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Received Date : 15-Dec-2014 Revised Date : 13-Jan-2015 Accepted Date : 15-Jan-2015 Article type : Original Manuscript
Higher Melatonin Secretion is Associated with Lower Leukocyte and Platelet Counts in the General Elderly Population: The HEIJO-KYO Cohort Running title: Melatonin secretion and systemic inflammation Kenji Obayashi,* Keigo Saeki,* and Norio Kurumatani Department of Community Health and Epidemiology (K.O., K.S., N.K.), Nara Medical University School of Medicine, Nara, Japan. *Drs. Obayashi and Saeki contributed equally to this work.
Corresponding author Kenji Obayashi, M.D., Ph.D. 840 Shijocho, Kashiharashi, Nara, 634-8521, Japan, Department of Community Health and Epidemiology Nara Medical University School of Medicine, Nara, Japan E-mail: [email protected] Phone: +81-744-22-3051 Fax: +81-744-25-7657
Keywords: melatonin, systemic inflammation, leukocyte, platelet, anti-oxidative effect
Abstract Circulating white blood cell (WBC) and platelet (PLT) counts are widely available and inexpensive cellular biomarkers of systemic inflammation and have been associated with a risk of cardiovascular disease, cancer, and mortality. Melatonin may reduce systemic This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/jpi.12209 This article is protected by copyright. All rights reserved.
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inflammation through its direct and indirect anti-oxidative effect; however, the associations of melatonin secretion with systemic inflammation remain unclear. In this cross-sectional study on 1,088 elderly individuals (mean age, 71.8 years), we measured overnight urinary 6-sulfatoxymelatonin excretion (UME) and WBC and PLT counts as indices of melatonin secretion and systemic inflammation, respectively. UME was naturally log-transformed for linear regression models because of skewed distribution (median, 6.8 μg; interquartile range, 4.1–10.6 μg). Univariate models revealed that higher log-transformed UME levels were significantly associated with lower WBC and PLT counts (P = 0.046 and 0.018). After adjusting for potential confounding factors significantly associated with WBC or PLT counts, higher log-transformed UME levels were significantly associated with lower WBC and PLT counts (WBC: β, −0.143; 95% confidence interval, −0.267 to −0.020; P = 0.023; PLT: β, −6.839; 95% confidence interval, −12.131 to −1.547; P = 0.011). Furthermore, the adjusted mean differences in WBC and PLT counts between the lowest and highest UME tertile groups were 0.225 × 109/L and 9.118 × 109/L, respectively. In conclusion, melatonin secretion was significantly and inversely associated with WBC and PLT counts in the general elderly population. The associations were independent of several major causes of systemic inflammation, including aging, obesity, smoking, hypertension, diabetes, and physical inactivity.
Introduction Circulating white blood cell (WBC) and platelet (PLT) counts have been recognized as widely available and inexpensive cellular biomarkers of systemic inflammation, which reflects chronic low-grade non-infectious inflammation mainly caused by oxidative stress. Numerous studies have suggested that higher WBC counts predict future cardiovascular events, canceration, and all-cause mortality independently of other risk factors [1–7]. This article is protected by copyright. All rights reserved.
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Moreover, higher PLT count has been reported to be associated with a higher risk of cardiovascular disease and all-cause mortality as well as cancer mortality [8–10].
Endogenous melatonin levels are a biomarker of circadian biological rhythmicity with almost all being produced at night [11]. Melatonin is a potent anti-oxidant, acting directly by free radical-scavenging action and indirectly by alternating sleep, circadian biological rhythmicity, blood pressure (BP), and metabolism [11–18]. In addition, melatonin’s anti-inflammatory actions were documented [19,20]. Previous epidemiological studies have suggested that higher melatonin secretion at levels significantly lower than the pharmacological levels reduces the risk of developing hypertension and type 2 diabetes [21,22]. These findings lead to the hypothesis that higher endogenous melatonin levels are associated with lower systemic inflammation; however, to the best of our knowledge, there are no previous studies, except for one Japanese cross-sectional study [23]. Although the Japanese study suggested that endogenous melatonin levels were significantly associated with biomarkers related to cardiovascular disease, including WBC count, the generalizability of the findings was limited because of the relatively small sample size (n = 181) and the target population of females only.
