CC BY-NC-ND
0Egyptian Journal of Chest Diseases and Tuberculosis (2014) 63, 87-97
The Egyptian Society of Chest Diseases and Tuberculosis Egyptian Journal of Chest Diseases and Tuberculosis
www.elsevier.com/locate/ejcdt www.sciencedirect.com
ORIGINAL ARTICLE
The relation between the blood osteopontin levels and body fat percentage in asthmatic women
Enas E. Mohamed a *, Doaa M. Samy b, Nesrine M. El Azhary b, Hanan M. Nomeir c
a Chest Diseases Department, Faculty of Medicine, Alexandria University, Egypt b Physiology Department, Faculty of Medicine, Alexandria University, Egypt
c Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Alexandria University, Egypt
Received 6 September 2013; accepted 10 October 2013 Available online 30 October 2013
KEYWORDS
Obesity; Osteopontin; Body fat percentage; Immunoglobulin E
Abstract Introduction: Obesity and asthma prevalence have been increasing over the past decade. Osteopontin (OPN) is a cytokine, with suggested diverse roles in tissue remodeling, fibrosis, immunomodulation, inflammation, and tumor metastasis.
Aim of the work: To assess the relation between serum osteopontin, immunoglobulin E (IgE) and body fat percentage in obese and non-obese asthmatic women in addition, to determine whether correlations exist between these parameters and asthma control.
Patients and methods: This study was conducted on 40 women after taking informed written consents. They were divided into 4 groups (10 each): healthy non-obese non-asthmatic (NO/NA), obese non-asthmatic (O/NA), non-obese asthmatic (NO/A) and obese asthmatic (O/A). All were subjected to full history taking, spirometry to non-asthmatic, asthma control questionnaire (ACQ) to asthmatic, determination of body fat percentage and serum levels of osteopontin and IgE.
Results: Body fat percentage was positively correlated to serum OPN levels. Body fat percentage was positively correlated to concentrations of IgE. In addition, the correlation between serum OPN levels and serum IgE levels was significantly positive. The improvement (presented by difference between ACQ before and after treatment (D ACQ)) was significantly superior in non-obese asthmatic. A negative correlation was detected between D ACQ and body fat percentage, serum OPN and IgE concentration.
* Corresponding author. Tel.: +20 01224474317. E-mail address: enas_elsayed73@yahoo.com (E.E. Mohamed). q Peer review under responsibility of The Egyptian Society of Chest Diseases and Tuberculosis.
0422-7638 © 2013 The Egyptian Society of Chest Diseases and Tuberculosis. Production and hosting by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ejcdt.2013.10.010
In conclusion: Because the multiple roles of OPN action potentially contribute to inflammation in obesity, it is suggested that, in addition to weight reduction, interference with OPN action could become a therapeutic strategy in the treatment of obesity worsening disorders like bronchial asthma.
© 2013 The Egyptian Society of Chest Diseases and Tuberculosis. Production and hosting by Elsevier
B.V. All rights reserved.
Introduction
Asthma is characterized by eosinophilic inflammation of the conducting airways, and is regarded as a typical type-2 T-helper cell (Th2) associated allergic disease [1]. Airway inflammation in asthma is a multicellular process that is associated with structural alterations of the airway components, a process known as airway remodeling. The prominent role of airway inflammation and remodeling in the pathogenesis and clinical presentation of asthma has led to the current focus on mediators potentially involved in both processes [2].
Obesity and asthma prevalence have been increasing over the past decade. Several studies have identified an association between obesity and asthma and demonstrated that obesity results in an increased risk of developing bronchial asthma. Even modest levels of increased weight increase asthma risk. Moreover, obese asthmatic patients demonstrate increased asthma severity, as indicated by increased exacerbations and worse asthma control [3-5]. Most of these studies restricted their measurement of excess body weight to body mass index (BMI); however, other measures, such as total body fat or body fat percentage are more precise in order to determine the relative importance of obesity in the pathophysiology of bronchial asthma. It has been suggested that the association between obesity and asthma prevalence is stronger in women than men. A cross-sectional study found that a one-unit increase of BMI was associated with a 6% increase in asthma risk in women and 3% increase in men [6].
