Gynecological Endocrinology
ISSN: 0951-3590 (Print) 1473-0766 (Online) Journal homepage: http://www.tandfonline.com/loi/igye20
Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure Zahra Taghadomi Masoumi, Mohammad Reza Eshraghian, Mahdi Hedayati & Hamideh Pishva To cite this article: Zahra Taghadomi Masoumi, Mohammad Reza Eshraghian, Mahdi Hedayati & Hamideh Pishva (2017): Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure, Gynecological Endocrinology, DOI: 10.1080/09513590.2017.1379492 To link to this article: http://dx.doi.org/10.1080/09513590.2017.1379492
Published online: 10 Oct 2017.
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Date: 13 October 2017, At: 22:48
GYNECOLOGICAL ENDOCRINOLOGY, 2017 https://doi.org/10.1080/09513590.2017.1379492
ORIGINAL ARTICLE
Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure Zahra Taghadomi Masoumia, Mohammad Reza Eshraghianb, Mahdi Hedayatic and Hamideh Pishvaa a
Department of cellular-Molecular Nutrition, School of Nutrition Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran; Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; cCellular-Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University, Tehran, Iran
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b
ABSTRACT
ARTICLE HISTORY
Obesity is recognized as the most prevalent metabolic disease worldwide. Decreases in energy expenditure may increase risk of obesity. One of the key regulators of energy balance is uncoupling protein2 (UCP2), a transporter protein presents in mitochondrial inner membrane. Moreover, adiponectin is the most abundant adipocytokine, it may play a role in energy metabolism and gene expression of UCP2. The aim of this study was to investigate potential associations between the level of uncoupling protein 2 and adiponectin and their relationship with REE (Resting Energy Expenditure) in obese women with normal and low resting energy expenditure. A total of 49 subjects (women, 25–50 years old), were included in current study, 16 subjects with BMI > 30 and low resting energy expenditure, 17 subjects with BMI > 30 and normal resting energy expenditure and 16 non-obese subjects as a control group. Anthropometric, body composition parameters and resting energy expenditure were measured. Plasma adiponectin, UCP2 protein and total protein in PBMC were determined. Measured resting energy expenditure in obese subjects with low REE was significantly lower than other groups. Plasma adiponectin in the obese subjects with low REE was significantly lower compared to normal weight group. There was a significant relationship between ‘UCP2 protein/Total protein’ ratio and plasma adiponectin in obese group with low REE and in three groups when we pooled. There was a significant association between REE and plasma adiponectin in three groups when we pooled. There was a significant association between plasma adiponectin and REE. Moreover, there was a significant relationship between UCP2 and REE.
Received 7 February 2017 Revised 17 March 2017 Accepted 11 September 2017 Published online 10 October 2017
Background Obesity is a major risk factor for some chronic diseases, including diabetes, cardiovascular diseases and cancer. It may increase risk of morbidity and mortality in critically ill patients [1]. Low resting energy expenditure (REE) is a risk factor for body weight gain [2]. Since REE was comprises 60–80% total energy expenditure (TEE), low REE may influence TEE and imbalance between energy intake and expenditure [3]. Recent studies have showed in some obese subjects measured resting energy expenditure (MREE) was much lower than estimated resting energy expenditure which was predicted by valid equations [4]. Uncoupling proteins (UCPs) belong to the family of mitochondrial transport proteins which play a role in cellular energy hemostasis by uncoupling transportation of protons across the inner mitochondria and generating heat rather than energy [5]. Uncoupling protein 2 (UCP2) is expressed widely in white adipose tissue, skeletal muscle, pancreatic islets and central nervous system [6]. Adipose tissue, in addition to its function as the major storage depot for triglycerides, is an endocrinologically active tissue that releases hormones called adipocytokines/adipokines that affect whole-body energy homeostasis [7,8]. Adiponectin is the most abundant adipocytokine [9]. Unlike other adipocytokines, which circulate at picograms or nanograms per milliliter, adiponectin circulates at very high levels (micrograms per milliliter) [10]. CONTACT Hamideh Pishva [email protected] Medical Sciences (TUMS), Tehran, Iran ß 2017 Informa UK Limited, trading as Taylor & Francis Group
KEYWORDS Uncoupling protein; adiponectin; obesity; resting energy expenditure
Some studies reported plasma adiponectin levels were reduced in obese subjects [9]. Several roles were recognized for adiponectin such as anti-inflammatory, antidiabetic properties [11]. Recent studies have suggested that adiponectin may involve in energy hemostasis [10]. Moreover, limited data proposed association between UCP2 and adiponectin [12]. Our study was carried out to investigate association between uncoupling protein 2, adiponectin and their relationship with REE in obese women with normal and low resting energy expenditure. Because in vivo investigation is challenging, an easier sampling should be pursued. It was proposed that peripheral blood mononuclear cells (PBMCs) are a suitable source for measuring UCP2 [13]. PBMCs include monocytes and lymphocytes and are easily obtainable in humans. It has been demonstrated that expression pattern of genes involved in lipid metabolism are reflected in human PBMCs. Moreover, adipose tissue and PBMCs derive from the same body compartment. Additionally, PBMCs are a source to detect early biomarkers of obesity based on their ability to reflect alterations in energy metabolism [14].
