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The relationship between cotinine concentrations and inflammatory markers among highly secondhand smoke exposed non-smoking adolescents
Cytokine 66 (2014) 17–22
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The relationship between cotinine concentrations and inflammatory markers among highly secondhand smoke exposed non-smoking adolescents Yuko Matsunaga a,⇑, Constantine I. Vardavas a,b, Maria Plada b, Julia Wärnberg c,d, Sonia Gómez-Martinez e, Manolis N. Tzatzarakis f, Aristeidis M. Tsatsakis f, Esperanza-Ligia Díaz e, Ascensión Marcos e, Anthony G. Kafatos b a
Center for Global Tobacco Control, Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, USA Department of Social Medicine, University of Crete, Greece c CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Spain d Unit for Nutrition Epidemiology, Department of Preventive Medicine, University of Málaga, Málaga, Spain e Immunonutrition Research Group, Instituto de Ciencia y Tecnología de los alimentos y Nutrición, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain f Centre of Toxicology Science and Research, University of Crete, Greece b
a r t i c l e
i n f o
Article history: Received 14 September 2013 Received in revised form 18 November 2013 Accepted 9 December 2013 Available online 31 December 2013 Keywords: Secondhand smoke exposure Adolescent Inflammatory marker Cotinine HELENA study
a b s t r a c t Background: Secondhand smoke (SHS) exposure is a risk factor of respiratory, cardiovascular and inflammatory diseases, however its association with inflammatory markers among highly SHS exposed adolescents has not yet been explored. Methods: Participants included in this study were a subset of 68 non-smoking adolescents, aged 12.5–17.5 from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study, recruited from Crete Greece. Smoking and SHS exposure was assessed via serum cotinine concentrations. Cytokines (Interleukin-1b, 2, 4, 5 and 6, tumor necrosis factor-a, interferon-c, tumor growth factor-b1), immunoglobulins IgG, IgA, IgM, complement factors C3, C4, high sensitivity C-reactive protein, and endothelial inflammatory markers [soluble E-selectin, soluble L-selectin, soluble intercellular adhesion molecules (sICAM-1) and soluble vascular cell adhesion molecules-1 (sVCAM-1)] were assessed. Inflammatory markers in the lower 25th percentile and upper 75th percentile groups of cotinine levels were compared and multivariate linear regression analysis was performed controlling for age, sex and BMI. Results: Cotinine concentrations were notably elevated (geometric mean 0.82 ng/ml, 95%CI 0.62–1.07) in this study population. A significant decrease in IL-4 (130.09 vs. 25.77 pg/ml, p = 0.014) and IL-6 (19.52 vs. 5.52 pg/ml, p = 0.008) concentrations between the upper 75th percentile cotinine level group and lower 25th percentile cotinine level group was observed. In a multivariate linear regression analysis, cotinine concentrations had a weak inverse association with IL-4 and IL-6 (p = 0.028 and p = 0.06) which was not statistically significant when adjusted for multiple comparisons (modified Bonferroni, p > 0.016). No differences in the other variables was noted. Conclusions: Among highly SHS exposed adolescents, cotinine levels had weak inverse association with IL-4 and IL-6, which did not achieve statistical significance. However, our results potentially indicate an immunosuppressive role of SHS. Further research is warranted to explore this hypothesis. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction The burden of smoking related diseases is substantial and includes conditions associated with both direct and secondhand Abbreviations: SHS, secondhand smoke; HELENA, Healthy Lifestyle in Europe by Nutrition in Adolescence. ⇑ Corresponding author. Address: Center for Global Tobacco Control, Department of Social and Behavioral Sciences, Harvard School of Public Health, 401 Park Drive, Landmark Center, 4th Floor, Boston, MA 02215, USA. Tel.: +1 (617) 9988809. E-mail address: [email protected] (Y. Matsunaga). 1043-4666/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.cyto.2013.12.007
smoke (SHS) exposure [1]. SHS in particular has a considerable impact on health status of exposed children. Previous research has shown a number of detrimental SHS related effects on children such as asthma, infection, cardiovascular effects and increased cancer risk later in life [2]. SHS exposure among young adolescents has also been identified to lead to an impaired endothelial function and suggested to increase the risk of atherosclerosis [3]. Early atherosclerotic processes may be initiated by the activation of circulating inflammatory cells and their migration into the endothelium. Cell adhesion molecules including; E-selectin (expressed on
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endothelial cells), P-selectin (expressed on platelet), L-selectin (expressed on leukocyte), intercellular adhesion molecules (ICAMs) and vascular cell adhesion molecules (VCAM-1) are responsible for cell migration and adhesion to the vascular wall, and are suggested as early markers of atherosclerosis [4]. Thus, these cell adhesion molecules are potent biomarkers for the early detection of atherosclerotic process. It is well acknowledged that inflammatory responses play a pivotal role in the development of chronic obstructive pulmonary disease (COPD) and cardiovascular disease. While the immune response to SHS exposure appears to be altered, the precise nature of the alteration is unclear, as human and animal studies have demonstrated inconsistent and sometimes contradictory results. Following acute SHS exposure for 1 h, Interleukin-5 (IL-5), IL-6 and interferon-c (IFN-c) have been identified to be increased among both genders, while IL-4 and tumor necrosis factor-a (TNF-a) were found to increase only among males [5]. Research on chronic SHS exposure has indicated increased IL-6 concentrations among SHS exposed adults [6]. On the other hand, other studies have reported no elevation in serum IL-6 or other any acute inflammatory cytokine such as IL-1a, IL-1b and TNF-a in SHS exposed populations. [7] [8] [6]. While among 1–6 year-old children exposed to SHS, Wilson et al. showed decreased serum IL-1b, IL-4, IL-5 and IFN-c levels, suggesting an immunosuppressive effect of SHS exposure [9]. These studies indicate equivocal results which may be attributable to different SHS exposure levels, and may be related to SHS exposure in a dose response relationship. Thus, to address the issue, we assessed the relationship between inflammatory markers and cotinine concentrations, among a unique population of highly SHS exposed adolescents.
