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

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.

Association between night shift work and methylation of a subset of immune-related genes

Introduction

Night shift (NS) work has been associated with an increased risk of different conditions characterized by altered inflammatory and immune responses, such as cardio-metabolic and infectious diseases, cancer, and obesity. Epigenetic modifications, such as DNA methylation, might mirror alterations in biological processes that are influenced by NS work.

Methods

The present study was conducted on 94 healthy female workers with different working schedules and aimed at identifying whether NS was associated with plasmatic concentrations of the inflammatory proteins NLRP3 and TNF-alpha, as well as with DNA methylation levels of ten human endogenous retroviral (HERV) sequences, and nine genes selected for their role in immune and inflammatory processes. We also explored the possible role of the body mass index (BMI) as an additional susceptibility factor that might influence the effects of NS work on the tested epigenetic modifications.

Results and discussion

We observed a positive association between NS and NLRP3 levels (p-value 0.0379). Moreover, NS workers retained different methylation levels for ERVFRD-1 (p-value = 0.0274), HERV-L (p-value = 0.0377), and HERV-P (p-value = 0.0140) elements, and for BIRC2 (p-value = 0.0460), FLRT3 (p-value = 0.0422), MIG6 (p-value = 0.0085), and SIRT1 (p-value = 0.0497) genes. We also observed that the BMI modified the relationship between NS and the methylation of ERVE, HERV-L, and ERVW-1 elements. Overall, our results suggest that HERV methylation could pose as a promising biomolecular sensor to monitor not only the effect of NS work but also the cumulative effect of multiple stressors.

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.