Subjects and methods Subjects A total of 49 subjects (women, 25–50 years old) were recruited to participate in current case–control study. All procedures
Department of cellular-Molecular Nutrition, School of Nutrition Sciences and Dietetics, Tehran University of
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performed were in accordance with the ethics committee of Tehran University of Medical Sciences (TUMS) and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. All participants were informed about the nature of the study and filled out a written informed consent. They were divided into three groups: 16 subjects with BMI > 30 and low resting energy expenditure, 17 subjects with BMI > 30 and normal resting energy expenditure and 16 subjects with BMI < 25 as a control group. Subjects with MREE less than 20% of their predicted resting energy expenditure were defined as low resting energy expenditure. Exclusion criteria included medical history of diabetes, coronary, thyroid diseases or other hormonal disease, GI surgery for weight lost, use of medications or treatments effective on their REE, alcohol, smoking or drug abuse, use of supplementary vitamins, use of hormonal therapy, being pregnant, lactating or in menopause. We calculated the sample size as follows [15]: Z1a2 ¼ 1:96 a ¼ 0:05 1 b ¼ 0:80 Z1b ¼ 0:84
n¼
pffiffiffiffiffiffiffiffiffiffiffiffi!2 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi2 Z1a2 þ Z1b 1 r2 1:96 þ 0:84 1 0:82 þ2¼ þ 2 ¼ 11:5 r 0:8
According to the equation above, sample size was calculated nearly 12% in each group and we selected more percent in each group for great accuracy. Anthropometric measurements Anthropometric measurements were performed while subjects were wearing only light clothing and no shoes. Body mass index (BMI) was then calculated. Waist circumference was measured at the midway between the lowest rib and the iliac crest by using a flexible tape. The hip circumference was measured at the largest protrusion.
RMR and body composition measurements Resting metabolic rate (RMR) was measured by using indirect calorimetry by means of the Meta CheckTM (Korr Medical Technologies, Salt Lake City,UT). Predicted resting energy expenditure for each subject was obtained using the Harris–Benedict equation [16]. Body composition was measured by bioelectrical impedance (RJL Systems, Clinton Twp, MI). Measurements were performed on all subjects by professional nutritionists using a standard protocol.
Laboratory analyses Blood sample was drawn after at least 12 h of overnight fasting. UCP2 protein was measured by Human Uncoupling Protein2, ELISA kit (SL2021 Hu, Sunlong Biotech, HangZhou, China) in peripheral blood mononuclear cells (PBMCs). Total protein in PBMCs was measured by Sensitive Protein (Bradford) Assay kit (ZB-BPA96A, V31130, ZellBio GmbH, Germany) to calculate ‘UCP2 protein/Total protein’ ratio. Since measurements were taken using extracted PBMCs from blood, the amount of cells extracted from different subjects may be different. Therefore, the more accurate measurement is ‘UCP2/Total protein ratio.’ Plasma adiponectin was measured by ELISE kit (Human adiponectin (ADP) ELISA Kit, SL0068Hu, Sunlong).
Statistical analyses Normal distribution of data was performed by using Kolmogorov–Smirnov. Differences between baseline characteristics, anthropometric measurements, body composition, REE, UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin between groups were tested by one-way analysis of variance (ANOVA) with post hoc tests and Kruskal–Wallis test, followed by Mann–Whitney U-test. Multiple linear regression analyses were performed to assess regression coefficients (b) and confidence intervals (95% CI) for association between the level of UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin. Two models were considered in these regression analyses. The first model was crude and the second model was adjusted for age and BMI. Moreover, multiple linear regression analyses were carried out to verify association between REE and plasma adiponectin. Besides, two models were considered in these multivariate regression analyses. The first model was crude and the second model was energy intake and BMI. Analyses were performed using SPSS version 20 (Chicago, IL). A p values < .05 was considered statistically significant.
Results Table 1 shows anthropometric measurements, body composition, REE, UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin in three groups. There was a significant difference in waist circumference between the two obese groups. Hip and waist circumference were significantly increased in obese subjects. There were no significant differences between age and height in the three groups. Fat mass and fat-free mass were significantly increased in obese subjects, but there was no significant difference in body composition between two obese groups. There was a significant difference in MREE between three groups. MREE in obese group with low REE was significantly lower than other groups. There were no significant differences between UCP2 protein and ‘UCP2 protein/Total protein’ ratio in three groups. Plasma adiponectin in the obese group with low REE was significantly lower compared to normal weight group. Table 2 shows association between the level of UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin. According to linear regression, there was no relationship between UCP2 protein and plasma adiponectin, when compared to each group separately and in three groups when we pooled. There was a significant relationship between ‘UCP2 protein/Total protein’ ratio and plasma adiponectin in obese subjects with low REE and in three groups when we pooled. Table 3 shows association between REE and plasma adiponectin. According to linear regression, there was a significant association between REE and plasma adiponectin in three groups when we pooled.
Discussion The aim of this study was to investigate association between adiponectin, uncoupling protein 2 and REE in obese women with normal and low resting energy expenditure. Adiponectin is a 244-amino acid collagen-like protein which secreted by adipocyte that acts as a hormone with anti-inflammatory and insulin-sensitizing properties. Moreover, it was suggested that adiponectin serves as a central regulatory protein in many metabolic pathways that play important role in many metabolic disorders [11].
