI -1.264, -0.102) when compared to blue collars. Association was found for working for more than 40 hours per week that increased the aging over 1.5 years, (HorvathAA β =2.058 95%CI 0.517,3.599, HannumAA β=1.567, 95%CI 0.415,2.719). The pattern of associations was different between women and men and some of the estimated effects are inconsistent with current literature. Our results provide the first evidence of association of work conditions with epigenetic aging biomarkers. However, further epidemiological research is needed to fully understand how work-related stress affects epigenetic age acceleration in men and women in different societies.

How to Slow Down the Ticking Clock: Age-Associated Epigenetic Alterations and Related Interventions to Extend Life Span

Epigenetic alterations pose one major hallmark of organismal aging. Here, we provide an overview on recent findings describing the epigenetic changes that arise during aging and in related maladies such as neurodegeneration and cancer. Specifically, we focus on alterations of histone modifications and DNA methylation and illustrate the link with metabolic pathways. Age-related epigenetic, transcriptional and metabolic deregulations are highly interconnected, which renders dissociating cause and effect complicated. However, growing amounts of evidence support the notion that aging is not only accompanied by epigenetic alterations, but also at least in part induced by those. DNA methylation clocks emerged as a tool to objectively determine biological aging and turned out as a valuable source in search of factors positively and negatively impacting human life span. Moreover, specific epigenetic signatures can be used as biomarkers for age-associated disorders or even as targets for therapeutic approaches, as will be covered in this review. Finally, we summarize recent potential intervention strategies that target epigenetic mechanisms to extend healthy life span and provide an outlook on future developments in the field of longevity research.

Healthy eating patterns and epigenetic measures of biological age

BACKGROUND

Healthy eating is associated with lower risks of disease and mortality, but the mechanisms underlying these associations are unclear. Age is strongly related to health outcomes, and biological age can be estimated using the blood methylome.

OBJECTIVES

To determine whether healthy eating patterns are associated with methylation-based measures of biological age.

METHODS

Among women in the Sister Study, we calculated scores on 4 recommendation-based healthy eating indexes [Dietary Approaches to Stop Hypertension diet, Healthy Eating Index-2015, Alternative Healthy Eating Index (aHEI-2010), and the Alternative Mediterranean diet] using a validated 110-item Block FFQ completed at enrollment. Genome-wide DNA methylation data were generated using the HumanMethylation450 BeadChip on whole blood samples collected at enrollment from a case-cohort sample of 2694 women and were used to calculate 4 measures of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Linear regression models, adjusted for covariates and cohort sampling weights, were used to examine cross-sectional associations between eating patterns and measures of biological age.

RESULTS

All 4 healthy eating indexes had inverse associations with epigenetic age acceleration, most notably with PhenoAgeAccel and GrimAgeAccel. Of these, the strongest associations were for aHEI-2010 [per 1-SD increase in diet quality, PhenoAgeAccel β = -0.5 y (95% CI: -0.8 to -0.2 y) and GrimAgeAccel β = -0.4 y (95% CI: -0.6 to -0.3 y)]. Although effect modification was not observed for most lifestyle factors, in analyses stratified by physical activity, the benefits of a healthy diet on epigenetic age acceleration were more pronounced among women who did not meet physical activity guidelines (reporting <2.5 h/wk of exercise).

CONCLUSIONS

Higher diet quality is inversely associated with methylation-based measures of biological age. Improving diet could have the most benefits in lowering biological age among women with lower levels of physical activity. This trial was registered at clinicaltrials.gov as NCT00047970.