Published data suggest that obese asthma patients may represent a distinct phenotype of asthma [7,8]. Obese asthma patients demonstrate increased asthma severity, as indicated by increased exacerbations and decreased responses to conventional asthma therapies, specifically, relative corticosteroid resistance [9]. Small studies suggest improvements in the disease with weight loss in obese asthma patients. It is possible that altered lung mechanics associated with obesity could increase severity and worsen asthma control [10]. However, it is unclear and controversial whether the effects of obesity on asthma are mechanically mediated through restrictive effects on chest wall expansion or mediated through other mechanisms that are specific to the obese state. These suggested mechanisms include: (1) the presence of co morbidities, such as gastroesophageal reflux disease and sleep disordered breathing, (2) systemic and/or airway inflammation associated with obesity (with elevated levels of circulating inflammatory cytokines, such as interleukin-6 (IL-6) and tumor necrosis factor-a (TNF-a), and (3) increased oxidative stress in obesity [8].
Multiple studies investigated the relationship between serum levels ofhormones related to adipose tissue, such as adiponectin, leptin, and resistin and bronchial asthma. Although the data are sometimes conflicting, it seems that these adipocytokines may modulate airway inflammation and bronchial hyperreactivity.
However, the relationship between serum levels of leptin/adipo-nectin and the presence of asthma is not sufficient to explain the relationship between asthma and obesity [11,12].
Osteopontin (OPN) is a cytokine, with suggested diverse roles in tissue remodeling, fibrosis, immunomodulation, inflammation, and tumor metastasis. It was originally described as a structural component of the extracellular matrix having the ability to bind to proteins and most types of collagen [13]. Although OPN is synthesized at the highest levels in the bone, it is produced by most cells of the immune system, including T-cells, B-cells, macrophages, neutrophils, eosino-phils, natural killer cells and mast cells, as well as structural cells, including fibroblasts and smooth muscle and epithelial cells. In humans, increased OPN expression has been observed in a number of type-1 T-helper cells (Th1)-mediated lung diseases, including granulomatous diseases and pulmonary fibro-sis [14]. There is now, also, emerging evidence to support an active role for OPN in type-2 T-helper cell (Th2)-linked inflammation and remodeling. OPN expression is upregulated in nasal tissue samples taken from asthmatic patients with chronic rhinosinusitis, and in the tear fluids of patients with allergic ocular diseases [15,16]. It has previously been demonstrated that OPN plays a crucial role in allergic airway inflammation [17-19]. Endobronchial biopsies from asthmatic individuals have shown increased osteopontin expression in bronchial epithelial cells and subepithelial inflammatory cells suggesting that eosinophils may be a cellular source of OPN [20]. Moreover, OPN is expressed in peripheral blood eosino-phils of atopic human subjects, and acts as a chemoattractant for eosinophils in vitro [17,18]. It also may participate in the regulation of serum immunoglobulin E (IgE) levels in both asthmatic and non-asthmatic subjects [20].
Experimental studies on murine animal models of allergic airway disease demonstrated that OPN levels are increased in allergen-induced chronic airway remodeling, whereas, oste-opontin deficiency, either through administration of blocking antibody or genetic deficiency, is protective against airway hyper-responsiveness (AHR) and airway remodeling [21,22].
Gomez-Ambrosi and his co-workers found that, plasma OPN levels and OPN expression in omental adipose tissue are increased in obese patients with high values of body fat percentage. It was suggested that measurement of OPN might be useful for evaluating the outcomes of obesity-related cardiovascular diseases [23].
Aim of the work
The aim of this study was to assess the relation between serum osteopontin, IgE levels and body fat percentage in obese and non-obese asthmatic women in addition, to determine whether correlations exist between these parameters and asthma control in these patients.
Patients and methods
After approval of the Ethics Committee of the Faculty of Medicine, Alexandria University, this study was conducted on 40 women, non-smokers, whose ages ranged between 20 and 40 years without co-morbidities that could potentially interfere with the study or other pulmonary diseases. Informed and written consents were obtained from all participating subjects. All asthmatic patients were recruited from the inpatients of Chest Diseases Department, Alexandria Main University Hospital. The study population were divided into 4 groups (10 each): healthy non-obese non-asthmatic women (NO/NA), obese non-asthmatic women (O/NA), non-obese asthmatic women (NO/A) and obese asthmatic women (O/A). All subjects were subjected to the following
• Full history taking including: age and history of other diseases.
• Thorough clinical examination including: general examination and local chest examination.