2. Methods 2.1. Study design and participants This report is based on the Healthy Lifestyle in Europe by Nutrition in Adolescence cross-sectional study (HELENA-CSS) conducted throughout Europe from October 2006 to December 2007 [10]. European adolescents of both sexes aged 12.5 up to 17.5 years were randomly selected centrally, while adolescents were recruited at schools in a city-based sample. Both the selection of schools and adolescents followed a central randomization procedure with both sexes equally distributed over the different grades. In Crete, 400 adolescents were randomly selected and 341 agreed to participate, of which 311 were within the valid age range. Demographic and smoking characteristics of the study participants were collected. All participants were Caucasians. Blood was collected from a random sample of 106 adolescents of the HELENA participants; however, as the cotinine analysis was an ad-hoc analysis, it was only performed on 83 blood samples for which surplus serum was available. Previous analysis between the HELENA-CSS participants from which blood samples were derived and those who did not give a blood sample were investigated into, and revealed no differences between their age category (>15 vs. <15, p = 0.352) nor gender (males vs. females, p = 0.223) [11]. Adolescents were excluded if they had: self-reported symptoms of acute infection within 1 week of recruitment or a white blood cell count greater than or equal to 10.0 103/ll (n = 5); incomplete questionnaires (n = 7); or cotinine levels over 15 ng/ml (the cut-off applied for active smoking) or any self-reported smoking in the past month (n = 11). Furthermore, subjects with cotinine levels below the level of quantification (LOQ) of 0.1 ng/ml were very few (n = 2), therefore also excluded. After applying the above exclusion criteria, complete biochemical, immunological, descriptive, and
toxicological data for 68 non-smoking adolescents from HELENA participants in Heraklion was compiled for analysis. The study was approved by the Research Ethics Committee of the University of Crete, while written informed consent was obtained from the parents of the adolescents and the adolescents themselves [11]. 2.2. SHS exposure Exposure to SHS was measured using serum cotinine levels. Cotinine, the main metabolite of nicotine in the human body, has a half-life of approximately 16–20 h and represents recent exposure to SHS [11]. For cotinine analysis, whole blood was centrifuged and the serum samples were stored at 20 °C until analysis. Cotinine concentrations were determined by gas chromatography–mass spectrometry chromatograms (Shimadzu, Kyoto, Japan). Further detailed cotinine measurement was described elsewhere [11]. 2.3. Blood sampling and laboratory measures Early morning (0800–1000 h) venous blood was drawn from the participants after a 12-h overnight fast. The logistics of the sampling, transportation, methodology and stability of samples during transport and storage have been previously described [10]. White blood cells (WBC) and differential (neutrophils and lymphocytes) were analyzed at local automated cell counter. Serum cytokines IL-1b, IL-4, IL-5, IL-6, IFN-c and TNF-a were determined using the High Sensitivity Human Cytokine MILLIPLEXTM MAP kit (Millipore Corp., Billerica, MA, USA) and collected by flow cytometry (Luminex-100 v.2.3, Luminex Corporation, Austin, TX, USA). C3 and C4 serum complement was analyzed by nephelometry (Behring Diagnostics). The total plasma C3 values in our study represented C3, C3b, and C3c production. Serum adhesion molecule sL-selectin and sE-selectin (g/L) were analyzed using commercial ELISA kits (Diaclone) on the Universal Microplate spectrophotometer (Power WaveTM XS, Biotek Instruments). The sensitivity was 1.0 g/L. Measurement of serum soluble sE-selectin, sVCAM-1, and sICAM-1 (all g/L) was performed with Luminex-100 IS (Integrated System: Luminex) technology by using the multiplex assay kit Linco Human Cardiovascular Disease (CVD) Panel 1 Lincoplex, 96 Well Plate Assay (HCVD1-67AK), manufactured by Linco Research. Multianalyte profiling calibration microspheres for classification and reporter readings, as well as sheath fluid, were also purchased from Luminex Corporation. Acquired fluorescence data were analyzed by the Luminex 2.3 version software. All analyses were performed according to the manufacturer’s protocols. The intra- and inter-assay precision CVs were: 3.5% and 4.5% respectively, for IL-6; and 3.5% and 3.8%, respectively, for TNF-a, 11.2% and 13.4%, respectively, for sE-selectin; 4.5% and 8.5%, respectively, for VCAM-1; and 7.9% and 9.7%, respectively, for ICAM-1, 6.7% and 8.5%, respectively, for TGF-b1. Detection limits (sensitivity) for all the analyses were 0.007 mg/L for CRP, 0.01 g/l for C3, 0.002 g/l for C4, 0.1 pg/ml for IL-6, and 0.05 pg/ml for TNF-a, 79.0 ng/L for sE-selectin, 16.0 ng/L for sVCAM-1, and 9.0 ng/L for sICAM-1. The intra- and inter-assay precision CV were: Serum TGF-b1 levels were measured using commercial ELISA kits (Diaclone) and analyzed by the Universal Microplate spectrophotometer (Power WaveTM XS, Biotek Instruments). All samples were analyzed at Consejo Superior de Investigaciones Cientificas in Madrid. 2.4. Statistical analysis IL-1b, IL-4, IL-5, IL-6, and IFN-c concentrations were the a priori primary interest endpoints. The normality of the distribution of
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cotinine and inflammatory marker levels was examined with the Shapiro–Wilk test and Kolmogorov–Smirnov test, and right skewed data was subsequently log transformed. Continuous variables are presented as geometric mean or mean with 95% confidence interval. During the investigation into the possible correlations between SHS exposure and the immunological response, two-sided Pearson correlations were initially performed, while two-sided t-tests were used to investigate the differences in the indicated variables according to low (lower 25th percentile) vs. high (upper 75th percentile) cotinine levels and thus lower and higher relative exposure. Finally, multivariate linear regression analyses were performed to adjust for BMI, age and sex, all of which may influence inflammatory marker concentrations. A modified Bonferroni adjustment for correlated endpoints was applied and defined a significance level of a = 0.016 [12]. All p-values are based on two-sided tests. The statistical analysis was completed with the statistical package STATA 12.1 (Stata Corp, College Station, TX). 3. Results Table 1 presents the participants’ age, BMI, cotinine and serum inflammatory marker concentrations. A total of 68 adolescents were included in the study; equally 50% (each n = 34) were male and female, while the mean age of the participants was 14.2 years. Geometric mean of cotinine levels (with their 95%CI) was 0.82 (0.62–1.07) ng/ml, with the measured cotinine concentrations found to range between 0.10 ng/ml and 6.92 ng/ml. We assessed if serum cotinine concentrations were correlated with the inflammatory markers as depicted in Table 2. A borderline non-statistical trend for an inverse correlation with log-transformed serum cotinine values and log-transformed IL-4 (correlation coefficient of 0.23, p = 0.056) and IL-6 (correlation coefficient of 0.22,
Table 1 Characteristics of the sample population of highly secondhand smoke exposed, nonsmoker adolescents in Greece. Variables
Nb
Lower limit
Upper limit
Age (years) BMI (kg/m2)a Cotinine (ng/ml)a
68 68 68
14.23 22.77 0.82
14.02 21.96 0.62
14.45 23.61 1.07
Inflammatory markers IL-1b (pg/ml)a IL-2 (pg/ml)a IL-4 (pg/ml)a IL-5 (pg/ml)a IL-6 (pg/ml)a IgG (mg/dl) IgA (mg/dl)a IgM (mg/dl)a C3 (g/l) C4 (g/l) TNF-a (pg/ml)a IFN-c (pg/ml)a TGF-b1 (ng/ml) sICAM-1 (ng/ml)a sVCAM-1 (ng/ml) sE-selectin (ng/ml)a sL-selectin (ng/ml)a hs-CRP (mg/l)a
68 68 68 68 68 65 65 65 65 65 68 68 68 68 68 68 67 63
0.22 1.20 69.51 1.05 11.43 1024.62 126.78 86.28 1.21 0.23 5.58 0.87 113.82 163.36 1378.18 35.89 4625.85 1.00
0.17 0.86 42.82 0.74 7.92 971.74 112.24 75.73 1.17 0.21 4.85 0.49 102.83 144.38 1284.27 31.63 4244.95 0.72
0.29 1.68 112.82 1.50 16.49 1077.49 143.21 98.30 1.25 0.25 6.43 1.53 124.80 184.84 1472.08 40.73 5040.93 1.41
Leukocyte counts (103/ll) WBCa 68 Neutrophilsa 68 Lymphocytes 68
6.63 3.56 2.22
6.32 3.31 2.09
6.95 3.83 2.35
Mean
95% CI
95%CI: 95% confidence interval. a Variables were natural log-transformed and geometric mean is presented. b Numbers differ to the different subsets for which complete data were available.
p = 0.069) was noted. Subsequently within Table 3, we performed a comparison in inflammatory marker concentrations between the lower 25th percentile cotinine group (0.10–0.32 ng/ml cotinine) with those in the upper 75th percentile cotinine group (2.05–6.92 ng/ml cotinine). The analysis indicated that participants in the highest cotinine exposure group had significantly lower IL-4 concentrations (mean 25.77 pg/ml vs. 130.09 pg/ml, p = 0.014) and IL-6 concentrations (mean 5.52 pg/ml vs. 19.52 pg/ml, p = 0.008) in comparison to participants within the lower 25th percentile in cotinine concentrations. Similarly, IL-5 concentrations were found to decrease, however not to a statistically significant level (mean 0.63 vs. 1.62 pg/ml, p = 0.055). When adjusting for the participants’ age, sex and BMI within a multivariate linear regression model (Table 4), a weak inverse association between cotinine levels and IL-4 (b-coefficient 0.50; 95%CI 0.95 to 0.06, p = 0.028) and IL-6 (b-coefficient 0.33; 95%CI 0.67 to 0.01, p = 0.060) concentrations was noted, but the findings were non-significant after applying a modified-Bonferroni adjustment (p > 0.016). Effect modification of cotinine level by BMI and sex to IL-4 and IL-6 was not evident following a stratified analysis. Linear trends were not statistically significant for IL-4 and IL-6 (p = 0.129 and p = 0.137, respectively). Endothelial markers sICAM1, sVCAM-1, sE-selectin and sL-selectin, were not associated with cotinine concentrations within this highly SHS exposed population of adolescents. 4. Discussion In this study, we demonstrated weak inverse association between cotinine levels and serum IL-4/IL-6 among highly SHS exposed adolescents, although statistical significance was not achieved. Despite the weak association, our finding is consistent with our previous report showing an increased percentage of naive CD4+T cell (CD4+CD45RA+) and a decreased percentage of activated CD4+T cells (CD4+CD45RO+) in the blood of SHS exposed
Table 2 Correlations between exposure to secondhand smoke (log cotinine levels) and inflammatory characteristics.
