BioMed Research International

BioMed Research International / 2019 / Article

Research Article | Open Access

Volume 2019 |Article ID 7582734 | 8 pages | https://doi.org/10.1155/2019/7582734

NOCTURNIN Gene Diurnal Variation in Healthy Volunteers and Expression Levels in Shift Workers

Academic Editor: Giuseppe Piccione
Received16 Mar 2019
Revised08 Jul 2019
Accepted14 Jul 2019
Published31 Jul 2019

Abstract

Objective. The NOCTURNIN gene links nutrient absorption and metabolism to the circadian clock. Shift workers are at a heightened risk of overweight and of developing obesity and metabolic syndrome. This study investigates the diurnal variation of NOCTURNIN in healthy volunteers and its expression levels in rotational shift and daytime workers. Methods. NOCTURNIN expression levels were evaluated in peripheral blood lymphocytes from 15 healthy volunteers at 4-hour intervals for 24 h. Metabolic parameters and NOCTURNIN expression were measured in workers engaged in shift and daytime work. Results. In the group of volunteers NOCTURNIN expression showed diurnal variation, with a peak at 8:00 AM. NOCTURNIN expression was higher in shift workers than in daytime workers. Multivariate analysis confirmed the role of shift work as an independent factor affecting NOCTURNIN expression. Notably, its level correlated directly with body mass index and inversely with total energy expenditure. Conclusions. Measuring NOCTURNIN expression levels in human peripheral blood lymphocytes can improve investigations on the relationship between changes in circadian rhythm and metabolic disorders. Shift workers show higher NOCTURNIN levels than daytime workers.

1. Introduction

The NOCTURNIN gene (also known as NOCT, NOC, CCR4L, Ccr4c, and CCRN4L) was identified by Green et al. in 1996 [1]. It encodes the deadenylase NOCTURNIN, which is implicated in a number of metabolic processes through posttranscriptional circadian regulation of genes involved in metabolism [2, 3]. In mice, NOCTURNIN is the sole deadenylase affecting the high-amplitude rhythms and shows nocturnal peaks, whereas most other deadenylases are arrhythmic or have very low-amplitude rhythms that peak during the day [2]. Several metabolic pathways are related to the circadian clock [4]. The NOCTURNIN gene regulates the circadian cycles and binds them to the metabolic rhythms; its involvement in lipid metabolism, adipogenesis, glycaemic homeostasis, and inflammation entails that it plays a role in promoting metabolic alterations [57]. Nocturnin-knockout mice show greater glucose tolerance and insulin sensitivity as well as increased resistance to obesity and hepatic steatosis, likely due to altered absorption of intestinal fats or to their consumption in alternative metabolic cycles [3]. The latter findings underscore the important role of the gene in adiposity regulation. A recent study of NOCTURNIN expression in subcutaneous and visceral adipose tissue from obese and nonobese Chinese subjects has found higher levels in obese individuals in both adipose depots [8].

Circadian desynchronization due to shift work affects not only the central nervous system, by altering the wake/sleep and hunger/satiety cycles [9], but also peripheral tissues, where clock-controlled genes are functionally regulated by the suprachiasmatic nucleus (SCN) and in turn regulate metabolic processes [1012]. The consequences of circadian rhythm desynchronization on the health and wellbeing of shift workers are mainly related to shift frequency, duration, regularity, and type of rotation [1315]. Shift and night work increases the risk of developing chronic conditions such as ischaemic heart disease [1618], type 2 diabetes [1821], metabolic syndrome [22, 23], and cancer [15, 24]. Indeed, overweight and obesity are more frequent among shift workers than among daytime workers [2528]. The trigger for the development of further metabolic disorders is abdominal adiposity [26, 27, 29]. The causes of this association are still unclear.

The aim of this study was to investigate the diurnal NOCTURNIN variation in healthy subjects and to test for differences in its expression levels in shift and daytime workers.

2. Materials and Methods

2.1. Diurnal Variation of NOCTURNIN Expression in Healthy Volunteers

NOCTURNIN is a clock-controlled gene which in rodents shows a variable expression during the day. To establish whether such variation also occurs in humans, its expression levels were investigated in lymphocytes from 15 healthy subjects, 8 men and 7 women aged 27-39 years [mean±standard deviation (SD), 32.4±4.3 years], who had been enrolled in a previous study [30]. The volunteers filled out a questionnaire to provide personal data and information on the inclusion criteria, thereby also providing their informed consent. The study was carried out according to the principles of the Declaration of Helsinki. Samples were processed after approval of a written consent statement (Prot. No. 737) by the Ethics Committee of Catania (Italy).

The inclusion criteria comprised regular sleep/wake patterns and a negative history of severe physical diseases; participants were excluded if they had been on medications or had made journeys across time zones in the previous two months. The volunteers’ health status was established by physical examination. All subjects agreed to follow their daily routines and to sleep 8 hours at regular times in the dark for 7 days before testing.

