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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Integr Cancer Ther. Author manuscript; available in PMC 2010 December 1.
Published in final edited form as:
PMCID: PMC2959170

Circadian Disruption, Per3, and Human Cytokine Secretion

Jaclyn Guess, MSPH,1,2 James B. Burch, MS, PhD,1,2,3 Kisito Ogoussan, MD, MPH,1 Cheryl A. Armstead, MS(R), PhD,1 Hongmei Zhang, PhD,1 Sara Wagner, MSPH, PhD,4 James R. Hebert, MSPH, ScD,1,2 Patricia Wood, MD, PhD,1,3 Shawn D. Youngstedt, PhD,1,3 Lorne J. Hofseth, PhD,1 Udai P. Singh, PhD,1 Dawen Xie, MD, PhD,1 and William J. M. Hrushesky, MD3


Circadian disruption has been linked with inflammation, an established cancer risk factor. Per3 clock gene polymorphisms have also been associated with circadian disruption and with increased cancer risk. Patients completed a questionnaire and provided a blood sample prior to undergoing a colonoscopy (n = 70). Adjusted mean serum cytokine concentrations (IL-6, TNF-alpha, gamma-INF, IL-I ra, IL-I-beta, VEGF) were compared among patients with high and low scores for fatigue (Multidimensional Fatigue Inventory), depressive symptoms (Beck Depression Inventory II), or sleep disruption (Pittsburgh Sleep Quality Index), or among patients with different Per3 clock gene variants. Poor sleep was associated with elevated VEGF, and fatigue-related reduced activity was associated with elevated TNF-alpha concentrations. Participants with the 4/5 or 5/5 Per3 variable tandem repeat sequence had elevated IL-6 concentrations compared to those with the 4/4 genotype. Biological processes linking circadian disruption with cancer remain to be elucidated. Increased inflammatory cytokine secretion may playa role.

Keywords: circadian rhythm, clock gene, cytokine, inflammation


Factors that disrupt circadian rhythms, for example, shift work or altered clock gene expression, are emerging as novel cancer risk factors. 1-4 Circadian rhythm disruption can lead to the development of fatigue, sleep disruption, and depressive symptoms, and these psychological perturbations have been associated with increased secretion of inflammatory cytokines.5-10 Chronic inflammation is an established risk factor for several types of cancer.11,12 Thus, the putative association between circadian disruption and cancer may be driven, at least in part, by immune system dysregulation and changes in the secretion of cytokines that influence inflammation or tumor development. Similarly, polymorphic variation in certain clock genes can result in the phenotypic expression of symptoms related to circadian rhythm disruption, including disrupted sleep and altered mood. 13,14 More recently, certain clock gene polymorphisms have been associated with increased cancer risk 15-18 The human Per3 clock gene is a putative tumor suppressor gene that contains a polymorphic domain expressing 4 or 5 copies of a 54-bp tandem repeat sequence. Variation in this sequence has been associated with circadian preference, sleep and mood disorders, and increased breast cancer risk among premenopausal women. 18-24 Rhythmic changes in Per and other clock genes have been linked with regulation of the innate immune system.25-27 However, no study has examined whether variation in the human Per3 clock gene is associated with altered cytokine secretion. The objective of this study was to test the hypothesis that individuals with fatigue, poor sleep, depressive symptoms or a Per3 clock gene variant genotype have altered serum concentrations of cytokines that can influence inflammation or growth regulation.

Materials and Methods

The study population consisted of male veterans scheduled for a screening or diagnostic colonoscopy at the Dom Veterans Affairs Medical Center (DVAMC) in Columbia, South Carolina. Data were collected from March through November 2007 between 9:00 AM and 5:00 PM. Following informed consent, participation included a personal interview and collection of a peripheral blood sample for recovery of serum and DNA. All data were collected prior to completion of the colonoscopy; therefore, participants had no knowledge of the procedure outcome at the time of interview. The questionnaire included information on sociodemographic characteristics, lifestyle, diet, employment and shift work, health status, medications and supplements, mental and physical well-being, physical activity,28 time spent outdoors, risk factors for colorectal polyps and cancer, sleep habits, major life events, stress and coping strategies, social support, and validated instruments targeting sleep disruption (Pittsburgh Sleep Quality Index [PSQI]),29 fatigue (Multidimensional Fatigue Inventory [MFI]),30 and depressive symptoms (Beck Depression Inventory II [BDI]).31,32 The study was approved by the institutional review boards of the DVAMC and University of South Carolina.

