SPECIAL COMMUNICATION
Gender differences in leptin levels during puberty are related to the subcutaneous fat depot and sex steroids

James N. Roemmich1, Pamela A. Clark1, Stuart S. Berr2, Vu Mai2, Christos S. Mantzoros3, Jeffrey S. Flier3, Arthur Weltman4,5, and Alan D. Rogol1,6

1 Division of Endocrinology, Department of Pediatrics, 2 Department of Radiology, 5 Division of Endocrinology and Metabolism, Department of Medicine, 6 Department of Pharmacology, University of Virginia Health Sciences Center, and 4 Department of Human Services, Curry School of Education, University of Virginia, Charlottesville, Virginia 22908; and 3 Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215

    ABSTRACT
Top
Abstract
Introduction
Methods
Results
Discussion
References

Little is known about the influence of adiposity and hormone release on leptin levels in children and adolescents. We utilized criterion methods to examine the relationships among sex steroids, body composition (4 compartment), abdominal visceral and subcutaneous fat (magnetic resonance imagery), total subcutaneous fat (sum of 9 skinfolds), energy expenditure (doubly labeled water), aerobic fitness, and serum leptin levels in prepubertal and pubertal boys (n = 16; n = 13) and girls (n = 12; n = 15). The sum of skinfolds accounted for more variance in leptin levels of all girls [coefficient of determination (R2) = 0.70, P < 0.001] and all boys (R2 = 0.60, P < 0.001) than the total fat mass (girls, R2 = 0.52, P < 0.001; boys, R2 = 0.23, P < 0.001). Total energy expenditure, corrected for the influence of fat-free mass, correlated inversely with leptin (R2 = 0.18, P = 0.02). Gender differences in leptin disappeared when corrected for sex steroid levels or the combination of adiposity and energy expenditure. In multiple regression, the sum of skinfolds and free testosterone and estrogen levels accounted for 74% of the variance in leptin levels. We conclude that serum leptin levels are positively related to subcutaneous adiposity but negatively related to androgen levels. Energy expenditure may be negatively related to leptin levels by reduction of the adiposity, or a common genetic factor may influence both the activity and serum leptin levels.

children; four-compartment body composition; obesity; subcutaneous fat; visceral fat

    INTRODUCTION
Top
Abstract
Introduction
Methods
Results
Discussion
References

THE HORMONE LEPTIN is thought to control satiety and adiposity by acting as a feedback signal between the adipocytes and the hypothalamus (30, 33). In children (2, 3, 5, 9, 15, 22) and adults (4, 12, 23), the serum leptin concentration is directly related to the amount of adiposity, suggesting leptin resistance. For a given level of adiposity in children, serum leptin concentrations can vary by up to 10-fold (2, 5, 9, 15). The wide dispersion of serum leptin concentrations may be due to genetic influences on leptin production and sensitivity and the use of inaccurate estimates of body composition that do not allow the leptin concentration to be properly corrected for the adiposity. Previous studies of children have used body composition estimates from dual-energy X-ray absorptiometry, body mass index, or bioelectrical impedance, which do not adequately account for the difference between the actual and the assumed density of the fat-free mass in children, resulting in large errors for a given child (27). The wide variation in serum leptin concentration may not exist after proper correction for the total fat mass.