Testing took place in the laboratory from 8:00 AM of one day to 8:00 AM the next day. In the 24-hour interval, subjects were allowed to move and drink ad libitum from 8:00 AM to 12:00 AM (awake time) and slept in the same room from 12:00 AM to 8:00 AM (sleep time). Breakfast was at 8:30 AM, lunch at 12:30 PM, and dinner at 8:30 PM. The light intensity in the laboratory was measured at eye level using a Minolta Chroma Meter CL-100 (Minolta Camera Company Ltd., Osaka, Japan). Its mean intensity during wake time was 407.7±112.5 lux, provided by 4000° K fluorescent lamps (Osram Lumilux, Osram, Münich, Germany) and 2.6±2.2 lux during sleep time, provided by a bulb emitting red (700° K) light (Philips PAR38 IR, Philips Lighting, Eindhoven, The Netherlands). Room temperature was 22±1°C throughout the study. Blood was collected in EDTA glass tubes every 4 h (8:00 AM, 12:00 PM, 4:00 PM, 8:00 PM, 12:00 AM, 4:00 AM, and 8:00 AM); lymphocytes were obtained immediately afterwards.

2.2. NOCTURNIN Gene Expression in Shift Workers

Forty nurses were selected among the staff of Area Vasta 2 (Ancona, Italy) as they underwent the periodic medical examinations envisaged by Italian regulations for health personnel; of these, 20 were involved in fast clockwise shift rotation that included night shifts (SW nurses), whereas 20 worked exclusively daytime shifts (DT nurses). All nurses were female.

The study criteria required participants to(i)be taking no drugs, melatonin supplements, or oestrogen/progestin treatment(ii)suffer from no psychiatric disorders, degenerative or cardiovascular disease (e.g. heart attack and stroke), insomnia, chronic viral infections, cancer, autoimmune disorders, or diseases such as uterine fibromatosis and polycystic ovary syndrome(iii)have worked the same shift for at least 2 years without changes (e.g., by swapping shifts with colleagues) for at least 6 months prior to testing(iv)work at least 48 night shifts a year (SW nurses)(v)have no occupational exposure to ionizing radiation or antiblastic drug preparation

Nurses provided their consent after receiving information about the aims and modalities of the study, which was conducted according to the Helsinki Statement of Ethical Standards. Being an integral part of the routine health surveillance, the study was not subject to formal approval by the local ethics committee. The schedule of SW nurses was as follows: day 1, 7:00 AM–2:00 PM; day 2, 2:00 PM–10:00 PM; day 3, 10:00 PM–07:00 AM; rest for 48 h; resumption of the cycle. The DT nurses worked a 07:00 AM–2:00 PM shift 6 days a week. To avoid the acute alterations associated with a night shift (SW nurses), all participants were tested during a day shift after a regular night sleep.

At 8:00 AM, venous blood was collected to evaluate fasting glycaemia, glycated haemoglobin, and lipids (total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides) and to obtain lymphocytes for measuring NOCTURNIN expression levels.

Subsequently, participants underwent medical examination and measurement of anthropometric parameters including body weight, height, blood pressure, body mass index (BMI), waist circumference, hip circumference, and skinfold (biceps, triceps, subscapular, and suprailiac) thickness. The Durnin and Womersley formula were used for fat mass calculation [31]. General information, including smoking habits and alcohol consumption, was collected as part of the medical history. Participants were asked to keep a food diary, reporting daily food intake and amount and time of intake for 5 consecutive days. A dietician explained how to compile it. Total energy intake and fat, carbohydrate, and protein intake were calculated [32] and expressed as daily average for each of the 5 days.

During physical examination, a SenseWear Armband® (SWA) (BodyMedia Inc., Pittsburgh, PA, USA), a metabolic monitor that quantifies energy expenditure using internal sensors, was secured high on each participant’s right arm and activated. The device consists of a two-axis accelerometer that measures movement through a microelectromechanical sensor, a galvanic sensor that records skin responses, a skin temperature sensor, and a sensor measuring external temperature [33]. The SWA was worn for 5 days. Total energy expenditure, energy expenditure due to motor activity, duration of physical activity (> 3.0 Metabolic Equivalents, METs), time lying down, and sleep duration were calculated using the SenseWear Armband® Software. There were no cases of interrupted or invalid recordings. Results were expressed as daily average for each of the 5 days.

2.3. NOCTURNIN Gene Expression Analysis

The peripheral blood samples were processed immediately after collection. Lymphocytes were isolated using a density gradient separation medium (Cedarlane Laboratories LTD, Hornby, ON, Canada) and stored at −80°C until RNA extraction. Total RNA was isolated using RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. RNA quality and quantity were evaluated with a Nanodrop 1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). cDNA was synthesized according to the High-Capacity cDNA Reverse Transcription Kit protocol (Applied Biosystems, Foster City, CA, USA).

Gene expression was analysed by real-time quantitative PCR (RT-qPCR) using TaqMan Gene Expression Master Mix (Applied Biosystems). To control for variations in the amount of cDNA available for RT-qPCR in the different samples, the gene expression levels of the target sequences were normalized to the expression of an endogenous control, glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The primer and probe sets used for RT-qPCR assays were as follows: nm012118.1.pt.CCRN4L for NOCTURNIN and Hs.PT.39a.22214836 for GAPDH (Integrated DNA Technologies Inc., Coralville, IA, USA). NOCTURNIN levels were calculated by the equation: [34].

