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Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2004-2328
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The Journal of Clinical Endocrinology & Metabolism Vol. 90, No. 7 4170-4176
Copyright © 2005 by The Endocrine Society

Genetic and Environmental Factors Influencing Fasting Serum Adiponectin in Hispanic Children

Nancy F. Butte, Anthony G. Comuzzie, Gouwen Cai, Shelley A. Cole, Nitesh R. Mehta and Carlos A. Bacino

U.S. Department of Agriculture/Agricultural Research Service Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine (N.F.B., N.R.M., C.A.B.), Houston, Texas 77030; and Department of Genetics, Southwest Foundation for Biomedical Research (A.G.C., G.C., S.A.C.), San Antonio, Texas 78245

Address all correspondence and requests for reprints to: Dr. Nancy F. Butte, Children’s Nutrition Research Center, 1100 Bates Street, Houston, Texas 77030. E-mail: nbutte{at}bcm.tmc.edu.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Because of its antiinflammatory and insulin-sensitizing properties, adiponectin may play a role in the development of cardiovascular disease and type 2 diabetes.

Objectives: The aims of these analyses were: 1) to estimate the heritability of fasting serum adiponectin; 2) to evaluate the effects of age, sex, and body composition on fasting serum adiponectin; 3) to test for associations between fasting serum adiponectin and diet, fitness, energy expenditure, and fat oxidation; and 4) to determine the relationships between fasting serum adiponectin, insulin and lipids, and blood pressure in Hispanic children.

Design: Genetic and environmental factors influencing fasting serum adiponectin were investigated in a cohort of children participating in the VIVA LA FAMILIA Study in 2000–2005.

Setting: This study was performed at the Children’s Nutrition Research Center.

Participants: The study participants were 805 Hispanic nonoverweight and overweight children, ages 4–19 yr.

Main Measure: The main measure of the study was fasting serum adiponectin.

Results: The heritability of serum adiponectin was 0.93 ± 0.10 (P = 2.4 x 10–40). Adiponectin differed by age (P = 0.001), sex (P = 0.04), and weight (P = 0.001) status. Adiponectin levels declined with age, in association with changes in sex hormones and growth factors. Adiponectin was not associated with macronutrient intake, fitness, 24-h energy expenditure, or fat oxidation. Controlling for age, sex, and percent fat mass, adiponectin was inversely associated with homeostasis model of insulin resistance, triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C), and systolic blood pressure (P = 0.001). Significant positive genetic correlations were detected between adiponectin and total cholesterol ({rho}G = 0.19), HDL-C ({rho}G = 0.32), low-density lipoprotein cholesterol ({rho}G = 0.24), and IGF-binding protein-1 ({rho}G = 0.39), and negative genetic correlations were detected between adiponectin and leptin ({rho}G = –0.30), TG ({rho}G = –0.21), TG/HDL-C ({rho}G = –0.33), and IGF-binding protein-3 ({rho}G = –0.32), indicating shared genetic components in their expression.

Conclusion: The high heritability of adiponectin and pleiotropy seen between adiponectin and leptin, growth factors, and lipids may play a role in the pathogenesis of cardiovascular disease and type 2 diabetes in overweight Hispanic children.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
ADIPONECTIN IS A protein exclusively secreted from adipose tissue and is encoded by the structural gene Apm1, which has been mapped to chromosome 3 (3q27). Because of its structural similarity to cytokines and its antiinflammatory and insulin-sensitizing properties, adiponectin is considered an adipocytokine (1). In contrast to all other known adipocytokines, such as leptin and TNF-{alpha}, adiponectin is reduced in obesity. Dysregulation of the expression and/or secretion of adiponectin may play a role in the pathogenesis of cardiovascular disease (CVD) and type 2 diabetes (T2D) associated with obesity. Genetic linkage for the metabolic syndrome, a constellation of metabolic risk factors for CVD and T2D including abdominal obesity, dyslipidemia, hypertension, and insulin resistance, was detected in the region of chromosome 3 containing the structural gene for adiponectin (2).

In adults, adiponectin is positively correlated with age, insulin sensitivity, and high-density lipoprotein cholesterol (HDL-C) and is negatively correlated with body mass index (BMI), sc adipose tissue, visceral adipose tissue, and serum triglycerides (TG) (3). Decreased adiponectin appears to be an independent risk factor for progression to T2D. Adiponectin expression in sc adipose tissue was 45% lower in 22 healthy, first-degree relatives of T2D patients, although serum adiponectin levels were similar to control values (4). In Japanese adults, those in the lowest tercile were 9.3 times more likely to develop diabetes than those in the highest tercile (5). Adiponectin has been measured in a few pediatric studies with conflicting results regarding age, sex, and other determinants (6, 7, 8, 9).

