Original Article Influence of Per3 genotypes on circadian rhythmicity in flight cadets after militarized management

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Int J Clin Exp Pathol 2014;7(10):6980-6984 www.ijcep.com /ISSN:1936-2625/IJCEP0001157 Original Article Influence of Per3 genotypes on circadian rhythmicity in flight cadets after militarized management Huai-Jie An 1*, Chang-Xi Zhou 3*, Peiliang Geng 4*, Hong-Tao Xu 2, Chenghe Shi 1, Xiao-Hang Zhao 1, Yang-Ming Qian 2 1 Center of Basic Medical Sciences, Navy General Hospital of PLA, Beijing 100037, P. R. China; 2 Department of Medical Administration, Navy General Hospital of PLA, Beijing 100037, P. R. China; 3 Department of Nanlou Respiratory Disease, Chinese PLA General Hospital, Beijing 100853, P. R. China; 4 Cancer Center, Division of Internal Medicine, Chinese PLA General Hospital, Beijing 100853, P. R. China. * Equal contributors. Received June 18, 2014; Accepted July 3, 2014; Epub September 15, 2014; Published October 1, 2014 Abstract: Objective: The purpose of this study was to explore the effect of PERIOD3 (PER3) genotypes on circadian rhythmicity in flight cadets after militarized management. Methods: We performed a preliminary study in 146 newly enrolled male flight cadets. Venous blood samples were collected, and genotyping of PER3 (4/5) was determined by using PCR. The morningness-eveningness questionnaire (MEQ) survey was given to flight cadets upon enrollment and after militarized management for 24 respectively. Comparison of frequency distribution of PER3 genotypes between cases and controls (120 well-matched civilians) was performed using the X 2 test. We also compared the circadian rhythmicity upon enrollment and 24 after enrollment in flight cadets, and analyzed the connection of changes in circadian clock with PER3 genotypes. Results: The frequency distribution of PER3 genotypes in flight cadets was not significantly different from that in controls subjects. MEQ survey results showed chronotype within flight cadet group varied widely at the two time-points: the moderately morning type (50%) and the neither type (41.1%) upon enrollment; the neither type (76.7%) and the moderately morning type (21.2%) 24 after enrollment. The circadian rhythm of individuals with the PER3 (5/5) genotype showed no significant difference before and of militarized management, whereas notable changes were found in individuals with the PER3 (4/4) genotype (n=116, X 2 =37.26, P < 0.001). Conclusion: In conclusion, we provide some evidence that circadian rhythm of flight cadets with the PER3 (5) allele are less likely to be affected compared to those with the PER3 (4) allele. Keywords: Circadian rhythmicity, PER3 gene, flight cadet, militarized management Introduction A prominent circadian rhythm in human is the sleep-wake daily routine [1, 2]. Sleep is reportedly to affect physiological and psychological status such as quality of life [3-5], learning [6], and work [7]. Recent studies have shown that a number of circadian genes play an important role in regulating circadian rhythmicity of the general population [3], including PERIOD3 (PER3), one of the core circadian clock genes. There is a 54-bp non-direct repeat variable number tandem repeat (VNTR) in exon 18 of the primate PER3 gene [8], which harbors four or five copies of tandem repeated 54 bp sequence encoding 18 amino acids. Existing data have shown that the PER3 (5) allele with long VNTRs is associated with morning preferences (morningness), whereas the PER3 (4) allele with short VNTRs is linked to night preferences (eveningness) [3, 9]. Relationship between the PER3 gene and circadian rhythmicity had been studied using subjects at one certain period, thus the results may be biased due to various confounding factors such as long-term unhealthy sleeping habits ascribed to study, work or illness. As yet, there have been no previous reports on circadian rhythmicity via comparisons at different time points. In the present study, we selected a group of newly enrolled flight cadets to investigate the

