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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2007-0468
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The Journal of Clinical Endocrinology & Metabolism Vol. 92, No. 11 4359-4365
Copyright © 2007 by The Endocrine Society

Serum Retinol-Binding Protein 4 Concentration and Its Ratio to Serum Retinol Are Associated with Obesity and Metabolic Syndrome Components in Children

Isabelle Aeberli, Ralf Biebinger, Roger Lehmann, Dagmar l’Allemand, Giatgen A. Spinas and Michael B. Zimmermann

Human Nutrition Laboratory (I.A., R.B., M.B.Z.), Institute of Food Science and Nutrition, Swiss Federal Institute of Technology Zürich, 8092 Zürich, Switzerland; Department of Endocrinology Diabetes and Clinical Nutrition (R.L., G.A.S.), University Hospital Zürich, 8091 Zürich, Switzerland; Children’s Hospital of Eastern Switzerland (D.A.), 9006 St. Gallen, Switzerland; and Division of Human Nutrition (M.B.Z.), Wageningen University, 6700 AH Wageningen, The Netherlands

Address all correspondence and requests for reprints to: Isabelle Aeberli, Institute of Food Science and Nutrition, Human Nutrition Laboratory, ETH Zurich, LFV D11, Schmelzbergstrasse 7, 8092 Zürich, Switzerland. E-mail: isabelle.aeberli{at}ilw.agrl.ethz.ch.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Although retinol-binding protein (RBP)-4 concentrations are elevated in animal models of obesity and insulin resistance (IR), the link between RBP4 and IR in humans is less clear. There are few published data on RBP4 levels in overweight children, and most previous studies did not control for vitamin A (VA) status and/or subclinical inflammation.

Objective: The objective of the study was to measure serum RBP4, serum retinol (SR), the RBP4-to-SR molar ratio, and dietary VA intakes in normal-weight and overweight children and investigate the relationship of these variables to IR, subclinical inflammation, and the metabolic syndrome in this age group.

Design: This was a cross-sectional study.

Setting: The study was conducted in Northern Switzerland.

Patients: Patients included 6- to 14-yr-old normal-weight, overweight, and obese children (n = 79).

Main Outcome Measures: Body mass index, body fat percentage, waist-to-hip ratio, dietary VA intakes, serum RBP4, and SR were determined. IR was assessed using fasting insulin and the quantitative insulin sensitivity check index, and components of the metabolic syndrome and indices of subclinical inflammation were measured.

Results: Only 3% of children had low VA status. Independent of age, VA intakes, and C-reactive protein, body mass index, body fat percentage, and waist-to-hip ratio were significant predictors of RBP4, SR, and RBP4/SR. Independent of adiposity, RBP4 and RBP4/SR were significantly correlated with serum triglycerides, and RBP4/SR was correlated with fasting insulin. The RBP4-to-SR ratio more strongly correlated with components of the metabolic syndrome than serum RBP4.

Conclusion: Independent of subclinical inflammation and vitamin A intakes, serum RBP4 and the RBP4-to-SR ratio are correlated with obesity, central obesity, and components of the metabolic syndrome in prepubertal and early pubertal children.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
THE PREVALENCE OF pediatric obesity is increasing in many countries and is often associated with insulin resistance, dyslipidemia, and hypertension (1). Adipose tissue is an endocrine organ that secretes a number of adipokines with hormone actions on distant tissues (2). These actions include regulation of energy expenditure, body weight, appetite, and insulin sensitivity. Retinol-binding protein (RBP)-4 is a recently discovered adipokine that, in mice, increases insulin resistance in muscle and hepatic gluconeogenesis (3). In humans, serum RBP4 concentrations are correlated with obesity and insulin resistance in adults in some studies (4, 5) but not others (6).

