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University Hospital for Children and Adolescents (A.B., G.M., T.M.K., S.B., E.K., W.K.); Institute of Laboratory Medicine, Clinical Chemistry, and Molecular Diagnosis (J.K.); and Interdisciplinary Center for Clinical Research (M.B.), University of Leipzig, 04317 Leipzig, Germany
Address all correspondence and requests for reprints to: Dr. Antje Böttner, Research Laboratory, University Hospital for Children and Adolescents, University of Leipzig, Oststrasse 21–25, 04317 Leipzig, Germany. E-mail: antje.boettner{at}medizin.uni-leipzig.de.
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Abstract |
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 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Obesity is also an increasing problem in children, with up to 30% of children and adolescents being obese in industrialized countries (12). Even more worrisome is the early development of obesity-associated metabolic alterations, such as impaired glucose tolerance and type 2 diabetes in obese children (13, 14). However, little is known about the association of adiponectin and obesity and its associated comorbidities in children. Although plasma adiponectin was suggested to decrease with the degree of adiposity in small cohorts of Hispanic and Pima Indian children (15, 16), adiponectin serum levels were not predictive for weight development in these groups, indicating that other factors may play an additive role (16). In particular, the influence of physical and pubertal development needs to be considered in children as has been shown for other adipocytokines (17). In animal studies it was suggested that pubertal development and the accompanying alterations in the endocrine system may affect adiponectin. In mice, adiponectin levels dynamically changed with sexual maturation (18) and were related to estrogens or testosterone (18, 19). However, the role of puberty has as yet not been systematically investigated in humans.
The goal of the present study was to elucidate the impact of gender, pubertal development, and obesity on adiponectin levels in children. To this end we analyzed adiponectin levels in two large and well characterized cohorts of normal weight and obese children covering a wide range of age and body mass indexes (BMI) to 1) assess systematically the dynamics of adiponectin during pubertal development in children, 2) compare adiponectin levels between obese and normal weight children, and 3) evaluate the association of adiponectin with the emergence of insulin resistance in children and adolescents.
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Subjects and Methods |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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The study population consisted of 200 healthy normal weight and 135 obese Caucasian children and adolescents. Characteristics of study populations are shown in Table 1
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Obese children. A total of 135 Caucasian children and adolescents with a BMI SDS greater than 1.5 were consecutively recruited from our obesity clinic. Ten of the obese children had follow-up analyses that were included in the correlation analysis but excluded from comparative analyses. The cohort included 22 girls (aged 15.11 ± 0.32 yr) diagnosed with polycystic ovary syndrome (PCOS) based on clinical criteria of hirsutism, oligo/amenorrhea, and hyperandrogenemia. A careful history and physical exam, including anthropometric measurements, were obtained from all subjects. Six adolescents with impaired glucose tolerance were receiving metformin therapy. Five patients received L-T4 replacement, but were clinically and biochemically euthyroid. Twelve girls were taking oral contraceptives.
Oral glucose tolerance test (oGTT)
An oGTT was performed in the obese children following the guidelines of the American Diabetes Association and the World Health Organization (21). Briefly, tests were performed at 0800 h after an overnight fast. Patients received 1.75 g/kg glucose, orally (maximum of 75 g). Blood samples were taken at –30, 0, 15, 30, 60, 90, 120, 150, and 180 min. All samples from an individual subject were analyzed together for adiponectin, glucose, and insulin serum concentrations.
The insulin resistance indexes were calculated according to the homeostasis model assessment (HOMA): HOMA = fasting plasma insulin (FPI, µU/ml) x fasting blood glucose (FBG, mmol/liter)/22.5 (22). The insulin sensitivity index (ISI) was calculated as: ISI = 10 000 / 
[(FBG x FPI) x (mean blood glucose x mean insulin during oGTT)] with glucose parameters given in millimoles per liter and insulin parameters given in microunits per milliliter (23).
Written informed consent for measurements and blood analyses was obtained from all guardians of the children. The study was approved by the ethical committee of University of Leipzig.
Measurement of anthropometric parameters
Height and weight were determined using precision stadiometers and scales to the nearest of 0.1 cm and 0.1 kg, respectively. For standardization of height and weight, reference percentiles for central Germany were applied (24, 25). The BMI was standardized referring to national reference data (26). The waist to hip ratio (WHR) was calculated from measurements of waist circumference at the smallest circumference between hip and chest, and hip circumference using a nonstretchable metric band. Stage of puberty was assessed according to Tanner. Data for these parameters are given as absolute values and/or SD score (SDS).