Can Night Shift Work Affect Biological Age? Hints from a Cross-Sectional Study on Hospital Female Nurses

Disruption of age-related processes seems to play a relevant role in health effects related to night shift (NS) work. We aim to verify whether NS work can influence biological age (BA), estimated through Zbieć-Piekarska's epigenetic signature, based on methylation of five CpG sites in ELOVL2, C1orf132/MIR29B2C, TRIM59, KLF14, and FHL2. Forty-six female nurses working in NS were matched by age and length of employment with 51 female colleagues not working in NS. Each subject filled in a questionnaire (including the Effort Reward Imbalance (ERI) index to assess job stress) and gave a blood sample. Age acceleration (AA) was estimated by regressing BA on chronological age and taking the residuals. Multivariate linear regression models were applied. BA was not associated with NS. However, we did observe an increase in AA per each year in NS in subjects with overweight/obesity (β = 0.46, 95% CI: 0.05; 0.87, p = 0.03), experiencing work-related stress (β = 0.58, 95% CI: 0.10; 1.06, p = 0.018), or both (β = 0.66, 95% CI: 0.03; 1.29, p = 0.041). Although based on a small sample size, our findings suggest an increased BA only among hypersusceptible subjects and is worth further investigation, also in light of recent results suggesting a higher breast cancer risk in women with increased AA.

Per- and polyfluoroalkyl substances, epigenetic age and DNA methylation: a cross-sectional study of firefighters

Background: Per- and polyfluoroalkyl substances (PFASs) are persistent chemicals that firefighters encounter. Epigenetic modifications, including DNA methylation, could serve as PFASs toxicity biomarkers. Methods: With a sample size of 197 firefighters, we quantified the serum concentrations of nine PFASs, blood leukocyte DNA methylation and epigenetic age indicators via the EPIC array. We examined the associations between PFASs with epigenetic age, site- and region-specific DNA methylation, adjusting for confounders. Results: Perfluorohexane sulfonate, perfluorooctanoate (PFOA) and the sum of branched isomers of perfluorooctane sulfonate (Sm-PFOS) were associated with accelerated epigenetic age. Branched PFOA, linear PFOS, perfluorononanoate, perfluorodecanoate and perfluoroundecanoate were associated with differentially methylated loci and regions. Conclusion: PFASs concentrations are associated with accelerated epigenetic age and locus-specific DNA methylation. The implications for PFASs toxicity merit further investigation.

How Are Epigenetic Modifications Related to Cardiovascular Disease in Older Adults?

The rate of aging has increased globally during recent decades and has led to a rising burden of age-related diseases such as cardiovascular disease (CVD). At the molecular level, epigenetic modifications have been shown recently to alter gene expression during the life course and impair cellular function. In this regard, several CVD risk factors, such as lifestyle and environmental factors, have emerged as key factors in epigenetic modifications within the cardiovascular system. In this study, we attempted to summarized recent evidence related to epigenetic modification, inflammation response, and CVD in older adults as well as the effect of lifestyle modification as a preventive strategy in this age group. Recent evidence showed that lifestyle and environmental factors may affect epigenetic mechanisms, such as DNA methylation, histone acetylation, and miRNA expression. Several substances or nutrients such as selenium, magnesium, curcumin, and caffeine (present in coffee and some teas) could regulate epigenetics. Similarly, physical inactivity, alcohol consumption, air pollutants, psychological stress, and shift working are well-known modifiers of epigenetic patterns. Understanding the exact ways that lifestyle and environmental factors could affect the expression of genes could help to influence the time of incidence and severity of aging-associated diseases. This review highlighted that a healthy lifestyle throughout the life course, such as a healthy diet rich in fibers, vitamins, and essential elements, and specific fatty acids, adequate physical activity and sleep, smoking cessation, and stress control, could be useful tools in preventing epigenetic changes that lead to impaired cardiovascular function.

Do Rotating Night Shifts Change Nurses' Nutritional Status? A Cross-Sectional Study

OBJECTIVE

Shift work disrupts circadian rhythms through environmental factors such as disruption of the light-dark and rest-activity cycle. This study aims to evaluate the nutritional status, circadian phenotype, sleep quality, and anthropometric measurements in nurses working in rotating night shifts.

METHOD

The study included 44 nurses working in rotating night shifts. Physical activity records for 4 days and 24-hour dietary recalls for 7 days were taken. To evaluate the circadian phenotypes and sleep quality, the Morningness-Eveningness Questionnaire and the Pittsburg Sleep Quality Index were used, respectively.