In this cross-sectional study involving 1,088 community-dwelling elderly males and females, we set out to identify any association of melatonin secretion with WBC and PLT counts. Urinary 6-sulfatoxymelatonin excretion (UME) correlating closely with secreted levels of melatonin, we used UME as an index of melatonin secretion [24].
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Measurement of WBC and PLT Counts Overnight fasting venous blood samples were obtained by two trained physicians at approximately 10:00–11:00 AM. For WBC and PLT counts, blood samples were drawn into ethylenediaminetetraacetic acid containing plastic tubes to stop clotting. WBC and PLT counts were measured at a commercial laboratory (SRL Co. Inc., Tokyo, Japan) in addition to plasma glucose, glycated hemoglobin, and serum creatinine levels.
Other Measurements Body mass index (BMI) was calculated using body weight and height. Current smoking status, drinking habits, and information on medicines were evaluated by having participants completing a questionnaire. Hypertension was defined on the basis of medical history and current anti-hypertensive therapy. Medical history, current anti-diabetic therapy, and blood glucose levels (fasting plasma glucose levels of ≥7.0 mmol/L and glycated hemoglobin levels ≥ 6.5% of the National Glycohemoglobin Standardization Program value) were used to define diabetes mellitus. Estimated glomerular filtration rates (eGFR) were calculated using the formula advocated by the Japanese Society of Nephrology-Chronic Kidney Disease Practice Guide: eGFR (mL/min/1.73 m2) = 194 × [serum creatinine (mg/dL)]−1.094 × [age (years)]−0.287, with the result being multiplied by a correction factor of 0.739 for females. Daytime physical activity was calculated as the average of physical activity counts from getting out of bed in the morning to bedtime in the evening measured at 1-min intervals using an actigraph (Actiwatch 2; Respironics Inc., PA, USA) worn on the non-dominant wrist. Participants were instructed to log their bedtime and rising time for two consecutive days using a standardized sleep diary. Data on day length in Nara (latitude 34°N) from sunrise to sunset on the days of measurement were available at the webpage of the National Astronomical Observatory of Japan.
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Statistical Analyses Variables with a normal distribution were indicated by means ± standard deviation (SD), while asymmetrically distributed variables were given as medians and interquartile ranges (IQRs). With regard to data on circadian rhythm parameters (physical activity, bedtime, duration in bed, and day length), the average of two consecutive days were used for analysis. Association trends of UME tertiles with means, proportions, and medians of variables were analyzed using linear and logistic regression models and the Jonckheere–Terpstra test for trends, respectively. Univariate linear regression models included WBC and PLT counts as dependent variables and UME, age, gender, BMI, current smoking status, alcohol consumption, hypertension, diabetes, eGFR, daytime physical activity, bedtime, duration in bed (scotoperiod), day length (photoperiod) as independent variables. In multivariate linear regression models, model 1 included adjustment for age and gender; model 2 was adjusted for independent variables significantly associated with WBC and PLT counts (P < 0.05), and model 3 was adjusted for all independent variables. PLT data were further adjusted for hematocrit values because plasma volume secondary influences PLT count. No serious multicollinearity was observed (all variance inflation factors < 10) in any of the multivariate models. Statistical analyses were performed using the SPSS version 19.0 for Windows (IBM SPSS Inc., IL, USA). A two-sided P value < 0.05 was considered statistically significant.
Results The mean age of the study participants was 71.8 ± 7.1 (SD) years, and 514 (47.2%) of them were male (Table 1). The median UME was 6.8 μg (IQR, 4.1–10.6), and participants were divided into tertiles groups being either low, intermediate, or high. When compared with the low tertile group of UME (median, 3.1 μg), the high tertile group exhibited four-fold higher UME levels (median, 12.4 μg). Higher UME levels were significantly associated with young age, male gender, high BMI, high alcohol consumption, and less hypertension. This article is protected by copyright. All rights reserved.
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The mean WBC count in the low, intermediate, and high UME groups was 5.43, 5.36, and 5.23 × 109/L, respectively (Table 2). Higher UME levels were significantly associated with lower WBC counts (regression coefficient, −0.121; 95% CI, −0.241 to −0.002; P = 0.046). The mean PLT count in the low, intermediate, and high UME groups was 235.2, 232.6, and 226.9 × 109/L, respectively. Higher UME levels were significantly associated with lower PLT counts (regression coefficient, −6.194; 95% CI, −11.330 to −1.058; P = 0.018).