a b c
Variables
Nb
Age (years) BMI (kg/m2)a
68 68
0.23 0.20
0.054 0.101
Inflammatory markers IL-1b (pg/ml)a IL-2 (pg/ml)a IL-4 (pg/ml)a IL-5 (pg/ml)a IL-6 (pg/ml)a IgG (mg/dl) IgA (mg/dl)a IgM (mg/dl)a C3 (g/l) C4 (g/l) TNF-a (pg/ml)a IFN-c (pg/ml)a TGF-b1 (ng/ml) sICAM-1 (ng/ml)a sVCAM-1 (ng/ml) sE-selectin (ng/ml)a sL-selectin (ng/ml)a hs-CRP (mg/l)a
68 68 68 68 68 65 65 65 68 68 68 68 68 68 68 68 67 63
0.08 0.12 0.23 0.16 0.22 0.12 0.20 0.01 0.03 0.12 0.02 0.02 0.08 0.17 0.03 0.13 0.11 0.06
0.510 0.325 0.056 0.202 0.069 0.361 0.107 0.924 0.789 0.363 0.830 0.921 0.820 0.203 0.732 0.294 0.395 0.514
Leukocyte counts (103/ll) WBCa 68 Neutrophilsa 68 Lymphocytes 68
0.11 0.11 0.01
0.379 0.388 0.937
Correlation coefficient
p-Valuec
Variables were natural log-transformed. Numbers differ to the different subsets for which complete data were available. p-Values based on two-sided Pearson correlation tests.
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Table 3 Differences in inflammatory marker concentrations between highest and lowest quartiles of cotinine concentrations. Variables
Lower 25th percentile of cotinine levels (Serum cotinine 0.10–0.32 ng/ml)
Upper 75th percentile of cotinine levels (Serum cotinine 2.05–6.92 ng/ml)
N
Nb
Inflammatory markers 17 IL-1b (pg/ml)a IL-2 (pg/ml)a 17 IL-4 (pg/ml)a 17 IL-5 (pg/ml)a 17 IL-6 (pg/ml)a 17 IgG (mg/dl) 17 a IgA (mg/dl) 17 a IgM (mg/dl) 17 C3 (g/l) 17 C4 (g/l) 17 TNF-a (pg/ml)a 17 IFN-c (pg/ml)a 17 TGF-b1 (ng/ml) 17 a 17 sICAM-1 (ng/ml) sVCAM-1 (ng/ml) 17 sE-selectin (ng/ml)a 17 sL-selectin (ng/ml)a 17 hs-CRP (mg/l)a 17 Leukocyte counts (103/ll) a WBC 17 Neutrophils a 17 Lymphocytes 17
Mean
95%CI Lower limit
Upper limit
0.20 1.29 130.09 1.62 19.52 946.53 107.05 85.87 1.19 0.22 5.37 0.70 115.11 179.24 1453.24 38.67 4213.13 0.88
0.13 0.81 45.40 0.72 9.25 838.04 82.47 69.52 1.12 0.20 4.35 0.20 93.96 152.81 1273.07 31.49 3645.03 0.46
0.30 2.08 372.75 3.67 41.19 1055.02 138.95 106.05 1.26 0.25 6.63 2.39 136.25 210.24 1633.40 47.49 4869.77 1.70
17 17 17 17 17 14 14 14 14 14 17 17 17 17 17 17 16 15
6.39 3.41 2.10
5.89 2.96 1.85
6.93 3.94 2.39
17 17 17
Mean
p-Valuec
95%CI Lower limit
Upper limit
0.17 0.81 25.77 0.63 5.52 1036.43 148.26 86.64 1.19 0.22 5.68 0.47 121.23 150.50 1259.69 32.51 4779.39 1.02
0.11 0.39 11.51 0.35 3.08 932.27 111.45 60.39 1.08 0.18 4.50 0.19 97.90 99.73 980.71 22.34 3854.65 0.49
0.27 1.69 57.72 1.13 9.87 1140.58 197.22 124.32 1.32 0.27 7.17 1.22 144.56 227.12 1618.02 47.31 5925.97 2.11
0.653 0.268 0.014 0.055 0.008 0.218 0.082 0.962 0.818 0.603 0.708 0.598 0.683 0.411 0.608 0.396 0.304 0.762
6.53 3.55 2.14
5.97 3.11 1.85
7.14 4.06 2.42
0.702 0.674 0.876
95%CI: 95% confidence interval. Statistical significant results with modified Bonferroni adjustment (p < 0.016) are shown in bold letters. a Variables were natural log-transformed and geometric mean in lower 25th percentile cotinine group and upper 75th percentile cotinine group is presented. Data presented is not log-transformed. b Numbers differ to the different subsets for which complete data were available. c p-Values based on two-sided student t-test statistics.
adolescents, as activated T cells are the major source of cytokines [13]. Although there is limited information on SHS exposure and T cell immune function, direct smoking and nicotine administration have been shown to alter function of T cells. Various components of cigarette have immunomodulatory properties, while nicotine is thought to be a major immunosuppressant [14] [15]. Smoking and nicotine exposure are reported to impact T cell proliferation. Prior research has shown that T cells from smokers and cigarette-smoke/nicotine treated rodents demonstrate a decreased ability to proliferate in response to T cell receptor-induced stimulation [14] [16]. In contrast, regulatory T cells in lungs are reported to be increased among smokers, particularly non-COPD smokers and mild to moderate COPD patients [17] [15]. To our knowledge, there has been no report regarding the effect of SHS on regulatory T cells. However, if chronic SHS exposure induces the expansion of Tregs with enhanced secretion of IL-10, this might explain the reduction of IL-4 and IL-6 that we observed in SHS exposed adolescents. Further investigation is needed to elucidate the mechanism behind immunomodulation attributable to SHS. Children exposed to SHS are at an increased risk for lower respiratory illnesses [18]. Moreover, SHS exposed children with influenza are known to have an increased risk of intubation, intensive care, and prolonged hospital stay [19]. Nicotine exposure has also been linked to an altered cytokine response to infection. [20]. Using the human derived monocytes, Rehani et al. demonstrated that cotinine may alter the nature of the inflammatory response to gram negative bacteria by affecting PI3 kinase activity to diminish TNF-a, IL-1b, IL-6, IL-12/23, p40 and increase IL-10 production [21]. Notably though, these studies achieve cotinine levels within the 50–100 ng/ml range – concentrations attributable only to active smoking – while the present study suggests that even lower levels of cotinine – those attributable to SHS exposure – are indic-
ative of an immunomodulatory effect that may lead to increased susceptibility to infection in SHS exposed adolescents. The discrepancy in the data across past studies on the cytokine/ SHS relationship could be explained by factors such as duration of exposure, types of cigarette, extent of SHS exposure, age and ethnicity of study population [14]. Chiu et al. reported the effect of SHS on IL-6 and sICAM-1 among workers in the trucking industry in the U.S., detecting no association in either IL-6 or sICAM-1 concentrations among categorized groups of plasma cotinine levels (below LOQ; < 0.02 ng/ml, low cotinine; 0.02–0.11 ng/ml and high cotinine; > 0.11 ng/ml) [7]. However we must note that our population of adolescents had substantially higher levels of exposure to SHS in comparison to adults within the U.S. trucking industry, a point of concern that warrants further research. Specifically, the cotinine concentrations of our study participants were notably 8 times higher than those of non-smoking adults in the aforementioned trucking industry study, a fact that we attribute to elevated population exposure to SHS in Greece. In fact, smoking prevalence in Greece was 41%, one of the highest in the world in 2006 [22]. Reflecting this high smoking prevalence, 89.8% of Greece adolescents were exposed to SHS at home, while 94.1% were exposed to SHS in public places according to the Greek Global Youth Tobacco Survey [11]. In contrast to our findings, Jefferis et al. indicated that IL-6 levels were positively associated with cotinine levels among adult non-smokers [6]. Similarly, acute SHS exposure among adults is reported to increase IL-5, IL-6, IL-4, IFN-c and TNF-a, with gender differences in IL-4 and TNF-a [5]. The reason for such discrepancy between past results and our study is unknown. However, it might be due to differences in population age and/or duration of SHS exposure or that there is a threshold of exposure, which limits the potential nicotine attributable immunosuppressive effect of SHS.