Numerous experimental studies in rodents and adult humans suggest a protective role for adiponectin against the development of insulin resistance and dyslipidemia (10). Adiponectin injected into mice accelerates the oxidation of nonesterified fatty acids, decreases TG storage in muscle and liver, improves hyperglycemia, and decreases plasma TG and nonesterified fatty acid concentrations. Using a euglycemic hyperinsulinemic clamp in adults, Mohlig et al. (11) demonstrated that insulin decreased adiponectin levels from 30.4 to 26.7 µg/ml (11). However, the function(s) and directionality of the relationship between adiponectin expression and insulin action are not completely understood. Adiponectin may enhance insulin sensitivity by blocking TNF-{alpha} signals, which block insulin action through inhibition of insulin receptor substrate-1 and tyrosine kinase activity (9). Adiponectin also may inhibit TNF-{alpha}-induced expression of adhesion molecules in endothelial cells and secretion of TNF-{alpha} from monocyte macrophages (6).

Given the paucity of pediatric studies in this area, we decided to examine genetic and environmental factors influencing fasting serum adiponectin in Hispanic children participating in the VIVA LA FAMILIA study, which was designed to genetically map childhood obesity in approximately 300 nuclear Hispanic families. The specific aims of these analyses were 1) to estimate the heritability of fasting serum adiponectin; 2) to evaluate the effects of age, sex, and body composition on fasting serum adiponectin; 3) to test for associations between fasting serum adiponectin and diet, fitness, energy expenditure, and fat oxidation; and 4) to determine the relationships between fasting serum adiponectin, insulin, and lipids and blood pressure in Hispanic children.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Study design and subjects

Genetic and environmental factors influencing fasting serum adiponectin were investigated in 805 of the 1030 children enrolled in the VIVA LA FAMILIA study, which was designed to genetically map childhood obesity in the Hispanic population. The age, weight, height, and BMI z-score of the 225 children enrolled later in the study did not differ from the 805 children described here. Each family was ascertained on an overweight proband between yr 4 and 19 of age using a bivariate ascertainment scheme [i.e. >95th percentile for BMI (12) and >85th percentile for fat mass (FM) (13, 14)]. Once identified, the overweight proband and all siblings, 4–19 yr of age, and their parents were invited to the Children’s Nutrition Research Center for a tour and full explanation of the study. All children and their parents gave written informed consent. Separate approvals were obtained from the institutional review boards for Human Subject Research for Baylor College of Medicine and Affiliated Hospitals and Southwest Foundation for Biomedical Research.

The overweight probands and all siblings were then characterized for body size, body composition, and endophenotypes associated with the development of obesity, including hormones and metabolites, energy expenditure, physical fitness, and diet. In this study, we report our findings on the endophenotype, adiponectin, in 422 overweight and 383 nonoverweight siblings.

Demographics and family history

A sociodemographic interview was conducted with the parents in their dominant language, English or Spanish. Included in the interview was a family history of chronic diseases, including T2D, among parents and grandparents.

Anthropometry and body composition

Body weight to the nearest 0.1 kg was measured with a digital balance, and height to the nearest 1 mm was measured with a stadiometer. Body composition was determined by dual energy x-ray absorptiometry using a Delphi-A whole-body scanner (Hologic, Inc., Waltham, MA). Total body estimates of FM and fat-free mass (FFM) were obtained.

Clinical signs

Blood pressure, heart rate, and temperature were determined in triplicate using a DINAMAP Vital Signs Monitor (8100T, Critikon, Inc., Tampa, FL). Each child was seated quietly for at least 5 min before measurement. The arm was supported at the heart level, and an appropriate cuff size was used. The presence or absence of acanthosis nigricans in the skin around the neck was assessed and recorded by a trained nurse. Tanner stages of sexual maturation, based on pubic hair and breast and genital development illustrated with drawings, were determined by self-report (15, 16, 17, 18).