In addition, variables such as age, gender, BMI, current smoker, hypertension, diabetes, daytime physical activity, and bedtime were significantly associated with WBC count (Table 3); and variables such as age, gender, BMI, habitual alcohol consumption, diabetes, eGFR, daytime physical activity, and duration in bed were significantly associated with PLT count. In multivariate linear regression models after adjusting for confounding factors (Table 4), higher UME levels were significantly associated with lower WBC count (model 1: regression coefficient, −0.140; 95%CI, −0.264 to −0.016; P = 0.027; model 2: regression coefficient, −0.143; 95%CI, −0.267 to −0.020; P = 0.023; model 3: regression coefficient, −0.129; 95%CI, −0.253 to −0.006; P = 0.041). Moreover, higher UME levels were significantly associated with lower PLT count (model 1: regression coefficient, −6.515; 95%CI, −11.713 to −1.318; P = 0.014; model 2: regression coefficient, −6.839; 95%CI, −12.131 to −1.547; P = 0.011; model 3: regression coefficient, −6.672; 95%CI, −11.886 to −1.257; P = 0.015). Furthermore, the adjusted mean differences in WBC and PLT counts between the low and high UME groups were 0.225 × 109/L and 9.118 × 109/L, respectively, in the multivariate regression models adjusted for variables significantly associated with WBC and PLT counts (Table 5).
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Discussion Our results provide, to the best of our knowledge, the first evidence that endogenous melatonin levels are significantly and inversely associated with WBC and PLT counts, which are biomarkers of systemic inflammation, in a large general elderly population. The associations were independent of several major causes of systemic inflammation, including aging, obesity, smoking, hypertension, diabetes, and physical inactivity. Furthermore, significant differences in WBC and PLT counts between the low and high UME groups were quantitatively suggested.
Plausible mechanisms underlying the associations of melatonin with WBC and PLT counts were proposed in previous studies on melatonin’s direct anti-oxidative action and indirect effect mediated by alternating sleep, circadian biological rhythmicity, blood pressure, and metabolism. Melatonin is a potent anti-oxidant and acts by scavenging on a variety of reactive oxygen and reactive nitrogen species at extra- and intra- cellular levels [11–14]. Melatonin stimulates anti-oxidant defense systems through receptors and activates the synthesis of anti-oxidant enzymes including superoxide dismutase [26,27]. Several human experimental studies reported that repeated melatonin administration reduced oxidative stress and also contributed to a decrease in pro-inflammatory cytokines such as tumor necrosis factor alpha and interleukin-6 (IL-6), which are associated with circulating WBC and PLT counts [18,28–32]. In a previous epidemiological study, higher endogenous melatonin levels, considerably lower than the pharmacological levels, were significantly associated with lower levels of IL-6 in elderly females [22].
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Melatonin is essentially related to sleep quality and circadian biological rhythmicity even at endogenous levels [11]. Poor sleep quality and circadian misalignment result in decreased leptin levels, increased ghrelin levels, adverse metabolic consequences, and sympathetic activation, all associated with excessive oxidative stress [15,16,31]. In previous experimental studies, sleep restriction increased WBC counts and IL-6 levels [32]. Moreover, shift work, an exposure causing circadian misalignment, was associated with systemic inflammation such as increased WBC count and IL-6 levels [33]. In addition, melatonin lowers arterial BP by increasing the nitric oxide levels in endothelial cells, which regulate vascular tone and suppresses vascular smooth muscle proliferation [17,27,34]. Lipid metabolism is also reported to be associated with melatonin [18]. Previous epidemiological studies have suggested that higher melatonin secretion reduces the risk of developing hypertension and type 2 diabetes [21,22]. Furthermore, we previously reported that melatonin secretion was significantly and inversely associated with arterial stiffness, an index of atherosclerosis, in addition to BP and diabetes [35–37]. Thus, melatonin may contribute to atheroprotection and improve oxidative capacity, possibly resulting in decreased systemic inflammation. The association between the detected difference in WBC count and cardiovascular events could be interpreted using data in the meta-analysis of 19 prospective studies, including a total of 7,229 cases aged 55 years at a baseline [1]. The meta-analysis indicated that an increase in WBC count from the lowest tertile group (mean, 5.6 × 109/L) to the highest tertile group (mean, 8.4 × 109/L) was significantly associated with a higher risk of coronary heart disease (risk ratio, 1.5; 95% CI, 1.4 to 1.6). In the present study, the 0.225 × 109/L decrease in WBC count in the high UME group (median, 12.4 μg/night) compared with that in the low UME group (median, 3.1 μg/night) was predicted to decrease subsequent coronary heart disease by 4.0% (95% CI, 3.2 to 4.8%). The association between the detected differences in PLT count and all-cause mortality could be interpreted using data from a prospective cohort