• Spirometry, all non-asthmatic women underwent standard spirometry. Techniques were carried out according to the American Thoracic Society/European Respiratory Society standards [24].
• Asthma control was assessed using the asthma control questionnaire (ACQ) [25]. It was applied to asthmatic obese and non-obese groups at the onset of hospital admission and after 2 weeks of treatment. Briefly, ACQ comprises of seven items; the patient completes six. The items quantify the extent of five symptom measures: nighttime awakenings, symptom severity upon awakening, activity limitation due to asthma, and shortness of breath due to asthma and wheezing within the past week, each rated on a 7-point scale, where 0 represents no symptoms or limitations, and 6 indicates severe symptoms or impairment. The sixth patient-reported item counts the past week's use of a short acting b-agonist (SABA), where 0 represents "None" and 6 represents "More than 16 puffs most days.'' The seventh item is the clinician-assessed FEV1 percentage predicted scored using a 7-point scale, where 0 represents ">95% predicted'' and 6 represents ''<50% predicted''. The overall score is the mean of the item responses and ranges from 0 (totally controlled) to 6 (severely uncontrolled). Scores below 1 represents well controlled asthma and scores above 1.5 indicates poorly controlled asthma.
• Determination of body fat percentage was performed by bioelectric impedance using Inbody-220 (Biospace, South Korea, 2005). The analysis was done under standardized conditions: after 8 h of fasting, no intense physical exercise in the previous 12 h, and absence of menstrual cycle 2 days before and after testing. According to Gallagher et al.'s results, adult females with body fat percentage between 21% and <33% were considered healthy, and those with body fat percentage P33 were considered obese [26].
• Under complete sterile conditions, five-milliliters of venous blood were withdrawn from every participant. Every sample was transferred into a disposable plastic tube and left to coagulate at room temperature for 10-20 min then cen-trifuged for 20 min at the speed of 5000 r.p.m. to separate the serum. The sera were stored in aliquots at —20 0C until measurement of osteopontin and IgE.
Estimation of serum osteopontin (OPN) level by ELISA technique
The commercial kit used was WKEA MED SUPPLIES CORP USA Address: 450 11TH AVE, NEW YORK, NY 10123. Briefly, standards and samples were pipetted into the wells and OPN present in a sample was bound to the wells by the immobilized antibody. The wells were washed and biotinylated anti-human OPN antibody was added. After washing away unbound biotinylated antibody, horseradish peroxidase (HRP)-conjugated streptavidin was pipetted to the wells. The wells were again washed; a tetramethyl-benzidine (TMB) substrate solution was added to the wells and color developed in proportion to the amount of OPN bound. The Stop Solution changed the color from blue to yellow, and the intensity of the color was measured at 450 nm. Assay range was from 2 to 40 ig/L, Intra-Assay and Inter-Assay coefficients of variation were CV < 10% and CV < 12%, respectively.
Estimation of IgE concentration by ELISA technique
ImmunoSpec IgE Quantitative Enzyme Immunoassay for total serum IgE was provided from IMMUNOSPEC CORPORATION 7018 Owens mouth Ave. Suite 103 Canoga Park, CA, 91303. Briefly, immunoSpec IgE Quantitative Test Kit was based on a solid phase enzyme-linked immunosorbent assay. The serum samples and standards were added to the IgE antibody coated microtiter wells and incubated with Zero Buffer. The wells were then washed to remove any residual test specimen, and then IgE antibody labeled with horseradish peroxi-dase (conjugate) was added. After incubation at room temperature, the wells were washed with water to remove unbound labeled antibodies. A solution of TMB was added and incubated for 20 min, resulting in the development of a blue color. The color development was stopped with the addition of the Stop Solution, and the color was changed to yellow and measured spectrophotometrically at 450 nm. The minimal sensitivity of this assay is about 5.0 IU/ml.
Statistical analysis
Data are presented as mean ± SD. Comparisons between groups regarding each variable were analyzed by one-way Analysis of Variances ANOVA followed by Multiple/Post Hoc Group Comparisons test using least significant difference procedure for computing the differences between the four groups. Unpaired t-tests for comparing ACQ scores between asthmatic groups and spirometric findings between non-asthmatic groups, and by paired t-tests for assessment of treatment effect on the ACQ. Correlations between variables were computed by Pearson's correlation coefficients (r). Statistical analysis was performed with Statistical Toolbox for the MATLAB (Matrices Laboratory software version R2008b). P value lower than 0.05, was considered statistically significant.