2.4. Statistical Analysis

A total sample size of 10 healthy volunteers was calculated a priori, to detect significant differences in NOCTURNIN expression with an effect size of 0.60, a power ≥ 0.80, and an α=0.05 (two-tailed). The theoretical sample size was increased by 50% to achieve more representative data. Normality of distribution was assessed with the Kolmogorov-Smirnov test. Since the transformed values approximated most closely a normal distribution, natural logarithms of NOCTURNIN values were used for the analysis. Continuous variables were expressed as mean ± SD and log-transformed variables as geometric mean and 95% confidence interval (95% CI). One-way repeated measures ANOVA was run to analyse NOCTURNIN expression at different time points. Mauchly’s test was performed to verify the sphericity assumption; an LSD test was used as a post hoc assessment. Cosinor analysis was applied to study circadian rhythmicity. Student’s t-test was used to test differences in independent measures between SW and DT nurses. The chi-square test was applied to test dichotomous parameters. Multivariate linear regression analysis was used to assess the dependency of NOCTURNIN expression levels on shift work. Explanatory variables associated with the outcome at a significance level of ≤ 0.20 (univariate analysis) were included as independent variables. BMI, total energy expenditure, and total food intake were considered as potential confounders a priori. Data were analysed with SPSS software (SPSS, Chicago, IL, USA) and Circadian software (available online at www.circadian.org). Statistical significance was set at p < 0.05.

3. Results

Analysis of the NOCTURNIN mRNA expression pattern in lymphocytes from the 15 healthy volunteers showed a significant diurnal variation (repeated measures ANOVA; p < 0.05; Figure 1) with the main peak at 8:00 AM and a secondary peak at 8:00 PM (repeated measures ANOVA, post hoc LSD, p < 0.05). There were no significant differences between men and women. Cosinor analysis confirmed the ANOVA results and yielded a period of 12.2 h, a mesor of 2.49, an amplitude of 0.49, and an acrophase of -22° for the oscillation of NOCTURNIN expression.

All 40 nurses involved in the study were female. Both groups consisted of participants coming from several different departments. SW nurses were significantly younger than DT nurses (p=0.027) and had significantly less job seniority (p=0.002) (Table 1). Shift work seniority for SW nurses was 19.9±4.2 years and coincided with job seniority, demonstrating that SW nurses had not changed their schedules for at least 2 years prior to the study. They worked 6.0±1.0 nights per month. There were no significant differences between SW and DT nurses in the number of smokers or of alcohol drinkers.


SW nursesDT nursesP-value
(n=20)(n=20)
MeanSD%MeanSD%

Age (years)43.63.245.93.10.027
Job seniority (years)19.94.224.54.50.002
Shift work seniority (years)19.94.2
Nights worked per month6.01.0
Smokers (%)35.050.00.337
Alcohol drinkers (%)25.035.00.490

There were no significant differences in BMI, waist or hip circumference, body fat, or systolic/diastolic pressure between SW and DT nurses. Similarly, fasting glycaemia, glycated haemoglobin, total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides did not show significant differences between the groups (Table 2).


SW nursesDT nursesP-value
(n=20)(n=20)
MeanSDMeanSD

BMI30.08.427.45.30.249
Waist circumference (cm)86.317.083.110.20.475
Hip circumference (cm)97.214.993.79.50.381
Body fat (%)37.75.137.54.80.899
Systolic pressure (mmHg)120.313.2117.910.80.533
Diastolic pressure (mmHg)78.08.575.46.80.292
Fasting glycaemia (mg/dl)87.09.589.715.10.503
Glycated haemoglobin (%)5.20.35.30.20.223
Total cholesterol (mg/dl)194.534.1210.044.10.221
HDL cholesterol (mg/dl)52.09.957.316.90.234
LDL cholesterol (mg/dl)127.530.6133.936.50.552
Triglycerides (mg/dl)114.575.192.146.70.264

The analysis of total energy intake and diet composition did not show significant differences between SW and DT nurses (Table 3).


SW nursesDT nursesP-value
(n=20)(n=20)
MeanSDMeanSD

Total energy intake (kcal)212830520303760.371
Fat (%)25.90.826.30.90.146
Carbohydrates (%)54.71.754.52.30.756
Protein (%)19.30.919.21.10.877

Total energy expenditure and energy expenditure due to motor activity, as calculated by the SWA software, were not significantly different between the groups (Table 4). However, SW nurses spent several more minutes performing intense physical activities (p=0.029) as well as more time lying down (p=0.041) than DT nurses. Sleep duration was not significantly different.


SW nursesDT nursesP-value
(n=20)(n=20)
MeanSDMeanSD

Total energy expenditure (kcal)201068719557080.805
Energy expenditure due to motor activity (kcal)133253112775670.753
Physical activity (minutes14411182670.039
Time lying down (minutes)49562457510.041
Sleep duration (minutes)40372382560.310

activity > 3 METs.