Whole blood samples used for DNA recovery were collected in ethylenediaminetetraacetic acid–preserved vacutainers and stored in 0.5-mL aliquots at –80°C prior to analysis. Genomic DNA was extracted using the DrGentle protocol (Takara, Japan). After extraction, genomic DNA pellets (50-100 μg) were dissolved in 100 to 200 μL of TE buffer, of which about 200 ng was subjected to polymerase chain reaction (PCR) using a Perkin Elmer GeneAmp System 9700 (Waltham, MA) according to the manufacturer's protocol. The Per3 variable number tandem repeat (VNTR) DNA sequence was amplified using the following primers (forward) 5′-CAAAATTTTATGACACTACCAGAATGGCTGAC-3′ and (reverse) 5′-AACCTTGTACTTCCACATCAGTGCCTGG-3′, with a reaction mixture consisting of 25 μL standard PCR buffer, 5% DMSO, 1.0 mM MgC12, 0.2 mM dNTP, 1 unit Taq polymerase (Gibco-Invitrogen, Carlsbad, CA), and 0.4 μM of each oligonucleotide primer. The reactions were heated to 94°C for 2 minutes followed by 35 cycles at 94°C for 30 seconds, 60°C for 30 seconds, and 72°C for 45 seconds. Finally, the reactions were extended for 7 minutes at 72°C. PCR products were then separated by electrophoresis on a 3% agarose gel to identify homozygous (4-repeat: 4/4), 5-repeat (5/5), or heterozygous (4/5) individuals. Laboratory personnel were blinded to the identity and characteristics of participants, and a 10% random sample was reanalyzed to assess genotyping concordance.

Following collection of a nonfasting venous whole blood sample in a red-top vacutainer, serum samples were clotted at room temperature for 15 to 30 minutes, centrifuged (5000 × g for 5 minutes at 4°C), and 0.5-mL serum aliquots were stored at –80°C until analysis. Serum cytokine concentrations (interferon [IFN]-γ, tumor necrosis factor [TNF]-α, interleukin [IL]-6, IL-1ra, IL-1-β, vascular endothelial growth factor [VEGF]) were determined using a Beadlyte human multicytokine detection system kit (Bio-Rad, Hercules, CA). Filter bottom ELISA plates were rinsed with 100 μL of Bio-plex assay buffer. The assay buffer was then removed using a Millipore Multiscreen Separation Vacuum Manifold System (Bedford, MA) set at 5 mm Hg. Analyte beads in assay buffer were then added to the wells followed by 50 μL of serum or standard solution. The plates were incubated for 30 minutes at room temperature with continuous shaking using a Lab-Line Instrument Titer Plate Shaker (Melrose, IL). The filter bottom plates were washed and centrifuged as before at 300 × g for 30 seconds. Subsequently, 50 μL of antihuman IFN-γ, TNF-α, IL-6, IL-1ra, IL-1-β, or VEGF antibody–biotin reporter solution was added to each reaction well, after which the plates were incubated with continuous shaking for 30 minutes followed by centrifugation and washing. Following this, 50 μL streptavidin–phycoerythrin solution was added, and the plates were incubated with continuous shaking for 10 minutes at room temperature. Next, 125 μL of Bio-plex assay buffer was added, and Beadlyte readings were measured using a Luminex System (Austin, TX) and calculated using Bioplex software. Samples below the limit of detection were assigned a value of one half the limit of detection (0.25) pg/mL for data analyses.

Data analyses were performed using the SAS statistical software package (Version 9.l, SAS Institute Inc, Cary, NC). Values for IL-6, TNF-α, INF-γ, IL-1ra, and IL-l-β were log-transformed prior to analysis, and mean concentrations were transformed back to original units for presentation. VEGF and psychosocial measures (BDI, MFI, and PSQI scores) were analyzed without transformation. One participant had elevated TNF-α and INF-γ concentrations, which were evaluated as potential outliers using the method described by Cook.33 These concentrations met the criteria for Cook's d statistic33 and were within a physiological range; thus, the values were retained in the analyses. A 2-step variable selection procedure was used to identify potential confounding factors associated with each cytokine and psychometric (MFI, BDI, PSQI) variable. First, each independent variable obtained from the questionnaire was compared with each dependent variable using the generalized linear models (GLM) procedure in SAS. Second, screened variables (P < .05) were combined in another GLM model, and factors that were no longer associated with the dependent variable (P > .10) were removed sequentially from further analysis. This step was repeated until a set of statistically significant (P < .05) covariates was identified for each dependent variable, and these were included in subsequent hypothesis testing analyses. To test the study hypotheses, the GLM procedure was used to determine whether mean serum cytokine concentrations (IL-6, TNF-α, IFN-γ, IL-1-β, IL-1ra, and VEGF) differed among individuals grouped according to different circadian disruption symptoms (using MFI, BDI, or PSQI scores) or among those with different Per3 genotypes. Adjusted (least squares [LS]) mean cytokine concentrations were calculated, and differences among symptom categories or genotype were determined using the least significant differences (LSD) statistic, after adjustment for selected potentially confounding factors. BDI scores were used to group participants into categories of normal (≥10), mild (11-20), or moderate to severe (≥21) depressive symtoms.32,34 Poor sleepers were defined as those with PSQI scores ≥5,29,35 and MFI cutpoints were chosen to obtain a distribution of 10 to 15 individuals in several fatigue categories. The relationship between cytokine concentrations and circadian disruption symptoms was also evaluated using each score as a continuous variable in separate GLM analyses. The GLM procedure was used to determine whether circadian disruption symptoms were associated with different Per3 variants by comparing adjusted mean MFI, BDI, or PSQI scores among the Per3 genotypes. Inclusion of polyp status (no polyp detected, benign or hyperplastic polyp, adenoma, or unknown—colonoscopy not yet performed), time of day, or month of sample collection in the statistical analyses did not affect the results obtained.