RESULTS

Most nurses were evening chronotype and had poor sleep quality. Shift work was associated with higher daily energy intake and lower total daily energy expenditure (p < 0.05). On the night shifts, while fiber-rich foods such as beans and fruit consumption decrease, the consumption of fats, sweets, and cereals increases. While carbohydrates, total fat, and cholesterol intake were higher in only women on the night shift (p < 0.05), saturated fat and calcium intake were higher in all nurses (p < 0.05). While the water intake of the nurses was lower on the night shift (p < 0.05), tea intake was higher in women (p < 0.05). A correlation was found between total shift work duration, body mass index (r = 0.525), waist circumference (r = 0.577), waist-height ratio (r = 0.584), and body fat percentage (r = 0.513) (p < 0.001).

CONCLUSIONS

Nurses should be encouraged to ensure adequate water intake and to make healthy food choices during the night shift to maintain health and work performance.

Maldonado J, Raj K, Schmitt D, Robeck TR, Horvath S. Epigenetic clock and methylation studies in elephants

Age-associated DNA-methylation profiles have been used successfully to develop highly accurate biomarkers of age ("epigenetic clocks") in humans, mice, dogs, and other species. Here we present epigenetic clocks for African and Asian elephants. These clocks were developed using novel DNA methylation profiles of 140 elephant blood samples of known age, at loci that are highly conserved between mammalian species, using a custom Infinium array (HorvathMammalMethylChip40). We present epigenetic clocks for Asian elephants (Elephas maximus), African elephants (Loxodonta africana), and both elephant species combined. Two additional human-elephant clocks were constructed by combining human and elephant samples. Epigenome-wide association studies identified elephant age-related CpGs and their proximal genes. The products of these genes play important roles in cellular differentiation, organismal development, metabolism, and circadian rhythms. Intracellular events observed to change with age included the methylation of bivalent chromatin domains, and targets of polycomb repressive complexes. These readily available epigenetic clocks can be used for elephant conservation efforts where accurate estimates of age are needed to predict demographic trends.

The Impact of Stress Within and Across Generations: Neuroscientific and Epigenetic Considerations

The impact of stress and trauma on biological systems in humans can be substantial. They can result in epigenetic changes, accelerated brain development and sexual maturation, and predisposition to psychopathology. Such modifications may be accompanied by behavioral, emotional, and cognitive overtones during one's lifetime. Exposure during sensitive periods of neural development may lead to long-lasting effects that may not be affected by subsequent environmental interventions. The cumulative effects of life stressors in an individual may affect offspring's methylome makeup and epigenetic clocks, neurohormonal modulation and stress reactivity, and physiological and reproductive development. While offspring may suffer deleterious effects from parental stress and their own early-life adversity, these factors may also confer traits that prove beneficial and enhance fitness to their own environment. This article synthesizes the data on how stress shapes biological and behavioral dimensions, drawing from preclinical and human models. Advances in this field of knowledge should potentially allow for an improved understanding of how interventions may be increasingly tailored according to individual biomarkers and developmental history.

Associations of Body Composition and Physical Activity Level With Multiple Measures of Epigenetic Age Acceleration