.18 4.98 ± 1.70 7.07 ± 1.57 .00 1.83 ± 0.84 7.07 ± 1.57 .40 4.98 ± 1.70 1.83 ± 0.84
Values are Means ± SE. Significant difference between REE (Measure), REE (Estimate), FM(%), FFM(kg), weight (kg) by ANOVA with Tukey's post hoc tests. Significant difference between FM (kg), FFM (%), REE (Estimate), Waist circumference (cm), Hip circumference (cm) by Kruskal–Wallis with Mann–Whitney.
.15 .00 .19 .00 .00 .01 .00 .00 .00 .00 .00 .16 .18 37.70 ± 1.85 86.86 ± 2.16 159.11 ± 1.48 90.47 ± 2.16 114.76 ± 2.07 1895.64 ± 76.71 1759.39 ± 28.75 41.65 ± 1.46 47.80 ± 0.71 45.20 ± 0.97 52.19 ± 0.71 281.28 ± 47.02 3.99 ± 0.71 32.87 ± 1.89 59.38 ± 1.04 161.87 ± 1.42 67.31 ± 1.08 95.18 ± 1.23 1624.50 ± 70.82 1498.50 ± 19.29 18.82 ± 0.54 31.68 ± 0.69 40.56 ± 0.79 68.31 ± 0.69 183.67 ± 49.27 2.61 ± 0.71 .14 .00 .95 .00 .00 .00 .00 .00 .00 .01 .00 .40 .89 37.81 ± 1.64 81.02 ± 2.23 161.18 ± 1.40 82.75 ± 1.40 111.31 ± 1.95 1235.81 ± 30.41 1699.78 ± 29.88 37.08 ± 1.77 45.43 ± 0.98 43.94 ± 0.64 51.56 ± 2.32 263.58 ± 67.44 3.17 ± 0.84 32.87 ± 1.89 59.38 ± 1.04 161.87 ± 1.42 67.31 ± 1.08 95.18 ± 1.23 1624.50 ± 70.82 1498.50 ± 19.29 18.82 ± 0.54 31.68 ± 0.69 40.56 ± 0.79 68.31 ± 0.69 183.67 ± 49.27 2.61 ± 0.71 37.81 ± 1.64 81.02 ± 2.23 161.18 ± 1.40 82.75 ± 1.40 111.31 ± 1.95 1235.81 ± 30.41 1699.78 ± 29.88 37.08 ± 1.77 45.43 ± 0.98 43.94 ± 0.64 51.56 ± 2.32 263.58 ± 67.44 3.17 ± 0.84
Age (years) Weight (kg) Height (cm) Waist circumference (cm) Hip circumference (cm) REE (kcal/day) measure REE (kcal/day) estimate FM (kg) FM (%) FFM (kg) FFM (%) UCP2 (pg/ml) ‘UCP2 protein/Total protein’ (pg/mg) Plasma adiponectin (mg/L)
.99 .08 .32 .00 .37 .00 .25 .05 .10 .52 .27 .91 .57 37.70 ± 1.85 86.86 ± 2.16 159.11 ± 1.48 90.47 ± 2.16 114.76 ± 2.07 1895.64 ± 76.71 1759.39 ± 28.75 41.65 ± 1.46 47.80 ± 0.71 45.20 ± 0.97 52.19 ± 0.71 281.28 ± 47.02 3.99 ± 0.71
Obese with low REE N ¼ 16 Groups variables
Table 1. Characteristics of study subjects.
Obese with normal REE N ¼ 17
p value
Control N ¼ 16
Obese with low REE N ¼ 16
p value
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Control N ¼ 16
Obese with normal REE N ¼ 17
p value
GYNECOLOGICAL ENDOCRINOLOGY
3
Some studies have showed the reduction in plasma adiponectin in obese subjects [10]. Similar to these finding, we showed plasma adiponectin in obese subjects was lower than normal weight subjects. Some studies have reported reverse correlation between plasma adiponectin and body mass index [17]. Moreover, some studies have suggested that increase and accumulation of abdominal visceral adipose tissue in obese subjects plays a crucial role in reduction of plasma adiponectin in these people [18]. Some mechanisms have been suggested for this relationship; fat accumulation in obese subjects may increase in oxidative stress and lead to dysregulation in production and secretion of adipocytokines such as adiponectin [19]. In this condition, PPAR-c (peroxisome proliferator-activated receptor-c) is the main regulator for adiponectin transcription in which suppresses by oxidative elements and lead to reduction in expression and plasma level of adiponectin [20]. Adiponectin has been shown to either increase [21] or reduce [22] energy expenditure. It has been reported intracerebroventricular administration of recombinant adiponectin decreases body weight and fat by increasing energy expenditure without affecting food intake [23,24]. Some studies have suggested that adiponectin plays a key role in the control of energy homeostasis through the regulation of glucose and fatty acid metabolism in peripheral tissues such as muscle and liver [10]. Adiponectin upregulated acyl-coenzyme A oxidase and uncoupling protein 2, leading to enhanced lipid catabolism [25]. Some studies have also reported that adiponectin decrease energy expenditure as manifested by lower body temperature, low oxygen consumption and downregulation of uncoupling protein 1 [22]. It has been suggested adiponectin effects on whole-body energy metabolism by controlling AMPK (monophosphate-activated protein kinase) activity in skeletal muscle, liver and adipose tissue and by the control of transcription factor expression [25]. Since mitochondria are essential for energy production at cellular level, differences in energy expenditure and basal metabolism may be attributed to mitochondrial functions [26]. Moreover some studies showed mitochondrial dysfunction, reduction in activity of marker enzymes of oxidative pathways, mitochondrial degeneration and reduced respiratory capacity in obese people [27,28]. Moreover, it was suggested some adipokines and hormones that produced by adipose tissue may affecting on mitochondrial functions and energy hemostasis [29] Uncoupling protein 2 belongs to the family of mitochondrial transporter proteins that may translocate protons into the mitochondrial matrix, resulting in heat generation without ATP synthesis [30]. We showed in other study association between UCP2 protein and resting energy expenditure. We demonstrated increased risk of reduced resting energy expenditure in obese subjects with low level of UCP2 protein. Association between adiponectin and UCP2 protein has suggested in some studies [12]. Our findings demonstrated association between adiponectin and UCP2 protein in obese group with low REE. Similar to our finding, Mahandik et al. has showed positive correlation between UCP2 mRNA and plasma adiponectin [31]. Some mechanisms have suggested for these relationships. Some studies that carried out on animal model have showed that uncoupling protein 2 controls adiponectin gene expression in adipose tissue through the modulation of reactive oxygen species production. It has been observed that circulating adiponectin levels and adiponectin