Biochemical analyses
For measurement of endocrine and metabolic parameters, we obtained blood samples at 0800 h from obese children and between 0800 and 1100 h from lean children. Serum was separated by centrifugation, and aliquots were stored at –80 C for biochemical analyses.
The soluble leptin receptor and leptin were measured using in-house RIAs as described previously (17, 27). Adiponectin levels were determined by RIA (Linco Research, Inc., St. Louis, MO) according to the manufacturer’s instructions. To minimize interassay variations, all samples were corrected for an internal control to attain comparable data. The sensitivity of the assay was calculated to be 1 ng/ml. Intra- and interassay coefficients of variation were less than 14% (n = 8) in our calculations. Testosterone and estradiol were determined by the Elecsys immunoassay system (Roche, Mannheim, Germany), with functional sensitivities of 0.42 nmol/liter and 55 pmol/liter, respectively. Intra- and interassay coefficients of variation were less than 7.0% (n = 14) for both methods. The determination of dehydroepiandrosterone sulfate (DHEA-S) and IGF-I levels in serum was performed by the Advantage immunoassay system (Nichols Institute, Bad Vilbel, Germany). An analytical sensitivity of 30 nmol/liter was calculated for DHEA-S, whereas the sensitivity of IGF-I was 6 ng/ml. Intra- as well as interassay coefficients of variation for both assays were less than 7.0% for samples in the normal range (n = 14). Insulin measurements were accomplished by the AutoDELFIA system (PerkinElmer, Brussels, Belgium). The analytical sensitivity of this assay was 3 pmol/liter; the intra- and interassay coefficients of variation were less than 5%. Leptin was measured by a competitive in-house RIA (27). The analytical sensitivity of the RIA was 0.2 ng/ml. Intra- and interassay coefficients of variation were lower than 12.5% for the range of 1–8 ng/ml leptin. Soluble leptin receptor was determined by an immunofunctional assay with an analytical sensitivity of 2 ng/ml; intra- and interassay coefficients of variation were less than 11.7% (17). Proinsulin was measured by a commercially available ELISA (IBL, Hamburg, Germany), with intra- and interassay coefficients of variation less than 12% and a sensitivity of 1 pmol/liter. Glucose, cholesterol, and uric acid were measured by the Modular system (Roche).
Statistical analyses
Data are presented as the mean ± SEM or as individual values for correlation plots. Because some parameters investigated did not adhere to normal distribution, comparison of variables was performed using Mann-Whitney U or Wilcoxon’s signed rank test. Spearman’s nonparametric correlations were calculated to determine relationships between variables. The threshold for statistical significance was set at P < 0.05.
Stepwise forward multiple regression analysis was performed gender-dependently using Statistica 5.0 (Statsoft, Tulsa, OK). Confidence limits for the coefficients of correlation were estimated by Stat Xact-5, version 5.0.3 (Cytel Software Corp., Cambridge, MA).
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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To characterize the association of adiponectin serum concentrations with the body fat mass and to evaluate differences between lean and obese children, we studied two large and well characterized cohorts of normal weight and obese children. Table 1
shows the baseline characteristics of the study populations.
We first aimed to establish normative data for adiponectin levels over a wide range of age and pubertal development in a cohort of healthy lean children and adolescents. For this, we selected 200 normal weight children and adolescents, aged 7.95–17.92 yr, from the Leipzig School Children project (20) (Fig. 1A) who were assigned to groups according to age and pubertal stage. Each group consisted of 17–22 individuals and evenly covered a wide range of BMI between –1.5 and +1.5 SDS, thus representing the normal age- and gender-specific range (Fig. 1B).