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study, including 487 middle-aged males [8]. The study indicated that an increase in PLT count from the lower three quartile groups (median, 211 × 109/L) to the highest quartile group (median, 298 × 109/L) was significantly associated with higher annual all-cause mortality (0.87% vs. 1.53%; P = 0.017). In our study, the 9.118 ×109/L decrease in PLT count in the high UME group compared with the low UME group is predicted to decrease all-cause mortality by 8%. However, the possible underestimation of the associations of UME with WBC and PLT counts may exist because covariates in multivariate models could be intermediators underlying the associations, such as BMI, hypertension, and diabetes. Further epidemiological research with a longitudinal design is required to better understand the associations of UME with WBC and PLT counts. Consistent with previous studies, older age and male gender were associated with lower PLT count in the present study. Previous large-scale studies including more than 10,000 participants indicated a progressive decline in PLT count with aging (38–40). Our result suggested that 10-year aging was associated with a 9.4 × 109/L decline in PLT count, which is almost the same as that in a previous study (39). Gender differences in PLT count was also reported in these studies, where PLT count was higher in females than that in males in all age classes [38–40], which is consistent with our results. Regarding endogenous melatonin levels, UME was significantly associated with age and gender in the present study; however, significant associations of UME with WBC and PLT counts were revealed in multivariate statistical models adjusted for age and gender.
The important strength of the present study is the large sample size from which UME and blood cell counts were measured. This contributes to showing the significant associations
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between UME and blood cell counts in both categorical and continuous data analyses. Several potential limitations of the present study must be considered. The first limitation was the cross-sectional design, which precluded us from ascertaining the causality for the association between UME and blood cell counts. Second, data collection was performed in the colder seasons ranging from September to March, and seasonal changes in the melatonin levels have been reported [41]. However, the inter-seasonal reproducibility of UME from our data was moderately high (ICC = 0.66). To take into account of seasonality, we included day length as a covariate in the final statistical models. Third, we used a non-random sampling method due to the fact that study subjects were recruited by assistance from local resident associations and elderly-resident clubs, which could lead to selection bias. However, the generalizability of our findings may be acceptable considering some of the basic data of the study individuals (e.g., BMI and eGFR) were commensurate with those of the National Health and Nutrition Survey in Japan [42].
In conclusion, endogenous melatonin levels were significantly and inversely associated with WBC and PLT counts, which are widely available and inexpensive cellular biomarkers of systemic inflammation, in this cross-sectional study. The associations were independent of several major causes of systemic inflammation, including aging, obesity, smoking, hypertension, diabetes, and physical inactivity. Although several previous experimental studies have reported that repeated melatonin administration reduced oxidative stress in humans, further longitudinal epidemiological studies are warranted to ascertain the effect of endogenous melatonin levels on systemic inflammation.
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We would like to thank Sachiko Uemura, Naomi Takenaka, Keiko Nakajima, and Nobuhiro Tone for their valuable support during the collection of data
Funding his work was supported by research funding from the Department of Indoor Environmental Medicine, Nara Medical University; Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology; Mitsui Sumitomo Insurance Welfare Foundation; Meiji Yasuda Life Foundation of Health and Welfare; Osaka Gas Group Welfare Foundation; Japan Diabetes Foundation; Daiwa Securities Health Foundation; the Japan Science and Technology Agency; YKK AP Inc.; Nara Prefecture Health Promotion Foundation; and the Special Collaboration Study from Nara Medical University.
Author contributions KO and KS contributed to study concept and design, acquisition of subjects and/or data, analysis and interpretation of data, and preparation of manuscript. NK contributed to acquisition of subjects, analysis and interpretation of data, and preparation of manuscript.
Competing interests None of the authors have any conflicts of interest to declare.