Fasting blood biochemistries

A fasting blood sample was drawn for biochemical determinations. Fasting serum concentrations of glucose, TG, total cholesterol (TC), and HDL-C were measured by enzymatic-colorimetric techniques using the GM7 analyzer (Analox Instruments, Lundeburg, MA) and the Microquant Platereader (Biotek Instruments, Winooski, VT). Glucose was assayed using glucose oxidase. TG was determined using lipase, glycerol kinase, glycerol phosphate oxidase, and peroxidase. TC and HDL-C were determined using cholesterol esterase, cholesterol oxidase, and peroxidase. Low-density lipoprotein cholesterol (LDL-C) was calculated as: TC – HDL-C – (TG/5). Serum adiponectin, leptin, and insulin were measured by RIA (Linco Research, Inc., St. Charles, MO). The homeostasis model of insulin resistance [fasting insulin (microunits per milliliter) x fasting glucose (millimoles per liter)/22.5)] was used as an indicator of insulin resistance. RIA was used to measure testosterone (Diagnostic Systems Laboratory, Webster, TX). Estradiol was measured by electrochemiluminescence (Elecsys 1010, Roche, Indianapolis, IN). Free and bound IGF-I, IGF-binding protein-1 (IGFBP-1), and IGFBP-3 were determined using ELISA kits (Diagnostic Systems Laboratory).

Room respiration calorimetry

Oxygen consumption, carbon dioxide production, and respiratory quotient were measured for 24 h in a room respiration calorimeter. The operation and calibration of the calorimeters were described previously in detail (19). Fat oxidation was computed using oxygen consumption, carbon dioxide production, and 24-h urinary excretion of nitrogen, determined by the Kjeldahl method (Tecator, Hoganas, Sweden) (20).

Fitness

The oxygen consumption (VO2) peak was measured to assess fitness by collecting expired gases with a metabolic cart (model 2900, SensorMedics Corp., Yorba Linda, CA) during an exercise test on a treadmill (model Q55, Quinton Instrument Co., Seattle, WA). The protocol involved a constant speed of 2.5 mph at an initial 0% grade for the first 4 min. The grade was then increased to 10%. Every minute thereafter, the grade was increased by 2.5% until a maximum grade of 22.5%, when speed was then increased incrementally by 0.6 mph. VO2 peak was determined by standard criterion, specifically a heart rate greater than 195 beats/min or a respiratory quotient greater than 1.0 at maximum (21).

Dietary intake

A multiple-pass, 24-h dietary recall was recorded on two occasions by a registered dietitian using Nutrition Data System software on a laptop computer (22). This system automates interviewing, editing and coding of dietary intake data. The multiple-pass, 24-h recall uses three distinct passes to garner information about a subject’s food intake during the preceding 24 h. Children, ages 7 yr or younger, were assisted by their mothers.

Statistical analysis

Data are summarized as the mean ± SD. ACCESS (version 9, Microsoft Corp., Redmond, WA) was used for database management. If the data were not normally distributed (kurtosis, >1.9), a log transformation was performed and used in additional analyses (23). Descriptive statistics, generalized estimating equations, and general least squares regression were performed using STATA (version 8.2, STATA Corp., College Station, TX) and MINITAB (version 13, Minitab, Inc., State College, PA). To account for correlated data within families, the family identification number was used as the cluster variable. Statistical significance was set at P < 0.05.

Quantitative genetic analysis

Univariate quantitative genetic analysis was used to partition the phenotypic variance for adiponectin into additive genetic and environmental variance components. The additive genetic heritability (h2) of a trait represents the portion of the total phenotypic variance accounted for by the additive genetic variance (i.e. h2 = {sigma}2g/{sigma}2p). The heritabilities were estimated using the maximum likelihood variance decomposition method (24, 25) implemented in the computer program SOLAR 2.0 (Southwest Foundation for Biomedical Research, San Antonio, TX) (26). An ascertainment correction is routinely performed in all genetic analyses in SOLAR. Bivariate analyses were conducted to partition the phenotypic relationships between two traits into genetic and environmental correlations. Evidence of pleiotropy (a common set of genes influence more than one trait) is indicated by a genetic correlation significantly different from zero. A shared environmental effect is implied by a significant environmental correlation. The phenotypic correlation ({rho}P) between two traits can be expressed in terms of genetic ({rho}G) and environmental correlations ({rho}E), as described in the following equation: {rho}P = {rho}G {surd}h12{surd}h22 + {rho}E {surd}(1 – h12) {surd}(1 – h22), where h12 and h22 correspond to the heritabilities of traits 1 and 2, respectively.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
The anthropometry and body composition of the 805 children are presented in Table 1Go. As expected, weight, height, BMI, BMI z-score, FM, and percent FM were higher in the overweight than in the nonoverweight children. The clinical features of the children are summarized in Table 2Go. Systolic blood pressure differed significantly by overweight status (P = 0.001) and sex (P = 0.001). The majority (64%) of the children had a family history of T2D among parents and/or grandparents. The prevalence of T2D among the children’s relatives was: mothers, 11%; fathers, 8%; maternal grandmother, 24%; maternal grandfather, 23%, paternal grandmother, 19%; and paternal grandfather, 18%. Adiponectin levels did not differ between children with or without a family history of T2D. Acanthosis nigricans was present in 30% of the overweight children. The presence of acanthosis nigricans in the overweight children was associated with significantly lower adiponectin levels (9.7 vs. 12.8 µg/ml; P = 0.001).