Epigenetic clocks use DNA methylation to estimate biological age. Whether body composition and physical activity are associated with these clocks is not well understood. Using blood samples collected at enrollment (2003-2009) from 2,758 women in the US nationwide Sister Study, we calculated 6 epigenetic age acceleration metrics using 4 epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge). Recreational physical activity was self-reported, and adiposity measures were assessed by trained medical examiners (body mass index (BMI), waist-to-hip ratio (WtH), waist circumference). In cross-sectional analyses, all adiposity measures were associated with epigenetic age acceleration. The strongest association was for BMI and PhenoAge, a measure of biological age that correlates with chronic disease (BMI of ≥35.0 vs. 18.5-24.9, β = 3.15 years, 95% confidence interval (CI): 2.41, 3.90; P for trend < 0.001). In a mutual-adjustment model, both were associated with PhenoAge age acceleration (BMI of ≥35.0 vs. 18.5-24.9, β = 2.69 years, 95% CI: 1.90, 3.48; P for trend < 0.001; quartile 4 vs.1 WtH, β = 1.00 years, 95% CI: 0.34, 1.65; P for trend < 0.008). After adjustment, physical activity was associated only with GrimAge (quartile 4 vs. 1, β = -0.42 years, 95% CI: -0.70, -0.14; P for trend = 0.001). Physical activity attenuated the waist circumference associations with PhenoAge and GrimAge. Excess adiposity was associated with epigenetic age acceleration; physical activity might attenuate associations with waist circumference.

Epigenetics of Hepatic Insulin Resistance

Insulin resistance (IR) is largely recognized as a unifying feature that underlies metabolic dysfunction. Both lifestyle and genetic factors contribute to IR. Work from recent years has demonstrated that the epigenome may constitute an interface where different signals may converge to promote IR gene expression programs. Here, we review the current knowledge of the role of epigenetics in hepatic IR, focusing on the roles of DNA methylation and histone post-translational modifications. We discuss the broad epigenetic changes observed in the insulin resistant liver and its associated pathophysiological states and leverage on the wealth of 'omics' studies performed to discuss efforts in pinpointing specific loci that are disrupted by these changes. We envision that future studies, with increased genomic resolution and larger cohorts, will further the identification of biomarkers of early onset hepatic IR and assist the development of targeted interventions. Furthermore, there is growing evidence to suggest that persistent epigenetic marks may be acquired over prolonged exposure to disease or deleterious exposures, highlighting the need for preventative medicine and long-term lifestyle adjustments to avoid irreversible or long-term alterations in gene expression.

Inflammaging in Endemic Areas for Infectious Diseases

Immunosenescence is marked by a systemic process named inflammaging along with a series of defects in the immunological activity that results in poor responses to infectious agents and to vaccination. Inflammaging, a state of low-grade chronic inflammation, usually leads to chronic inflammatory diseases and frailty in the elderly. However, some elderly escape from frailty and reach advanced age free of the consequences of inflammaging. This process has been called immunological remodeling, and it is the hallmark of healthy aging as described in the studies of centenarians in Italy. The biological markers of healthy aging are still a matter of debate, and the studies on the topic have focused on inflammatory versus remodeling processes and molecules. The sub-clinical inflammatory status associated with aging might be a deleterious event for populations living in countries where chronic infectious diseases are not prevalent. Nevertheless, in other parts of the world where they are, two possibilities may occur. Inflammatory responses may have a protective effect against these infectious agents. At the same time, the long-term consequences of protective immune responses during chronic infections may result in accelerated immunosenescence in these individuals. Therefore, the biological markers of healthy aging can vary according to environmental, cultural, and geographical settings that reflect worldwide, and in a non-biased, non-westernized perspective, the changes that we experience regarding our contacts with microorganisms and the outcomes of such contacts.

Age-related DNA methylation in paired normal and tumour breast tissue in Chinese breast cancer patients

Age-related DNA methylation is a potential mechanism contributing to breast cancer development. Studies of primarily Caucasian women have identified many CpG sites of age-related methylation in non-diseased breast tissue possibly driving cancer development over time. There is a paucity of studies involving Asian women whose ages at breast cancer onset are usually younger than Caucasians. We identified the 181 most consistent age-related methylation events in non-diseased breast tissue across published studies. Age-related methylation events were measured in adjacent normal and breast tumour tissue in an exclusively Asian population at the previously identified age-related methylation sites. Age-related methylation was found in 118 probes in adjacent normal breast tissue. Methylation of 99% of these sites was increased with age and predominantly located on CpG islands in promoter regions. To ascertain biological relevance to breast cancer, we focused on the 37 sites with overall higher methylation in tumour compared to adjacent normal samples. Some sites positively related to age, including AQP5 and CORO6, inversely correlated with gene expression. Several others have known involvement in suppression of carcinogenesis including GPC5 and SST, suggesting that perturbation of epigenetic regulation at these sites due to ageing may contribute to the progression of carcinogenesis. This study highlights an age-related methylation landscape in non-tumour tissue, consistent not just across studies, but also across different populations. We present candidate age-related methylation sites warranting further investigation as potential epigenetic drivers of breast cancer. They may serve as potential targets of site-specific demethylation intervention strategies for the prevention of age-related breast cancer.