Results
Body fat percentage, serum OPN levels and IgE concentrations
In this study, as expected, the body fat percentage was significantly higher (P < 0.0001) in obese asthmatics and
Table 1 Body fat percentage, serum osteopontin levels (in ig/L) and IgE concentrations (in IU/mL).
Parameters Non-obese Obese Non-obese Obese asthmatic F(P)
non-asthmatic non-asthmatic asthmatic
Body fat % 29.260 ± 2.605 46.840 ± 5.157* 29.650 ± 1.696# 49.950 ± 4.557*h 85.014912 (P < 0.0001)
(23.5-32.0) (38.0-53.6) (26.5-31.7) (40.8-54.8)
Serum osteopontin levels (ig/L) 37.900 ± 3.771 56.910 ± 7.465* 60.160 ± 8.159* 84.620 ± 8.246*#h 71.981007 (P < 0.0001)
(33.1-45.5) (43.5-65.8) (47.9-71.3) (70.7-96.4)
Serum IgE levels (Iu/mL) 12.510 ± 2.669 24.870 ± 9.130 589.030 ± 72.158*# 799.050 ± 60.749*#h 709.458665 (P < 0.0001)
(8.3-16.3) (8.1-38.5) (481.1-730.3) (683.4-899.6)
Data are presented as mean ± sd (minimum-maximum). Differences between groups were analyzed by ANOVA followed by least significant
difference tests.
Significant from non obese-non asthmatic group P < 0.0001.
# Significant from obese non asthmatic group P < 0.0001.
8 Significant from non obese asthmatic group P < 0.0001.
<D M (S
■o o m
Non-Obese Non-Asthmatic
Obese Non-Asthmatic
Non-Obese Asthmatic
Obese Asthmatic
Figure 1 Comparison of body fat percentage in the different groups.
non-asthmatics (49.950 ± 4.557% and 46.840 ± 5.157%, respectively) as compared to non-obese asthmatics and non-asthmatics (29.650 ± 1.696% and 29.260 ± 2.605%, respectively). As regards serum OPN levels, the highest values were observed in the obese asthmatic (84.620 ± 8.246 ig/L) while the lowest in the non-obese non-asthmatic patients (37.900 ± 3.771 ig/L) with a significant difference (P < 0.0001), however, no significant difference between obese non-asthmatic (56.910 ± 7.465 ig/L) and asthmatic non-obese (60.160 ± 8.159 ig/L) patients was detected (P = 0.31625). Increased concentrations of IgE (P < 0.0001) were observed only in the asthmatic groups but it was significantly higher (P < 0.0001) in the obese (799.050 ± 60.749 Iu/mL) than in the non-obese (589.030 ± 72.158 Iu/mL) patients (Table 1 and Figs. 1-3).
The present study conveyed that body fat percentage was positively correlated to serum OPN levels (r = 0.940728; P < 0.0001 in non-asthmatic groups and r = 0.92191; P < 0.0001 in asthmatic groups) and to the concentrations of IgE (r = 0.818011; P < 0.0001 in non-asthmatic groups and r = 0.83522; P < 0.0001 in asthmatic groups). Again, the correlation between serum OPN levels and serum IgE levels was significantly positive (r = 0.857439; P < 0.0001 in non-asthmatics and r = 0.77018; P < 0.0001 in asthmatics). (Tables 3 and 4 and Figs. 4-6).
100 90 80 70
._. 60
50 40 30 20 10 0
Non-Obese Non-Asthmatic
Obese Non-Asthmatic
Non-Obese Obese Asthmatic Asthmatic
Figure 2 Comparison of serum OPN concentrations in the different groups.
Spirometric findings for non-asthmatic women
By comparing spirometric results (Table 2) in non-asthmatic women; it was observed that the percentage of predicted of forced vital capacity (FVC) (P < 0.0001), forced expiratory volume after the first second (FEV1) (P < 0.0001) and maximum voluntary ventilation (MVV) (P = 0.0002) were significantly higher in the healthy non-obese-non asthmatic women (93.200 ± 4.517, 92.600 ± 5.522 and 98.300 ± 5.618, respectively) as compared to the obese-non asthmatic women (77.400 ± 3.340, 84.300 ± 2.669 and 77.000 ± 5.055, respectively). However forced expiratory volume after the first second/forced vital capacity (FEV1/FVC) ratio showed no statistical significant difference (P = 0.3867) between the two groups (87.100 ± 2.279 vs 86.820 ± 1.995). These findings indicate that obesity has some restrictive effect on pulmonary functions.