Table 1. Comparison of the PER3 genotypic frequency in the flight cadets and controls [n (%)] PER3 genotypes Controls X 2 value P value PER3 (4/4) 116 (79.5%) 96 (80.0%) 0.7110 0.70 PER3 (4/5) 27 (18.5%) 23 (19.2%) PER3 (5/5) 3 (2.0%) 1 (0.8%) Total 146 (100%) 120 (100%) Table 2. Distribution of the PER3 allelic frequency in the flight cadets and controls PER3 allele Controls X 2 value P value PER3 (4) 259 (88.7%) 215 (89.6%) 0.1061 0.7446 PER3 (5) 33 (11.3%) 25 (10.4%) Total 292 (100%) 240 (100%) influence of PER3 genotypes on circadian rhythmicity. Materials and methods Subjects This study was approved by the institutional review board (ethics committee of PLA Navy General Hospital). One hundred and forty-six new male flight cadets were recruited. All cases were Han Chinese (mean age 18.8±0.7 years) and had went through a rigorous physical examination and screening for familial disease history before enrollment. The individuals with acute or chronic diseases that might affect sleeping status were excluded. 120 sex-, ageand ethnicity-matched controls were randomly selected from a healthy civilian population who visited our hospital to have a routine physical examination. Patients and control subjects were genetically unrelated and provided written informed consent to participate. Morningness-eveningness questionnaire (MEQ) The HO MEQ comprising 19 physiological clockrelated questions is widely used to identify human circadian rhythms [10]. The survey was conducted at two time points: on enrollment and 24 after enrollment. According to the questionnaire score, the chronotypes of subjects were grouped into 5 categories: definitely morning, moderately morning, neither, moderately evening, and definitely evening. er the following conditions: 10 microl mixture containing 1 PCR Hot Start buffer, 150 ng genomic DNA, 10 pm primers (forward: 5 pm, reverse: 5 pm), 200 mm dntp, 0.025 U/ml of Hotmaster Taq DNA polymorphism (Eppendorf, Italy). The reactions were carried out according to the following protocal: 6 min at 94 C, followed by 35 cycles of 94 C for 40 s, 60 C for 30 s, 70 C for 40 s, with the final step of 70 C for 12 min. The amplified products were analyzed on ethidium bromide stained agarose gel electrophoresis. A 401 bp fragment was amplified by 5 repeat allele. The fragment of 4 repeat allele was 347 bp. The two bands of different sizes could be amplified by heterozygous individuals. Statistical analysis Statistical data were performed using SSPS 16.0 software (StataCorp LP, College Station, TX, USA). Hardy-Weinberg equivalence (HWE) was checked by two-tailed X 2 test, which was also used to detect the frequency difference between groups. P < 0.05 was taken as the significance level. Results Genotyping Blood collection tubes (K 2 EDTA, Cat. 367-861, BD Vacutainer) were obtained from BD (Becton, Dickinson and Company), and Taq PCR MasterMix was obtained from TIANGEN BIOTECH (Cat. KT201). Two millimeters of venous blood was collected, and genomic DNA was extracted using PAXgene Blood DNA Kit. Genotypes for PER3 4/5 repeats were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR- RFLP) as previously described [11]. In brief, PCR amplifications were performed using the primers 5 -TGTCTTTTCATGT- GCCCTTACTT-3 (forward) and 5 -TGT- CTGGCATTGGAGTTTGA-3 (reverse) und- Comparison between PER3 genotypic distribution of the flight cadets and controls As shown in Table 1 and Figure 1, the genotypes of PER3 4/5 repeats between flight cadets [116 homozygous wild type (79.5%), 27 heterozygous mutated (18.5%), and 3 homozygous mutated (2.0%)] and controls [96 homozygous wild type (80.0%), 23 heterozygous mutated (19.2%), and 1 homozygous mutated (0.8%)] 6981 Int J Clin Exp Pathol 2014;7(10):6980-6984

Table 3. Comparison of chronotype in flight cadets at the time of enrollment and 24 after enrollment Sleep type 0 month (number of people (%)) 24 (number of people (%)) Z P value Definitely morning type 12 (8.2%) 0 (0%) 6.6591 <0.0001 Moderately morning type 73 (50.0%) 31 (21.2%) Neither type 60 (41.1%) 112 (76.7%) Moderately evening type 1 (0.7%) 3 (2.1%) Definitely evening type 0 (0.0%) 0 (0%) Total 146 (100%) 146 (100%) Table 4. Distribution of the MEQ scores in flight cadets upon enrollment and 24 after enrollment PER3 genotype MEQ scores of flight cadet MEQ score of flight cadets 24 after enrollment t P value PER3 (4/4) 60.1±7.2 53.9±6.1 14.55 <0.001 PER3 (4/5) 59.6±6.6 51.6±5.1 5.68 <0.001 PER3 (5/5) 50.7±8.0 48.0±8.2 1.91 0.1281 Table 5. PER3 genotypes and chronotype of flight cadets based on the MEQ Type PER3 (4/4) PER3 (4/5) PER3 (5/5) Definitely morning type 9 0 3 0 0 0 Moderately morning type 62 27 10 4 1 0 Neither type 44 87 14 23 2 2 Moderately evening type 1 2 0 0 0 1 Definitely evening type 0 0 0 0 0 0 Total 116 116 27 27 3 3 X 2 value 37.26 7.70 2.0 P value < 0.001 0.016 0.367 were similarly distributed and no significant difference was revealed (Fisher s exact test: X 2 =0.7110, P=0.70, P > 0.05). The observed genotype frequencies in cases and controls were in accord with HWE (P > 0.05). Also, cases were not significantly different from the controls