It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.

Night-shift work involving disruption of circadian rhythms has been associated with breast cancer risk. A role in prostate cancer is also suspected, but evidence is limited. We investigated the association between night-shift work and prostate cancer incidence in the Prostate Cancer and Environment Study (PROtEuS), a population-based case-control study conducted in 2005-2012 in Montreal, Quebec, Canada. Participants were 1,904 prostate cancer cases (432 high-grade cancers) and 1,965 population controls. Detailed work schedules for each job held for at least 2 years (n = 15,724) were elicited in face-to-face interviews. Night-shift work was defined as having ever worked ≥3 hours between midnight and 5:00 am ≥3 nights/month for ≥1 year. Unconditional logistic regression was used to estimate odds ratios and 95% confidence intervals for the association between night-shift work and prostate cancer, adjusting for age, ancestry, and education. No association was found between overall prostate cancer and night-shift work metrics, including ever exposure, duration, intensity, cumulative exposure, rotating shifts, and early-morning shifts. For none of the exposure indices was there evidence of heterogeneity in odds ratios between low- and high-grade cancers. Sensitivity analyses restricting exposures to ≥7 nights/month or considering screening history yielded similar results. Our findings lend no support for a major role of night-shift work in prostate cancer development.