Gene-x-environment analysis supports protective effects of eveningness chronotype on self-reported and actigraphy-derived sleep duration among those who always work night shifts in the UK Biobank

Abstract

Previous research has linked having an eveningness chronotype with a higher tolerance for night shift work, suggesting the ability to work nights without health consequences may partially depend upon having a circadian clock optimized for these times. As chronotypes entrain over time to environmental cues, it remains unclear whether higher relative eveningness among healthy night workers reflects a moderating or mediating effect of chronotype on health. We address these concerns conducting a genome-wide association study and utilizing a polygenic score (PGS) for eveningness as a time-invariant measure of chronotype. On a sample of 53 211 workers in the UK Biobank (2006-2018), we focus on the effects of night shift work on sleep duration, a channel through which night shift work adversely affects health. We ask whether a higher predisposition toward eveningness promotes night shift work tolerance. Results indicate that regular night shift work is associated with a 13-minute (3.5%) reduction in self-reported sleep per night relative to those who never work these hours (95% confidence interval [CI] = -17:01, -8:36). We find that eveningness has a strong protective effect on night workers: a one-SD increase in the PGS is associated with a 4-minute (28%) reduction in the night shift work sleep penalty per night (CI = 0:10, 7:04). This protective effect is pronounced for those working the longest hours. Consistent patterns are observed with an actigraphy-derived measure of sleep duration. These findings indicate that solutions to health consequences of night shift work should take individual differences in chronotype into account.

Keywords: GWAS; eveningness chronotype; gene-environment interaction; night shift work; sleep duration.

Graphical Abstract

Figure 1.

Predicted sleep duration, by regularity of night shift work. “All covariates” estimates are conditional on the full set of covariates. Dashed lines show the upper and lower confidence intervals for the reference group (never/rarely works nights); treatment groups for which confidence intervals overlap with these dashed lines show no significant difference at a = 0.05.

Figure 2.

Predicted sleep duration, by regularity of night shift work and work hours. All estimates are conditional on the full set of covariates. Vertical capped lines show 95% confidence intervals, which are calculated using bootstrapped standard errors based on 1000 replications that are clustered around the family ID. Dashed lines show the upper and lower confidence intervals for the reference group (never/rarely works nights); treatment groups for which confidence intervals overlap with these dashed lines show no significant difference at a = 0.05.

Figure 3.

Comparing marginal effects of night shift work on self-reported and accelerometer-derived sleep duration. All estimates are conditional on the full set of covariates. Vertical capped lines show 95% confidence intervals, which are calculated using bootstrapped standard errors based on 1000 replications that are clustered around the family ID.

Figure 4.

Predicted sleep duration of individuals never/rarely and always working nights, over eveningness PGS (std.). Estimates are conditional on the full list of covariates provided in Table 2. Vertical lines show 95% confidence intervals, which are calculated using bootstrapped standard errors based on 1000 replications that are clustered around the family ID.

Figure 5.

Predicted sleep duration of individuals never/rarely and always working nights, over 5 eveningness PGS quintiles. Estimates are conditional on the full list of covariates provided in Table 2. Vertical lines show 95% confidence intervals, which are calculated using bootstrapped standard errors based on 1000 replications that are clustered around the family ID.

Figure 6.

Marginal effects of always night work on self-reported and actigraphy-derived sleep duration, over eveningness PGS. Estimates are conditional on the full list of covariates provided in Table 2. Vertical lines show 95% confidence intervals, which are calculated using bootstrapped standard errors based on 1000 replications that are clustered around the family ID. Marginal effects represent the change in minutes of sleep relative to those who never/rarely work nights.

Figure 7.

Predicted sleep duration of individuals never/rarely and always working nights (≥45 h/wk), over PGS for eveningness. Estimates are conditional on the full set of covariates. Vertical lines depict 95% confidence intervals constructed from bootstrapped standard errors (1000 replications) clustered around the family ID.