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  		TABLE 1. Anthropometry and body composition of the nonoverweight and overweight Hispanic children

 

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  		TABLE 2. Clinical indices of the nonoverweight and overweight Hispanic children

 
Mean fasting serum adiponectin and other biochemistries are presented in Table 3Go. Adiponectin differed by age (P = 0.001), sex (boys < girls; P = 0.04), and overweight status (overweight < nonoverweight; P = 0.001). Adiponectin was negatively associated with indices of body size (weight, height, and BMI) and body composition (FFM, FM, and percent FM; all P values < 0.001). Serum adiponectin declined with age at a rate of –0.5 µg/ml·yr; the rate of decline did not differ by overweight status. Adiponectin levels were significantly higher in prepubertal children in Tanner stage 1 than in maturing children in Tanner stages 2–5 (15.6 vs. 11.9 µg/ml; P = 0.001). Adiponectin expressed per kilogram of FM declined precipitously from 4 to 10 yr of age, then tended to plateau from 10 to 19 yr of age (Fig. 1AGo).


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  		TABLE 3. Fasting biochemistries of the nonoverweight and overweight Hispanic children

 


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  		FIG. 1. A, Fasting serum adiponectin per fat mass (micrograms per milliliter per kilogram) as a function of age (years) in nonoverweight and overweight Hispanic children. B, Fasting serum IGFBP-1 (nanograms per milliliter) as a function of age (years) in Hispanic nonoverweight and overweight children. C, The relationship between log fasting serum IGFBP-1 (nanograms per milliliter) and log fasting serum adiponectin per kilogram of fat mass (micrograms per milliliter per kilogram) in nonoverweight and overweight Hispanic children.

 
Environmental, genetic and phenotypic correlations between adiponectin and other fasting serum biochemistries are summarized in Table 4Go. Negative environmental correlations were seen between adiponectin and insulin, homeostasis model of insulin resistance, leptin, triglycerides, TC, and LDL-C. Positive environmental correlations were seen between adiponectin and HDL-C, IGFBP-1, and IGFBP-3. Negative genetic correlations were seen between adiponectin and leptin, TG, and IGFBP-3. Positive genetic correlations were seen between adiponectin and TC, HDL-C, LDL-C, and IGFBP-1.


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  		TABLE 4. Environmental, genetic, and phenotypic correlations between ln adiponectin and other biochemistries of the nonoverweight and overweight Hispanic children

 
Age-related changes in adiponectin per kilogram of FM were strikingly similar to the age-related changes in IGFBP-1 (Fig. 1BGo). The relationship between adiponectin per kilogram of FM and IGFBP-1 is shown in Fig. 1CGo. Accounting for family membership, 31% of the variance in fasting serum adiponectin and 80% of the variance in adiponectin per kilogram of FM were accounted for by independent effects of age (P = 0.001), BMI z-score (P = 0.001), serum insulin (P = 0.001), IGFBP-1 (P = 0.001), and IGFBP-3 (P = 0.001) by multiple regression.

Fasting serum insulin was associated with both fasting serum adiponectin and percent FM, as shown in Fig. 2Go (adiponectin x percent FM interaction, P = 0.001). The combination of low adiponectin and high percent FM was associated with the highest insulin level. The negative association between adiponectin and fasting insulin was evident at each percent FM quartile. Similarly, fasting serum adiponectin and percent FM were related to fasting TG/HDL-C, as shown in Fig. 3Go (adiponectin x percent FM interaction, P = 0.001). At each percent FM quartile, adiponectin was inversely associated with TG/HDL-C. Although their interaction was not statistically significant, adiponectin and percent FM exerted independent effects on systolic blood pressure (Fig. 4Go).



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  		FIG. 2. Fasting serum insulin (microunits per milliliter) as a function of fasting serum adiponectin (micrograms per milliliter) quartile and percent fat mass quartile in Hispanic children.

 


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  		FIG. 3. Fasting serum TG/HDL-C (millimoles per millimole) as a function of fasting serum adiponectin (micrograms per milliliter) quartile and percent fat mass quartile in Hispanic children.

 


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  		FIG. 4. Systolic blood pressure (millimeter of mercury) as a function of fasting serum adiponectin (micrograms per milliliter) quartile and percent fat mass quartile in Hispanic children.