In the current work, we demonstrated a significant negative correlation that was found between the body fat percentage and the percentage of predicted of FVC (r = —0.894877; P < 0.0001), FEV1 (r = —0.704924; P = 0.0005) and MVV (r = —0.930590; P < 0.0001). Furthermore, the percentage of predicted of FVC, FEV1 and MVV were negatively correlated to serum OPN levels (r = —0.791279; P < 0.0001, r = —0.593556; P = 0.0058 and r = 0.923399; P < 0.0001, respectively) (Table 3).
1000 900 800 700 600 500 400 BOO 200 100
12.510
24.870
589.030
799.050
Non-Obese Non- Obese Non-Asthmatic Non-Obese Asthmatic Obese Asthmatic Asthmatic
Figure 3 Comparison of serum IgE levels in the different groups.
Table 2 Spirometrie findings for non-asthmatic women.
Parameters Non-obese non-asthmatic Obese non-asthmatic t (P)
FVC 93.200 ± 4.517 77.400 ± 3.340 8.894451507
(88.000-102.000) (71.000-83.000) (P < 0.0001)*
FEV1 92.600 ± 5.522 84.300 ± 2.669 4.279765866
(84.000-104.000) (80.000-88.000) (P = 0.0002)*
FEV1/FVC ratio 87.100 ± 2.279 86.820 ± 1.995 0.292280457
(82.900-89.700) (83.300-89.300) (P = 0.38671)
MVV 98.300 ± 5.618 77.000 ± 5.055 8.912038546
(94.000-109.000) (70.000-84.000) (P < 0.0001)*
Data are presented as mean ± sd (minimum-maximum).
Differences between groups were analyzed by unpaired t test. FVC: forced vital capacity, FEV1: forced expiratory volume after the first second,
FEV1/FVC: forced expiratory volume after the first second/ forced vital capacity and MVV: maximum voluntary ventilation.
* Significant from the non-obese non-asthmatic group.
Table 3 The correlations between different parameters studied in non-asthmatic groups.
Parameters studied Body fat Serum osteopontin Serum IgE FVC FEV1 FEV1/FVC ratio
percentage level (ig/L) levels (Iu/mL)
Serum osteopontin levels (ig/L) r 0.940728
P <0.0001*
Serum IgE levels (Iu/mL) r 0.818011 0.857439
P <0.0001* <0.0001*
FVC r -0.894877 -0.791279 -0.632872
p <0.0001* <0.0001* 0.0027*
FEV1 r -0.704924 -0.593556 -0.492693 0.840026
P 0.0005* 0.00588 0.0273 <0.0001*
FEV1/FVC ratio r 0.049518 0.169317 0.068836 0.180152 0.126266
P 0.8357 0.475457 0.7730 0.447230 0.5958
MVV r -0.930590 -0.923399 -0.761158 0.854850 0.766868 -0.117326
P <0.0001* <0.0001* <0.0001* <0.0001* <0.0001* 0.6223
FVC: forced vital capacity, FEV1: forced expiratory volume after the first second, FEV1/FVC: forced expiratory volume after the first second/
forced vital capacity and MVV: maximum voluntary ventilation.
* Significant correlation.
ACQ results for asthmatic patients
ACQ scoring (Table 4) was significantly better (P = 0.0084) in non-obese than obese patients before treatment (3.860 ± 0.924 vs 4.840 ± 0.728). After receiving treatment for two weeks,
both groups had significantly improved ACQ scores (0.660 ± 0.620 vs 2.500 ± 0.577), (P < 0.0001). However, the improvement (presented by difference between ACQ before and after treatment (A ACQ)) was significantly superior (P = 0.0031) in non-obese than obese women (3.200 ± 0.670 vs 2.340 ± 0.568).
Table 4 Asthma control questionnaire before and after treatment.