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Table 2. Association between the level of UCP2 protein (pg/mg), ‘UCP2 protein/Total protein’ ratio and plasma adiponectin (mg/L) in linear regression. Plasma adiponectin (mg/L) 95% CIa
95% CI Groups Obese with low REE (N ¼ 16) Obese with normal REE (N ¼ 17) Control (N ¼ 16) Total (N ¼ 49) Obese with low REE (N ¼ 16) Obese with normal REE (N ¼ 17) Control (N ¼ 16) Total (N ¼ 49) a
b
Lower
Upper
p value
ba
Lower
Upper
p valuea
31.08 5.66 1.64 2.96 0.63 0.07 0.03 0.11
15.21 10.55 21.29 8.40 0.05 0.19 0.25 0.04
77.37 21.88 18.01 14.34 1.20 0.34 0.32 0.27
.16 .46 .85 .60 .03 .55 .79 .15
25.44 13.92 3.19 11.14 0.41 0.18 .004 0.17
59.63 3.02 36.33 1.70 0.24 0.08 0.51 0.003
110.51 30.86 42.72 23.99 1.06 0.45 0.50 0.34
.50 .09 .85 .08 .18 .15 .98 .04
Variables UCP2 (pg/ml)
UCP2/Tpr (pg/mg)
Adjusted for age and BMI.
Table 3. Association between REE (kcal/day) and plasma adiponectin (mg/L) in linear regression. REE (kcal/day) 95% CIa
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95% CI Groups Obese with low REE (N ¼ 16) Obese with normal REE (N ¼ 17) Control (N ¼ 16) Total (N ¼ 49) a
Variables
b
Lower
Upper
p value
ba
Lower
Upper
p valuea
Plasma adiponectin (mg/L)
8.66 6.85 8.71 9.74
30.99 23.38 32.54 9.97
13.67 37.10 15.10 29.46
.41 .63 .44 .32
18.21 6.59 5.28 21.39
91.88 29.44 32.63 0.94
55.44 42.64 22.06 41.85
.57 .69 .67 .04
Adjusted for energy intake and BMI.
gene expression in adipose tissue were reduced in UCP2-null mice [12]. Other studies have showed that adiponectin plays a role in UCP2 gene expression. Adiponectin stimulates UCP2 expression through AMPK and PPAR-alpha-signaling pathways in many tissues [32]. In conclusion, there was a significant association between plasma adiponectin and REE. Moreover, there was a significant relationship between UCP2 and REE. It was suggested that variation in resting energy expenditure in obese subjects may be relate to these factors.
7. 8. 9. 10. 11. 12.
Disclosure statement
13.
All authors declare that they have no conflict of interests. 14.
Funding We would like to thank the Research Council of Tehran University of Medical Sciences (28767) for their financial support and all the subjects who participated in this study.
15. 16. 17.
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Mohamed-Ali V, Pinkney JH, Coppack SW. Adipose tissue as an endocrine and paracrine organ. Int J Obes Relat Metab Disord 1998;22:1145–58. Ahima RS, Flier JS. Adipose tissue as an endocrine organ. Trends Endocrinol Metab 2000;11:27–32. Kadowaki T. Adiponectin and adiponectin receptors in insulin resistance, diabetes, and the metabolic syndrome. J Clin Invest 2006;116:1784–92. Dridia S, Taouis M. Adiponectin and energy homeostasis: consensus and controversy. J Nutr Biochem 2009;20:831–9. Ghoshal K, Bhattacharyya M. Adiponectin: probe of the molecular paradigm associating diabetes and obesity. World J Diabetes 2015;6:151–66. Chevillotte E, Giralt M, Miroux B, et al. Uncoupling protein-2 controls adiponectin gene expression in adipose tissue through the modulation of reactive oxygen species production. Diabetes 2007;56:1042–50. Telle-Hansen V, Halvorsen B, Dalen B, et al. Altered expression of genes involved in lipid metabolism in obese subjects with unfavourable phenotype. Genes Nutr 2013;8:425–34. Caimari A, Keijer J, Palou A. Regulation of adiponutrin expression by feeding conditions in rats is altered in the obese state. Obesity (Silver Spring) 2007;15:591–9. Oktavianthi S, Febinia C, Suastika K, Saraswati M. Uncoupling protein 2 gene polymorphisms are associated with obesity. Cardiovasc Diabetol 2012;11:41. Harris JA, Benedict FG. A biometric study of basal metabolism in man. Washington: Carnegie Institution of Washington, 1919. Arita Y, Kihara S, Ouhi N, et al. Paradoxical decrease of an adiposespecific protein, adiponectin, in obesity. Biochem Biophys Res Commun 1999;257:79–83. Kishida k, Kon Kim K, Funahashi T, et al. Relationships between circulating adiponectin level and fat distribution in obese subjects. J Atheroscler Thromb 2011;18:592–5. Furukawa S, Fujita T, Shimabukuro M, et al. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest 2004;114:1752–61. Iwaki M, Matsuda M, Maeda N, et al. Induction of adiponectin, a fatderived antidiabetic and antiatherogenic factor, by nuclear receptors. Diabetes 2003;52:1655–63. Qi Y, Takahashi N, Hileman SM, et al. Adiponectin acts in the brain to decrease body weight. Nat Med 2004;10:524–9. Kubota N, Yasuo Y, Kubota T, et al. Adiponectin stimulates AMP-activated protein kinase in the hypothalamus and increases food intake. Cell Metab 2007;6:55–68. Yamauchi T, Kamon J, Waki H, et al. The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 2001;7:941–6.