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National
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Received Date : 15-Dec-2014 Revised Date : 13-Jan-2015 Accepted Date : 15-Jan-2015 Article type : Original Manuscript
Higher Melatonin Secretion is Associated with Lower Leukocyte and Platelet Counts in the General Elderly Population: The HEIJO-KYO Cohort Running title: Melatonin secretion and systemic inflammation Kenji Obayashi,* Keigo Saeki,* and Norio Kurumatani Department of Community Health and Epidemiology (K.O., K.S., N.K.), Nara Medical University School of Medicine, Nara, Japan. *Drs. Obayashi and Saeki contributed equally to this work.
Corresponding author Kenji Obayashi, M.D., Ph.D. 840 Shijocho, Kashiharashi, Nara, 634-8521, Japan, Department of Community Health and Epidemiology Nara Medical University School of Medicine, Nara, Japan E-mail: [email protected] Phone: +81-744-22-3051 Fax: +81-744-25-7657
Keywords: melatonin, systemic inflammation, leukocyte, platelet, anti-oxidative effect
Abstract Circulating white blood cell (WBC) and platelet (PLT) counts are widely available and inexpensive cellular biomarkers of systemic inflammation and have been associated with a risk of cardiovascular disease, cancer, and mortality. Melatonin may reduce systemic This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/jpi.12209 This article is protected by copyright. All rights reserved.
Accepted Article
inflammation through its direct and indirect anti-oxidative effect; however, the associations of melatonin secretion with systemic inflammation remain unclear. In this cross-sectional study on 1,088 elderly individuals (mean age, 71.8 years), we measured overnight urinary 6-sulfatoxymelatonin excretion (UME) and WBC and PLT counts as indices of melatonin secretion and systemic inflammation, respectively. UME was naturally log-transformed for linear regression models because of skewed distribution (median, 6.8 μg; interquartile range, 4.1–10.6 μg). Univariate models revealed that higher log-transformed UME levels were significantly associated with lower WBC and PLT counts (P = 0.046 and 0.018). After adjusting for potential confounding factors significantly associated with WBC or PLT counts, higher log-transformed UME levels were significantly associated with lower WBC and PLT counts (WBC: β, −0.143; 95% confidence interval, −0.267 to −0.020; P = 0.023; PLT: β, −6.839; 95% confidence interval, −12.131 to −1.547; P = 0.011). Furthermore, the adjusted mean differences in WBC and PLT counts between the lowest and highest UME tertile groups were 0.225 × 109/L and 9.118 × 109/L, respectively. In conclusion, melatonin secretion was significantly and inversely associated with WBC and PLT counts in the general elderly population. The associations were independent of several major causes of systemic inflammation, including aging, obesity, smoking, hypertension, diabetes, and physical inactivity.
Introduction Circulating white blood cell (WBC) and platelet (PLT) counts have been recognized as widely available and inexpensive cellular biomarkers of systemic inflammation, which reflects chronic low-grade non-infectious inflammation mainly caused by oxidative stress. Numerous studies have suggested that higher WBC counts predict future cardiovascular events, canceration, and all-cause mortality independently of other risk factors [1–7]. This article is protected by copyright. All rights reserved.
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Moreover, higher PLT count has been reported to be associated with a higher risk of cardiovascular disease and all-cause mortality as well as cancer mortality [8–10].
Endogenous melatonin levels are a biomarker of circadian biological rhythmicity with almost all being produced at night [11]. Melatonin is a potent anti-oxidant, acting directly by free radical-scavenging action and indirectly by alternating sleep, circadian biological rhythmicity, blood pressure (BP), and metabolism [11–18]. In addition, melatonin’s anti-inflammatory actions were documented [19,20]. Previous epidemiological studies have suggested that higher melatonin secretion at levels significantly lower than the pharmacological levels reduces the risk of developing hypertension and type 2 diabetes [21,22]. These findings lead to the hypothesis that higher endogenous melatonin levels are associated with lower systemic inflammation; however, to the best of our knowledge, there are no previous studies, except for one Japanese cross-sectional study [23]. Although the Japanese study suggested that endogenous melatonin levels were significantly associated with biomarkers related to cardiovascular disease, including WBC count, the generalizability of the findings was limited because of the relatively small sample size (n = 181) and the target population of females only.
In this cross-sectional study involving 1,088 community-dwelling elderly males and females, we set out to identify any association of melatonin secretion with WBC and PLT counts. Urinary 6-sulfatoxymelatonin excretion (UME) correlating closely with secreted levels of melatonin, we used UME as an index of melatonin secretion [24].