In these studies, the major biological determinant of serum RBP4, i.e. vitamin A status, was not measured. RBP4 is the specific transport protein for retinol in the blood, and alterations of retinol intake and vitamin A status affect hepatic release of RBP4 and circulating RBP4 (7, 8, 9). It is unclear whether the link between RBP4 and insulin sensitivity occurs through retinol-dependent or retinol-independent mechanisms (10). Moreover, most previous studies did not control for inflammation as a confounder. Subclinical inflammation is a characteristic of obesity, and RBP4 may decrease during acute inflammation because it is secreted from the liver bound to transthyretin (TTR). TTR is a negative acute phase protein, and its concentration is reduced by acute stress, malnutrition, and inflammation (11).

Therefore, we assessed whether serum RBP4 concentrations are correlated with adiposity and/or components of the metabolic syndrome in pre- and early pubertal children. In addition, we investigated whether subclinical inflammation, vitamin A status and/or other dietary factors are predictors of serum RBP4 or the serum retinol/RBP4 ratio in this age group.


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
The subjects for this study were 6- to 14-yr-old children (n = 79) living in northern Switzerland. Data on subclinical inflammation of this cohort of children have been reported previously (12). The children were recruited through letters to primary schools and pediatric clinics. Our intent was to enroll 25 normal-weight, 25 overweight, and 25 obese children for the study. Informed written consent was obtained from the parents and informed oral assent from the children. Ethical approval for the study was obtained from the ethics committee of the Swiss Federal Institute of Technology in Zürich.

Dietary assessment of each child was done using two 24-h recalls and one 1-d weighed food record. These were done by well-trained female interviewers in the family home. Each child was visited three times by the same interviewer within 3 wk. The 24-h recalls were done at the first and second visits, and at the second visit, the interviewer gave instructions and guidelines for the 1-d weighed food record. At the third visit, the 1-d food record was carefully reviewed, and a questionnaire on usual dietary habits was completed with the child. The questionnaire included queries on food and beverage preferences, including sweets, baked goods, and snacks, and frequency and temporal patterns of snacking. Volumes and portion sizes for the 24-h recalls were estimated using measuring cups and spoons, photographs of food portions, and graduated food samples of cheese and bread. Combining 24-h recalls and a food record provides a good overview of a child’s habitual diet; this approach has been validated in children as young as 8 yr of age (13). An appointment was scheduled at the hospital clinic, at the parents’ convenience, usually within 1–2 wk of the dietary assessment.

The children presented to the hospital clinic in the morning after a 12-h overnight fast. Twelve milliliters of blood, 2 ml into EDTA-containing tubes, was taken by venipuncture. Height was measured to the nearest 0.5 cm and weight to the nearest 100 g using a digital balance (BF 18; Beurer, Ulm, Germany). Pubertal staging was done using illustrations of the different gender-specific Tanner stages (breast and pubic hair development in girls and genital stage and pubic hair in boys) shown to the family (14). Waist and hip circumferences were measured using a nonstretchable measuring tape according to Gibson (15). Skinfold thicknesses were measured at the triceps and subscapular sites using a Harpenden skinfold caliper (HSK-BI; British Indicators, West Sussex, UK) with a constant spring pressure of 10 g/mm2 and a resolution of 0.2 mm. A single experienced observer (I.A.) did all the measurements of waist and hip circumferences and skinfold thicknesses. After a 15-min rest, supine resting blood pressure was measured by auscultation.

Data analysis

Dietary data obtained from the three records were checked carefully and entered by the lead interviewer (I.A.) into a nutrition software system (EBISpro for Windows 4.0; Dr. J. Erhardt, University of Hohenheim, Hohenheim, Germany). This system translates the amount of food eaten into individual nutrients and assigns consumed foods into 22 food groups. The program is based on the German Food and Nutrition Data Base BLS 2.3 (Federal Health Department, Berlin, Germany) and, for foods specific to Switzerland, incorporates values from the Swiss Food Composition Database (16). Energy and nutrient data were averaged across the 3 d to obtain a mean daily energy and nutrient intake for each child. The reference values for nutrient intake for Germany, Austria, and Switzerland, the D-A-CH references (17) were used for comparison of the actual intake to the recommendations for the respective age groups. Total vitamin A content of the diet in milligrams retinol activity equivalent (RAE) was calculated as follows: milligrams ß-carotene/12 + milligrams preformed vitamin A (18).