Y. Matsunaga et al. / Cytokine 66 (2014) 17–22 Table 4 Multivariate linear regression analysis assessing the effect of cotinine concentrations on inflammatory marker levels. Variables
b-Coefficient
95%CI Lower limit
Inflammatory markers IL-1b (pg/ml)a IL-2 (pg/ml)a IL-4 (pg/ml)a IL-5 (pg/ml)a IL-6 (pg/ml)a IgG (mg/dl) IgA (mg/dl)a IgM (mg/dl)a C3 (g/l) C4 (g/l) TNF-a (pg/ml)a IFN-c (pg/ml)a TGF-b1 (ng/ml) sICAM-1 (ng/ml)a sVCAM-1 (ng/ml) sE-selectin (ng/ml)a sL-selectin (ng/ml)a hs-CRP (mg/l)a
0.03 0.10 0.50 0.17 0.33 20.45 0.09 0.02 0.01 0.01 0.02 0.04 0.29 0.10 36.61 0.09 0.02 0.02
Leukocyte counts (103/ll) WBC a 0 Neutrophils a 0 Lymphocytes 0.04
p-Value
b
Upper limit
0.26 0.41 0.95 0.50 0.67 31.37 0.02 0.1 0.05 0.01 0.15 0.49 10.95 0.21 123.18 0.21 0.06 0.30
0.21 0.21 0.06 0.16 0.01 72.28 0.21 0.14 0.02 0.02 0.12 0.57 10.34 0.01 49.96 0.03 0.10 0.33
0.826 0.538 0.028 0.307 0.060 0.430 0.116 0.693 0.521 0.499 0.803 0.888 0.955 0.065 0.401 0.123 0.671 0.924
0.04 0.06 0.16
0.04 0.07 0.08
0.974 0.956 0.541
95%CI: 95% confidence interval. a Variables are log-transformed for analysis. b p-Value is obtained by multivariate linear regression analysis comparing logtransformed cotinine concentrations on levels of each markers adjusted for sex, age and log-transformed BMI.
Impaired endothelial function has been previously reported in SHS exposed 11 year-old adolescents, [3] and young adults [23]. In regards to endothelial inflammatory markers, we found no association with cotinine levels. Previous reports have shown an increase in sICAM-1 concentrations in bronchoalveolar lavage fluid obtained from SHS exposed children [24] and an increase in serum or plasma sICAM-1 concentrations in adult smokers [25] [26]. As the adolescents in the current study were mainly highly exposed to SHS, we could not make comparison with non-smoking and no SHS exposed subjects. In this study, we did not detect a difference in serum sICAM-1 among higher and relatively lower SHS exposed adolescents. There are some limitations in our study. First, it is possible that we could not exclude all subjects with infectious disease, atopic disease and asthma among adolescents with the exclusion criteria we applied. Hence the presence of infection or allergic diseases might alter the observed profile of cytokine production. Moreover, because of small sample size (n = 68) and general homogeneity in the exposure to SHS, we did not detect substantial variability in the concentrations of the assessed inflammatory markers. Nevertheless, this study population was rather unique as it assessed the relationship between cotinine concentrations and inflammatory markers using a highly SHS exposed adolescent population.
5. Conclusions Despite the study limitations, our results suggested that IL-4 and IL-6 levels might be reduced in adolescents with high exposure to SHS. For future research, it is necessary to include adolescents with very low or no SHS exposure to compare the population with highly exposed population, so as to assess the dose-response relationship between cotinine levels and inflammatory markers, or threshold of exposure which limits the immunosuppressive effect of SHS.
21
Authors contributions Author Y.M. is responsible for data analysis, manuscript preparation and participated in the current study design. C.I.V. supervised the study, conceived the idea and the organization of the HELENA substudy. M.P. was responsible for data collection and participant organization, J.W., S.G.M., E.L.D. and A.M. performed the laboratory measurement of inflammatory marker and advised for the study design. Authors M.N.T. and A.M.T. performed the cotinine analysis. A.G.K. provided supervision and responsible for the HELENA study at a regional level. All authors contributed to manuscript preparation and have approved its content. Funding This research was co-funded by a Flight Attendant Medical Research Institute award grant for research into SHS exposure (Author C.I.V.) and a European Community Sixth RTD Framework Programme. The HELENA study takes place with the financial support of the European Community Sixth RTD Framework Programme (Contract FOODCT-2005-007034). The content of this article reflects the authors views, and the European community is not liable for any use that may be made of the information contained therein. Acknowledgements We thank Dr. Marcia Testa, Department of Biostatistics Harvard School of Public Health and Dr. Donald Simonson, Brigham and Women’s Hospital/Harvard Medical School for valuable advices on statistical analysis. We are in debt to Dr. Luis Moreno from the University of Zaragoza as the PI of the HELENA proposal. The work performed by author Y.M. within this article took place as part of her practicum within the MPH program of the Harvard School of Public Health. We would like to thank Prof. Gregory Connolly for his support and contributions. References [1] Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2224–60. [2] Treyster Z, Gitterman B. Second hand smoke exposure in children: environmental factors, physiological effects, and interventions within pediatrics. Rev Environ Health 2011;26:187–95. [3] Kallio K, Jokinen E, Raitakari OT, Hamalainen M, Siltala M, Volanen I, et al. Tobacco smoke exposure is associated with attenuated endothelial function in 11-year-old healthy children. Circulation 2007;115:3205–12. [4] Blankenberg S, Barbaux S, Tiret L. Adhesion molecules and atherosclerosis. Atherosclerosis 2003;170:191–203. [5] Flouris AD, Metsios GS, Carrillo AE, Jamurtas AZ, Gourgoulianis K, Kiropoulos T, et al. Acute and short-term effects of secondhand smoke on lung function and cytokine production. Am J Respir Crit Care Med 2009;179:1029–33. [6] Jefferis BJ, Lowe GD, Welsh P, Rumley A, Lawlor DA, Ebrahim S, et al. Secondhand smoke (SHS) exposure is associated with circulating markers of inflammation and endothelial function in adult men and women. Atherosclerosis 2010;208:550–6. [7] Chiu YH, Spiegelman D, Dockery DW, Garshick E, Hammond SK, Smith TJ, et al. Secondhand smoke exposure and inflammatory markers in nonsmokers in the trucking industry. Environ Health Perspect 2011;119:1294–300. [8] Anderson R, Theron AJ, Richards GA, Myer MS, van Rensburg AJ. Passive smoking by humans sensitizes circulating neutrophils. Am Rev Respir Dis 1991;144:570–4. [9] Wilson KM, Wesgate SC, Pier J, Weis E, Love T, Evans K, et al. Secondhand smoke exposure and serum cytokine levels in healthy children. Cytokine 2012;60:34–7. [10] Moreno LA, Gonzalez-Gross M, Kersting M, Molnar D, de Henauw S, Beghin L, et al. Assessing, understanding and modifying nutritional status, eating habits and physical activity in European adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) Study. Public Health Nutr 2008;11:288–99.
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[11] Vardavas CI, Tzatzarakis MN, Plada M, Tsatsakis AM, Papadaki A, Saris WH, et al. Biomarker evaluation of Greek adolescents’ exposure to secondhand smoke. Hum Exp Toxicol 2010;29:459–66. [12] Testa MA, Gill J, Su M, Turner RR, Blonde L, Simonson DC. Comparative effectiveness of basal-bolus versus premix analog insulin on glycemic variability and patient-centered outcomes during insulin intensification in type 1 and type 2 diabetes: a randomized, controlled, crossover trial. J Clin Endocrinol Metab 2012;97:3504–14. [13] Vardavas CI, Plada M, Tzatzarakis M, Marcos A, Warnberg J, GomezMartinez S, et al. Passive smoking alters circulating naive/memory lymphocyte T-cell subpopulations in children. Pediatr Allergy Immunol 2010;21:1171–8. [14] Sopori M. Effects of cigarette smoke on the immune system. Nat Rev Immunol 2002;2:372–7. [15] Cosio MG, Saetta M. Evasion of COPD in smokers: at what price? Eur Respir J 2012;39:1298–303. [16] Kalra R, Singh SP, Savage SM, Finch GL, Sopori ML. Effects of cigarette smoke on immune response: chronic exposure to cigarette smoke impairs antigenmediated signaling in T cells and depletes IP3-sensitive Ca(2+) stores. J Pharmacol Exp Ther 2000;293:166–71. [17] Smyth LJ, Starkey C, Vestbo J, Singh D. CD4-regulatory cells in COPD patients. Chest 2007;132:156–63. [18] Holberg CJ, Wright AL, Martinez FD, Morgan WJ, Taussig LM. Child day care, smoking by caregivers, and lower respiratory tract illness in the first 3 years of life. Group Health Med Assoc Pediatr 1993;91:885–92.