Parameters Non-obese asthmatic Obese asthmatic Unpaired t (P1)
ACQ before treatment ACQ after treatment Paired t (P2) Mean change (A ACQ) 3.860 ± 0.924 (2.700-5.100) 0.660 ± 0.620 (0.000-1.900) 15.10360261 P2 < 0.0001 3.200 ± 0.670 (1.800-4.100) 4.840 ± 0.728 (3.600-5.700) 2.500 ± 0.577 (1.400-3.300) 13.02683181 P2 < 0.0001 2.340 ± 0.568 (1.500-3.200) -2.635102667 P1 -6.865756612 P1 3.096099077 P1 = = 0.0084 < 0.0001 0.0031
ACQ: asthma control questionnaire. P1: Significant difference between obese and non-obese asthmatics by unpaired t test. P2: Significant difference between ACQ before and after treatment in the same group by paired t test.
Figure 4 Scatter diagram showing the significant positive correlation found between body fat percentages and circulating concentrations of OPN in both asthmatics (right) and non asthmatic (left) women.
Figure 5 Scatter diagram showing the significant positive correlation found between body fat percentage and serum IgE levels in both asthmatic (right) and non asthmatic (left) women.
Although baseline ACQ scoring was not significantly correlated to either body fat, serum OPN or IgE, a negative correlation was detected between A ACQ and the three parameters (body fat: r = —0.69957; P = 0.0006, serum OPN: r = —0.68387; P = 0.0009 and IgE concentration: r = —0.75795; P = 0.0001) (Table 5 and Figs. 7-9).
Discussion
Obesity is a determinant of asthma control that is independent of airway inflammation, lung function, and AHR. Asthma in obese individual tends to be more severe, does not respond well to treatment and is becoming a major public health issue [27].
Figure 6 Scatter diagram showing the significant positive correlation found between serum osteopontin levels and serum IgE levels in both asthmatic (right) and nonasthmatic (left) women.
Table 5 The correlations between different parameters studied in asthmatic groups.
Parameters studied Body Fat Serum osteopontin Serum IgE levels ACQ before ACQ after
Percentage level (ig/l) (Iu/ml) treatment treatment
Serum osteopontin r 0.92191
levels (ig/L) P <0.0001*
Serum IgE levels (Iu/ r 0.83522 0.77018
mL) p <0.0001* <0.0001*
ACQ before r 0.42267 0.22555 0.28457
treatment p 0.0633 0.3389 0.2239
ACQ after treatment r 0.83482 0.65496 0.75560 0.74673
p <0.0001* 0.0017* 0.0001* 0.0002*
Mean change (A r -0.69957 -0.68387 -0.75795 0.16606 -0.53189
ACQ) p 0.0006* 0.0009* 0.0001* 0.4841 0.0158
ACQ: asthma control questionnaire.
* Significant correlation.
In the present study, the body fat percentage was significantly higher in obese asthmatics and non-asthmatics as compared to non-obese asthmatics and non-asthmatics while serum OPN levels, the highest values were observed in the obese asthmatic and the lowest in the non-obese non-asthmatic patients. Body fat percentage was positively correlated to serum OPN levels in asthmatic and non-asthmatic groups.
Giirsoy et al. [28] showed that body fat percentage were found to be significantly higher in obese group than non-obese group and OPN levels of obese patients were significantly higher than those levels of non-obese controls.
Gomez-Ambrosi et al. [23] established that obese patients exhibited a 2-fold increase in plasma OPN concentrations compared with lean individuals. The significant positive correlation between OPN and body fat (assessed by measuring body fat percentage) seems to indicate that OPN levels are related to the adipose tissue amount. Again, the increased body fat is accompanied by high concentrations of OPN in addition to high levels of some inflammatory markers like C-reactive protein (CRP), TNF-a and fibrinogen, thus reinforcing the observation that excess adiposity may contribute to the obesity-associated low-grade chronic inflammation. Diet-induced
weight loss significantly decreased OPN concentrations from 64.7 ± 22.1 to 36.6 ± 20.1 ng/mL.
Increased concentrations of IgE were observed only in the asthmatic groups but it was significantly higher in obese than non-obese patients. Body fat percentage was positively correlated to concentrations of IgE in non-asthmatic and in asthmatic groups. In addition, the correlation between serum OPN levels and serum IgE levels was significantly positive in non-asthmatics and in asthmatics groups.