Reproduction, DNA methylation and biological age

STUDY QUESTION

Are reproductive characteristics associated with genome-wide DNA methylation and epigenetic age?

SUMMARY ANSWER

Our data suggest that increasing parity is associated with differences in blood DNA methylation and small increases in epigenetic age.

WHAT IS KNOWN ALREADY

A study of 397 young Filipino women (ages 20-22) observed increasing epigenetic age with an increasing number of pregnancies.

STUDY DESIGN, SIZE, DURATION

We used data from 2356 non-Hispanic white women (ages 35-74) enrolled in the Sister Study cohort.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Data on reproductive history were ascertained via questionnaire. Of the 2356 women, 1897 (81%) reported at least one live birth. Among parous women, 487 (26%) women reported ever experiencing a pregnancy complication. Three epigenetic clocks (i.e. Hannum, Horvath and Levine) and genome-wide methylation were measured in DNA from whole blood using Illumina's HumanMethylation450 BeadChip. We estimated association β-values and 95% CIs using linear regression.

MAIN RESULTS AND THE ROLE OF CHANCE

All three epigenetic clocks showed weak associations between number of births and epigenetic age (per live birth; Hannum: β = 0.16, 95% CI = 0.02, 0.29, P = 0.03; Horvath: β = 0.12, 95% CI = -0.04, 0.27, P = 0.14; Levine: β = 0.27, 95% CI = 0.08, 0.45, P = 0.01); however, additional adjustment for current BMI attenuated the associations. Among parous women, a history of abnormal glucose tolerance during pregnancy was associated with increased epigenetic age by the Hannum clock (β = 0.96; 95% CI = 0.10, 1.81; P = 0.03) and Levine clocks (β = 1.69; 95% CI = 0.54, 2.84; P < 0.01). In epigenome-wide analysis, increasing parity was associated with methylation differences at 17 CpG sites (Bonferroni corrected P≤ 1.0 × 10-7).

LIMITATIONS, REASONS FOR CAUTION

We relied on retrospective recall to ascertain reproductive history and pregnancy complications.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings suggest that parity is associated with small increases in epigenetic age and with DNA methylation at multiple sites in the genome.

STUDY FUNDING/COMPETING INTEREST(S)

This research was supported by the Intramural Research program of the NIH, National Institute of Environmental Health Sciences (Z01-ES049033, Z01-ES049032 and Z01-ES044055). None of the authors have a conflict of interest.

TRIAL REGISTRATION NUMBER

Not applicable.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.

Epigenetic Regulation of Circadian Rhythm and Its Possible Role in Diabetes Mellitus

This review aims to summarize the knowledge about the relationship between circadian rhythms and their influence on the development of type 2 diabetes mellitus (T2DM) and metabolic syndrome. Circadian rhythms are controlled by internal molecular feedback loops that synchronize the organism with the external environment. These loops are affected by genetic and epigenetic factors. Genetic factors include polymorphisms and mutations of circadian genes. The expression of circadian genes is regulated by epigenetic mechanisms that change from prenatal development to old age. Epigenetic modifications are influenced by the external environment. Most of these modifications are affected by our own life style. Irregular circadian rhythm and low quality of sleep have been shown to increase the risk of developing T2DM and other metabolic disorders. Here, we attempt to provide a wide description of mutual relationships between epigenetic regulation, circadian rhythm, aging process and highlight new evidences that show possible therapeutic advance in the field of chrono-medicine which will be more important in the upcoming years.