[19] Wilson KM, Pier JC, Wesgate SC, Cohen JM, Blumkin AK. Secondhand tobacco smoke exposure and severity of influenza in hospitalized children. J Pediatr 2013;162:16–21. [20] Wittebole X, Hahm S, Coyle SM, Kumar A, Calvano SE, Lowry SF. Nicotine exposure alters in vivo human responses to endotoxin. Clin Exp Immunol 2007;147:28–34. [21] Rehani K, Scott DA, Renaud D, Hamza H, Williams LR, Wang H, et al. Cotinineinduced convergence of the cholinergic and PI3 kinase-dependent antiinflammatory pathways in innate immune cells. Biochim Biophys Acta 2008;1783:375–82. [22] Filippidis FT, Vardavas CI, Loukopoulou A, Behrakis P, Connolly GN, Tountas Y. Prevalence and determinants of tobacco use among adults in Greece: 4 year trends. Eur J Public Health 2013;23:772–6. [23] Frey PF, Ganz P, Hsue PY, Benowitz NL, Glantz SA, Balmes JR, et al. The exposure-dependent effects of aged secondhand smoke on endothelial function. J Am Coll Cardiol 2012;59:1908–13. [24] Grigg J, Riedler J, Robertson CF. Bronchoalveolar lavage fluid cellularity and soluble intercellular adhesion molecule-1 in children with colds. Pediatr Pulmonol 1999;28:109–16. [25] Fraser HS, Palmer RM, Wilson RF, Coward PY, Scott DA. Elevated systemic concentrations of soluble ICAM-1 (sICAM) are not reflected in the gingival crevicular fluid of smokers with periodontitis. J Dent Res 2001;80:1643–7. [26] Mazzone A, Cusa C, Mazzucchelli I, Vezzoli M, Ottini E, Ghio S, et al. Cigarette smoking and hypertension influence nitric oxide release and plasma levels of adhesion molecules. Clin Chem Lab Med 2001;39:822–6.
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Cytokine journal homepage: www.journals.elsevier.com/cytokine
The relationship between cotinine concentrations and inflammatory markers among highly secondhand smoke exposed non-smoking adolescents Yuko Matsunaga a,⇑, Constantine I. Vardavas a,b, Maria Plada b, Julia Wärnberg c,d, Sonia Gómez-Martinez e, Manolis N. Tzatzarakis f, Aristeidis M. Tsatsakis f, Esperanza-Ligia Díaz e, Ascensión Marcos e, Anthony G. Kafatos b a
Center for Global Tobacco Control, Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, USA Department of Social Medicine, University of Crete, Greece c CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Spain d Unit for Nutrition Epidemiology, Department of Preventive Medicine, University of Málaga, Málaga, Spain e Immunonutrition Research Group, Instituto de Ciencia y Tecnología de los alimentos y Nutrición, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain f Centre of Toxicology Science and Research, University of Crete, Greece b
a r t i c l e
i n f o
Article history: Received 14 September 2013 Received in revised form 18 November 2013 Accepted 9 December 2013 Available online 31 December 2013 Keywords: Secondhand smoke exposure Adolescent Inflammatory marker Cotinine HELENA study
a b s t r a c t Background: Secondhand smoke (SHS) exposure is a risk factor of respiratory, cardiovascular and inflammatory diseases, however its association with inflammatory markers among highly SHS exposed adolescents has not yet been explored. Methods: Participants included in this study were a subset of 68 non-smoking adolescents, aged 12.5–17.5 from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study, recruited from Crete Greece. Smoking and SHS exposure was assessed via serum cotinine concentrations. Cytokines (Interleukin-1b, 2, 4, 5 and 6, tumor necrosis factor-a, interferon-c, tumor growth factor-b1), immunoglobulins IgG, IgA, IgM, complement factors C3, C4, high sensitivity C-reactive protein, and endothelial inflammatory markers [soluble E-selectin, soluble L-selectin, soluble intercellular adhesion molecules (sICAM-1) and soluble vascular cell adhesion molecules-1 (sVCAM-1)] were assessed. Inflammatory markers in the lower 25th percentile and upper 75th percentile groups of cotinine levels were compared and multivariate linear regression analysis was performed controlling for age, sex and BMI. Results: Cotinine concentrations were notably elevated (geometric mean 0.82 ng/ml, 95%CI 0.62–1.07) in this study population. A significant decrease in IL-4 (130.09 vs. 25.77 pg/ml, p = 0.014) and IL-6 (19.52 vs. 5.52 pg/ml, p = 0.008) concentrations between the upper 75th percentile cotinine level group and lower 25th percentile cotinine level group was observed. In a multivariate linear regression analysis, cotinine concentrations had a weak inverse association with IL-4 and IL-6 (p = 0.028 and p = 0.06) which was not statistically significant when adjusted for multiple comparisons (modified Bonferroni, p > 0.016). No differences in the other variables was noted. Conclusions: Among highly SHS exposed adolescents, cotinine levels had weak inverse association with IL-4 and IL-6, which did not achieve statistical significance. However, our results potentially indicate an immunosuppressive role of SHS. Further research is warranted to explore this hypothesis. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction The burden of smoking related diseases is substantial and includes conditions associated with both direct and secondhand Abbreviations: SHS, secondhand smoke; HELENA, Healthy Lifestyle in Europe by Nutrition in Adolescence. ⇑ Corresponding author. Address: Center for Global Tobacco Control, Department of Social and Behavioral Sciences, Harvard School of Public Health, 401 Park Drive, Landmark Center, 4th Floor, Boston, MA 02215, USA. Tel.: +1 (617) 9988809. E-mail address: [email protected] (Y. Matsunaga). 1043-4666/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.cyto.2013.12.007
smoke (SHS) exposure [1]. SHS in particular has a considerable impact on health status of exposed children. Previous research has shown a number of detrimental SHS related effects on children such as asthma, infection, cardiovascular effects and increased cancer risk later in life [2]. SHS exposure among young adolescents has also been identified to lead to an impaired endothelial function and suggested to increase the risk of atherosclerosis [3]. Early atherosclerotic processes may be initiated by the activation of circulating inflammatory cells and their migration into the endothelium. Cell adhesion molecules including; E-selectin (expressed on
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endothelial cells), P-selectin (expressed on platelet), L-selectin (expressed on leukocyte), intercellular adhesion molecules (ICAMs) and vascular cell adhesion molecules (VCAM-1) are responsible for cell migration and adhesion to the vascular wall, and are suggested as early markers of atherosclerosis [4]. Thus, these cell adhesion molecules are potent biomarkers for the early detection of atherosclerotic process. It is well acknowledged that inflammatory responses play a pivotal role in the development of chronic obstructive pulmonary disease (COPD) and cardiovascular disease. While the immune response to SHS exposure appears to be altered, the precise nature of the alteration is unclear, as human and animal studies have demonstrated inconsistent and sometimes contradictory results. Following acute SHS exposure for 1 h, Interleukin-5 (IL-5), IL-6 and interferon-c (IFN-c) have been identified to be increased among both genders, while IL-4 and tumor necrosis factor-a (TNF-a) were found to increase only among males [5]. Research on chronic SHS exposure has indicated increased IL-6 concentrations among SHS exposed adults [6]. On the other hand, other studies have reported no elevation in serum IL-6 or other any acute inflammatory cytokine such as IL-1a, IL-1b and TNF-a in SHS exposed populations. [7] [8] [6]. While among 1–6 year-old children exposed to SHS, Wilson et al. showed decreased serum IL-1b, IL-4, IL-5 and IFN-c levels, suggesting an immunosuppressive effect of SHS exposure [9]. These studies indicate equivocal results which may be attributable to different SHS exposure levels, and may be related to SHS exposure in a dose response relationship. Thus, to address the issue, we assessed the relationship between inflammatory markers and cotinine concentrations, among a unique population of highly SHS exposed adolescents.