Grotta et al. [29] assessed serum IgE levels and eosinophil counts and found that, they were significantly higher in the asthmatic individuals (obese and non-obese) compared with the non-asthmatic individuals (obese and non-obese). Circulating leptin levels were directly correlated with adipose tissue mass. Leptin is also a proinflammatory mediator that enhances systemic and pulmonary inflammation. Therefore, high levels of leptin are essential in linking obesity to allergic airway inflammation.
Although Fenger et al. [30] explored the association between adiposity and asthma; they found that all adiposity measurements were associated with a higher prevalence of asthma but only among non-atopic individuals. OPN enters mast cell biology and the regulation of IgE-dependent immune
Figure 7 Scatter diagram showing the significant negative correlation found between body fat percentage and mean change in ACQ (D ACQ) in asthmatic patients.
Scatter plot of Serum osteopontin level (pg/l) vs Mean change ( A ACQ)
Non-Oboso Asthma be Oboso Asthmatic
- o r = -0.6839 p = 0.0009
- o
- : o 1 ! 1
Serum osteopontin level (pg/i)
Figure 8 Scatter diagram showing the significant negative correlation found between serum osteopontin levels and mean change in ACQ (A ACQ) in asthmatic patients.
Figure 9 Scatter diagram showing the significant negative correlation found between serum IgE levels and mean change in ACQ (A ACQ) in asthmatic patients.
responses since it is, reported that connective tissue-type mast cells from fetal murine skin constitutively secrete biologically active OPN. Moreover, it is shown that, in vitro, OPN augments IgE-mediated mast cell degranulation and migration via ligand binding to cognate OPN receptors on the mast cell surface (CD44, alpha vs integrin) and that the magnitude of an IgE-mediated passive cutaneous anaphylaxis reaction is augmented by OPN in vivo [31].
A previous study by Samitas et al. [19] who measured OPN levels in the serum, bronchoalveolar lavage fluid (BALF) and bronchial tissue of healthy controls and asthmatics identified cellular sources of OPN and examined possible correlations between OPN expression, disease severity and airway remodeling. Serum samples were obtained from 35 mild-to-moderate asthmatics, 19 severe asthmatics and 17 healthy controls in the steady state and in cases of exacerbation. Of these subjects, 29 asthmatics and 9 controls underwent bronchoscopy with endobronchial biopsy and BALF collection. Reticular basement membrane thickness and goblet cell hyperplasia were also determined. Serum and BALF OPN levels were significantly increased in all asthmatics in the steady state, whereas serum levels decreased during exacerbations. OPN was upreg-ulated in the bronchial tissue of all patients, and expressed by epithelial, airway and vascular smooth muscle cells, myofibro-blasts, T-lymphocytes and mast cells. OPN expression correlated with reticular basement membrane thickness and was more prominent in subepithelial inflammatory cells in severe compared to mild-to-moderate asthma. OPN expression is upregulated in human asthma and associated with remodeling changes, and its subepithelial expression correlates with disease severity.
The spirometric results in non-asthmatic women showed that the percentage of predicted of FVC, FEV1 and MVV were significantly higher in the healthy non obese-non asthmatic women as compared to the obese non-asthmatic women. However, FEV1/FVC ratio showed no statistical significant difference between the two groups. These findings indicate that obesity has some restrictive effect on pulmonary functions. A significant negative correlation was found between the body fat percentage and the percentage of predicted of FVC, FEV1 and MVV' Furthermore, the percentage of predicted of FVC, FEV1 and MVV were negatively correlated to serum OPN levels.
Airflow obstruction, as measured by the FEV1/FVC ratio, is not usually associated with obesity. Indeed, the FEV1/FVC ratio may be increased in obese individuals if airway closure and gas trapping reduces the FVC. Because of breathing at lower functional residual capacity (FRC), airway caliber is decreased throughout the tidal breathing cycle, resulting in an increase in airway resistance. Some studies have suggested that the increase in airflow resistance may not be due entirely to the reduced lung volume, but the cause of the additional resistance remains unknown [32,33].
Salome et al. [34] observed that, obese and non-obese subjects without asthma had similar changes in the percentage of predicted of FEV1 following methacholine-induced airway narrowing, but the severity of dyspnea was greater in the obese group. This difference in symptoms was attributed to a greater change in the respiratory system reactance in the obese, reflecting increased elastic loads. The occurrence of additional elastic loads in the obese during bronchoconstriction, which are not well reflected by spirometry, may explain why some obese
individuals with asthma have more severe symptoms than their lean counterparts despite similar spirometry.
