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OBESITY | VOLUME 18 NUMBER 11 | NOVEMBER 2010 2125 nature publishing group ARTICLES INTEGRATIVE PHYSIOLOGY INTRODUCTION It was believed for a long time that simply an inert energy storage tissue with irrelevant metabolic activity, in the last years the adipose tissue, properly defned adipose organ (1), has been assuming a constantly growing metabolic relevance due to its pleiotropic functions. Indeed, besides its well-known funda- mental function in regulating energy homeosta
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  OBESITY |  VOLUME 18 NUMBER 11  |  NOVEMBER 2010  2125 nature publishing group  ARTICLES INTEGRATIVE PHYSIOLOGY INTRODUCTION It was believed or a long time that simply an inert energy storage tissue with irrelevant metabolic activity, in the last years the adipose tissue, properly defined adipose organ (1), has been assuming a constantly growing metabolic relevance due to its pleiotropic unctions. Indeed, besides its well-known unda- mental unction in regulating energy homeostasis, adipocytes also mediate many physiologic and pathologic processes by means o numerous secretory products. In this regard, adipocytokines, such as leptin and adipo-nectin, and proinflammatory actors, such as tumor necrosis actor (NF-α), interleukin (IL)-6 and 1, have been demon-strated to play an important role in the onset o the major obesity-related comorbidities (2,3). Several lines o evidence suggest that obesity cannot be characterized only by BMI. Percentage at mass (FM) and at distribution may be different in subjects with the same BMI, and lean and obese subjects share different metabolic characteristics (4,5). Furthermore, ethnic differences in body composition are well known (6) and specific values or waist circumerence (W) and central obesity definition have been thereore proposed (7). Moreover, in white women two condi- tions o normal weight and increased body at composition have been recently characterized and have been described as metabolically obese normal weight (8) and normal-weight obese (NWO) (9).Te NWO syndrome, the distinctive characteristic o 33.7% o healthy emale subjects studied, was characterized by a normal BMI (<25 kg/m 2 ), but high FM percentage (FM% >30%), and significantly higher values o proinflammatory cytokines (10). NWO were similar to preobese-obese (OB) women not only or at body mass distribution, but also or cardiovascular (CVD) risk index values. Tey also do not maniest the metabolic syndrome, despite ew, i any, metabolic abnormalities (11). Oxidative Stress in Normal-Weight Obese Syndrome Laura Di Renzo 1,2 , Fabio Galvano 3 , Carmine Orlandi 1 , Alessia Bianchi 1 , Claudia Di Giacomo 3 , Luca La Fauci 3 , Rosaria Acquaviva 3  and Antonino De Lorenzo 1,2 The normal-weight obese (NWO) syndrome was identified in women whose body weight (BW) and BMI are normal but whose fat mass (FM) is >30%. In these subjects, an early inflammatory status has been demonstrated. The aim was to verify whether oxidative stress occurs in NWO. Sixty age-matched white Italian women were studied and subdivided as follows: 20 normal-weight individuals (NW) (BMI <25 kg/m 2 ; FM% <30%); 20 NWO (BMI <25 kg/m 2 ; FM% >30%); 20 preobese-obese (OB) (BMI >25 kg/m 2 ; FM% >30%). Anthropometric, body composition (by dual-energy X-ray absorptiometry) variables, plasma levels of some cytokines, reduced glutathione (GSH), lipid hydroperoxide (LOOH), nitric oxide (NO) metabolites (NO 2−  /NO 3−  ), antioxidant nonproteic capacity (ANPC) were measured and compared between groups. Glucose and lipid