 
Energy expenditure and fat oxidation were assessed by 24-h room calorimetry (data not shown). Univariate analyses indicated that 24-h energy expenditure was significantly correlated with adiponectin; however, controlling for family membership, age, sex, percent FM, and FFM, the relationship was no longer significant. Adjusted for energy balance, 24-h fat oxidation rate, and respiratory quotient were not found to be associated with adiponectin. Although absolute VO2 peak was negatively correlated with adiponectin, VO2 peak, adjusted for family membership, age, gender, FFM, and percent FM, was not significantly associated with adiponectin. Dietary recall records indicated that the percentages of energy intake from total fat, carbohydrate, and protein were not significantly correlated with adiponectin.

The heritability (h2) of serum adiponectin in this cohort of Hispanic siblings was 0.93 ± 0.10 (P = 2.4 x 10–40). Using variance decomposition techniques, significant positive genetic correlations were detected between adiponectin and HDL-C, LDL-C, and IGFBP-1, and negative genetic correlations were seen between adiponectin and TG, TG/HDL, and IGFBP-3, indicating pleiotropy or shared genetic components in their expression.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
Genetic factors strongly influenced fasting serum adiponectin in this large cohort of Hispanic children at risk for development of CVD and T2D. Age, sex, and overweight status exhibited independent effects on adiponectin. Adiponectin declined with age, in part attributable to changes in sex hormones and growth factors. Fasting serum adiponectin was shown to be highly heritable, with genes accounting for 93% of the variance in its circulating levels. Significant genetic correlations between circulating levels of adiponectin and leptin, growth factors, and lipids indicate shared genetic regulation in their expression.

Heritability (h2) is defined as the relative proportion of the total phenotypic variance in a complex trait that is attributable to the additive effects of genes. Using quantitative genetic analysis, the total phenotypic variance is decomposed into its genetic and environmental components. In the broad sense, the genetic component represents the variance attributable to additive genetic effects, dominance, and epistasis, whereas the environmental component is attributable to measured environmental factors and random, unmeasured factors. In the narrow sense, heritability (h2) is defined and computed as the proportion of the variation attributed to the additive genetic effects only; therefore, the other genetic effects are subsumed under environmental factors.

The heritability (h2) of adiponectin in these Hispanic children is higher than our observations in 1100 northern European adults (h2 = 0.93 vs. 0.46), indicating that a greater portion of the variance in circulating levels in children is due to the additive genetic effect (27). The heritability (h2) of adiponectin in this cohort of Hispanic children is higher than our observations in 1100 northern European adults (h2 = 0.93 vs. 0.46), indicating that a greater portion of the variance in circulating levels in these children is due to the additive genetic effect (27). In children, the cumulative effect of environmental factors may be less than in adults. The ascertainment of our cohort was based on an obese proband that theoretically could introduce bias into our estimate of heritability. However, we routinely correct for ascertainment bias in all of our genetic analyses. Therefore, this estimate of heritability is generalizable to Hispanic children and, therefore, substantiates a strong genetic contribution to circulating levels of adiponectin in Hispanic children.

In our northern European adult study, the genomic scan revealed a maximum LOD score for adiponectin of 4.06, located 35 cM from pter on chromosome 5; the second highest LOD score (3.2) was on chromosome 14, 29 cM from pter. Evidence for pleiotropy was detected between adiponectin and HDL-C and TG (genetic correlations {rho}G = 0.32, and –0.36, respectively), similar to the genetic correlations observed in the Hispanic children. Shared genetic regulation of adiponectin and lipids may contribute to the clustering of metabolic comorbidities seen with obesity. In the genomic scan examining metabolic syndrome and obesity traits in these northern European families, a quantitative trait locus was found on chromosome 3q27 in the region of the adiponectin gene, with LOD scores of 2.4–3.5 (2). Single nucleotide polymorphisms in the adiponectin gene have been associated with BMI, insulin sensitivity, and T2D in a number of cross-sectional studies (28, 29, 30, 31, 32, 33, 34, 35, 36, 37). In a prospective study, variations in the adiponectin gene affected weight gain, body fat distribution, and onset of hyperglycemia (37).

In the Hispanic children, age, sex, and overweight status exerted independent effects on the expression of serum adiponectin. Adiponectin per kilogram of FM declined precipitously during the prepubertal period and then plateaued, in parallel, but always lower in the overweight than nonoverweight children. Serum adiponectin and adiponectin per kilogram of FM were negatively influenced by developmental changes in growth and sexual maturation associated with increasing age; in addition, independent, negative effects were exerted by obesity and insulin resistance. Serum adiponectin was inversely associated with serum insulin, TG/HDL-C, and systolic blood pressure, independent of age, sex, and percent FM. The association with adiponectin was apparent at each level of adiposity, but was especially striking at the higher levels of adiposity. The cross-sectional nature of our data, however, does not allow us to make any conclusions regarding the directionality of associations with adiponectin. Serum adiponectin may prove to be a useful marker for identifying children at risk for the development of CVD and T2D, but prospective studies will be required to prove its clinical significance.