with respect to the allelic distributions (chi-square test: X 2 =0.1061, P=0.7446, P > 0.05) (Table 2). These results showed that genetic background of the flight cadets was comparable to the controls, and this implicated the representiveness of our samples. Comparison of circadian rhythmicity in flight cadets on enrollment and 24 after enrollment The chronotype of flights cadets at the two time points was classified according to the typing method of MEQ (Table 3). We found the circadian rhythmicity in flight cadets at the time of enrollment and 24 after enrollment was significantly different (Wilcoxon Score: Z=6.6591, P < 0.0001), suggesting militarized management may have major effects on chronotype. Analysis of MEQ scores of PER3 genotypes in flight cadets ( and 24 after enrollment) The average MEQ score for individuals who harbored the PER3 (4/4) was the highest with ~10 points difference compared with the individuals with the PER3 (5/5) genotype (Table 4). The score difference was reduced to ~5 points of the militarized management. The MEQ scores of PER3 (5/5) individuals were not significantly different 6982 Int J Clin Exp Pathol 2014;7(10):6980-6984

Figure 1. Identification of the PER3 genotypes in 10 flight cadets. 2.5% Agarose gel electrophoresis of PCR amplification products of the 18th exon of PER3 in 1 TAE buffer. Lanes 1, 6-10 show individuals with homozygous PER3 (4/4), lanes 2-4 show individuals with heterozygous PER3 (4/5), lane 5 is individual with homozygous PER3 (5/5). (t=1.91, P=0.1281) before and after militarized management, suggesting that the chronotype of PER3 (5/5) individuals is stable and resistant to external changes, whereas PER3 (4/4) individuals are prone to be influenced by environmental factors. Analysis of the relationship between chronotype and PER3 genotypes Analysis of chronotype and PER3 genotype distribution in flight cadets uncovered a couple of trends: (1) individuals with PER3 genotypes were mainly definitely morning type, moderately morning type, and neither type (one person and 3 persons were moderately evening type); (2) no individuals were categorized as the definitely evening type (Table 5). Statistical analysis showed significant differences in circadian rhythm associated with the PER3 (4/4) genotype but not the PER3 (4/5) or PER3 (5/5) genotype. The results indicated that the PER3 (4) allele may serve as a circadian rhythm modifier and the PER3 (5) allele maintains circadian rhythm in a stable condition. Discussion ence in circadian rhythmicity between upon enrollment and 24 after enrollment, and this suggested that the chronotype of flight cadets would be altered as environment changes. Seve ral lines of evidence have shown the ability of MEQ to detect chronotype is associated with age. For example, Jones et al. [10] investigated the association of circadian rhythmicity using MEQ with There has been much speculation on the role of PER3 gene in human circadian rhythmicity regulation. Herein, we reported for the first time changes of chronotype in a Han Chinese population comprising 146 flight cadets at different time points. The purpose of our study was to explore the influence of militarized management on chronotype in flight cadets with PER3 4/5 genotypes. We observed significant differ- age and found a significant association, with the youngest age group (18-29 years) having the highest MEQ scores. In this work, we enrolled a group of young subjects (age range 18.8-20.8) and therefore infer that changes in chronotype of flight cadets is associated with militarized management, and life under militarized management constitutes a cause of these changes. The role of PER3 in morningness or eveningness preference remains largely unknown. Although many groups have set out to determine the relation of PER3 and circadian rhythmicity, the previous studies have produced mixed results. Archer et al. [3] investigated the linkage between PER3 and Delayed Sleep Phase Syndrome (DSPS), showing PER3 (4) is linked with eveningness preference. However, the results of a Brazilian study in DSPS patients by Pereira et al. [12] showed a clear association of PER3 (5) with eveningness preference. A circadian rhythm phenotype-related study by Viola et al. [14] showed that the homozygous PER3 (5/5) had significant effects on sleep structure including sleep homeostasis and shorter waiting time before sleep compared with the homozygous PER3 (4/4). In addition, a circadian rhythm phenotype-related study by Viola et al. [14] showed that the homozygous PER3 (5/5) had significant effects on sleep structure including sleep homeostasis and shorter waiting time before sleep compared with the homozygous PER3 (4/4). Conversely, the study by Osland et al. [13] with a fixed 75% power to detect an association of the PER3 (4) with preference for morningness or eveningness suggested no association of the PER3 clock gene and chronotype in a Norway population. In this investigation, we selected a repre- 6983 Int J Clin Exp Pathol 2014;7(10):6980-6984