NOCTURNIN expression levels, measured in peripheral venous blood lymphocytes sampled at 8:00 AM, were significantly higher in SW than in DT nurses [GM (95% CI) 3.74 (2.64-5.31) x103 vs. 2.92 (2.34-3.63) x103, respectively; p=0.010] (Figure 2).

Multivariate analysis confirmed a positive dependency of NOCTURNIN expression levels on shift work (β 0.533 p=0.009). It also highlighted a positive correlation of NOCTURNIN levels with BMI (β 0.770 p=0.002) and a negative correlation with total energy expenditure (β -0.470 p=0.036) (Table 5).


NOCTURNIN
gene expression
βP-value

Shift work0.5330.009
Age0.1470.417
BMI0.7700.002
Total energy intake-0.0980.403
Total energy expenditure-0.4700.036
Physical -0.0560.788
Time lying down-0.1380.410

activity >3 METs.

4. Discussion

NOCTURNIN is the only deadenylase showing high-amplitude rhythms in mice [2]. Tests in human volunteers showed diurnal variation in NOCTURNIN gene expression, with the main peak at 8:00 AM and a secondary peak at 8:00 PM. In mice, the peak corresponds with the peak of the PER2 gene [35]. Since human PER2 expression peaks in the early morning [30, 36], the main NOCTURNIN peak measured at 8:00 AM in the present study was expected.

Various intestinal functions such as peristalsis, emptying, gastric pH, and absorption of food are ultradian events [37]. The secondary NOCTURNIN peak may be related to food intake and intestinal activities [38].

The NOCTURNIN gene links the circadian cycles to the metabolic rhythms and, given its specific role in fat absorption and metabolism [37, 39, 40], it may be implicated in promoting metabolic alterations [57]. Shift work has been shown to be associated with metabolic alterations and obesity, although the causes of the association have not been fully clarified. The hypothesis that shift workers would eat more calories and/or fatty foods has not been demonstrated conclusively [4144]. There are also conflicting data regarding energy expenditure and physical activity as assessed by self-administered questionnaires [4547]. However, sleep deprivation, which is common among shift workers, is accompanied by weight gain [26, 27] and by increased ghrelin and reduced leptin concentrations in the circulation [48, 49]. An imbalance due to increased food intake and reduced energy expenditure may be the cause of the weight gain and metabolic alterations reported in shift workers. Our findings indicate that total energy expenditure, energy expenditure due to motor activity, and sleep duration were not significantly different between SW and DT nurses. The longer time spent by SW nurses performing intense physical activity was probably compensated for by the longer time spent by SW nurses lying down. The food diaries also failed to demonstrate significant differences in energy intake or diet composition between the two groups. The same applies to their metabolic parameters. Nocturnin-knockout mice are resistant to diet-induced obesity. This is not due to increased physical activity, reduced food intake, or accelerated metabolism, but probably to a metabolic deficit or reduced lipid absorption [3].

NOCTURNIN expression was significantly higher in SW nurses, and multivariate analysis confirmed the role of shift work as an independent factor influencing NOCTURNIN expression. Circadian desynchronization associated with shift work involves both the SCN and the expression of peripheral clock genes [36, 50] which, in turn, tune the expression of clock-controlled genes such as NOCTURNIN. Chronic NOCTURNIN overexpression may promote metabolic disorders through increased absorption and storage of fats in adipocytes. In addition, NOCTURNIN seems to be involved in the regulation of glucose homeostasis and insulin sensitivity and may promote insulin resistance [2]. It has also been reported that its expression may be influenced by hormones like melatonin and cortisol, whose rhythms are affected by the circadian disruption induced by shift work [36, 51, 52]. Melatonin is a regulator of fat metabolism, and its predominantly antiadipogenic activity suggests that it may be a NOCTURNIN antagonist [53]. Although no information is available on the interaction between NOCTURNIN and cortisol, antagonism may be hypothesized in this case, too.

The selection of GAPDH as the reference gene was due to its successful use in NOCTURNIN mRNA studies [54] and in investigations of clock gene expression in human tissues [30, 55, 56]. Notably, some studies have reported that GAPDH is rhythmically expressed in some mice and rat tissues [5760]. Although no data are available about the rhythmicity of GAPDH expression in human blood lymphocytes, it has been reported that the evidence for gene rhythmicity can be impaired by using GAPDH as the reference gene [58]. Although we have found diurnal variation in NOCTURNIN gene expression, the use of GAPDH as the reference gene may be a limitation of the study.