metabolism parameters were assessed. GSH and NO 2−  /NO 3−  levels resulted lower in OB and NWO compared to NW (  P  < 0.01). LOOH levels resulted higher in OB and NWO (  P  < 0.01). ANPC in NWO was lower than NW but higher with respect to OB (  P  < 0.01). Correlation analysis revealed strong associations between GSH levels and BW, BMI, FM% (  R  = −0.45, at least P  < 0.05); waist circumference (W) (  R  = −0.33, P  < 0.05); FFM% (  R  = 0.45, P  < 0.01); IL-1 α , IL-6, IL-10, IL-15 (  R  = −0.39, −0.33, −0.36 −0.34, respectively, P  < 0.05); triglycerides (  R  = −0.416, P  < 0.05). LOOH levels were negatively related to FFM% (  R  = −0.413, P  < 0.05) and positively to FM%, IL-15, TNF- α , insulin, total cholesterol, low-density lipoprotein cholesterol, and triglycerides (  R  = 0.408, R  = 0.502, R = 0.341, R  = 0.412, R  = 0.4036, R  = 0.405, R  = 0.405, respectively, P  < 0.05). The study clearly indicates that NWO, besides being in early inflammatory status, are contextually exposed to an oxidative stress related to metabolic abnormalities occurring in obesity. Obesity   (2010) 18,  2125–2130. doi:10.1038/oby.2010.50 1 Division of Human Nutrition, Department of Neuroscience, University of Rome Tor Vergata, Rome, Italy; 2 I.N.Di.M., National Institute for Mediterranean Diet and Nutrigenomic, Reggio Calabria, Italy; 3 Division of Medical Chemistry and Molecular Biology, Department of Biological Chemistry, University of Catania, Catania, Italy. Correspondence: Antonino De Lorenzo (delorenzo@uniroma2.it ) Received 14 October 2009; accepted 16 February 2010; published online 25 March 2010. doi:10.1038/oby.2010.50  2126    VOLUME 18 NUMBER 11 |  NOVEMBER 2010 |  www.obesityjournal.org ARTICLES INTEGRATIVE PHYSIOLOGY Overall, in obese subjects an inflammatory status is accompanied by oxidative stress as recently underlined by two  valuable reviews (12,13). According to Grattagliano et al. , the associations between increased abdominal at and systemic oxidative stress, the diminished concentration o nitric oxide (NO) derivatives and antioxidant vitamins, and the endothe- lial oxidative damages, observed in subjects with the metabolic syndrome, definitively support oxidative stress, as the common second-level event, in a uniying pathogenic view. de Ferranti and Mozaffarian efficaciously defined as the  perfect storm  the  vicious circle linking obesity, oxidative stress, inflammation, and metabolic disorders.Te objective o the present study was to veriy the hypoth-esis that in NWO women early inflammation is accompanied by oxidative stress. With this aim, we evaluated our oxidative stress markers in plasma: glutathione (GSH), lipid hydroper-oxide (LOOH), NO metabolites (NO 2− /NO 3− ) levels, and antioxidant nonproteic capacity (ANPC) on the same NWO women previously investigated (10). Moreover, we examined the relationship among markers o oxidative stress and body composition, and cytokines level, and metabolic parameters, in all the study population. METHODS AND PROCEDURESSubject characteristics Te study population comprised 60 white Italian women (aged 20–35 years) previously selected in the study o De Lorenzo et al.  (10). Subjects were divided into three groups: (i) 20 women with a normal weight and a BMI <25 kg/m 2  (control group, NW); (ii) 20 NWO women with a normal weight, a BMI <25 kg/m 2 , and a FM% >30%; and (iii) 20 OB women with a BMI >25 kg/m 2  and a FM% >30%. Te subjects were classified as OB according to a World Health Organization echnical Report and a World Health Organization echnical Report Series (14,15). All o the women were ree o hypertension and CVD, had regular 28-day menstrual cycles, were in generally good health, did not assume antioxidant supplementations, did not smoke or abuse alcohol, and did not take any hormonal contraceptives or any other drug. All o the subjects provided consent to take part in the study, which was conducted according to the guidelines of the “Tor Vergata” University Medical Ethical Committee, Rome, Italy. Anthropometric measurements Afer a 12-h overnight ast, all subjects underwent anthropometric evaluation. Anthropometric parameters o all the participants were measured according to standard methods (body weight (BW), height and W) (16). Subjects were instructed to take off their clothes and shoes beore perorming all the measurements. BW (kg) was measured to the nearest 0.1 kg, using a balance scale (Invernizzi, Rome, Italy). Height (cm) was measured using a stadiometry to the nearest 0.1 cm (Invernizzi, Rome, Italy). W was measured with a flexible steel metric tape to the nearest 0.5 cm, at the horizontal plane that corresponds with the narrowest point between the crest iliac and the bottom rib. BMI was calculated using the ormula: BMI = BW (kg)/height (m) 2 . Dual-energy X-ray absorptiometry Te total body composition was assessed by dual-energy X-ray absorp-tiometry (Lunar DPX; GE Medical Systems, Milwaukee, WI), according to the previously described procedure (11). Te average measurement time was 20 min. Te effective radiation dose rom this procedure is about 0.01 mSv. Te coefficient o variation (CV% = 100 × s.d./mean) intra- and intersubjects ranged rom 1 to 5%. Te coefficient o vari- ation or bone measurements is <1%; coefficient o variations on this instrument or five subjects scanned six times over a 9-month period were 2.2% or FM, and 1.1% or lean body mass. Te expected and reerence values or FM% in NWO women were 30.1–48.3%. Hematological sampling and measurements Heparinized venous blood was collected afer overnight asting and between days 8 and 12 o the preovulation phase. Standard serum lab- oratory tests o asting glucose, insulin, cholesterol, and triglycerides were carried out by the accredited Clinical Chemical Laboratories o the “or Vergata” Polyclinic (PV) o Rome, Italy. Plasma or GSH, LOOH, NO 2− /NO 3−  and ANPC assays was separated by centriugation at 800  g    or 10 min. Levels o total GSH were measured, in 200 µl o plasma, using Miao Lin’s method (17). Plasmatic LOOH levels were measured ollowing the oxidation o Fe 2+  to Fe 3+  in the presence o xylenol orange at  λ  = 560 nm (18). Plasmatic NO 2− /NO 3−  concentrations were deter- mined with Griess reagent at  λ  = 540 nm (19). ANPC o human plasma was evaluated measuring its ree-radical scavenging ability. Superoxide anion was generated in vitro  as described by Russo et al.  (20). Immunological assay Blood samples (5 ml) were collected between days 8 and 12 o the preo-  vulation phase into sterile tubes containing EDA (evacuated tubes),  via venipuncture early in the morning, afer an overnight ast (12 h). All materials were immediately placed in ice, and plasma was separated by centriugation at 1,600  g   or 10 min at 4 °C. Plasma samples were stored at −70 °C in 1-ml aliquots until assayed. Plasma concentrations o IL-1α, IL-1β, IL-6, IL-10, IL-15, NF-α cytokines were determined in duplicate using a high sensitivity commercial sandwich enzyme-linked immunosorbent assay kit (SearchLight Human Inflammatory Cytokine Array 1; Endogen, Perbio, Brebières, France). All assay procedures were perormed as described by the manuacturer. Te lower limit o cytokine’s detection was 