Epigenetic mortality predictors and incidence of breast cancer

Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or “epigenetic clocks” appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: ‘GrimAgeAccel’ and the ‘mortality score’ (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14, P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer (HR: 1.08, 95% CI: 0.99-1.17, P=0.08). Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer (HR: 1.10, 95% CI: 1.01, 1.20, P=0.04). Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.

Air pollution, particulate matter composition and methylation-based biologic age

BACKGROUND

Epigenetic age, as defined by DNA methylation, may be influenced by air pollution exposure.

OBJECTIVE

To evaluate the relationship between NO₂, particulate matter (PM), PM components and accelerated epigenetic age.

METHODS

In a sample of non-Hispanic white women living in the contiguous U.S. (n = 2747), we estimated residential exposure to PM_2.5, PM₁₀ and NO₂ using a model incorporating land-use regression and kriging. Predictive k-means was used to assign participants to clusters representing different PM_2.5 component profiles. We measured DNA methylation (DNAm) in blood using the Illumina's Infinium HumanMethylation450 BeadChip and calculated DNAm age using the Hannum, Horvath and Levine epigenetic clocks. Age acceleration was defined based on residuals after regressing DNAm age on chronological age. We estimated associations between interquartile range (IQR) increases in pollutants and age acceleration using linear regression. For PM_2.5, we stratified by cluster membership. We examined epigenome-wide associations using robust linear regression models corrected with false discovery rate q-values.

RESULTS

NO₂ was inversely associated with age acceleration using the Hannum clock (β = -0.24, 95% CI: -0.47, -0.02). No associations were observed for PM₁₀. For PM_2.5, the association with age acceleration varied by PM_2.5 component cluster. For example, with the Levine clock, an IQR increase in PM_2.5 was associated with an over 6-year age acceleration in a cluster that has relatively high fractions of crustal elements relative to overall PM_2.5 (β = 6.57, 95% CI: 2.68, 10.47), and an almost 2-year acceleration in a cluster characterized by relatively low sulfur fractions (β = 1.88, 95% CI: 0.51, 3.25). In a cluster distinguished by lower relative nitrate concentrations, PM_2.5 was inversely associated with age acceleration (β = -1.33, 95% CI: -2.43, -0.23). Across the epigenome, NO₂ was associated with methylation at 2 CpG sites.

CONCLUSION

Air pollution was associated with epigenetic age, a marker of mortality and disease risk, among certain PM_2.5 component profiles.

Mini Nutritional Assessment Scores Indicate Higher Risk for Prospective Mortality and Contrasting Correlation With Age-Related Epigenetic Biomarkers

The plasticity of the individual epigenetic landscape that goes to countless rearrangements throughout life is closely the reflection of environmental factors such as chemical exposure, socio-economic status and nutrient intakes both early and late in life. The Mini Nutritional Assessment (MNA) is a well-validated tool for assessing malnutrition in old people. It includes 6 (MNA-SF) or 18 (MNA-LF) self-reported questions derived from general, anthropometric, dietary, and self- assessment. We evaluated the association between the nutritional status, as measured by MNA, and methylation biomarkers we previously demonstrated to be associated with chronological and biological age in human. We found that malnutrition is positively correlated with DNA methylation status at the global level, in line with our previous reports. On the contrary, most of the sites located within specific genes, which were previously reported to be correlated with chronological and biological aging, showed to be not affected by malnutrition, or even to have correlations with malnutrition opposite to those previously reported with frailty. These results may suggest that malnutrition is among the first effects of disability and other age- related problems and a generalized non-specific epigenetic remodeling may be the initial response of the organism. By contrast, the fine remodeling of specific genomic sites is scarcely affected by malnutrition and may respond to a more complex interaction of different factors. Therefore, although malnutrition in the elderly is certainly a risk factor for survival, this is partially independent of the aging process of the organism which leads to the methylation remodeling previously described to measure chronological and biological aging.