Adiponectin has been measured in a few other studies in children (6, 7, 8, 9). In 30 Hispanic and Asian American children, aged 12–14 yr, adiponectin values were higher than those reported for adults and were higher in boys than in girls (6). These investigators reported a negative correlation between VO2 peak and adiponectin; however, VO2 peak was not standardized for body size. In our study, VO2 peak adjusted for weight or FFM using covariate analysis was not associated with adiponectin. In 10-yr-old Pima children, the percent FM, but not fasting plasma insulin, was independently associated with adiponectin (8). In contrast, in another study of 14 obese adolescents and eight nonobese controls, adiponectin was negatively correlated with percent FM, intramyocellular lipid content, and plasma TG and was positively correlated with insulin sensitivity (7).

Adiponectin purportedly is a regulator of energy homeostasis (38, 39). Attempts to demonstrate a relationship between adiponectin and whole body energy metabolism have failed in humans to date. Plasma adiponectin was not associated with fat oxidation in 75 nondiabetic Pima adults (40). Consistent with our findings, no significant correlations were detected among adiponectin, 24-h energy expenditure, and respiratory quotient. We did not detect any effect of diet on fasting serum adiponectin.

In conclusion, age, sex, and overweight status exerted independent effects on the expression of fasting serum adiponectin in these Hispanic children. Serum adiponectin was inversely associated with serum insulin, TG/HDL-C, and systolic blood pressure, independent of age, sex, and percent FM. The high heritability of adiponectin and pleiotropy seen among adiponectin and leptin, growth factors, and lipids may play a role in the pathogenesis of CVD and T2D in overweight Hispanic children.


   Acknowledgments
 
We thank the families who participated in this study and acknowledge the contributions of Mercedes Alejandro and Marilyn Navarrete for study coordination, Sopar Seributra for nursing, Theresa Wilson and Sandra Kattner for dietary support, and Tina Ziba, Maurice Puyau, Firoz Vohra, Anne Adolph, Roman Shypailo, JoAnn Pratt, and Maryse Laurent for technical assistance.


   Footnotes
 
This work is a publication of the U.S. Department of Agriculture/Agricultural Research Service, Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine and Texas Children’s Hospital (Houston, TX). This project was funded with federal funds from National Institutes of Health Grant R01-DK-59264 and from U.S. Department of Agriculture/Agricultural Research Service under Cooperative Agreement 58-6250-51000-037. The contents of this publication do not necessarily reflect the views or policies of the U.S. Department of Agriculture, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government.

First Published Online April 12, 2005

Abbreviations: BMI, Body mass index; CVD, cardiovascular disease; FFM, fat-free mass; FM, fat mass; HDL-C, high-density lipoprotein cholesterol; IGFBP, IGF-binding protein; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; T2D, type 2 diabetes; TG, triglycerides; VO2, oxygen consumption.

Received November 30, 2004.