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), aged 3.36–17.77 yr, were consecutively recruited from our obesity clinic. This cohort included 22 girls with PCOS. As expected, the lean and obese groups were significantly different with regard to measures of body fat as well as height, in accordance with the developmental acceleration frequently seen in obese children. Effect of oral glucose load on adiponectin levels
To evaluate the effect of oral glucose load on adiponectin levels, we performed oral glucose tolerance tests in a subgroup of obese patients (n = 11). These patients included six girls and five boys, aged 5.4–16.3 yr, with a BMI between 2.1 and 4.1 SDS (one girl and one boy for every 0.5 BMI SDS between 2.0 and 
4.0 SDS). Five patients were prepubertal, and five patients had completed puberty.
After glucose administration, blood glucose and serum insulin levels expectedly increased several-fold (Fig. 2A). Adiponectin levels, in contrast, did not show significant alterations after glucose challenge (Fig. 2B). There was also no statistical correlation between adiponectin and glucose or insulin. Thus, adiponectin serum levels do not appear to be modulated by acute glucose challenge.
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We measured adiponectin serum levels in 200 normal weight school children to assess the association of adiponectin with anthropometric parameters. As expected, adiponectin levels correlated inversely with BMI (r = –0.23; P = 0.0009).
In our pediatric cohort, there was a tendency toward lower adiponectin levels in boys compared with girls (6.72 ± 0.22 vs. 7.30 ± 0.20 mg/liter; P = 0.062). Interestingly, in addition to BMI, adiponectin levels were significantly inversely related to parameters of physical and pubertal development, such as age, height, and IGF-I serum concentrations (Table 2).
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), which was not seen in girls. Accordingly, in boys there was a significant negative correlation between adiponectin and pubertal stage (r = –0.48; n = 98; P < 0.0001), whereas there was no such relationship in girls. This decline eventually led to significantly lower adiponectin levels in boys compared with girls after completion of puberty, similar to the differences reported for adults. To confirm this relationship between adiponectin and pubertal development and to more appropriately evaluate the association of adiponectin with gonadal development, we measured serum estrogen and testosterone levels. In addition, we determined DHEA-S as a marker of adrenarche and the first endocrine parameter of induction of puberty. All sex steroids showed the expected increase with pubertal development. Correlation analyses revealed the strongest negative correlation of adiponectin serum levels with testosterone in boys, whereas estradiol concentrations in girls were not significantly associated with adiponectin (Table 2). DHEA-S levels were higher in boys than in girls and showed a significant negative correlation with adiponectin similar to testosterone (Table 2).
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and in addition, pubertal stage, testicular volume, and serum testosterone and DHEA-S levels with adiponectin as the dependent variable, we identified pubertal stage (r2 = 0.206; ß = –0.433; P < 0.0001), BMI SDS (r2 = 0.034; ß = –0.247; P = 0.021), and testosterone (r2 = 0.039; ß = –0.219; P = 0.031) as significant independent determinants of adiponectin, explaining 29% of the variance (r2 = 0.292; P < 0.00002). Thus, in normal lean boys, the impact of pubertal stage is stronger than the degree of obesity or age. In summary, gender differences in adiponectin levels developed during pubertal development and were strongly associated with serum androgen concentrations.
Comparison of adiponectin levels between lean and obese children
Because gender and pubertal stage need to be considered when comparing adiponectin levels, we performed a comparative analysis of lean and obese children stratified for gender and pubertal stage. Adiponectin levels were significantly lower in obese children and adolescents compared with normal weight subjects (Fig. 4). These differences were present in prepubertal children and were even more pronounced in adolescents (data not shown).
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Association of adiponectin with anthropometric and metabolic parameters
Serum adiponectin levels were significantly associated with parameters of 1) obesity, such as BMI (Fig. 5A) and waist and hip circumference; 2) physical and pubertal development, including height and IGF-I levels; and 3) endocrine parameters, particularly androgens (Table 2). Generally, these associations appeared to be stronger in boys than in girls (data not shown). In addition, adiponectin levels were strongly associated with indexes of the metabolic syndrome, as determined by a significant negative correlation with the HOMA index (Fig. 5B), the insulin response to an oral glucose load (Fig. 5C), blood pressure, uric acid (Fig. 5D), and dyslipidemia. The coefficients of correlation for these parameters are shown in Table 2.
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). However, leptin did not show a similar relationship to androgens as that found for adiponectin.