Body mass index (BMI) of the children was calculated as weight (kilograms)/height (meters)2. BMI SD scores (SDS: individual BMI value – reference mean BMI value divided by SD to scale the data for comparison across ages and sex) were calculated and used in the analysis. Age- and gender-specific criteria from the U.S. Centers for Disease Control and Prevention (19) were used to classify children as normal weight, overweight (above the 85th percentile), or obese (above the 95th percentile). These criteria have been previously validated in Swiss children at this age (20). Body fat percentage was calculated using the equation of Lohman (21). Fat-free body mass (FFB) was determined as follows:

Formula

Formula

Formula

Laboratory analysis

The blood samples were centrifuged for 15 min at 2500 rpm. On fresh serum high-density lipoprotein (HDL)-cholesterol and triglycerides were measured on Hitachi 917 (Triglyceride GPO-PAP and HDL-C plus second generation, Roche, Basel, Switzerland). Serum was stored at –20 C for later determination of insulin [using RIA, Schering (Schweiz) AG, Baar, Switzerland], IL-6 (using high sensitivity ELISA, Quantikine HS human IL-6 immunoassay; R&D Systems, Minneapolis, MN), Leptin [using ELISA, leptin (human) ELISA kit; BioVender, Alexis Biochemicals, Lausen, Switzerland], and high-sensitivity C-reactive protein (CRP; by chemiluminescent immunometry; IMMULITE Bühlmann Laboratories AG, Allschwil, Switzerland). Serum retinol (SR) was measured by HPLC (22) using retinyl-acetate as an internal standard and commercially available reference material from the National Institute of Standards and Technology (Gaithersburg, MD; USA SRM 986c) as an external standard. The quantitative insulin sensitivity check index (QUICKI) was calculated as follows: QUICKI = 1/[log (fasting insulin, milliunits per liter) + log (fasting glucose milligrams per deciliter)] (23).

The RBP and TTR serum concentrations were measured in duplicate by an ELISA (RBP4 ELISA kit K6110 and TTR ELISA kit K6331, respectively, by Immundiagnostik, Bensheim, Germany) with standards supplied by the manufacturer. Absorption was measured at 450 nm in a microplate reader (MRX; Dynatech Produkte AG, Embrach-Embraport, Switzerland)) with 650 nm as the reference wavelength. The RBP4 ELISA kit has been validated by Western blotting as described by Graham et al. (24). It uses a polyclonal antibody that detects both full-length and urinary RBP4; the relative affinities are unknown (our personal communication with Immundiagnostik). The concentrations of RBP, TTR, and SR were measured in serum samples of 75 of the 79 children. The intraassay coefficient of variation for RBP4 was 5% at a concentration of 24.1 and 11.1 µg/ml and for TTR, 3.2% at a concentration of 217 µg/ml. The RBP4 to SR ratio was calculated by dividing plasma RBP4 concentration (micromoles per liter) by the plasma retinol concentration (micromoles per liter). For the calculation of molar concentration of RBP4, a molecular mass of 21,000 g/mol was used (25). The RBP4 to TTR ratio was calculated by dividing the plasma RBP4 concentration (micromoles per liter) by the plasma TTR concentration (micromoles per liter). For the calculation of molecular concentration of TTR, a molecular mass of 54,000 g/mol was used (26).