Accepted April 5, 2005.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

  1. Havel PJ 2002 Control of energy homeostasis and insulin action by adipocyte hormones: leptin, acylation stimulating protein, and adiponectin. Curr Opin Lipidol 13:51–59[CrossRef][Medline]
  2. Kissebah AH, Sonnenberg GE, Myklebust J, Goldstein M, Broman K, James RG, Marks JA, Krakower GR, Jacob HJ, Weber J, Martin L, Blangero J 2000 Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc Natl Acad Sci USA 97:14478–14483[Abstract/Free Full Text]
  3. Cnop M, Havel PJ, Utzschneider KM, Carr DB, Sinha MK, Boyko EJ, Retzlaff BM, Knopp RH, Brunzell JD, Kahn SE 2003 Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia 46:459–469[Medline]
  4. Lihn AS, Ostergard T, Nyholm B, Pedersen SB, Richelsen B, Schmitz O 2003 Adiponectin expression in adipose tissue is reduced in first-degree relatives of type 2 diabetic patients. Am J Physiol 284:E443–E448
  5. Daimon M, Oizumi T, Saitoh T, Kameda W, Hirata A, Yamaguchi H, Ohnuma H, Igarashi M, Tominaga M, Kato T 2003 Decreased serum levels of adiponectin are a risk factor for the progression of type 2 diabetes in the Japanese population. Diabetes Care 26:2015–2020[Abstract/Free Full Text]
  6. Nemet D, Wang P, Funahashi T, Matsuzawa Y, Tanaka S, Engelman L, Cooper DM 2003 Adipocytokines, body composition, and fitness in children. Pediatr Res 53:148–152[CrossRef][Medline]
  7. Weiss R, Dufour S, Groszmann A, Petersen K, Dziura J, Taksali SE, Shulman G, Caprio S 2003 Low adiponectin levels in adolescent obesity: a marker of increased intramyocellular lipid accumulation. J Clin Endocrinol Metab 88:2014–2018[Abstract/Free Full Text]
  8. Stefan N, Bunt JC, Salbe AD, Funahashi T, Matsuzawa Y, Tataranni PA 2002 Plasma adiponectin concentrations in children: relationships with obesity and insulinemia. J Clin Endocrinol Metab 87:4652–4656[Abstract/Free Full Text]
  9. Asayama K, Hayashibe H, Dobashi K, Uchida N, Nakane T, Kodera K, Shirahata A, Taniyama M 2003 Decrease in serum adiponectin level due to obesity and visceral fat accumulation in children. Obes Res 11:1072–1079[Medline]
  10. Hoffstedt J, Arvidsson E, Sjolin E, Wahlen K, Arner P 2004 Adipose tissue adiponectin production and adiponectin serum concentration in human obesity and insulin resistance. J Clin Endocrinol Metab 89:1391–1396[Abstract/Free Full Text]
  11. Mohlig M, Wegewitz U, Osterhoff M, Isken F, Ristow M, Pfeiffer AFH, Spranger J 2002 Insulin decreases human adiponectin plasma levels. Horm Metab Res 34:655–658[CrossRef][Medline]
  12. Must A, Dallal GE, Dietz WH 1991 Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht2) and triceps skinfold thickness. Am J Clin Nutr 53:839–846[Abstract/Free Full Text]
  13. Ellis KJ 1997 Body composition of a young, multiethnic, male population. Am J Clin Nutr 66:1323–1331[Abstract/Free Full Text]
  14. Ellis KJ, Abrams SA, Wong WW 1997 Body composition of a young, multiethnic female population. Am J Clin Nutr 65:724–731[Abstract/Free Full Text]
  15. Hofmann AD 1983 Adolescent medicine. Menlo Park, CA: Addison-Wesley
  16. Speroff L, Glass RH, Kase NG 1989 Clinical gynecologic endocrinology and infertility. 4th ed. Baltimore: Williams & Wilkins
  17. Duke PM, Litt IF, Gross RT 1980 Adolescents’ self-assessment of sexual maturation. Pediatrics 66:918–920[Abstract/Free Full Text]
  18. Brooks-Gunn J, Warren MP, Rosso J, Gargiulo J 1987 Validity of self-report measures of girls’ pubertal status. Child Dev 58:829–841[CrossRef][Medline]
  19. Moon JK, Vohra FA, Valerio Jimenez OS, Puyau MR, Butte NF 1995 Closed-loop control of carbon dioxide concentration and pressure improves response of room respiration calorimeters. J Nutr 125:220–228
  20. Livesey G, Elia M 1988 Estimation of energy expenditure, net carbohydrate utilization, and net fat oxidation and synthesis by indirect calorimetry: evaluation of errors with special reference to the detailed composition of fuels. Am J Clin Nutr 47:608–628[Abstract/Free Full Text]
  21. Forster MA, Hunter GR, Hester DH, Dunaway D, Shuleva K 1994 Aerobic capacity and grade-walking economy of children 5–9 years old: a longitudinal study. Pediatr Exerc Sci 6:31–38
  22. Johnson RK, Driscoll P, Goran MI 1996 Comparison of multiple-pass 24-hour recall estimates of energy intake with total energy expenditure determined by the doubly labeled water method in young children. J Am Diet Assn 96:1140–1144[CrossRef][Medline]