The significantly different NOCTURNIN gene expression levels found in SW and DT nurses related to the specific type of shifts examined. Notably, blood was sampled after a day off and a regular night sleep, to avoid the acute alterations induced by night work. Data from workers with a shift schedule that includes several consecutive nights would provide valuable information, since a larger effect might be expected. The values obtained in the present study are also affected by the time of blood collection. The single sample taken from the nurses clearly prevented examination of diurnal variation. However, the peak hour is probably the best time to investigate difference in NOCTURNIN expression levels between SW and DT nurses. The interindividual variability in NOCTURNIN gene expression was greater among SW nurses, a finding that probably depends on a different tolerance of shift work. Although several factors influence the response to shift work, chronotype probably plays a major role [6164]. BMI and waist circumference, which are usually significantly different in shift compared with daytime workers [22, 27, 29, 65], did not reach significance in the present study, suggesting that the effect size of shift work on these parameters is lower than the effect on NOCTURNIN expression levels. However, multivariate analysis highlighted a positive correlation between NOCTURNIN expression and BMI, in line with a previous study [8]. Moreover, the inverse correlation found between NOCTURNIN expression and total energy expenditure suggests that shift workers should be encouraged to engage in physical activity.

5. Conclusions

The human NOCTURNIN gene is a clock-controlled gene characterized by diurnal variation and a peak at 8:00 AM. Measurement of its expression level in peripheral blood lymphocytes at 8:00 AM can provide useful information on the relationship between changes in circadian rhythm and metabolic disorders. It may be hypothesized that the higher NOCTURNIN expression levels found in shift workers in this study have the potential to promote metabolic alterations and/or activation of alternative metabolic pathways that may increase the risk of developing obesity and metabolic syndrome.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Authors’ Contributions

Massimo Bracci and Alfredo Copertaro contributed equally, conceived and designed the study, interpreted the data, and wrote the manuscript; Veronica Ciarapica performed laboratory tests; Mariella Barbaresi collected blood samples; Stefano Esposito and Antonella Albanesi collected anthropometric and metabolic data; Matteo Valentino contributed reagents and materials; Caterina Ledda performed analysis and interpretation of data; Venerando Rapisarda performed analysis and interpretation of data; Lory Santarelli supervised the project and approved the final manuscript.

Acknowledgments

This work was supported by the Polytechnic University of Marche, Ancona, Italy.

Supplementary Materials

The supplementary file includes individual profiles of NOCTURNIN expression of healthy volunteers. There were no significant differences between men and women. (Supplementary Materials)