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ISSN: 0951-3590 (Print) 1473-0766 (Online) Journal homepage: http://www.tandfonline.com/loi/igye20
Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure Zahra Taghadomi Masoumi, Mohammad Reza Eshraghian, Mahdi Hedayati & Hamideh Pishva To cite this article: Zahra Taghadomi Masoumi, Mohammad Reza Eshraghian, Mahdi Hedayati & Hamideh Pishva (2017): Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure, Gynecological Endocrinology, DOI: 10.1080/09513590.2017.1379492 To link to this article: http://dx.doi.org/10.1080/09513590.2017.1379492
Published online: 10 Oct 2017.
Submit your article to this journal
Article views: 3
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=igye20 Download by: [Australian Catholic University]
Date: 13 October 2017, At: 22:48
GYNECOLOGICAL ENDOCRINOLOGY, 2017 https://doi.org/10.1080/09513590.2017.1379492
ORIGINAL ARTICLE
Association between uncoupling protein 2, adiponectin and resting energy expenditure in obese women with normal and low resting energy expenditure Zahra Taghadomi Masoumia, Mohammad Reza Eshraghianb, Mahdi Hedayatic and Hamideh Pishvaa a
Department of cellular-Molecular Nutrition, School of Nutrition Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran; Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; cCellular-Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University, Tehran, Iran
Downloaded by [Australian Catholic University] at 22:48 13 October 2017
b
ABSTRACT
ARTICLE HISTORY
Obesity is recognized as the most prevalent metabolic disease worldwide. Decreases in energy expenditure may increase risk of obesity. One of the key regulators of energy balance is uncoupling protein2 (UCP2), a transporter protein presents in mitochondrial inner membrane. Moreover, adiponectin is the most abundant adipocytokine, it may play a role in energy metabolism and gene expression of UCP2. The aim of this study was to investigate potential associations between the level of uncoupling protein 2 and adiponectin and their relationship with REE (Resting Energy Expenditure) in obese women with normal and low resting energy expenditure. A total of 49 subjects (women, 25–50 years old), were included in current study, 16 subjects with BMI > 30 and low resting energy expenditure, 17 subjects with BMI > 30 and normal resting energy expenditure and 16 non-obese subjects as a control group. Anthropometric, body composition parameters and resting energy expenditure were measured. Plasma adiponectin, UCP2 protein and total protein in PBMC were determined. Measured resting energy expenditure in obese subjects with low REE was significantly lower than other groups. Plasma adiponectin in the obese subjects with low REE was significantly lower compared to normal weight group. There was a significant relationship between ‘UCP2 protein/Total protein’ ratio and plasma adiponectin in obese group with low REE and in three groups when we pooled. There was a significant association between REE and plasma adiponectin in three groups when we pooled. There was a significant association between plasma adiponectin and REE. Moreover, there was a significant relationship between UCP2 and REE.