To identify independent associations of these metabolic parameters with adiponectin, we performed stepwise multiple regression analysis. First, parameters were clustered and assigned to glucose metabolism, insulin parameters, and metabolic parameters. All models also included pubertal stage, gender, BMI, and age. Adiponectin was the dependent variable. In the group of glucose metabolism, only BMI and BMI SDS remained significant predictors of adiponectin. From the insulin parameters and calculated insulin resistance indexes, the ISI accounted for 26% of the variance in adiponectin. In the group of metabolic parameters, we identified uric acid, high-density lipoprotein (HDL) cholesterol, and pubertal stage as independent predictors of adiponectin. Finally, in a multiple regression model including the significant parameters from the clustered analyses, we confirmed that ISI, uric acid, ratio of proinsulin to insulin, and HDL cholesterol are independent predictors of adiponectin that override the effects of BMI and pubertal stage (Table 3).
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Initial analyses of our data indicated that adiponectin was associated with clinical and biochemical parameters of physical and pubertal development apart from the degree of obesity. This association needs to be considered when interpreting data from pediatric populations. One major finding of our study was that adiponectin levels decrease in parallel with the progression through puberty in boys, but this is not as pronounced in girls. The decline was significantly related to plasma androgen levels and subsequently leads to lower adiponectin levels in adolescent boys compared with girls after completion of puberty. In the multiple regression analysis in lean boys, pubertal stage was a much stronger predictor for adiponectin levels than BMI, underlining the strong impact of pubertal development. This progressive pattern with sexual maturation has to date not been shown for humans, but is well in accordance with animal studies. In mice, an increase in adiponectin during sexual differentiation was significantly less pronounced in male animals compared with females (18). The abrogation of androgen effects through neonatal castration led to increased adiponectin levels comparable to those in females, whereas ovariectomy did not interfere with the pubertal dynamics of adiponectin (18). Another study showed an elevation of adiponectin levels in castrated adult, but not neonatal, mice that decreased after testosterone had been substituted (19). This is consistent with experimental observations showing that testosterone inhibited adiponectin secretion from 3T3 adipocytes (19). Therefore, androgens are likely to play an important role in adiponectin levels in animals. The finding that androgens more closely correlate with adiponectin as opposed to estrogens in our study indicates that this hypothesis also applies to humans. In addition, an inhibitory role of adrenal androgens and steroids should be considered. Adrenalectomy restored the diminished adiponectin levels in obese ob/ob mice (28), and glucocorticoids were shown to suppress adiponectin expression in vitro (29). In our cohort, DHEA-S, which is an adrenal androgen that rises at the initiation of puberty, also significantly correlated inversely with adiponectin levels. Thus, increasing androgen levels during puberty may account for the decreased adiponectin levels in adolescent boys.
Hence, these androgen effects on adiponectin levels and the decline in adiponectin in boys, but not in girls, may well explain the uniformly reported gender differences in adults with lower adiponectin levels in males (30, 31, 32).
From numerous studies it was suggested that adiponectin constitutes an important protective factor in the pathogenesis of the metabolic syndrome and cardiovascular disease by exerting profound antidiabetic and antiatherogenic actions (33, 34). This is further supported by experimental studies showing that replenishment or administration of adiponectin results in an improvement of insulin sensitivity and endothelial function (6, 35). Diminished serum adiponectin concentrations, on the other hand, are predictive for the development of diabetes and cardiovascular disease (36, 37). Given the antidiabetic and antiatherogenic actions of adiponectin and the association of low adiponectin levels with higher risk for cardiovascular disease (8), reduced adiponectin concentrations in males may at least in part account for the higher incidence of cardiovascular disease in men due to a diminished protective effect of this molecule (37).
There is more evidence for a direct role of adiponectin in cardiovascular disease, in that endothelial function was shown to be impaired in proportion to the severity of obesity and was closely related to adiponectin (38). We recently reported that blood pressure values continuously increase with BMI in children and are particularly elevated in overweight and obese children (20). This observation along with data from other studies (39) suggest that higher blood pressure levels in obese children in relation to low adiponectin levels may constitute an early sign of disturbances in cardiovascular function (40) that occur as early as in adolescence and may eventually lead to the higher incidence of cardiovascular disease in obese adults.