Statistical analysis

Statistical analysis was performed using the statistical package SPSS 13.0 for Windows (SPSS, Chicago, IL). Nonnormally distributed variables were expressed as medians (ranges) and normally distributed data as means (SD). Nonnormally distributed data were log transformed for comparisons. One-way ANOVA with a post hoc Bonferroni test was used to compare means. Multiple regression and analysis of covariance were used to study the effect of nutrients and metabolic and personal covariates on RBP4 and SR. In all equations, BMI-SDS was introduced as a covariate together with age, gender, and puberty status and their quadratic polynomials when necessary.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Anthropometric and metabolic data of the children, by weight classification, are shown in Table 1Go. Ninety-six percent of the sample were Tanner stage I or II. Only 3% of the children had SR values less than 1.05 µmol/liter, suggesting low vitamin A status (27). Serum RBP4 (P < 0.01), SR, RBP4 to SR (P < 0.05), and TTR (P < 0.02) but not RBP4 to TTR were significantly increased in the overweight and obese children, compared with the normal-weight children (Fig. 1Go). As reported previously (12), body fat percentage, waist to hip ratio (WHR), fasting insulin, insulin resistance as defined by QUICKI, triglycerides, leptin, and systolic blood pressure increased significantly with increasing adiposity (P < 0.01), as did CRP and IL-6 (P < 0.02). HDL-cholesterol levels were lower with increasing adiposity (P < 0.01). There was a highly significant correlation between QUICKI and fasting insulin concentrations in the sample (P < 0.001, r = 0.977).


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  		TABLE 1. Anthropometric and metabolic data of 6- to 14-yr-old Swiss children by weight classification

 

Figure 1
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  		FIG. 1. Boxplots (median, box indicates 25th and 75th percentiles, whiskers indicate the range) illustrating the changes in RBP and the serum retinol: RBP ratios among normal-weight, overweight, and obese children. *, Significant difference, compared with normal-weight group (P < 0.05); **, significant difference, compared with normal-weight and overweight group (P < 0.05).

 
Daily intakes of energy, macronutrients, meat, ß-carotene, preformed vitamin A, and total vitamin A, by weight classification, are shown in Table 2Go. None of the children were taking supplements containing vitamin A. Dietary vitamin A intakes were adequate, compared with recommended daily intakes of 0.4–1.1 mg RAEs for this age group (17, 18). The only significant differences were in intakes of meat and protein (P < 0.05) between normal-weight and obese children. In the regression analyses examining the relationship between dietary factors and BMI-SDS, only protein intake (r = 0.326, P = 0.003) and meat intake (r = 0.388, P < 0.001) were significantly predicted by adiposity. Dietary intakes of ß-carotene, preformed vitamin A, and total vitamin A were not correlated with BMI-SDS.


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  		TABLE 2. Nutritional intakes of 6- to 14-yr-old Swiss children by weight classification

 
Multiple regression analyses of the different measures of adiposity on RBP4, SR, the RBP4 to SR ratio and the RBP4 to TTR ratio are shown in Table 3Go. SR, but not age or gender, was a significant predictor of RBP4. In separate models, after controlling for SR, all three, adiposity (BMI) (P = 0.026), body fat percent (P = 0.025), and central distribution of body fat (WHR) (P = 0.006), remained significant predictors of RBP4. Besides RBP4, SR and the RBP4 to SR ratio were significantly predicted by all three measures of adiposity. Those associations remained the same if boys and girls were analyzed separately. The RBP4 to TTR ratio was significantly predicted only by BMI.


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  		TABLE 3. Associations of adiposity [BMI-SDS, body fat (BF) percent, WHR] on RBP4, SR, the RBP4 to SR ratio, and the RBP4 to TTR ratio in 6- to 14-yr-old Swiss children (n = 75)1

 
Table 4Go shows the associations of RBP4, SR, RBP4 to SR, and TTR to RBP4 with selected individual components of the metabolic syndrome and indices of subclinical inflammation. For SR and the RBP4 to TTR ratio, no significant associations with components of the metabolic syndrome could be identified. In contrast, RBP4 and the RBP4 to SR ratio significantly correlated with triglycerides, and the RBP4 to SR ratio correlated with fasting insulin. Subclinical inflammation, as measured by CRP and IL-6, was not correlated with RBP4, SR, RBP4 to SR, or RBP4 to TTR. There were no significant correlations between other components of the metabolic syndrome shown in Table 1Go and RBP4, SR, RBP4 to SR, or RBP4 to TTR.