References

  1. C. B. Green and J. C. Besharse, “Identification of a novel vertebrate circadian clock-regulated gene encoding the protein nocturnin,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 93, no. 25, pp. 14884–14888, 1996. View at: Publisher Site | Google Scholar
  2. N. Douris and C. B. Green, “NOC out the fat: A short review of the circadian deadenylase Nocturnin,” Annals of Medicine, vol. 40, no. 8, pp. 622–626, 2009. View at: Publisher Site | Google Scholar
  3. C. B. Green, N. Douris, S. Kojima et al., “Loss of Nocturnin, a circadian deadenylase, confers resistance to hepatic steatosis and diet-induced obesity,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 104, no. 23, pp. 9888–9893, 2007. View at: Publisher Site | Google Scholar
  4. M. Vinciguerra, M. F. Tevy, and G. Mazzoccoli, “A ticking clock links metabolic pathways and organ systems function in health and disease,” Clinical and Experimental Medicine, vol. 14, no. 2, pp. 133–140, 2014. View at: Publisher Site | Google Scholar
  5. N. Douris, S. Kojima, X. Pan et al., “Nocturnin regulates circadian trafficking of dietary lipid in intestinal enterocytes,” Current Biology, vol. 21, no. 16, pp. 1347–1355, 2011. View at: Publisher Site | Google Scholar
  6. S. W. Hee, S. H. Tsai, Y. C. Chang et al., “The role of nocturnin in early adipogenesis and modulation of systemic insulin resistance in human,” Obesity, vol. 20, no. 8, pp. 1558–1565, 2012. View at: Publisher Site | Google Scholar
  7. J. J. Stubblefield, J. Terrien, and C. B. Green, “Nocturnin: At the crossroads of clocks and metabolism,” Trends in Endocrinology & Metabolism, vol. 23, no. 7, pp. 326–333, 2012. View at: Publisher Site | Google Scholar
  8. Y. Chang, Y. Chiu, P. Liu et al., “Genetic variation in the noc gene is associated with body mass index in chinese subjects,” PLoS ONE, vol. 8, no. 7, Article ID e69622, 2013. View at: Publisher Site | Google Scholar
  9. P. L. Lowrey and J. S. Takahashi, “Genetics of circadian rhythms in mammalian model organisms,” Advances in Genetics, vol. 74, pp. 175–230, 2011. View at: Publisher Site | Google Scholar
  10. K. Bozek, A. Relógio, S. M. Kielbasa et al., “Regulation of clock-controlled genes in mammals,” PLoS ONE, vol. 4, no. 3, Article ID e4882, 2009. View at: Publisher Site | Google Scholar
  11. S. A. Brown and A. Azzi, “Peripheral circadian oscillators in mammals,” Handbook of Experimental Pharmacology, vol. 217, pp. 45–66, 2013. View at: Publisher Site | Google Scholar
  12. C. B. Green, J. S. Takahashi, and J. Bass, “The meter of metabolism,” Cell, vol. 134, no. 5, pp. 728–742, 2008. View at: Publisher Site | Google Scholar
  13. G. Costa, “Sleep deprivation due to shift work,” Handbook of Clinical Neurology, vol. 131, pp. 437–446, 2015. View at: Publisher Site | Google Scholar
  14. G. Costa, M. M. Anelli, G. Castellini, S. Fustinoni, and L. Neri, “Stress and sleep in nurses employed in "3 × 8" and "2 × 12" fast rotating shift schedules,” Chronobiology International, vol. 31, no. 10, pp. 1169–1178, 2014. View at: Publisher Site | Google Scholar
  15. R. G. Stevens, G. C. Brainard, D. E. Blask, S. W. Lockley, and M. E. Motta, “Breast cancer and circadian disruption from electric lighting in the modern world,” CA: A Cancer Journal for Clinicians, vol. 64, no. 3, pp. 207–218, 2014. View at: Publisher Site | Google Scholar
  16. C. Vetter, E. E. Devore, L. R. Wegrzyn et al., “Association between rotating night shift work and risk of coronary heart disease among women,” Journal of the American Medical Association, vol. 315, no. 16, pp. 1726–1734, 2016. View at: Publisher Site | Google Scholar
  17. X. Wang, M. E. Armstrong, B. J. Cairns, T. J. Key, and R. C. Travis, “Shift work and chronic disease: the epidemiological evidence,” Occupational Medicine , vol. 61, no. 2, pp. 78–89, 2011. View at: Publisher Site | Google Scholar
  18. S. Strohmaier, E. E. Devore, Y. Zhang, and E. S. Schernhammer, “A review of data of findings on night shift work and the development of DM and CVD events: a synthesis of the proposed molecular mechanisms,” Current Diabetes Reports, vol. 18, no. 12, p. 132, 2018. View at: Publisher Site | Google Scholar
  19. M. C. B. Brum, F. F. D. Filho, C. C. Schnorr, G. B. Bottega, and T. C. Rodrigues, “Shift work and its association with metabolic disorders,” Diabetology & Metabolic Syndrome, vol. 7, no. 1, p. 45, 2015. View at: Google Scholar
  20. A. Pan, E. S. Schernhammer, Q. Sun, and F. B. Hu, “Rotating night shift work and risk of type 2 diabetes: two prospective cohort studies in women,” PLoS Medicine, vol. 8, no. 12, Article ID e1001141, 2011. View at: Publisher Site | Google Scholar
  21. C. Ledda, D. Cinà, S. Matera, N. Mucci, M. Bracci, and V. Rapisarda, “High HOMA-IR index in healthcare shift workers,” Medicina, vol. 55, no. 5, p. 186, 2019. View at: Publisher Site | Google Scholar
  22. A. Copertaro, M. Bracci, M. Barbaresi, and L. Santarelli, “Assessment of cardiovascular risk in shift healthcare workers,” European Journal of Cardiovascular Prevention & Rehabilitation, vol. 15, no. 2, pp. 224–229, 2008. View at: Publisher Site | Google Scholar
  23. B. Karlsson, A. Knutsson, and B. Lindahl, “Is there an association between shift work and having a metabolic syndrome? Results from a population based study of 27,485 people,” Occupational and Environmental Medicine, vol. 58, no. 11, pp. 747–752, 2001. View at: Publisher Site | Google Scholar