Adiponectin levels are closely related to important risk factors of insulin resistance and the metabolic syndrome (4). Besides the well established relationship between adiponectin and obesity, low adiponectin serum concentrations were proposed to predict the occurrence of type 2 diabetes in adults (9, 36). Interestingly, the reduction of adiponectin appears to precede the actual development of insulin resistance and diabetes in mammals (10) and humans (11). Considering that the pediatric cohort is experiencing an increasing prevalence of diabetes in parallel with increasing obesity (13, 14), but is comparably free from confounding comorbidities, children represent a unique population to study the sequence of events and associations leading from obesity to overt type 2 diabetes. Here we show that in accordance to studies in adults (5, 41, 42), adiponectin decreases with increasing degree of obesity. As a consequence, adiponectin levels are reduced in obese children compared with normal weight peers. In addition, adiponectin significantly negatively correlated with parameters of insulin resistance, including HOMA index, FPI, peak insulin response after oral glucose load, and uric acid, and positively with insulin sensitivity and HDL cholesterol in our cohort. In fact, the ISI had the strongest influence on adiponectin levels in obese children in the multiple regression model, even overriding the influences of pubertal development and BMI. These results are in accordance with other studies (15, 43) and emphasize that clinicians should be aware that the complete panel of features of the metabolic syndrome may already occur early in childhood. On the other hand, weight reduction was shown to increase adiponectin levels (43) and may ameliorate metabolic derangements in children. Therefore, screening for these comorbidities in children is necessary to initiate intervention as early as possible. Detailed studies in the pediatric population are highly warranted to analyze these associations in more detail.
We also measured adiponectin levels in a subgroup of girls with PCO syndrome. Adiponectin levels in this group were not different compared with those in obese girls of corresponding age and pubertal stage, even though DHEA-S levels were slightly higher. This finding, however, is in accordance with previous studies showing similar adiponectin levels in adult women with PCO syndrome and BMI-matched controls (44). Hence, one may assume that the degree of obesity and insulin resistance has a stronger impact on adiponectin levels in the special entity of the PCO syndrome.
The design of our study with well characterized cohorts of healthy normal weight and obese children covering a wide range of age, BMI, and pubertal stage allows establishing representative data for serum adiponectin concentrations in children and adolescents. Potential diurnal rhythms and variations after food ingestion need to be considered when interpreting results of endocrine or metabolic factors.
Adiponectin levels in humans show only minimal daytime variations (8, 45) and are stable during morning hours, the time interval when our samples were obtained. Also, caloric intake did not have a substantial effect on adiponectin levels (46). To control for potential interferences of adiponectin serum concentrations with glucose ingestion, we performed an oGTT in a subgroup of obese children. We did not find any significant variations in adiponectin levels despite substantial increases in blood glucose and insulin levels after glucose challenge. This further confirms that postprandial stage (45), high fat load (47), or elevations of free fatty acids (48) do not acutely affect adiponectin serum concentrations. Hence, diurnal variations and food intake are not likely to constitute confounding factors for our study.
In summary, we demonstrate a progressive decline in adiponectin levels in parallel with physical and pubertal development in boys that lead to reduced adiponectin levels compared with girls after completion of pubertal development. This decline was strongly associated with androgen levels and may account for the gender differences seen in adults. In addition, we show that adiponectin levels are already decreased in childhood adiposity and are related to measures of obesity. Such reduced adiponectin levels in obese children are closely associated with insulin resistance and metabolic derangements that occur already in children.
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Acknowledgments |
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Footnotes |
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Abbreviations: BMI, Body mass index; BP, blood pressure; DHEA-S, dehydroepiandrosterone sulfate; FPI, fasting plasma insulin; HDL, high-density lipoprotein; HOMA, homeostasis model assessment; ISI, insulin sensitivity index; Ob-BP, leptin-binding protein, also termed soluble leptin receptor; oGTT, oral glucose tolerance test; PCOS, polycystic ovary syndrome; SDS, SD score; WHR, waist to hip ratio.
Received February 17, 2004.
Accepted April 27, 2004.
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Y. Bottcher, A. Korner, T. Reinehr, B. Enigk, W. Kiess, M. Stumvoll, and P. Kovacs ENPP1 Variants and Haplotypes Predispose to Early Onset Obesity and Impaired Glucose and Insulin Meta |
, P < 0.001; 
, P < 0.01.
) but not in girls (
). Data are given as the mean ± SEM for each pubertal stage with a minimum of 17 individuals per group (total number of children, 200). *, P < 0.05; (*), P = 0.057. Spearman’s correlation analysis revealed a significant negative correlation between adiponectin and pubertal stage in boys (r = –0.48; n = 98; P < 0.0001), whereas there was no such relationship in girls.