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Measurement of WBC and PLT Counts Overnight fasting venous blood samples were obtained by two trained physicians at approximately 10:00–11:00 AM. For WBC and PLT counts, blood samples were drawn into ethylenediaminetetraacetic acid containing plastic tubes to stop clotting. WBC and PLT counts were measured at a commercial laboratory (SRL Co. Inc., Tokyo, Japan) in addition to plasma glucose, glycated hemoglobin, and serum creatinine levels.
Other Measurements Body mass index (BMI) was calculated using body weight and height. Current smoking status, drinking habits, and information on medicines were evaluated by having participants completing a questionnaire. Hypertension was defined on the basis of medical history and current anti-hypertensive therapy. Medical history, current anti-diabetic therapy, and blood glucose levels (fasting plasma glucose levels of ≥7.0 mmol/L and glycated hemoglobin levels ≥ 6.5% of the National Glycohemoglobin Standardization Program value) were used to define diabetes mellitus. Estimated glomerular filtration rates (eGFR) were calculated using the formula advocated by the Japanese Society of Nephrology-Chronic Kidney Disease Practice Guide: eGFR (mL/min/1.73 m2) = 194 × [serum creatinine (mg/dL)]−1.094 × [age (years)]−0.287, with the result being multiplied by a correction factor of 0.739 for females. Daytime physical activity was calculated as the average of physical activity counts from getting out of bed in the morning to bedtime in the evening measured at 1-min intervals using an actigraph (Actiwatch 2; Respironics Inc., PA, USA) worn on the non-dominant wrist. Participants were instructed to log their bedtime and rising time for two consecutive days using a standardized sleep diary. Data on day length in Nara (latitude 34°N) from sunrise to sunset on the days of measurement were available at the webpage of the National Astronomical Observatory of Japan.
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Statistical Analyses Variables with a normal distribution were indicated by means ± standard deviation (SD), while asymmetrically distributed variables were given as medians and interquartile ranges (IQRs). With regard to data on circadian rhythm parameters (physical activity, bedtime, duration in bed, and day length), the average of two consecutive days were used for analysis. Association trends of UME tertiles with means, proportions, and medians of variables were analyzed using linear and logistic regression models and the Jonckheere–Terpstra test for trends, respectively. Univariate linear regression models included WBC and PLT counts as dependent variables and UME, age, gender, BMI, current smoking status, alcohol consumption, hypertension, diabetes, eGFR, daytime physical activity, bedtime, duration in bed (scotoperiod), day length (photoperiod) as independent variables. In multivariate linear regression models, model 1 included adjustment for age and gender; model 2 was adjusted for independent variables significantly associated with WBC and PLT counts (P < 0.05), and model 3 was adjusted for all independent variables. PLT data were further adjusted for hematocrit values because plasma volume secondary influences PLT count. No serious multicollinearity was observed (all variance inflation factors < 10) in any of the multivariate models. Statistical analyses were performed using the SPSS version 19.0 for Windows (IBM SPSS Inc., IL, USA). A two-sided P value < 0.05 was considered statistically significant.
Results The mean age of the study participants was 71.8 ± 7.1 (SD) years, and 514 (47.2%) of them were male (Table 1). The median UME was 6.8 μg (IQR, 4.1–10.6), and participants were divided into tertiles groups being either low, intermediate, or high. When compared with the low tertile group of UME (median, 3.1 μg), the high tertile group exhibited four-fold higher UME levels (median, 12.4 μg). Higher UME levels were significantly associated with young age, male gender, high BMI, high alcohol consumption, and less hypertension. This article is protected by copyright. All rights reserved.
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The mean WBC count in the low, intermediate, and high UME groups was 5.43, 5.36, and 5.23 × 109/L, respectively (Table 2). Higher UME levels were significantly associated with lower WBC counts (regression coefficient, −0.121; 95% CI, −0.241 to −0.002; P = 0.046). The mean PLT count in the low, intermediate, and high UME groups was 235.2, 232.6, and 226.9 × 109/L, respectively. Higher UME levels were significantly associated with lower PLT counts (regression coefficient, −6.194; 95% CI, −11.330 to −1.058; P = 0.018).