2. Methods 2.1. Study design and participants This report is based on the Healthy Lifestyle in Europe by Nutrition in Adolescence cross-sectional study (HELENA-CSS) conducted throughout Europe from October 2006 to December 2007 [10]. European adolescents of both sexes aged 12.5 up to 17.5 years were randomly selected centrally, while adolescents were recruited at schools in a city-based sample. Both the selection of schools and adolescents followed a central randomization procedure with both sexes equally distributed over the different grades. In Crete, 400 adolescents were randomly selected and 341 agreed to participate, of which 311 were within the valid age range. Demographic and smoking characteristics of the study participants were collected. All participants were Caucasians. Blood was collected from a random sample of 106 adolescents of the HELENA participants; however, as the cotinine analysis was an ad-hoc analysis, it was only performed on 83 blood samples for which surplus serum was available. Previous analysis between the HELENA-CSS participants from which blood samples were derived and those who did not give a blood sample were investigated into, and revealed no differences between their age category (>15 vs. <15, p = 0.352) nor gender (males vs. females, p = 0.223) [11]. Adolescents were excluded if they had: self-reported symptoms of acute infection within 1 week of recruitment or a white blood cell count greater than or equal to 10.0 103/ll (n = 5); incomplete questionnaires (n = 7); or cotinine levels over 15 ng/ml (the cut-off applied for active smoking) or any self-reported smoking in the past month (n = 11). Furthermore, subjects with cotinine levels below the level of quantification (LOQ) of 0.1 ng/ml were very few (n = 2), therefore also excluded. After applying the above exclusion criteria, complete biochemical, immunological, descriptive, and
toxicological data for 68 non-smoking adolescents from HELENA participants in Heraklion was compiled for analysis. The study was approved by the Research Ethics Committee of the University of Crete, while written informed consent was obtained from the parents of the adolescents and the adolescents themselves [11]. 2.2. SHS exposure Exposure to SHS was measured using serum cotinine levels. Cotinine, the main metabolite of nicotine in the human body, has a half-life of approximately 16–20 h and represents recent exposure to SHS [11]. For cotinine analysis, whole blood was centrifuged and the serum samples were stored at 20 °C until analysis. Cotinine concentrations were determined by gas chromatography–mass spectrometry chromatograms (Shimadzu, Kyoto, Japan). Further detailed cotinine measurement was described elsewhere [11]. 2.3. Blood sampling and laboratory measures Early morning (0800–1000 h) venous blood was drawn from the participants after a 12-h overnight fast. The logistics of the sampling, transportation, methodology and stability of samples during transport and storage have been previously described [10]. White blood cells (WBC) and differential (neutrophils and lymphocytes) were analyzed at local automated cell counter. Serum cytokines IL-1b, IL-4, IL-5, IL-6, IFN-c and TNF-a were determined using the High Sensitivity Human Cytokine MILLIPLEXTM MAP kit (Millipore Corp., Billerica, MA, USA) and collected by flow cytometry (Luminex-100 v.2.3, Luminex Corporation, Austin, TX, USA). C3 and C4 serum complement was analyzed by nephelometry (Behring Diagnostics). The total plasma C3 values in our study represented C3, C3b, and C3c production. Serum adhesion molecule sL-selectin and sE-selectin (g/L) were analyzed using commercial ELISA kits (Diaclone) on the Universal Microplate spectrophotometer (Power WaveTM XS, Biotek Instruments). The sensitivity was 1.0 g/L. Measurement of serum soluble sE-selectin, sVCAM-1, and sICAM-1 (all g/L) was performed with Luminex-100 IS (Integrated System: Luminex) technology by using the multiplex assay kit Linco Human Cardiovascular Disease (CVD) Panel 1 Lincoplex, 96 Well Plate Assay (HCVD1-67AK), manufactured by Linco Research. Multianalyte profiling calibration microspheres for classification and reporter readings, as well as sheath fluid, were also purchased from Luminex Corporation. Acquired fluorescence data were analyzed by the Luminex 2.3 version software. All analyses were performed according to the manufacturer’s protocols. The intra- and inter-assay precision CVs were: 3.5% and 4.5% respectively, for IL-6; and 3.5% and 3.8%, respectively, for TNF-a, 11.2% and 13.4%, respectively, for sE-selectin; 4.5% and 8.5%, respectively, for VCAM-1; and 7.9% and 9.7%, respectively, for ICAM-1, 6.7% and 8.5%, respectively, for TGF-b1. Detection limits (sensitivity) for all the analyses were 0.007 mg/L for CRP, 0.01 g/l for C3, 0.002 g/l for C4, 0.1 pg/ml for IL-6, and 0.05 pg/ml for TNF-a, 79.0 ng/L for sE-selectin, 16.0 ng/L for sVCAM-1, and 9.0 ng/L for sICAM-1. The intra- and inter-assay precision CV were: Serum TGF-b1 levels were measured using commercial ELISA kits (Diaclone) and analyzed by the Universal Microplate spectrophotometer (Power WaveTM XS, Biotek Instruments). All samples were analyzed at Consejo Superior de Investigaciones Cientificas in Madrid. 2.4. Statistical analysis IL-1b, IL-4, IL-5, IL-6, and IFN-c concentrations were the a priori primary interest endpoints. The normality of the distribution of
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cotinine and inflammatory marker levels was examined with the Shapiro–Wilk test and Kolmogorov–Smirnov test, and right skewed data was subsequently log transformed. Continuous variables are presented as geometric mean or mean with 95% confidence interval. During the investigation into the possible correlations between SHS exposure and the immunological response, two-sided Pearson correlations were initially performed, while two-sided t-tests were used to investigate the differences in the indicated variables according to low (lower 25th percentile) vs. high (upper 75th percentile) cotinine levels and thus lower and higher relative exposure. Finally, multivariate linear regression analyses were performed to adjust for BMI, age and sex, all of which may influence inflammatory marker concentrations. A modified Bonferroni adjustment for correlated endpoints was applied and defined a significance level of a = 0.016 [12]. All p-values are based on two-sided tests. The statistical analysis was completed with the statistical package STATA 12.1 (Stata Corp, College Station, TX). 3. Results Table 1 presents the participants’ age, BMI, cotinine and serum inflammatory marker concentrations. A total of 68 adolescents were included in the study; equally 50% (each n = 34) were male and female, while the mean age of the participants was 14.2 years. Geometric mean of cotinine levels (with their 95%CI) was 0.82 (0.62–1.07) ng/ml, with the measured cotinine concentrations found to range between 0.10 ng/ml and 6.92 ng/ml. We assessed if serum cotinine concentrations were correlated with the inflammatory markers as depicted in Table 2. A borderline non-statistical trend for an inverse correlation with log-transformed serum cotinine values and log-transformed IL-4 (correlation coefficient of 0.23, p = 0.056) and IL-6 (correlation coefficient of 0.22,
Table 1 Characteristics of the sample population of highly secondhand smoke exposed, nonsmoker adolescents in Greece. Variables
Nb
Lower limit
Upper limit
Age (years) BMI (kg/m2)a Cotinine (ng/ml)a
68 68 68
14.23 22.77 0.82
14.02 21.96 0.62
14.45 23.61 1.07
Inflammatory markers IL-1b (pg/ml)a IL-2 (pg/ml)a IL-4 (pg/ml)a IL-5 (pg/ml)a IL-6 (pg/ml)a IgG (mg/dl) IgA (mg/dl)a IgM (mg/dl)a C3 (g/l) C4 (g/l) TNF-a (pg/ml)a IFN-c (pg/ml)a TGF-b1 (ng/ml) sICAM-1 (ng/ml)a sVCAM-1 (ng/ml) sE-selectin (ng/ml)a sL-selectin (ng/ml)a hs-CRP (mg/l)a
68 68 68 68 68 65 65 65 65 65 68 68 68 68 68 68 67 63
0.22 1.20 69.51 1.05 11.43 1024.62 126.78 86.28 1.21 0.23 5.58 0.87 113.82 163.36 1378.18 35.89 4625.85 1.00
0.17 0.86 42.82 0.74 7.92 971.74 112.24 75.73 1.17 0.21 4.85 0.49 102.83 144.38 1284.27 31.63 4244.95 0.72
0.29 1.68 112.82 1.50 16.49 1077.49 143.21 98.30 1.25 0.25 6.43 1.53 124.80 184.84 1472.08 40.73 5040.93 1.41
Leukocyte counts (103/ll) WBCa 68 Neutrophilsa 68 Lymphocytes 68
6.63 3.56 2.22
6.32 3.31 2.09
6.95 3.83 2.35
Mean
95% CI
95%CI: 95% confidence interval. a Variables were natural log-transformed and geometric mean is presented. b Numbers differ to the different subsets for which complete data were available.