sentative Han Chinese population, and found no extreme diurnal preference associated with PER3 (4) allele or the PER3 (5) allele. The mixed findings may be caused by sampling variances, study design and different ethnic groups. Therefore, the exact role of PER3 (4/5) genotypes in circadian rhythmicity merits further investigation. In conclusion, our study indicated the PER3 (4) allele, rather than the PER3 (5) allele, represented a potent modifier of circadian rhythmicity. Further well-designed studies are warranted to validate the association between PER3 (4/5) genotypes and chronotype and to identify the population more adaptable to environmental changes. Acknowledgements This work was supported by grants from the China Postdoctoral Science Foundation (2009-0451531), The National High-tech R & D Program (2012AA020206), The Innovation and Engagement Fund (CX201204) of NGH, and Navy Health foundation (CHJ12J025, BHJ09- JD11, AHJ10L002, 11BJZ204, CHJ12L024) of China. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Disclosure of conflict of interest None. Address correspondence to: Dr. Yang-Ming Qian, Department of Medical Administration, Navy General Hospital of PLA, Beijing 100037, P. R. China. Tel: +86-10-66951666; Fax: 86-10-66951666; E-mail: qianyangmingq@163.com References [1] Roenneberg T, Wirz-Justice A, Merrow M. Life between clocks: daily temporal patterns of human chronotypes. J Biol Rhythms 2003; 18: 80-90. [2] Roenneberg T, Kuehnle T, Juda M, Kantermann T, Allebrandt K, Gordijn M, Merrow M. Epidemiology of the human circadian clock. Sleep Med Rev 2007; 11: 429-8. [3] Archer SN, Robilliard DL, Skene DJ, Smits M, Williams A, Arendt J, von Schantz M. A length polymorphism in the circadian clock gene PER3 is linked to delayed sleep phase syndrome and extreme diurnal preference. Sleep 2003; 26: 413-5. [4] Kripke DF, Rex KM, Ancoli-Israel S, Nievergelt CM, Klimecki W and Kelsoe JR. Delayed sleep phase cases and controls. J Circadian Rhythms 2008; 6: 6. [5] Dijk DJ, Archer SN. PERIOD3, circadian phenotypes, and sleep homeostasis. Sleep Med Rev 2010; 14: 151-160. [6] Giannotti F, Cortesi F, Sebastiani T, Ottaviano S. Circadian preference, sleep and daytime behavior in adolescence. J Sleep Res 2002; 11: 191-9. [7] Gamble KL, Motsinger-Reif AA, Hida A, Borsetti HM, Servick SV, Ciarleglio CM, Robbins S, Hicks J, Carver K, Hamilton N, Wells N, Summar ML, McMahon DG, Johnson CH. Shift work in nurses: contribution of phenotypes and genotypes to adaptation. PLoS One 2011; 6: e18-395. [8] Ebisawa T, Uchiyama M, Kajimura N, Mishima K, Kamei Y, Katoh M, Wata-nabe T, Sekimoto M, Shibui K, Kim K, Kudo Y, Ozeki Y, Sugishita M, Toyoshima R, Inoue Y, Yamada N, Nagase T, Ozaki N, Ohara O, Ishida N, Okawa M, Takahashi K, Yamauchi T. Association of structural polymorphisms in the human period3 gene with delayed sleep phase syndrome. EMBO Rep 2001; 2: 342-6. [9] Jones KH, Ellis J, Schantz MV, Skene DJ, Dijk DJ, Archer S. Age-related change in the association between a polymorphism in the PER3 gene and preferred timing of sleep and waking activities. J Sleep Res 2007; 16: 12-6. [10] Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in humam circadian rhythms. Int J Chronobiol 1976; 4: 97-110. [11] Benedetti F, Dallaspezia S, Colombo C, Pirovano A, Marino E, Smeraldi E. A length polymorphism in the circadian clock gene PER3 influences age at onset of bipolar disorder. Neurosci Lett 2008; 445: 184-7. [12] Pereira DS, Tufik S, Louzada FM, Silva AAB, Lopez AR, Lemos NA, Korczak AL, D Almeida V, Pedrazzoli M. Association of the length polymorphism in the human PER3 gene with the delayed sleep-phase syndrome: does latitude have an influence upon it? Sleep 2005; 28: 29-32. [13] Osland TM, Bjorvatn B, Steen VM, Pallesen S. Association study of a variable-number tandem repeat polymorphism in the clock gene PERIOD3 and chronotype in Norwegian university students. Chronobiol Int 2011; 28: 764-70. [14] Viola AU, Archer SN, James LM, Groeger JA, Lo JC, Skene DJ, von Schantz M, Dijk DJ. PER3 polymorphism predicts sleep structure and waking performance. Curr Biol 2007; 3: 613-8. 6984 Int J Clin Exp Pathol 2014;7(10):6980-6984