  23. Blangero J, Williams JT, Almasy L 2001 Variance component methods for detecting complex trait loci. Adv Genet 42:151–181[Medline]
  24. Hopper JL, Mathews JD 1982 Extensions to multivariate normal models for pedigree analysis. Ann Hum Genet 46:373–383
  25. Lange K, Boehnke M 1983 Extensions to pedigree analysis. IV. Covariance components models for multivariate traits. Am Med Genet 14:513–524
  26. Almasy L, Blangero J 1998 Multipoint quantitative-trait linkage analysis in general pedigrees. Am J Hum Genet 62:1198–1211[CrossRef][Medline]
  27. Comuzzie AG, Funahashi T, Sonnenberg G, Martin LJ, Jacob HJ, Black AE, Maas D, Takahashi M, Kihara S, Tanaka S, Matsuzawa Y, Blangero J, Cohen D, Kissebah AH 2001 The genetic basis of plasma variation in adiponectin, a global endophenotype for obesity and the metabolic syndrome. J Clin Endocrinol Metab 86:4321–4325[Abstract/Free Full Text]
  28. Stumvoll M, Tschritter O, Fritsche A, Staiger H, Renn W, Weisser M, Machicao F, Haring H 2002 Association of the T-G polymorphism in adiponectin (Exon 2) with obesity and insulin sensitivity. Interaction with family history of type 2 diabetes. Diabetes 51:37–41[Abstract/Free Full Text]
  29. Yang WS, Tsou PL, Lee WJ, Tseng DL, Chen CL, Peng CC, Lee KC, Chen MJ, Huang CJ, Tai TY, Chuang LM 2003 Allele-specific differential expression of a common adiponectin gene polymorphism related to obesity. J Mol Med 81:428–434[CrossRef][Medline]
  30. Hu FB, Doria A, Li T, Meigs JB, Liu S, Memisoglu A, Hunter D, Manson JE 2004 Genetic variation at the adiponectin locus and risk of type 2 diabetes in women. Diabetes 53:209–213[Abstract/Free Full Text]
  31. Filippi E, Sentinelli F, Trischitta V, Romeo S, Arca M, Leonetti F, Di Mario U, Baroni MG 2003 Association of the human adiponectin gene and insulin resistance. Eur J Hum Genet (Epub ahead of print) www.doi:10.1038/sj.ejhg. 5201120
  32. Ukkola O, Ravussin E, Jacobson P, Sjostrom L, Bouchard C 2003 Mutations in the adiponectin gene in lean and obese subjects from the Swedish obese subjects cohort. Metabolism 52:881–884[CrossRef][Medline]
  33. Hara K, Boutin P, Mori Y, Tobe K, Dina C, Yasuda K, Yamauchi T, Otabe S, Okada T, Eto K, Kadowaki H, Hagura R, Akanuma Y, Yazaki Y, Nagai R, Taniyama M, matsurbara K, Yoda M, Nakano Y, Tomita M, Kimura S, Ito C, Froguel P, Kadowaki T 2002 Genetic variation in the gene encoding adiponectin is associated with an increased risk of type 2 diabetes in the Japanese population. Diabetes 51:536–540[Abstract/Free Full Text]
  34. Menzaghi C, Ercolino T, Di Paola R, Berg AH, Warram JH, Scherer PE, Trischitta V, Doria A 2002 A haplotype at the adiponectin locus is associated with obesity and other features of the insulin resistance syndrome. Diabetes 51:2306–2312[Abstract/Free Full Text]
  35. Vasseur F, Helbecque N, Dina C, Lobbens S, Delannoy V, Gaget S, Boutin P, Vaxillaire M, Lepretre F, Dupont S, Hara K, Clement K, Bihain B, Kadowaki T, Froguel P 2002 Single-nucleotide polymorphism haplotypes in the both proximal promoter and exon 3 of the APM1 gene modulate adipocyte-secreted adiponectin hormone levels and contribute to the genetic risk for type 2 diabetes in French Caucasians. Hum Mol Genet 11:2607–2614[Abstract/Free Full Text]
  36. Kondo H, Shimomura I, Matsukawa Y, Kumada M, Takahashi M, Matsuda M, Ouchi N, Kihara S, Kawamoto T, Sumitsuji S, Funahashi T, Matsuzawa Y 2002 Association of adiponectin mutation with type 2 diabetes. Diabetes 51:2325–2328[Abstract/Free Full Text]
  37. Fumeron F, Aubert R, Siddiq A, Betoulle D, Pean F, Hadjadj S, Tichet J, Wilpart E, Chesnier MC, Balkau B, Froguel P, Marre M 2004 Adiponectin gene polymorphisms and adiponectin levels are independently associated with the development of hyperglycemia during a 3-year period. The epidemiologic data on the Insulin Resistance Syndrome Prospective Study. Diabetes 53:1150–1157[Abstract/Free Full Text]
  38. Havel PJ 2001 Peripheral signals conveying metabolic information to the brain: short-term and long-term regulation of food intake and energy homeostasis. Exp Biol Med 226:963–977[Abstract/Free Full Text]
  39. Wolf G 2003 Adiponectin: a regulator of energy homeostasis. Nutr Rev 61:290–292[CrossRef][Medline]
  40. Stefan N, Vozarova B, Funahashi T, Matsuzawa Y, Ravussin E, Weyer C, Tataranni PA 2002 Plasma adiponectin levels are not associated with fat oxidation in humans. Obes Res 10:1016–1020[Medline]



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