p = 0.069) was noted. Subsequently within Table 3, we performed a comparison in inflammatory marker concentrations between the lower 25th percentile cotinine group (0.10–0.32 ng/ml cotinine) with those in the upper 75th percentile cotinine group (2.05–6.92 ng/ml cotinine). The analysis indicated that participants in the highest cotinine exposure group had significantly lower IL-4 concentrations (mean 25.77 pg/ml vs. 130.09 pg/ml, p = 0.014) and IL-6 concentrations (mean 5.52 pg/ml vs. 19.52 pg/ml, p = 0.008) in comparison to participants within the lower 25th percentile in cotinine concentrations. Similarly, IL-5 concentrations were found to decrease, however not to a statistically significant level (mean 0.63 vs. 1.62 pg/ml, p = 0.055). When adjusting for the participants’ age, sex and BMI within a multivariate linear regression model (Table 4), a weak inverse association between cotinine levels and IL-4 (b-coefficient 0.50; 95%CI 0.95 to 0.06, p = 0.028) and IL-6 (b-coefficient 0.33; 95%CI 0.67 to 0.01, p = 0.060) concentrations was noted, but the findings were non-significant after applying a modified-Bonferroni adjustment (p > 0.016). Effect modification of cotinine level by BMI and sex to IL-4 and IL-6 was not evident following a stratified analysis. Linear trends were not statistically significant for IL-4 and IL-6 (p = 0.129 and p = 0.137, respectively). Endothelial markers sICAM1, sVCAM-1, sE-selectin and sL-selectin, were not associated with cotinine concentrations within this highly SHS exposed population of adolescents. 4. Discussion In this study, we demonstrated weak inverse association between cotinine levels and serum IL-4/IL-6 among highly SHS exposed adolescents, although statistical significance was not achieved. Despite the weak association, our finding is consistent with our previous report showing an increased percentage of naive CD4+T cell (CD4+CD45RA+) and a decreased percentage of activated CD4+T cells (CD4+CD45RO+) in the blood of SHS exposed
Table 2 Correlations between exposure to secondhand smoke (log cotinine levels) and inflammatory characteristics.
a b c
Variables
Nb
Age (years) BMI (kg/m2)a
68 68
0.23 0.20
0.054 0.101
Inflammatory markers IL-1b (pg/ml)a IL-2 (pg/ml)a IL-4 (pg/ml)a IL-5 (pg/ml)a IL-6 (pg/ml)a IgG (mg/dl) IgA (mg/dl)a IgM (mg/dl)a C3 (g/l) C4 (g/l) TNF-a (pg/ml)a IFN-c (pg/ml)a TGF-b1 (ng/ml) sICAM-1 (ng/ml)a sVCAM-1 (ng/ml) sE-selectin (ng/ml)a sL-selectin (ng/ml)a hs-CRP (mg/l)a
68 68 68 68 68 65 65 65 68 68 68 68 68 68 68 68 67 63
0.08 0.12 0.23 0.16 0.22 0.12 0.20 0.01 0.03 0.12 0.02 0.02 0.08 0.17 0.03 0.13 0.11 0.06
0.510 0.325 0.056 0.202 0.069 0.361 0.107 0.924 0.789 0.363 0.830 0.921 0.820 0.203 0.732 0.294 0.395 0.514
Leukocyte counts (103/ll) WBCa 68 Neutrophilsa 68 Lymphocytes 68
0.11 0.11 0.01
0.379 0.388 0.937
Correlation coefficient
p-Valuec
Variables were natural log-transformed. Numbers differ to the different subsets for which complete data were available. p-Values based on two-sided Pearson correlation tests.
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Table 3 Differences in inflammatory marker concentrations between highest and lowest quartiles of cotinine concentrations. Variables
Lower 25th percentile of cotinine levels (Serum cotinine 0.10–0.32 ng/ml)
Upper 75th percentile of cotinine levels (Serum cotinine 2.05–6.92 ng/ml)
N
Nb
Inflammatory markers 17 IL-1b (pg/ml)a IL-2 (pg/ml)a 17 IL-4 (pg/ml)a 17 IL-5 (pg/ml)a 17 IL-6 (pg/ml)a 17 IgG (mg/dl) 17 a IgA (mg/dl) 17 a IgM (mg/dl) 17 C3 (g/l) 17 C4 (g/l) 17 TNF-a (pg/ml)a 17 IFN-c (pg/ml)a 17 TGF-b1 (ng/ml) 17 a 17 sICAM-1 (ng/ml) sVCAM-1 (ng/ml) 17 sE-selectin (ng/ml)a 17 sL-selectin (ng/ml)a 17 hs-CRP (mg/l)a 17 Leukocyte counts (103/ll) a WBC 17 Neutrophils a 17 Lymphocytes 17
Mean
95%CI Lower limit
Upper limit
0.20 1.29 130.09 1.62 19.52 946.53 107.05 85.87 1.19 0.22 5.37 0.70 115.11 179.24 1453.24 38.67 4213.13 0.88
0.13 0.81 45.40 0.72 9.25 838.04 82.47 69.52 1.12 0.20 4.35 0.20 93.96 152.81 1273.07 31.49 3645.03 0.46
0.30 2.08 372.75 3.67 41.19 1055.02 138.95 106.05 1.26 0.25 6.63 2.39 136.25 210.24 1633.40 47.49 4869.77 1.70
17 17 17 17 17 14 14 14 14 14 17 17 17 17 17 17 16 15
6.39 3.41 2.10
5.89 2.96 1.85
6.93 3.94 2.39
17 17 17
Mean
p-Valuec
95%CI Lower limit
Upper limit
0.17 0.81 25.77 0.63 5.52 1036.43 148.26 86.64 1.19 0.22 5.68 0.47 121.23 150.50 1259.69 32.51 4779.39 1.02
0.11 0.39 11.51 0.35 3.08 932.27 111.45 60.39 1.08 0.18 4.50 0.19 97.90 99.73 980.71 22.34 3854.65 0.49
0.27 1.69 57.72 1.13 9.87 1140.58 197.22 124.32 1.32 0.27 7.17 1.22 144.56 227.12 1618.02 47.31 5925.97 2.11
0.653 0.268 0.014 0.055 0.008 0.218 0.082 0.962 0.818 0.603 0.708 0.598 0.683 0.411 0.608 0.396 0.304 0.762
6.53 3.55 2.14
5.97 3.11 1.85
7.14 4.06 2.42
0.702 0.674 0.876
95%CI: 95% confidence interval. Statistical significant results with modified Bonferroni adjustment (p < 0.016) are shown in bold letters. a Variables were natural log-transformed and geometric mean in lower 25th percentile cotinine group and upper 75th percentile cotinine group is presented. Data presented is not log-transformed. b Numbers differ to the different subsets for which complete data were available. c p-Values based on two-sided student t-test statistics.
adolescents, as activated T cells are the major source of cytokines [13]. Although there is limited information on SHS exposure and T cell immune function, direct smoking and nicotine administration have been shown to alter function of T cells. Various components of cigarette have immunomodulatory properties, while nicotine is thought to be a major immunosuppressant [14] [15]. Smoking and nicotine exposure are reported to impact T cell proliferation. Prior research has shown that T cells from smokers and cigarette-smoke/nicotine treated rodents demonstrate a decreased ability to proliferate in response to T cell receptor-induced stimulation [14] [16]. In contrast, regulatory T cells in lungs are reported to be increased among smokers, particularly non-COPD smokers and mild to moderate COPD patients [17] [15]. To our knowledge, there has been no report regarding the effect of SHS on regulatory T cells. However, if chronic SHS exposure induces the expansion of Tregs with enhanced secretion of IL-10, this might explain the reduction of IL-4 and IL-6 that we observed in SHS exposed adolescents. Further investigation is needed to elucidate the mechanism behind immunomodulation attributable to SHS. Children exposed to SHS are at an increased risk for lower respiratory illnesses [18]. Moreover, SHS exposed children with influenza are known to have an increased risk of intubation, intensive care, and prolonged hospital stay [19]. Nicotine exposure has also been linked to an altered cytokine response to infection. [20]. Using the human derived monocytes, Rehani et al. demonstrated that cotinine may alter the nature of the inflammatory response to gram negative bacteria by affecting PI3 kinase activity to diminish TNF-a, IL-1b, IL-6, IL-12/23, p40 and increase IL-10 production [21]. Notably though, these studies achieve cotinine levels within the 50–100 ng/ml range – concentrations attributable only to active smoking – while the present study suggests that even lower levels of cotinine – those attributable to SHS exposure – are indic-
ative of an immunomodulatory effect that may lead to increased susceptibility to infection in SHS exposed adolescents. The discrepancy in the data across past studies on the cytokine/ SHS relationship could be explained by factors such as duration of exposure, types of cigarette, extent of SHS exposure, age and ethnicity of study population [14]. Chiu et al. reported the effect of SHS on IL-6 and sICAM-1 among workers in the trucking industry in the U.S., detecting no association in either IL-6 or sICAM-1 concentrations among categorized groups of plasma cotinine levels (below LOQ; < 0.02 ng/ml, low cotinine; 0.02–0.11 ng/ml and high cotinine; > 0.11 ng/ml) [7]. However we must note that our population of adolescents had substantially higher levels of exposure to SHS in comparison to adults within the U.S. trucking industry, a point of concern that warrants further research. Specifically, the cotinine concentrations of our study participants were notably 8 times higher than those of non-smoking adults in the aforementioned trucking industry study, a fact that we attribute to elevated population exposure to SHS in Greece. In fact, smoking prevalence in Greece was 41%, one of the highest in the world in 2006 [22]. Reflecting this high smoking prevalence, 89.8% of Greece adolescents were exposed to SHS at home, while 94.1% were exposed to SHS in public places according to the Greek Global Youth Tobacco Survey [11]. In contrast to our findings, Jefferis et al. indicated that IL-6 levels were positively associated with cotinine levels among adult non-smokers [6]. Similarly, acute SHS exposure among adults is reported to increase IL-5, IL-6, IL-4, IFN-c and TNF-a, with gender differences in IL-4 and TNF-a [5]. The reason for such discrepancy between past results and our study is unknown. However, it might be due to differences in population age and/or duration of SHS exposure or that there is a threshold of exposure, which limits the potential nicotine attributable immunosuppressive effect of SHS.