Received 7 February 2017 Revised 17 March 2017 Accepted 11 September 2017 Published online 10 October 2017
Background Obesity is a major risk factor for some chronic diseases, including diabetes, cardiovascular diseases and cancer. It may increase risk of morbidity and mortality in critically ill patients [1]. Low resting energy expenditure (REE) is a risk factor for body weight gain [2]. Since REE was comprises 60–80% total energy expenditure (TEE), low REE may influence TEE and imbalance between energy intake and expenditure [3]. Recent studies have showed in some obese subjects measured resting energy expenditure (MREE) was much lower than estimated resting energy expenditure which was predicted by valid equations [4]. Uncoupling proteins (UCPs) belong to the family of mitochondrial transport proteins which play a role in cellular energy hemostasis by uncoupling transportation of protons across the inner mitochondria and generating heat rather than energy [5]. Uncoupling protein 2 (UCP2) is expressed widely in white adipose tissue, skeletal muscle, pancreatic islets and central nervous system [6]. Adipose tissue, in addition to its function as the major storage depot for triglycerides, is an endocrinologically active tissue that releases hormones called adipocytokines/adipokines that affect whole-body energy homeostasis [7,8]. Adiponectin is the most abundant adipocytokine [9]. Unlike other adipocytokines, which circulate at picograms or nanograms per milliliter, adiponectin circulates at very high levels (micrograms per milliliter) [10]. CONTACT Hamideh Pishva [email protected] Medical Sciences (TUMS), Tehran, Iran ß 2017 Informa UK Limited, trading as Taylor & Francis Group
KEYWORDS Uncoupling protein; adiponectin; obesity; resting energy expenditure
Some studies reported plasma adiponectin levels were reduced in obese subjects [9]. Several roles were recognized for adiponectin such as anti-inflammatory, antidiabetic properties [11]. Recent studies have suggested that adiponectin may involve in energy hemostasis [10]. Moreover, limited data proposed association between UCP2 and adiponectin [12]. Our study was carried out to investigate association between uncoupling protein 2, adiponectin and their relationship with REE in obese women with normal and low resting energy expenditure. Because in vivo investigation is challenging, an easier sampling should be pursued. It was proposed that peripheral blood mononuclear cells (PBMCs) are a suitable source for measuring UCP2 [13]. PBMCs include monocytes and lymphocytes and are easily obtainable in humans. It has been demonstrated that expression pattern of genes involved in lipid metabolism are reflected in human PBMCs. Moreover, adipose tissue and PBMCs derive from the same body compartment. Additionally, PBMCs are a source to detect early biomarkers of obesity based on their ability to reflect alterations in energy metabolism [14].
Subjects and methods Subjects A total of 49 subjects (women, 25–50 years old) were recruited to participate in current case–control study. All procedures
Department of cellular-Molecular Nutrition, School of Nutrition Sciences and Dietetics, Tehran University of
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performed were in accordance with the ethics committee of Tehran University of Medical Sciences (TUMS) and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. All participants were informed about the nature of the study and filled out a written informed consent. They were divided into three groups: 16 subjects with BMI > 30 and low resting energy expenditure, 17 subjects with BMI > 30 and normal resting energy expenditure and 16 subjects with BMI < 25 as a control group. Subjects with MREE less than 20% of their predicted resting energy expenditure were defined as low resting energy expenditure. Exclusion criteria included medical history of diabetes, coronary, thyroid diseases or other hormonal disease, GI surgery for weight lost, use of medications or treatments effective on their REE, alcohol, smoking or drug abuse, use of supplementary vitamins, use of hormonal therapy, being pregnant, lactating or in menopause. We calculated the sample size as follows [15]: Z1a2 ¼ 1:96 a ¼ 0:05 1 b ¼ 0:80 Z1b ¼ 0:84
n¼
pffiffiffiffiffiffiffiffiffiffiffiffi!2 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi2 Z1a2 þ Z1b 1 r2 1:96 þ 0:84 1 0:82 þ2¼ þ 2 ¼ 11:5 r 0:8
According to the equation above, sample size was calculated nearly 12% in each group and we selected more percent in each group for great accuracy. Anthropometric measurements Anthropometric measurements were performed while subjects were wearing only light clothing and no shoes. Body mass index (BMI) was then calculated. Waist circumference was measured at the midway between the lowest rib and the iliac crest by using a flexible tape. The hip circumference was measured at the largest protrusion.
RMR and body composition measurements Resting metabolic rate (RMR) was measured by using indirect calorimetry by means of the Meta CheckTM (Korr Medical Technologies, Salt Lake City,UT). Predicted resting energy expenditure for each subject was obtained using the Harris–Benedict equation [16]. Body composition was measured by bioelectrical impedance (RJL Systems, Clinton Twp, MI). Measurements were performed on all subjects by professional nutritionists using a standard protocol.
Laboratory analyses Blood sample was drawn after at least 12 h of overnight fasting. UCP2 protein was measured by Human Uncoupling Protein2, ELISA kit (SL2021 Hu, Sunlong Biotech, HangZhou, China) in peripheral blood mononuclear cells (PBMCs). Total protein in PBMCs was measured by Sensitive Protein (Bradford) Assay kit (ZB-BPA96A, V31130, ZellBio GmbH, Germany) to calculate ‘UCP2 protein/Total protein’ ratio. Since measurements were taken using extracted PBMCs from blood, the amount of cells extracted from different subjects may be different. Therefore, the more accurate measurement is ‘UCP2/Total protein ratio.’ Plasma adiponectin was measured by ELISE kit (Human adiponectin (ADP) ELISA Kit, SL0068Hu, Sunlong).
Statistical analyses Normal distribution of data was performed by using Kolmogorov–Smirnov. Differences between baseline characteristics, anthropometric measurements, body composition, REE, UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin between groups were tested by one-way analysis of variance (ANOVA) with post hoc tests and Kruskal–Wallis test, followed by Mann–Whitney U-test. Multiple linear regression analyses were performed to assess regression coefficients (b) and confidence intervals (95% CI) for association between the level of UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin. Two models were considered in these regression analyses. The first model was crude and the second model was adjusted for age and BMI. Moreover, multiple linear regression analyses were carried out to verify association between REE and plasma adiponectin. Besides, two models were considered in these multivariate regression analyses. The first model was crude and the second model was energy intake and BMI. Analyses were performed using SPSS version 20 (Chicago, IL). A p values < .05 was considered statistically significant.