0.02 pg/ml. Statistical analysis Data are presented as group means ± s.d. Data were analyzed by non- parametric methods to avoid assumptions about the distribution o the measured variables. Te Mann–Whitney analysis o variance test was used to compare groups. Associations between parameters were assessed using the Spearman’s rank correlation test. All tests were con-sidered significant at P   < 0.05. Statistical analysis was perormed using a computer sofware package (SPSS or Windows, version 13.0; SPSS, Chicago, IL). RESULTS All the 60 enrolled individuals completed the study and their results were eligible or data analysis. Te anthropometric and body composition characteris-tics, i.e., BMI and FM%, o the studied groups are presented in Figures 1  and  2 . As expected, BMI and FM% values o NWO were ound in an intermediate position between NW and OB. Significant differences in FM% between NW and NWO, NW and OB were observed ( P   < 0.05), but not between NWO and OB. Te z  -score BMI was calculated or each group; NW: −0.89 ± 0.40; NOW: −0.24 ± 0.34; OB: 1.16 ± 0.95. Significant difference in BMI between each group was obtained ( P   < 0.05). Moreover, the three groups differed also or BW (NW: 51.8 ± 4.6 kg; NWO: 59.6 ± 7.2 kg; OB: 70.9 ± 10.3 kg; P   < 0.05) and or W (NW: 65.1 ± 3.9 cm; NWO: 72.3 ± 4.9 cm; OB: 85.9 ± 10.2 cm; P   < 0.05; data not shown).Te mean values o GSH, ANPC, LOOH, NO 2− /NO 3−  or the NW, NWO, and OB are given in  Table 1 . Plasma GSH levels were lower in OB and NWO than in NW ( P   < 0.01). Te present  OBESITY |  VOLUME 18 NUMBER 11  |  NOVEMBER 2010  2127 ARTICLES INTEGRATIVE PHYSIOLOGY study highlighted a significant reduction o ANPC values in NWO with respect to controls ( P   < 0.01); moreover, ANPC in OB was significantly lower ( P   < 0.01) than in NWO and NW. Coherently with low plasmatic GSH and ANPC levels, LOOH concentration resulted higher in OB and NWO than in NW ones ( P   < 0.01). Additionally, the concentration o NO 2− /NO 3−  resulted lower in OB and NWO than in NW ( P   < 0.01).Plasma IL-1α, IL-2β, IL-6, IL-10, IL-15 and NF-α levels o the three groups are shown in  Figure 3 . Plasma cytokines con- centration was higher in OB and NWO, with respect to NW (NF-α and IL-6, both P   < 0.001; IL-1α, IL-2β, IL-15, all P   < 0.05). Instead, the anti-inflammatory IL-10 was not altered both in NWO and OB with respect to NW. No significant differ-ences in cytokines levels between NWO and OB were obtained. Spearman’s correlation between inflammatory cytokines con- centration and body composition parameters revealed signifi-cant associations o BW ( R  = 0.436, P   < 0.01), BMI ( R  = 0.520, P   < 0.01), ree FM percentage (FFM%) ( R  = −0.651, P   < 0.001), FM% ( R  = 0.630, P   < 0.001), W ( R  = 0.508, P   < 0.01), only with IL-15 (data not shown). Spearman’s correlation was perormed to evaluate the rela-tionship between oxidative stress, inflammation, and body composition parameters ( Table 2 ). GSH concentration was negatively related to weight, BMI, W, FM% ( P   < 0.01), IL-1α, IL-6, IL-10, IL-15 ( P   < 0.05); and positively related to FFM% ( P   < 0.01). LOOH was negatively associated with FFM% ( P   < 0,01) and positively with FM% ( P   < 0.01), NF-α and IL-15 ( P   < 0,05 both). A strong negative correlation between GSH and LOOH levels was also ound ( R  = −0.762, P   < 0.01). NO 2− /NO 3−  con-centration was negatively related to IL-15 ( P   < 0.05). Any corre-lation between ANPC% and body composition, inflammatory parameters was obtained. A significant negative correlation between ANPC% and GSH was highlighted ( P   < 