In addition, variables such as age, gender, BMI, current smoker, hypertension, diabetes, daytime physical activity, and bedtime were significantly associated with WBC count (Table 3); and variables such as age, gender, BMI, habitual alcohol consumption, diabetes, eGFR, daytime physical activity, and duration in bed were significantly associated with PLT count. In multivariate linear regression models after adjusting for confounding factors (Table 4), higher UME levels were significantly associated with lower WBC count (model 1: regression coefficient, −0.140; 95%CI, −0.264 to −0.016; P = 0.027; model 2: regression coefficient, −0.143; 95%CI, −0.267 to −0.020; P = 0.023; model 3: regression coefficient, −0.129; 95%CI, −0.253 to −0.006; P = 0.041). Moreover, higher UME levels were significantly associated with lower PLT count (model 1: regression coefficient, −6.515; 95%CI, −11.713 to −1.318; P = 0.014; model 2: regression coefficient, −6.839; 95%CI, −12.131 to −1.547; P = 0.011; model 3: regression coefficient, −6.672; 95%CI, −11.886 to −1.257; P = 0.015). Furthermore, the adjusted mean differences in WBC and PLT counts between the low and high UME groups were 0.225 × 109/L and 9.118 × 109/L, respectively, in the multivariate regression models adjusted for variables significantly associated with WBC and PLT counts (Table 5).
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Discussion Our results provide, to the best of our knowledge, the first evidence that endogenous melatonin levels are significantly and inversely associated with WBC and PLT counts, which are biomarkers of systemic inflammation, in a large general elderly population. The associations were independent of several major causes of systemic inflammation, including aging, obesity, smoking, hypertension, diabetes, and physical inactivity. Furthermore, significant differences in WBC and PLT counts between the low and high UME groups were quantitatively suggested.
Plausible mechanisms underlying the associations of melatonin with WBC and PLT counts were proposed in previous studies on melatonin’s direct anti-oxidative action and indirect effect mediated by alternating sleep, circadian biological rhythmicity, blood pressure, and metabolism. Melatonin is a potent anti-oxidant and acts by scavenging on a variety of reactive oxygen and reactive nitrogen species at extra- and intra- cellular levels [11–14]. Melatonin stimulates anti-oxidant defense systems through receptors and activates the synthesis of anti-oxidant enzymes including superoxide dismutase [26,27]. Several human experimental studies reported that repeated melatonin administration reduced oxidative stress and also contributed to a decrease in pro-inflammatory cytokines such as tumor necrosis factor alpha and interleukin-6 (IL-6), which are associated with circulating WBC and PLT counts [18,28–32]. In a previous epidemiological study, higher endogenous melatonin levels, considerably lower than the pharmacological levels, were significantly associated with lower levels of IL-6 in elderly females [22].
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Melatonin is essentially related to sleep quality and circadian biological rhythmicity even at endogenous levels [11]. Poor sleep quality and circadian misalignment result in decreased leptin levels, increased ghrelin levels, adverse metabolic consequences, and sympathetic activation, all associated with excessive oxidative stress [15,16,31]. In previous experimental studies, sleep restriction increased WBC counts and IL-6 levels [32]. Moreover, shift work, an exposure causing circadian misalignment, was associated with systemic inflammation such as increased WBC count and IL-6 levels [33]. In addition, melatonin lowers arterial BP by increasing the nitric oxide levels in endothelial cells, which regulate vascular tone and suppresses vascular smooth muscle proliferation [17,27,34]. Lipid metabolism is also reported to be associated with melatonin [18]. Previous epidemiological studies have suggested that higher melatonin secretion reduces the risk of developing hypertension and type 2 diabetes [21,22]. Furthermore, we previously reported that melatonin secretion was significantly and inversely associated with arterial stiffness, an index of atherosclerosis, in addition to BP and diabetes [35–37]. Thus, melatonin may contribute to atheroprotection and improve oxidative capacity, possibly resulting in decreased systemic inflammation. The association between the detected difference in WBC count and cardiovascular events could be interpreted using data in the meta-analysis of 19 prospective studies, including a total of 7,229 cases aged 55 years at a baseline [1]. The meta-analysis indicated that an increase in WBC count from the lowest tertile group (mean, 5.6 × 109/L) to the highest tertile group (mean, 8.4 × 109/L) was significantly associated with a higher risk of coronary heart disease (risk ratio, 1.5; 95% CI, 1.4 to 1.6). In the present study, the 0.225 × 109/L decrease in WBC count in the high UME group (median, 12.4 μg/night) compared with that in the low UME group (median, 3.1 μg/night) was predicted to decrease subsequent coronary heart disease by 4.0% (95% CI, 3.2 to 4.8%). The association between the detected differences in PLT count and all-cause mortality could be interpreted using data from a prospective cohort