A total of 83 eligible subjects participated (participation rate = 45%), and complete data were available for 70 men (n = 13 with no blood sample). The average age was 57 ± 9 years, and the racial composition of African Americans and European Americans was approximately equal (51 % and 49%, respectively). Summary scores for general fatigue (mean ± standard deviation = 12 ± 2) and depressive symptoms (14 ± 11) among participants were generally consistent with published normative data (MFI30: 15 ± 7, BDI36: 11 ± 8). The mean global PSQI score in this population (10 ± 5) was elevated, and a bimodal distribution was suggested, with scores centering on approximately 5 and 13 (data not shown).

There were no statistically significant differences in adjusted mean inflammatory cytokine concentrations between those with adequate and poor quality sleep (Table 1). However, poor sleep was associated with a statistically significant increase in circulating VEGF concentrations (P = .04, Table 1). There was no association between serum cytokine concentrations and scores for depressive symptoms, reduced motivation, or general, physical, or mental fatigue (data not shown). Participants with higher MFI subscale scores for fatigue-related reductions in activity tended to have higher TNF-α concentrations compared with those with lower scores (P = .05, Table 2), although the results were of borderline statistical significance.

Table 1
Cytokine Concentrations by Sleep Qualitya
Table 2
Cytokine Concentrations by Reduced Activity Scoresa

Genotyping for the Per3 VNTR was in Hardy–Weinberg equilibrium (P = .81), and there was 100% concordance with independently genotyped quality control samples. The overall frequency of the homozygous 5/5 VNTR (10%) or the combined genotype frequency (4/5 and 5/5, 51%) agreed well with previous reports (approximately 7% to 10% and 40% to 54%, respectively).18,37 Evening circadian preference was reported among 67%, 54%, and 57% of participants with the 5/5, 4/5, and 4/4 Per3 tandem repeat sequences, respectively. Table 3 presents adjusted mean cytokine concentrations among individuals with different Per3 VNTR genotypes. Mean IL-6 concentrations were elevated among individuals with the 4/5 or 5/5 VNTR sequence compared with those homozygous for the common (4/4) genotype. Table 4 presents mean scores for sleep, fatigue, and depressive symptoms among those with different Per3 variant genotypes. A tendency toward reduced motivation and a modest increase in depressive symptoms was suggested among subjects with the 4/5 or 5/5 genotype, whereas physical fatigue and sleep disruption tended to be reduced among these individuals compared with those with the 4/4 genotype (Table 4).

Table 3
Cytokine Concentrations by Per3 VNTR Genotypea
Table 4
Circadian Disruption Symptoms by Per3 VNTR Genotypea


Circadian rhythm disruption is emerging as a novel and important cancer risk factor. In experimental animals, circadian disruption induced by simulated jet lag or via light exposure at night results in accelerated tumor formation and increased cancer mortality.38-45 Shift work can have significant impacts on workers; it has been associated with sleep disruption, fatigue, and, in some cases, depression.46-50 More recently, shift work has been identified as a risk factor for cancers of the colon, breast, prostate, endometrium, and lymphatic system,1,51-58 and the International Agency for Research on Cancer classified shift work as a probable human carcinogen.4 The biological mechanisms underlying the association between circadian disruption and cancer remain to be fully elucidated but may involve changes in the secretion of cytokines that control proinflammatory or proliferative processes.