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  		TABLE 4. Associations of RBP4, SR, the RBP4-to-SR ratio, and the RBP4-to-TTR ratio with selected components of the metabolic syndrome and indices of subclinical inflammation in 6- to 14-yr-old Swiss children (n = 75)1

 
Using multiple regression models controlling for age, gender, puberty, BMI-SDS, SR, and total energy intake, potential associations of the dietary factors shown in Table 2Go with RBP4, SR, and RBP4 to SR were analyzed. Total vitamin A intakes, as well as intakes of vitamin A as ß-carotene or retinol, did not correlate with RBP, SR, or the RBP4 to SR ratio. Similarly, intakes of total fat, individual fatty acids, and protein or protein-rich foods, such as dairy products and meat products, were not correlated with RBP4, SR, or RBP4 to SR ratio. The intake of animal fat showed a trend toward correlation with RBP4 (P = 0.085) and the RBP4 to SR ratio (P = 0.05) but not SR. None of the other dietary factors in Table 2Go were significantly correlated with RBP, SR, or the RBP4 to SR ratio.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
Circulating RBP4 concentrations are elevated in several mouse models of obesity and insulin resistance, and deleting the RBP4 gene in mice increases insulin sensitivity (3). The link between RBP4 and insulin resistance in human cross-sectional studies is less clear. Previous studies in adults have reported significant associations among RBP4, obesity, and the metabolic syndrome (4, 5, 28, 29). Graham et al. (5) found serum RBP4 concentrations correlated with insulin resistance in subjects with obesity, impaired glucose tolerance, or type 2 diabetes. In contrast, other studies have not found a link between RBP and obesity and/or insulin resistance in adults (30, 31). For example, Janke et al. (6) reported no differences in serum RBP4 among normal-weight, overweight, and obese women and found RBP4 mRNA was down-regulated in adipose tissue of obese women. Studies done before RBP4 was identified as an adipokine investigated vitamin A status in adults with type 2 diabetes and reported equivocal results (32, 33, 34).

Two recent studies in adolescents (35, 36) reported increased RBP4 concentrations with increasing adiposity. In Korean adolescents, Lee et al. (35) found an association between RBP4 and insulin resistance and serum triglycerides in nonobese adolescents and between RBP4 and triglycerides in obese adolescents. Balagopal et al. (36) found RBP4 was positively correlated with serum CRP concentrations (36).

Our data in younger children indicate that RBP4 is significantly correlated with adiposity (BMI) and central adiposity (WHR), independent of age. Similar to data in overweight adults and adolescents (5, 35), we found that, independent of BMI and WHR, RBP4 and the RBP4 to SR ratio are significantly correlated with components of the metabolic syndrome, i.e. serum triglycerides and fasting insulin. A limitation of our sample is the wide age range of the subjects (6–14 yr), which could have introduced difficulties due to differences in pubertal stage among the sample. However, 96% of the children were Tanner stage I or II, and we used multivariate models controlling for age, gender, and pubertal stage.

Although RBP4 is a negative acute-phase protein (37), nearly all previous studies did not assess the potential confounding of RBP4 by subclinical inflammation, a common finding in obesity (37, 38). In our sample, although indices of inflammation (CRP, IL-6, and leptin) were increased in the obese children, they were not correlated with RBP4, suggesting subclinical inflammation is not a confounder in this age group. These data differ from those of Balagopal et al. (36), in which CRP correlated with RBP4 in adolescents. This difference may be due to differences in age and/or pubertal stage because the subjects in the study of Balagopal et al. (36) were older (14–18 yr) and all were Tanner stage IV, and in our group the children were younger and most of them were Tanner stage I or II.