Y. Matsunaga et al. / Cytokine 66 (2014) 17–22 Table 4 Multivariate linear regression analysis assessing the effect of cotinine concentrations on inflammatory marker levels. Variables
b-Coefficient
95%CI Lower limit
Inflammatory markers IL-1b (pg/ml)a IL-2 (pg/ml)a IL-4 (pg/ml)a IL-5 (pg/ml)a IL-6 (pg/ml)a IgG (mg/dl) IgA (mg/dl)a IgM (mg/dl)a C3 (g/l) C4 (g/l) TNF-a (pg/ml)a IFN-c (pg/ml)a TGF-b1 (ng/ml) sICAM-1 (ng/ml)a sVCAM-1 (ng/ml) sE-selectin (ng/ml)a sL-selectin (ng/ml)a hs-CRP (mg/l)a
0.03 0.10 0.50 0.17 0.33 20.45 0.09 0.02 0.01 0.01 0.02 0.04 0.29 0.10 36.61 0.09 0.02 0.02
Leukocyte counts (103/ll) WBC a 0 Neutrophils a 0 Lymphocytes 0.04
p-Value
b
Upper limit
0.26 0.41 0.95 0.50 0.67 31.37 0.02 0.1 0.05 0.01 0.15 0.49 10.95 0.21 123.18 0.21 0.06 0.30
0.21 0.21 0.06 0.16 0.01 72.28 0.21 0.14 0.02 0.02 0.12 0.57 10.34 0.01 49.96 0.03 0.10 0.33
0.826 0.538 0.028 0.307 0.060 0.430 0.116 0.693 0.521 0.499 0.803 0.888 0.955 0.065 0.401 0.123 0.671 0.924
0.04 0.06 0.16
0.04 0.07 0.08
0.974 0.956 0.541
95%CI: 95% confidence interval. a Variables are log-transformed for analysis. b p-Value is obtained by multivariate linear regression analysis comparing logtransformed cotinine concentrations on levels of each markers adjusted for sex, age and log-transformed BMI.
Impaired endothelial function has been previously reported in SHS exposed 11 year-old adolescents, [3] and young adults [23]. In regards to endothelial inflammatory markers, we found no association with cotinine levels. Previous reports have shown an increase in sICAM-1 concentrations in bronchoalveolar lavage fluid obtained from SHS exposed children [24] and an increase in serum or plasma sICAM-1 concentrations in adult smokers [25] [26]. As the adolescents in the current study were mainly highly exposed to SHS, we could not make comparison with non-smoking and no SHS exposed subjects. In this study, we did not detect a difference in serum sICAM-1 among higher and relatively lower SHS exposed adolescents. There are some limitations in our study. First, it is possible that we could not exclude all subjects with infectious disease, atopic disease and asthma among adolescents with the exclusion criteria we applied. Hence the presence of infection or allergic diseases might alter the observed profile of cytokine production. Moreover, because of small sample size (n = 68) and general homogeneity in the exposure to SHS, we did not detect substantial variability in the concentrations of the assessed inflammatory markers. Nevertheless, this study population was rather unique as it assessed the relationship between cotinine concentrations and inflammatory markers using a highly SHS exposed adolescent population.
5. Conclusions Despite the study limitations, our results suggested that IL-4 and IL-6 levels might be reduced in adolescents with high exposure to SHS. For future research, it is necessary to include adolescents with very low or no SHS exposure to compare the population with highly exposed population, so as to assess the dose-response relationship between cotinine levels and inflammatory markers, or threshold of exposure which limits the immunosuppressive effect of SHS.
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Authors contributions Author Y.M. is responsible for data analysis, manuscript preparation and participated in the current study design. C.I.V. supervised the study, conceived the idea and the organization of the HELENA substudy. M.P. was responsible for data collection and participant organization, J.W., S.G.M., E.L.D. and A.M. performed the laboratory measurement of inflammatory marker and advised for the study design. Authors M.N.T. and A.M.T. performed the cotinine analysis. A.G.K. provided supervision and responsible for the HELENA study at a regional level. All authors contributed to manuscript preparation and have approved its content. Funding This research was co-funded by a Flight Attendant Medical Research Institute award grant for research into SHS exposure (Author C.I.V.) and a European Community Sixth RTD Framework Programme. The HELENA study takes place with the financial support of the European Community Sixth RTD Framework Programme (Contract FOODCT-2005-007034). The content of this article reflects the authors views, and the European community is not liable for any use that may be made of the information contained therein. Acknowledgements We thank Dr. Marcia Testa, Department of Biostatistics Harvard School of Public Health and Dr. Donald Simonson, Brigham and Women’s Hospital/Harvard Medical School for valuable advices on statistical analysis. We are in debt to Dr. Luis Moreno from the University of Zaragoza as the PI of the HELENA proposal. The work performed by author Y.M. within this article took place as part of her practicum within the MPH program of the Harvard School of Public Health. We would like to thank Prof. Gregory Connolly for his support and contributions. References [1] Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2224–60. [2] Treyster Z, Gitterman B. Second hand smoke exposure in children: environmental factors, physiological effects, and interventions within pediatrics. Rev Environ Health 2011;26:187–95. [3] Kallio K, Jokinen E, Raitakari OT, Hamalainen M, Siltala M, Volanen I, et al. Tobacco smoke exposure is associated with attenuated endothelial function in 11-year-old healthy children. Circulation 2007;115:3205–12. [4] Blankenberg S, Barbaux S, Tiret L. Adhesion molecules and atherosclerosis. Atherosclerosis 2003;170:191–203. [5] Flouris AD, Metsios GS, Carrillo AE, Jamurtas AZ, Gourgoulianis K, Kiropoulos T, et al. Acute and short-term effects of secondhand smoke on lung function and cytokine production. Am J Respir Crit Care Med 2009;179:1029–33. [6] Jefferis BJ, Lowe GD, Welsh P, Rumley A, Lawlor DA, Ebrahim S, et al. Secondhand smoke (SHS) exposure is associated with circulating markers of inflammation and endothelial function in adult men and women. Atherosclerosis 2010;208:550–6. [7] Chiu YH, Spiegelman D, Dockery DW, Garshick E, Hammond SK, Smith TJ, et al. Secondhand smoke exposure and inflammatory markers in nonsmokers in the trucking industry. Environ Health Perspect 2011;119:1294–300. [8] Anderson R, Theron AJ, Richards GA, Myer MS, van Rensburg AJ. Passive smoking by humans sensitizes circulating neutrophils. Am Rev Respir Dis 1991;144:570–4. [9] Wilson KM, Wesgate SC, Pier J, Weis E, Love T, Evans K, et al. Secondhand smoke exposure and serum cytokine levels in healthy children. Cytokine 2012;60:34–7. [10] Moreno LA, Gonzalez-Gross M, Kersting M, Molnar D, de Henauw S, Beghin L, et al. Assessing, understanding and modifying nutritional status, eating habits and physical activity in European adolescents: the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescence) Study. Public Health Nutr 2008;11:288–99.
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