  24. K. Straif, R. Baan, Y. Grosse et al., “Carcinogenicity of shift-work, painting, and fire-fighting,” The Lancet Oncology, vol. 8, no. 12, pp. 1065-1066, 2007. View at: Publisher Site | Google Scholar
  25. L. Di Lorenzo, G. De Pergola, C. Zocchetti et al., “Effect of shift work on body mass index: results of a study performed in 319 glucose-tolerant men working in a Southern Italian industry,” International Journal of Obesity, vol. 27, no. 11, pp. 1353–1358, 2003. View at: Publisher Site | Google Scholar
  26. G. Lee, K. Kim, S. Kim et al., “Effects of shift work on abdominal obesity among 20–39-year-old female nurses: a 5-year retrospective longitudinal study,” Annals of Occupational and Environmental Medicine, vol. 28, no. 1, p. 69, 2016. View at: Publisher Site | Google Scholar
  27. B. Peplonska, A. Bukowska, W. Sobala, and C. R. Sirtori, “Association of rotating night shift work with bmi and abdominal obesity among nurses and midwives,” PLoS ONE, vol. 10, no. 7, Article ID e0133761, 2015. View at: Publisher Site | Google Scholar
  28. B. A. van Drongelen, C. R. L. Boot, S. L. Merkus, T. Smid, and A. J. van der Beek, “The effects of shift work on body weight change - A systematic review of longitudinal studies,” Scandinavian Journal of Work, Environment & Health, vol. 37, no. 4, pp. 263–275, 2011. View at: Publisher Site | Google Scholar
  29. A. Copertaro, M. Bracci, M. Barbaresi, and L. Santarelli, “Role of waist circumference in the diagnosis of metabolic syndrome and assessment of cardiovascular risk in shift workers,” La Medicina del Lavoro, vol. 99, no. 6, pp. 444–453, 2008. View at: Google Scholar
  30. N. Manzella, M. Bracci, E. Strafella et al., “Circadian modulation of 8-oxoguanine DNA damage repair,” Scientific Reports, vol. 5, no. 1, Article ID 13752, 2015. View at: Publisher Site | Google Scholar
  31. J. V. Durnin and J. Womersley, “Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 Years,” British Journal of Nutrition, vol. 32, no. 01, pp. 77–97, 1974. View at: Publisher Site | Google Scholar
  32. S. Salvini, P. Gnagnarella, M. T. Parpinel et al., “The food composition database for an italian food frequency questionnaire,” Journal of Food Composition and Analysis, vol. 9, no. 1, pp. 57–71, 1996. View at: Publisher Site | Google Scholar
  33. P. J. Manns and R. G. Haennel, “SenseWear armband and stroke: Validity of energy expenditure and step count measurement during walking,” Stroke Research and Treatment, vol. 2012, Article ID 247165, 8 pages, 2012. View at: Publisher Site | Google Scholar
  34. T. D. Schmittgen and K. J. Livak, “Analyzing real-time PCR data by the comparative CT method,” Nature Protocols, vol. 3, no. 6, pp. 1101–1108, 2008. View at: Publisher Site | Google Scholar
  35. A. N. Filiano, T. Millender-Swain, R. Johnson et al., “Chronic ethanol consumption disrupts the core molecular clock and diurnal rhythms of metabolic genes in the liver without affecting the suprachiasmatic nucleus,” PLoS ONE, vol. 8, no. 8, Article ID e71684, 2013. View at: Publisher Site | Google Scholar
  36. M. Bracci, V. Ciarapica, A. Copertaro et al., “Peripheral skin temperature and circadian biological clock in shift nurses after a day off,” International Journal of Molecular Sciences, vol. 17, no. 5, Article ID e623, 2016. View at: Publisher Site | Google Scholar
  37. L. A. Scheving, “Biological clocks and the digestive system,” Gastroenterology, vol. 119, no. 2, pp. 536–549, 2000. View at: Publisher Site | Google Scholar
  38. D. J. Skene, E. Skornyakov, N. R. Chowdhury et al., “Separation of circadian- and behavior-driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 115, no. 30, pp. 7825–7830, 2018. View at: Publisher Site | Google Scholar
  39. M. M. Hussain, “Regulation of intestinal lipid absorption by clock genes,” Annual Review of Nutrition, vol. 34, no. 1, pp. 357–375, 2014. View at: Publisher Site | Google Scholar
  40. M. M. Hussain and X. Pan, “Circadian regulators of intestinal lipid absorption,” Journal of Lipid Research, vol. 56, no. 4, pp. 761–770, 2015. View at: Publisher Site | Google Scholar
  41. M. S. Alves, R. Z. Andrade, G. C. Silva et al., “Social jetlag among night workers is negatively associated with the frequency of moderate or vigorous physical activity and with energy expenditure related to physical activity,” Journal of Biological Rhythms, vol. 32, no. 1, pp. 83–93, 2017. View at: Publisher Site | Google Scholar
  42. M. P. Bonham, E. K. Bonnell, and C. E. Huggins, “Energy intake of shift workers compared to fixed day workers: A systematic review and meta-analysis,” Chronobiology International, vol. 33, no. 8, pp. 1086–1100, 2016. View at: Publisher Site | Google Scholar
  43. G. Heath, A. Coates, C. Sargent, and J. Dorrian, “Sleep duration and chronic fatigue are differently associated with the dietary profile of shift workers,” Nutrients, vol. 8, no. 12, Article ID E771, 2016. View at: Publisher Site | Google Scholar
  44. G. Hulsegge, J. M. Boer, A. J. van der Beek et al., “Shift workers have a similar diet quality but higher energy intake than day workers,” Scandinavian Journal of Work, Environment & Health, vol. 42, no. 6, pp. 459–468, 2016. View at: Publisher Site | Google Scholar