Results from the present study provide some support for this hypothesis. Poor sleep was associated with increased serum VEGF concentrations, and mean PSQI scores among our participants (10 ± 5) were similar to those observed among cancer patients (11 ± 5).35 VEGF is important among cancer patients because its angiogenic properties support tumor progression. Additionally, it may affect risk among cancer-free individuals because it can participate in the development of premalignant lesions such as colonic adenomas.59,60 It has been suggested that VEGF levels may be elevated in depression,61 a condition frequently accompanied by poor sleep,62 although there was no association between VEGF and depressive symptoms in this study. Sleep deprivation has been linked with increased circulating concentrations of several inflammation mediators, including TNF-α, IFN-γ, IL-6, and IL-l in humans.7,8,63-66 Results from our study did not support an association between sleep disruption and circulating inflammatory cytokines, although fatigue-related inactivity was linked with increased TNF-α concentrations. TNF-α is an established mediator offatigue,9 10 and therapeutic strategies targeting this cytokine for fatigue reduction are under development.67,68 Reasons for the inconsistencies among the cytokines measured in this study and results from the existing literature may have been due to the inherent variability of the cytokines measured or due to the cross-sectional nature of the study design. However, we used validated instruments, and our psychometric measures were generally consistent with normative data. We were also able to rigorously evaluate and control for numerous potential confounding factors in the analysis. It may be that multiple, severe, and/or prolonged circadian disruption symptoms are needed to elicit immune dysfunction and robust changes in circulating cytokine concentrations. More detailed longitudinal studies with larger samples and quantitative sleep measures, such as actigraphy or polysomnography, would help in clarifying these issues and in characterizing potential thresholds of biological dysfunction and disease risk that may be linked with circadian disruption.

The molecular clock responsible for human circadian rhythm generation consists of 9 core clock genes, and their expression has been characterized in virtually every tissue investigated.2,69-71 Clock genes regulate the timing of DNA repair, apoptosis, and cell proliferation, processes that are hallmarks of carcinogenesis.2,72,73 About 5% to 15% of genome-wide mRNA expression exhibits a circadian rhythm that is driven by the clock genes, including some established tumor suppressor genes and oncogenes.74,75 Mutation or dysregulation of the Period or other clock genes has been associated with increased cancer susceptibility in several animal models as well as in human populations.15,17,18,76-80 The Per3 gene has a polymorphic repeat region with 4 to 5 copies of a 54-bp repetitive sequence in exon 18. This variation results in an insertion/deletion of 18 amino acids, and it has been linked with sleep and mood disorders and circadian preference in humans.19-24 A recent breast cancer study found that the 4/5 or 5/5 Per3 VNTR was more common among premenopausal cases (63%) than controls (49%; odds ratio = 1.7; 95% confidence interval = 1.0-3.0).18 In the present study, individuals with the 4/5 or 5/5 genotype had higher adjusted mean IL-6 cytokine concentrations compared with those with the 4/4 genotype. IL-6 is a pro inflammatory cytokine involved in tumor progression81 that can induce expression of the Perl clock gene.82 Although the function of human Per3 in conjunction with IL-6 is currently not known, results from the present study suggest a need for additional research to determine whether the cancer risks associated with the Per3 VNTR variant may be related to elevated IL-6 or other inflammatory cytokine concentrations.

In summary, chronic inflammation is a known risk factor for cancer, and symptoms of depression, fatigue, and sleep disruption are associated with inflammatory cytokine secretion. However, few studies have attempted to determine whether the association between circadian disruption and cancer is driven by the secretion of inflammatory cytokines. Results from this study suggest that individuals with poor sleep had higher VEGF concentrations compared with good sleepers, participants with greater fatigue-related inactivity had higher TNF-α concentrations, and those with a 4/5 or 5/5 Per3 variant genotype had higher mean IL-6 concentrations compared with referents. The results provide some support for the hypothesis that fatigue, poor sleep, or the Per3 VNTR polymorphism is associated with elevated serum cytokine concentrations. If a link between circadian disruption and inflammation is established, therapeutic strategies targeting improved circadian hygiene may provide a benefit by ameliorating inflammation and reducing cancer risks.


Declaration of Conflicting Interests

The authors declared no conflicts of interest with respect to the authorship and/or publication of this article.


The authors disclosed receipt of the following financial support for the research and/or authorship of this article: This research was supported by the Arnold School of Public Health and Center for Colorectal Cancer Research, University of South Carolina, Columbia, South Carolina. Dr Burch was supported by a Career Development Award from the US Department of Veterans Affairs, VISN-7, Charleston, South Carolina, by the William Jennings Bryan Dorn Department of Veterans Affairs Medical Center, Columbia, South Carolina. Dr. Hébert was supported by an Established Investigator Award in Cancer Prevention and Control from the Cancer Training Branch of the National Cancer Institute (K05 CA136975). Dr Xie was partially supported by Contract No 212-2008-M-24052 from the Biostatistics and Epidemiology Branch of the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, West Virginia.


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