In previous studies linking RBP4 to insulin resistance, the major biologic determinant of serum RBP4, i.e. vitamin A status, was not measured. RBP4 is mainly synthesized by the liver, and, bound to retinol and TTR (7, 39, 40), its function is to transport retinol from hepatic storage to target tissues. However, not all serum RBP is bound to retinol, and the proportion that is not (apo-RBP) varies because the binding of RBP to retinol and TTR is affected by multiple factors, including vitamin A status, the acute-phase response, protein-energy malnutrition, liver disease, and renal failure (41, 42, 43, 44).

The RBP4-SR relationship may be important in obesity in that the link between RBP4 and insulin resistance may occur through retinol-dependent (i.e. changes in retinol metabolism or delivery) or retinol-independent mechanisms. Retinoids can stimulate phosphoenolpyruvate-carboxykinase expression in the liver and hepatic gluconeogenesis. In addition, retinol is a precursor for the synthesis of ligands of the retinoic acid receptor and retinoid X receptor nuclear receptors (45, 46); these are partners of the peroxisome-proliferator-activated receptor family that regulate genes central to fatty acid metabolism (47). RBP4 could thus be linked to insulin resistance through impaired fatty acid metabolism (48), and increased expression of several retinoid-responsive genes, retinoic acid receptor-2, stearoyl-CoA desaturase-1, and acetyl CoA carboxylase, is increased in muscle of RBP4-transgenic mice (3). Thus, increased delivery of retinol by RBP4 might explain its effects on insulin metabolism. However, the link between retinoids and insulin action is complex: some retinoids activate the retinoid X receptor-peroxisome-proliferator-activated receptor heterodimer and increase insulin sensitivity (48), whereas others produce insulin resistance in humans (49, 50). Yang et al. (3) showed that RBP4 itself stimulates phosphoenolpyruvate-carboxykinase expression and glucose production in cell cultures, which suggests the peptide has a direct, retinol-independent, effect.

In our study, BMI and WHR, independent of age, subclinical inflammation, and dietary vitamin A intake, were positively correlated with RBP4, SR, and RBP4 to SR ratio. However, only the RBP4 to SR ratio was correlated with fasting insulin. These data suggest that RBP4 may be linked to adiposity and the metabolic syndrome via both retinol-dependent and -independent mechanisms, at least in children.


   Acknowledgments
 
We thank the participating children and families, and special thanks go to M. T. Achermann, H. Seiler, C. Zwimpfer, S. Jacob (University Hospital Zurich); R. F. Hurrell, K. Hotz, and C. Zeder (ETH Zurich); I. Hutter (Children’s Hospital, St. Gallen) as well as the staff from the Children’s Hospitals in Biel and Basel.


   Footnotes
 
This study was supported by the Swiss Diabetes Foundation (Steinhausen, Switzerland), the Swiss Ministry of Health (Bern, Switzerland), and the ETH Zürich (Switzerland). Each of the authors contributed to the study design. I.A., M.B.Z., G.A.S., R.L., and D.A. performed the field work and data collection. I.A., M.B.Z., R.B., G.A.S., and R.L. supervised the laboratory analysis and completed the data analysis. I.A. and M.B.Z. conducted the statistical analysis. The first draft of the manuscript was written by I.A. and M.B.Z. All authors edited the manuscript.

Disclosure Statement: None of the authors had a financial or personal conflict of interest in regard to this study.

First Published Online August 28, 2007

Abbreviations: BMI, Body mass index; CRP, C-reactive protein; FFB, fat-free body mass; HDL, high-density lipoprotein; QUICKI, quantitative insulin sensitivity check index; RAE, retinol activity equivalent; RBP, retinol-binding protein; SDS, SD score; SR, serum retinol; TTR, transthyretin; WHR, waist-to-hip ratio.

Received February 28, 2007.

Accepted August 17, 2007.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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