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study, including 487 middle-aged males [8]. The study indicated that an increase in PLT count from the lower three quartile groups (median, 211 × 109/L) to the highest quartile group (median, 298 × 109/L) was significantly associated with higher annual all-cause mortality (0.87% vs. 1.53%; P = 0.017). In our study, the 9.118 ×109/L decrease in PLT count in the high UME group compared with the low UME group is predicted to decrease all-cause mortality by 8%. However, the possible underestimation of the associations of UME with WBC and PLT counts may exist because covariates in multivariate models could be intermediators underlying the associations, such as BMI, hypertension, and diabetes. Further epidemiological research with a longitudinal design is required to better understand the associations of UME with WBC and PLT counts. Consistent with previous studies, older age and male gender were associated with lower PLT count in the present study. Previous large-scale studies including more than 10,000 participants indicated a progressive decline in PLT count with aging (38–40). Our result suggested that 10-year aging was associated with a 9.4 × 109/L decline in PLT count, which is almost the same as that in a previous study (39). Gender differences in PLT count was also reported in these studies, where PLT count was higher in females than that in males in all age classes [38–40], which is consistent with our results. Regarding endogenous melatonin levels, UME was significantly associated with age and gender in the present study; however, significant associations of UME with WBC and PLT counts were revealed in multivariate statistical models adjusted for age and gender.
The important strength of the present study is the large sample size from which UME and blood cell counts were measured. This contributes to showing the significant associations
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between UME and blood cell counts in both categorical and continuous data analyses. Several potential limitations of the present study must be considered. The first limitation was the cross-sectional design, which precluded us from ascertaining the causality for the association between UME and blood cell counts. Second, data collection was performed in the colder seasons ranging from September to March, and seasonal changes in the melatonin levels have been reported [41]. However, the inter-seasonal reproducibility of UME from our data was moderately high (ICC = 0.66). To take into account of seasonality, we included day length as a covariate in the final statistical models. Third, we used a non-random sampling method due to the fact that study subjects were recruited by assistance from local resident associations and elderly-resident clubs, which could lead to selection bias. However, the generalizability of our findings may be acceptable considering some of the basic data of the study individuals (e.g., BMI and eGFR) were commensurate with those of the National Health and Nutrition Survey in Japan [42].
In conclusion, endogenous melatonin levels were significantly and inversely associated with WBC and PLT counts, which are widely available and inexpensive cellular biomarkers of systemic inflammation, in this cross-sectional study. The associations were independent of several major causes of systemic inflammation, including aging, obesity, smoking, hypertension, diabetes, and physical inactivity. Although several previous experimental studies have reported that repeated melatonin administration reduced oxidative stress in humans, further longitudinal epidemiological studies are warranted to ascertain the effect of endogenous melatonin levels on systemic inflammation.
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We would like to thank Sachiko Uemura, Naomi Takenaka, Keiko Nakajima, and Nobuhiro Tone for their valuable support during the collection of data
Funding his work was supported by research funding from the Department of Indoor Environmental Medicine, Nara Medical University; Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology; Mitsui Sumitomo Insurance Welfare Foundation; Meiji Yasuda Life Foundation of Health and Welfare; Osaka Gas Group Welfare Foundation; Japan Diabetes Foundation; Daiwa Securities Health Foundation; the Japan Science and Technology Agency; YKK AP Inc.; Nara Prefecture Health Promotion Foundation; and the Special Collaboration Study from Nara Medical University.
Author contributions KO and KS contributed to study concept and design, acquisition of subjects and/or data, analysis and interpretation of data, and preparation of manuscript. NK contributed to acquisition of subjects, analysis and interpretation of data, and preparation of manuscript.
Competing interests None of the authors have any conflicts of interest to declare.
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The
National
Health
and
Nutrition
Survey
Japan
2010;
available
at:
http://www.mhlw.go.jp/bunya/kenkou/eiyou/h22-houkoku.html (Japanese; accessed on December 1, 2014).
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