  45. G. Atkinson, S. Fullick, C. Grindey, and D. Maclaren, “Exercise, energy balance and the shift worker,” Sports Medicine, vol. 38, no. 8, pp. 671–685, 2008. View at: Publisher Site | Google Scholar
  46. B. Loef, G. Hulsegge, G. C. Wendel-Vos et al., “Non-occupational physical activity levels of shift workers compared with non-shift workers,” Occupational and Environmental Medicine, vol. 74, no. 5, pp. 328–335, 2017. View at: Publisher Site | Google Scholar
  47. F. M. Nea, J. Kearney, M. B. Livingstone, L. K. Pourshahidi, and C. A. Corish, “Dietary and lifestyle habits and the associated health risks in shift workers,” Nutrition Research Reviews, vol. 28, no. 2, pp. 143–166, 2015. View at: Publisher Site | Google Scholar
  48. J.-P. Chaput, J.-P. Després, C. Bouchard, and A. Tremblay, “Short sleep duration is associated with reduced leptin levels and increased adiposity: results from the Québec Family Study,” Obesity, vol. 15, no. 1, pp. 253–261, 2007. View at: Publisher Site | Google Scholar
  49. S. Taheri, L. Lin, D. Austin, T. Young, and E. Mignot, “Short sleep duration is associated with reduced leptin, elevated ghrelin, and increased body mass index,” PLoS Medicine, vol. 1, no. 3, article e62, 2004. View at: Publisher Site | Google Scholar
  50. M. Bracci, N. Manzella, A. Copertaro et al., “Rotating-shift nurses after a day off: Peripheral clock gene expression, urinary melatonin, and serum 17-β-estradiol levels,” Scandinavian Journal of Work, Environment & Health, vol. 40, no. 3, pp. 295–304, 2014. View at: Publisher Site | Google Scholar
  51. T. W. Kim, J.-H. Jeong, and S.-C. Hong, “The impact of sleep and circadian disturbance on hormones and metabolism,” International Journal of Endocrinology, vol. 2015, Article ID 591729, 9 pages, 2015. View at: Publisher Site | Google Scholar
  52. K. Papantoniou, O. J. Pozo, A. Espinosa et al., “Circadian variation of melatonin, light exposure, and diurnal preference in day and night shift workers of both sexes,” Cancer Epidemiology Biomarkers & Prevention, vol. 23, no. 7, pp. 1176–1186, 2014. View at: Publisher Site | Google Scholar
  53. R. Hardeland, “Melatonin, noncoding rnas, messenger rna stability and epigenetics—evidence, hints, gaps and perspectives,” International Journal of Molecular Sciences, vol. 15, no. 10, pp. 18221–18252, 2014. View at: Publisher Site | Google Scholar
  54. J. J. Stubblefield, P. Gao, G. Kilaru, B. Mukadam, J. Terrien, and C. B. Green, “Temporal control of metabolic amplitude by nocturnin,” Cell Reports, vol. 22, no. 5, pp. 1225–1235, 2018. View at: Publisher Site | Google Scholar
  55. X. Zhuang, A. Magri, M. Hill et al., “The circadian clock components BMAL1 and REV-ERBalpha regulate flavivirus replication,” Nature Communications, vol. 10, p. 377, 2019. View at: Publisher Site | Google Scholar
  56. M. Bracci, A. Copertaro, N. Manzella et al., “Influence of night-shift and napping at work on urinary melatonin, 17-beta-estradiol and clock gene expression in pre-menopausal nurses,” Journal of Biological Regulators and Homeostatic Agents, vol. 27, no. 1, pp. 267–274, 2013. View at: Google Scholar
  57. C. Cai, P. Cai, and G. Chu, “Selection of suitable reference genes for core clock gene expression analysis by real-time qPCR in rat ovary granulosa cells,” Molecular Biology Reports, vol. 46, no. 3, pp. 2941–2946, 2019. View at: Publisher Site | Google Scholar
  58. D. d. Figueredo, M. R. Barbosa, D. G. Coimbra et al., “Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns,” Chronobiology International, vol. 35, no. 3, pp. 378–391, 2017. View at: Publisher Site | Google Scholar
  59. W. Kamphuis, C. Cailotto, F. Dijk, A. Bergen, and R. M. Buijs, “Circadian expression of clock genes and clock-controlled genes in the rat retina,” Biochemical and Biophysical Research Communications, vol. 330, no. 1, pp. 18–26, 2005. View at: Publisher Site | Google Scholar
  60. R. Matsumura, A. Okamoto, K. Node, and M. Akashi, “Compensation for intracellular environment in expression levels of mammalian circadian clock genes,” Scientific Reports, vol. 4, no. 1, p. 4032, 2015. View at: Publisher Site | Google Scholar
  61. K. Papantoniou, C. Vetter, and E. S. Schernhammer, “Shift work practices and opportunities for intervention,” Occupational and Environmental Medicine, vol. 74, no. 1, pp. 2-3, 2016. View at: Publisher Site | Google Scholar
  62. C. Vetter, E. E. Devore, C. A. Ramin, F. E. Speizer, W. C. Willett, and E. S. Schernhammer, “Mismatch of sleep and work timing and risk of type 2 diabetes,” Diabetes Care, vol. 38, no. 9, pp. 1707–1713, 2015. View at: Publisher Site | Google Scholar
  63. A. Copertaro and M. Bracci, “Working against the biological clock: a review for the occupational physician,” Industrial Health, 2019. View at: Publisher Site | Google Scholar
  64. J. Ritonja, K. J. Aronson, R. W. Matthews, D. B. Boivin, and T. Kantermann, “Working Time Society consensus statements: Individual differences in shift work tolerance and recommendations for research and practice,” Industrial Health, vol. 57, no. 2, pp. 201–212, 2019. View at: Publisher Site | Google Scholar
  65. P. Barbadoro, L. Santarelli, N. Croce et al., “Rotating shift-work as an independent risk factor for overweight in Italian workers: A cross-sectional study,” PLoS ONE, vol. 8, no. 6, Article ID e63289, 2013. View at: Google Scholar

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