0.05). Spearman’s correlation between inflammation, oxidative stress, and glucose/lipid metabolism blood parameters was perormed ( Table 3 ). GSH levels were negatively related to triglycerides ( R  = −0,4416, P   < 0.05). A multiple positive cor-relation was observed between LOOH and: insulin ( R  = 0.414, P   < 0.05); total cholesterol ( R  = 0.436, P   < 0.05); low-density lipoprotein cholesterol ( R  = 0.405, P   < 0.05); and triglycer- ides ( R  = 0.405, P   < 0.05). No significant correlations between inflammation and glucose/lipid metabolism blood parameters were observed. 051015202530NWNWOOB ** *    B   M   I   (   k  g   /  m    2    ) 35 Figure 1 Characterization of the studied groups through BMI. All values are mean ± s.d.; BMI z  -score NW: −0.89 ± 0.40; NWO: −0.24 ± 0.34; OB: 1.16 ± 0.95. *Significantly different, P   < 0.05 (Mann–Whitney test); n   = 20 for each group. NW, normal weight; NWO, normal-weight obese; OB, preobese-obese. 051015202530NWNWOOB **    F  a   t  m  a  s  s   (   %   )  3540455055 Figure 2 Characterization of the studied groups through fat mass content (in percentage). All values are mean ± s.d. *Significantly different, P   < 0.05 (Mann–Whitney test); n   = 20 for each group. NW, normal weight; NWO, normal-weight obese; OB, preobese-obese. Table 1 Plasma oxidative markers of the studied groups ParametersGroupsNW (   n  = 20)NWO (   n  = 20)OB (   n  = 20) GSH (µmol/ml)0.56 ± 0.050.44 ± 0.05*0.43 ± 0.04*LOOH (µmol/ml)38.61 ± 1.9466.76 ± 4.73*71.50 ± 6.94*NO 2−  /NO 3−  (nmol/ml)91.94 ± 4.6063.09 ± 4.41*66.43 ± 3.98* ANPC (%)99.25 ± 2.0375.47 ± 4.11*54.61 ± 5.52* , **  All values are mean ± s.d. ANPC, antioxidant non proteic capacity (%); GSH, reduced glutathione; LOOH, lipid hydroperoxide; NO 2−  /NO 3− , nitrite/nitrate; NW, normal weight; NWO, normal weight obese; OB, preobese-obese.*Significantly different from NW group, P   < 0.01 (Mann–Whitney test). **Signifi-cantly different from NWO group, P   < 0.01 (Mann–Whitney test). 0IL-1 α  IL-1 β  IL-6 IL-10 IL-15 TNF- α 510 ******* 15202530NWNWOOB    P   l  a  s  m  a  c  o  n  c  e  n   t  r  a   t   i  o  n   (  p  g   /  m   l   ) 3540605550456570 Figure 3 Plasma cytokine levels in all studied groups. All values are mean ± s.d. *Significantly different from other groups. P   < 0.05 (Mann–Whitney test); **significantly different from other groups, P   < 0.001 (Mann–Whitney test); n   = 20 for each group. NW, normal weight; NWO, normal-weight obese; OB, preobese-obese.  2128    VOLUME 18 NUMBER 11 |  NOVEMBER 2010 |  www.obesityjournal.org ARTICLES INTEGRATIVE PHYSIOLOGY DISCUSSION Oxidant stress may be an important pathogenic mechanism in the obesity-associated metabolic syndrome (21), and it plays a critical role in the pathogenesis o various diseases such as atherosclerosis cancer, CVDs, and diabetes mellitus (22,23). Oxidant stress results when ree-radical ormation is greatly increased or protective antioxidant mechanisms are compro-mised. Several research studies have suggested that obesity is associated with increased oxidant stress (24,25). However, recently, Brown et al.  demonstrated that only obesity, and not moderate overweight, elevates LOOH levels (26). In this article, we demonstrate, or the first time, that in NWO syndrome (12–14) overall the inflammatory status and the FM in excess are accompanied by oxidative stress. Indeed, in NWO, all the investigated markers o oxidative stress were comparable to those o OB except or ANPC that remains at an intermediate position between NW and OB. GSH represents about 90% o nonproteic thiol groups and has a protective