Results Table 1 shows anthropometric measurements, body composition, REE, UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin in three groups. There was a significant difference in waist circumference between the two obese groups. Hip and waist circumference were significantly increased in obese subjects. There were no significant differences between age and height in the three groups. Fat mass and fat-free mass were significantly increased in obese subjects, but there was no significant difference in body composition between two obese groups. There was a significant difference in MREE between three groups. MREE in obese group with low REE was significantly lower than other groups. There were no significant differences between UCP2 protein and ‘UCP2 protein/Total protein’ ratio in three groups. Plasma adiponectin in the obese group with low REE was significantly lower compared to normal weight group. Table 2 shows association between the level of UCP2 protein, ‘UCP2 protein/Total protein’ ratio and plasma adiponectin. According to linear regression, there was no relationship between UCP2 protein and plasma adiponectin, when compared to each group separately and in three groups when we pooled. There was a significant relationship between ‘UCP2 protein/Total protein’ ratio and plasma adiponectin in obese subjects with low REE and in three groups when we pooled. Table 3 shows association between REE and plasma adiponectin. According to linear regression, there was a significant association between REE and plasma adiponectin in three groups when we pooled.
Discussion The aim of this study was to investigate association between adiponectin, uncoupling protein 2 and REE in obese women with normal and low resting energy expenditure. Adiponectin is a 244-amino acid collagen-like protein which secreted by adipocyte that acts as a hormone with anti-inflammatory and insulin-sensitizing properties. Moreover, it was suggested that adiponectin serves as a central regulatory protein in many metabolic pathways that play important role in many metabolic disorders [11].
.18 4.98 ± 1.70 7.07 ± 1.57 .00 1.83 ± 0.84 7.07 ± 1.57 .40 4.98 ± 1.70 1.83 ± 0.84
Values are Means ± SE. Significant difference between REE (Measure), REE (Estimate), FM(%), FFM(kg), weight (kg) by ANOVA with Tukey's post hoc tests. Significant difference between FM (kg), FFM (%), REE (Estimate), Waist circumference (cm), Hip circumference (cm) by Kruskal–Wallis with Mann–Whitney.
.15 .00 .19 .00 .00 .01 .00 .00 .00 .00 .00 .16 .18 37.70 ± 1.85 86.86 ± 2.16 159.11 ± 1.48 90.47 ± 2.16 114.76 ± 2.07 1895.64 ± 76.71 1759.39 ± 28.75 41.65 ± 1.46 47.80 ± 0.71 45.20 ± 0.97 52.19 ± 0.71 281.28 ± 47.02 3.99 ± 0.71 32.87 ± 1.89 59.38 ± 1.04 161.87 ± 1.42 67.31 ± 1.08 95.18 ± 1.23 1624.50 ± 70.82 1498.50 ± 19.29 18.82 ± 0.54 31.68 ± 0.69 40.56 ± 0.79 68.31 ± 0.69 183.67 ± 49.27 2.61 ± 0.71 .14 .00 .95 .00 .00 .00 .00 .00 .00 .01 .00 .40 .89 37.81 ± 1.64 81.02 ± 2.23 161.18 ± 1.40 82.75 ± 1.40 111.31 ± 1.95 1235.81 ± 30.41 1699.78 ± 29.88 37.08 ± 1.77 45.43 ± 0.98 43.94 ± 0.64 51.56 ± 2.32 263.58 ± 67.44 3.17 ± 0.84 32.87 ± 1.89 59.38 ± 1.04 161.87 ± 1.42 67.31 ± 1.08 95.18 ± 1.23 1624.50 ± 70.82 1498.50 ± 19.29 18.82 ± 0.54 31.68 ± 0.69 40.56 ± 0.79 68.31 ± 0.69 183.67 ± 49.27 2.61 ± 0.71 37.81 ± 1.64 81.02 ± 2.23 161.18 ± 1.40 82.75 ± 1.40 111.31 ± 1.95 1235.81 ± 30.41 1699.78 ± 29.88 37.08 ± 1.77 45.43 ± 0.98 43.94 ± 0.64 51.56 ± 2.32 263.58 ± 67.44 3.17 ± 0.84
Age (years) Weight (kg) Height (cm) Waist circumference (cm) Hip circumference (cm) REE (kcal/day) measure REE (kcal/day) estimate FM (kg) FM (%) FFM (kg) FFM (%) UCP2 (pg/ml) ‘UCP2 protein/Total protein’ (pg/mg) Plasma adiponectin (mg/L)
.99 .08 .32 .00 .37 .00 .25 .05 .10 .52 .27 .91 .57 37.70 ± 1.85 86.86 ± 2.16 159.11 ± 1.48 90.47 ± 2.16 114.76 ± 2.07 1895.64 ± 76.71 1759.39 ± 28.75 41.65 ± 1.46 47.80 ± 0.71 45.20 ± 0.97 52.19 ± 0.71 281.28 ± 47.02 3.99 ± 0.71
Obese with low REE N ¼ 16 Groups variables
Table 1. Characteristics of study subjects.