Recent literatures suggest that asthma is different in obese from non-obese patient. Obesity not only affects lung mechanics, but also has significant effects on asthma control and response to medication, and these changes appear to be independent of airway cellular inflammation. These differences may justify adding a new phenotype, ''obesity-associated asthma,'' to the existing list that includes allergic, occupational, exercise-induced, nocturnal, aspirin-sensitive, and severe asthma [27,29,30].
ACQ scoring in asthmatic women was significantly better in non-obese than obese patients before treatment. After receiving treatment for two weeks, both groups had significantly improved ACQ scores. However, the improvement (presented by difference between ACQ before and after treatment (A ACQ)) was significantly superior in non-obese women. A negative correlation was detected between A ACQ and the three parameters body fat percentage, serum OPN and IgE concentration.
Although there is a plethora of asthma symptoms questionnaires, ACQ is the first to be specifically developed and validated to measure asthma control. The ACQ is needed for research studies to measure the primary goal of asthma treatment, to identify populations at risk and to facilitate comparison of results across studies [25]. ACQ can be used in different settings by both patients and care providers to assess current asthma control. Assessment of asthma control by the ACQ; is influenced by the type of administration. Honkoop et al.
[35] suggested that better control of asthma is perceived when interacting with a caregiver than by online self-assessment.
Obesity may worsen asthma via specific pathophysiologic mechanisms, such as airway inflammation, remodeling and bronchial hyperresponsiveness, or by the mechanical effects of obesity on airway function, or there could be other explanations. For example, obesity related co morbidities, such as gas-troesophageal reflux or sleep disordered breathing, could interact with asthma to increase respiratory dysfunction. In addition, it is known that obese patients tend to experience wheezing and breathlessness due to their excess weight. Therefore, obese patients may have falsely attributed weight related respiratory symptoms to asthma, causing increased use of their bronchodilator. Asthma and obesity exhibit a well-established relationship with evidence pointing toward a more severe and difficult-to-control obese-asthma phenotype that has altered responses to controller medications. This phenotype is more likely to have a worse quality of life, more daily symptoms, and more exacerbations as well as use more rescue medications
Obesity has a significant adverse effect on asthma control. Taylor et al. [37] showed that obese individuals with asthma had more severe symptoms and increased medication use in multivariate regression adjusted for age, sex, race, income, and education status. Vortmann and Eisner [38] also found that obese subjects with asthma who were recruited following hospital discharge had increased symptoms and decreased asthma-specific quality of life when controlling for age, sex, race, income, and educational status, but did not find increased emergency health care utilization.
In a cross sectional survey study, Mosen et al. [39] showed that obesity has significant adverse effects on symptoms, medication use, and quality of life, and that, in addition, obese individuals with asthma have a 4.6-fold increased risk of
hospitalization for asthma compared with non-obese individuals with asthma in multivariate analysis. The finding of increased hospitalizations in the obese by Mosen et al. contrasts with the finding of similar emergency health care utilization by Vortmann and Eisner. This may be related to the different patient populations; all participants in the study by Vortmann and Eisner had severe asthma and were recruited following a hospitalization for asthma, whereas Mosen et al. included individuals with asthma of all disease severities. Therefore, identifying strategies to improve asthma control in the obese should be a research priority in this field.
Obese patients do not respond as well as normal-weight individuals to inhaled corticosteroids or inhaled corticoste-roid/long-acting bronchodilator combination medications. The explanation for this altered response to asthma controller therapy is likely to be more complicated than a difficulty with inhaled drug delivery or differences in airway mechanics. Sutherland et al. [40] reported that obesity was associated with attenuated in vitro response to glucocorticoids in a well-characterized adult group of individuals with moderate to severe asthma.
In conclusion, this study provided the first evidence that osteopontin is a novel link between obesity and bronchial asthma. Again, it showed a significant negative correlation between asthma improvement and body fat percentage, serum OPN and IgE concentration. In addition, there was a significant positive correlation between OPN and body fat percentage. Therefore, multiple roles of OPN action potentially contribute to inflammation in obesity. In this context, it is suggested that, in addition to weight reduction, interference with OPN action could become a therapeutic strategy in the treatment of obesity-associated and obesity worsening disorders like bronchial asthma.
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