role against oxidative and ree radical-medi- ated injury. An overall decrease in GSH levels has been associ-ated with chronic inflammatory diseases, and obesity does not seem to be an exception (27,28). Our data not only confirmed a significant lower GSH level in OB than NW, but also evidenced a comparable concentration o GSH between NWO and OB. Te negative correlations between GSH and body composition parameters, IL-lα, IL-6, and the anti-inflammatory IL-10, IL-15 urther support the association between oxidative stress and inflammation. Moreover, the negative correlation with triglyc-eride levels highlights the implication o a reduced antioxidant deense on metabolic abnormalities occurring in obesity. Lipid peroxidation is a well-known example o early oxi-dative damage in cell membranes, lipoproteins, and other lipid-containing structures. Our data clearly add urther evidences o the increased LOOH level in OB, comparable to NWO. Te significant association between LOOH levels and body composition, i.e., positive with FM% and negative with FFM%, gives efforts to the relationship between LOOH and some inflammatory cytokines herein observed. Te sig- nificant correlation between LOOH and most o the glucose/ lipid metabolism blood parameters finally stresses the direct effect o oxidative stress on metabolic abnormalities, involved in CVDs. Te increase o lipid peroxidation in OB is coherent with other studies (29,30). However, to our best knowledge, no literature data are available about lipid peroxidation in NWO. Recently, Brown et al.  (26) confirmed that LOOH was increased in obese subjects but not in overweight subjects, and Table 3 Correlation analysis between oxidative stress, inflammation and glucose/lipid metabolism blood parameters in all the study population Fasting glucoseFasting insulinTotal cholesterolLDL cholesterolHDL cholesterolTriglycerides IL-1 α −0,1520,081−0,097−0,1060,151−0,036IL-1 β −0,162−0,0580,1460,0980,3210,032IL-6−0,1860,140−0,118−0,1170,120−0,142IL-10−0,165−0,0840,1390,0580,2780,195IL-15−0,0410,074−0,0620,068−0,2380,006 TNF- α 0,0000,1480,1150,276−0,1520,061GSH0,029−0,031−0,291−0,229−0,049−0,416*LOOH0,0370,412*0,436*0,405*−0,0610,405*NO 2−  /NO 3− −0,0680,0650,1050,0740,0310,163 ANPC%−0,0880,249−0,083−0,051−0,1600,217 Data are correlation coefficients of Spearman analysis. ANPC, antioxidant non proteic capacity (%); GSH, reduced glutathione; HDL, high-density lipoprotein; IL, interleukin; LDL, low-density lipoprotein; LOOH, lipid hydroper-oxide;  n  = 60, total population; NO 2−  /NO 3− , nitrite/nitrate; TNF- α , tumor necrosis factor- α .* P   ≤  0.05. Table 2 Correlation analysis between oxidative stress, inflammation and body composition parameters in all the study population GSHLOOHNO 2−  /NO 3−  ANPC% BW−0.453**0.091−0.1000.257BMI−0.459**0.249−0.1740.249FFM%0.450**−0.413*0.172−0.280FM%−0.445*0.408*−0.1790.276W−0.326*0.106−0.191−0.243IL-1 α −0.391*0.0780.1680.266IL-1 β −0.216−0.0180.1430.051IL-6−0.325*0.0480.1090.261IL-10−0.357*0.343−0.0730.088IL-15−0.341*0.502*−0.405*0.059 TNF α 0.0590.341*−0.245−0.203GSH—−0.762**−0.183−0.490**LOOH−0.762**—−0.1330.210NO 2−  /NO 3− −0.183−0.133—0.279 ANPC%−0.490*0.2100.279— Data are correlation coefficients of Spearman analysis. ANPC, antioxidant non proteic capacity (%); BW, body weight; FFM, fat free mass; FM, fat mass; GSH, reduced glutathione; IL, interleukin; LOOH, lipid hydroperoxide;  n  = 60, total population; NO 2−  /NO 3− , nitrite/nitrate; TNF- α , tumor necrosis factor- α ; W, waist circumference.* P   ≤  0.05; ** P ≤ 0.01.
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