Obese with normal REE N ¼ 17
p value
Control N ¼ 16
Obese with low REE N ¼ 16
p value
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Control N ¼ 16
Obese with normal REE N ¼ 17
p value
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Some studies have showed the reduction in plasma adiponectin in obese subjects [10]. Similar to these finding, we showed plasma adiponectin in obese subjects was lower than normal weight subjects. Some studies have reported reverse correlation between plasma adiponectin and body mass index [17]. Moreover, some studies have suggested that increase and accumulation of abdominal visceral adipose tissue in obese subjects plays a crucial role in reduction of plasma adiponectin in these people [18]. Some mechanisms have been suggested for this relationship; fat accumulation in obese subjects may increase in oxidative stress and lead to dysregulation in production and secretion of adipocytokines such as adiponectin [19]. In this condition, PPAR-c (peroxisome proliferator-activated receptor-c) is the main regulator for adiponectin transcription in which suppresses by oxidative elements and lead to reduction in expression and plasma level of adiponectin [20]. Adiponectin has been shown to either increase [21] or reduce [22] energy expenditure. It has been reported intracerebroventricular administration of recombinant adiponectin decreases body weight and fat by increasing energy expenditure without affecting food intake [23,24]. Some studies have suggested that adiponectin plays a key role in the control of energy homeostasis through the regulation of glucose and fatty acid metabolism in peripheral tissues such as muscle and liver [10]. Adiponectin upregulated acyl-coenzyme A oxidase and uncoupling protein 2, leading to enhanced lipid catabolism [25]. Some studies have also reported that adiponectin decrease energy expenditure as manifested by lower body temperature, low oxygen consumption and downregulation of uncoupling protein 1 [22]. It has been suggested adiponectin effects on whole-body energy metabolism by controlling AMPK (monophosphate-activated protein kinase) activity in skeletal muscle, liver and adipose tissue and by the control of transcription factor expression [25]. Since mitochondria are essential for energy production at cellular level, differences in energy expenditure and basal metabolism may be attributed to mitochondrial functions [26]. Moreover some studies showed mitochondrial dysfunction, reduction in activity of marker enzymes of oxidative pathways, mitochondrial degeneration and reduced respiratory capacity in obese people [27,28]. Moreover, it was suggested some adipokines and hormones that produced by adipose tissue may affecting on mitochondrial functions and energy hemostasis [29] Uncoupling protein 2 belongs to the family of mitochondrial transporter proteins that may translocate protons into the mitochondrial matrix, resulting in heat generation without ATP synthesis [30]. We showed in other study association between UCP2 protein and resting energy expenditure. We demonstrated increased risk of reduced resting energy expenditure in obese subjects with low level of UCP2 protein. Association between adiponectin and UCP2 protein has suggested in some studies [12]. Our findings demonstrated association between adiponectin and UCP2 protein in obese group with low REE. Similar to our finding, Mahandik et al. has showed positive correlation between UCP2 mRNA and plasma adiponectin [31]. Some mechanisms have suggested for these relationships. Some studies that carried out on animal model have showed that uncoupling protein 2 controls adiponectin gene expression in adipose tissue through the modulation of reactive oxygen species production. It has been observed that circulating adiponectin levels and adiponectin
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Table 2. Association between the level of UCP2 protein (pg/mg), ‘UCP2 protein/Total protein’ ratio and plasma adiponectin (mg/L) in linear regression. Plasma adiponectin (mg/L) 95% CIa
95% CI Groups Obese with low REE (N ¼ 16) Obese with normal REE (N ¼ 17) Control (N ¼ 16) Total (N ¼ 49) Obese with low REE (N ¼ 16) Obese with normal REE (N ¼ 17) Control (N ¼ 16) Total (N ¼ 49) a
b
Lower
Upper
p value
ba
Lower
Upper
p valuea
31.08 5.66 1.64 2.96 0.63 0.07 0.03 0.11
15.21 10.55 21.29 8.40 0.05 0.19 0.25 0.04
77.37 21.88 18.01 14.34 1.20 0.34 0.32 0.27
.16 .46 .85 .60 .03 .55 .79 .15
25.44 13.92 3.19 11.14 0.41 0.18 .004 0.17
59.63 3.02 36.33 1.70 0.24 0.08 0.51 0.003
110.51 30.86 42.72 23.99 1.06 0.45 0.50 0.34
.50 .09 .85 .08 .18 .15 .98 .04
Variables UCP2 (pg/ml)
UCP2/Tpr (pg/mg)
Adjusted for age and BMI.
Table 3. Association between REE (kcal/day) and plasma adiponectin (mg/L) in linear regression. REE (kcal/day) 95% CIa
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95% CI Groups Obese with low REE (N ¼ 16) Obese with normal REE (N ¼ 17) Control (N ¼ 16) Total (N ¼ 49) a
Variables
b
Lower
Upper
p value
ba
Lower
Upper
p valuea
Plasma adiponectin (mg/L)
8.66 6.85 8.71 9.74
30.99 23.38 32.54 9.97
13.67 37.10 15.10 29.46
.41 .63 .44 .32
18.21 6.59 5.28 21.39
91.88 29.44 32.63 0.94
55.44 42.64 22.06 41.85
.57 .69 .67 .04
Adjusted for energy intake and BMI.
gene expression in adipose tissue were reduced in UCP2-null mice [12]. Other studies have showed that adiponectin plays a role in UCP2 gene expression. Adiponectin stimulates UCP2 expression through AMPK and PPAR-alpha-signaling pathways in many tissues [32]. In conclusion, there was a significant association between plasma adiponectin and REE. Moreover, there was a significant relationship between UCP2 and REE. It was suggested that variation in resting energy expenditure in obese subjects may be relate to these factors.
7. 8. 9. 10. 11. 12.
Disclosure statement
13.
All authors declare that they have no conflict of interests. 14.
Funding We would like to thank the Research Council of Tehran University of Medical Sciences (28767) for their financial support and all the subjects who participated in this study.
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