Pubertal girls have two- to threefold greater serum leptin concentrations than pubertal boys after correction for adiposity (2, 9, 22). The lower serum leptin concentrations in males may be due to an androgen-induced reduction in leptin production (36). However, the gender difference in serum leptin concentration is also present prepubertally (9), suggesting that factors other than sex steroids (e.g., body fat patterning, energy expenditure, aerobic fitness) influence serum leptin concentrations. Some fat depots may have a greater importance for leptin production and secretion and thus a greater impact on the leptin-neuropeptide Y axis than others (21). Understanding which fat depots are most highly related to serum leptin concentrations is important, because puberty is the time when the adult-type fat distribution patterns are established. For instance, leptin mRNA expression is greater in abdominal subcutaneous fat than in abdominal visceral fat, and the ratio of subcutaneous to visceral fat leptin mRNA expression is 3.6-fold higher in women than in men (21). The serum leptin concentration is more highly correlated with the abdominal subcutaneous fat than with the abdominal visceral fat in children (3, 22). However, the subcutaneous fat from one portion of the abdomen may not accurately represent the influence of the total subcutaneous fat depot on serum leptin concentrations, because subcutaneous fat patterning is dependent on gender and the stage of pubertal maturation (18). A composite measure of the subcutaneous fat taken from many body regions may better represent the influence of the total subcutaneous fat depot on serum leptin concentrations. This is the first investigation to properly examine the independent influences of various fat depots vs. the total fat mass on serum leptin concentrations during puberty, because ours is the only study to use valid estimates of both total fat (27) and fat distribution.

The relationship between serum leptin and adiposity may also be influenced by the energy expenditure. Leptin treatments increase the metabolic rate and reduce the adiposity of the ob/ob mouse, which does not produce leptin (10, 13, 24). The influence of energy expenditure on the size of various fat depots of children and adolescents has not been widely studied. If increasing the energy expenditure has a greater effect on the size of the subcutaneous fat depot of girls but the visceral fat depot of boys, it could indirectly contribute to the gender difference in serum leptin concentrations. The purpose of this investigation was to evaluate the influence of criterion estimates of sex steroids, body composition, body fat distribution, energy expenditure, and aerobic fitness on serum leptin concentrations in girls and boys.

    METHODS
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Abstract
Introduction
Methods
Results
Discussion
References

Subjects. Measurements were made in a cross-sectional sample of boys (n = 29) and girls (n = 27) enrolled in a longitudinal growth study to determine the influence of sex steroids, body composition, body fat distribution, and energy expenditure on serum leptin concentrations. The study was approved by the University of Virginia Human Investigation Committee. Informed consent was obtained from a parent and assent from each child. Entrance into the study required a height, height velocity, and weight within two standard deviations (SD) of the mean for chronological age. Bone age was determined by the Fels method (26) by an experienced assessor (J. N. Roemmich). Stage of secondary sex characteristics was assessed by the method of Tanner (35). Boys with genital development of stage 2 or greater and girls with breast development of stage 2 or greater were placed into the pubertal groups.

Energy expenditure/total body water. The basal metabolic rate (BMR) was measured for 30 min via indirect calorimetry (Deltatrac, SensorMedics, Yorba Linda, CA). The measure was made on waking after an overnight stay in the General Clinical Research Center. The reliability of the resting metabolic rate data was tested by measuring the BMR of 12 young adults from 1030 to 1100, 1130 to 1200, and 1230 to 1300. Intraclass correlation (ANOVA followed by calculation of R) found no significant differences between trials (1,759 ± 68 kcal, 1,761 ± 74 kcal, 1,773 ± 73 kcal), and R = 0.98. To measure the total energy expenditure (TEE), the subjects drank a mixed oral dose of 2H2O (0.5 g/kg) and H218O (1.5 g/kg). Urine samples were collected before dosing, 4 and 5 h postdose and 1, 6, and 12 days postdose. The samples were kept frozen at -20°C in cryovials until analysis by isotope ratio mass spectroscopy (Metabolic Solutions, Merrimack, NH). The difference between 2H and 18O in the predose and postdose urine samples was determined by use of the unprocessed mass spectrometric data, as previously described (25). Linear regression was used to determine the slope and intercept of the relationship between baseline and the normalized isotope 2H and 18O data. The pool sizes for 2H2O (ND) and H218O (NO) were the reciprocals of the intercepts. For the four-compartment body composition model, the total body water (TBW) was calculated by dividing the 2H2O dilution space by 1.04 (29). The TBW was then converted to kilograms by dividing by 0.9937, the density of water at body temperature. The intercept of the regression line was the ND-to-NO ratio (ND/NO). If the ND/NO was outside of the range of 1.015 and 1.060, the samples were reanalyzed. The fractional turnover rates of 2H and 18O were determined from the slope of the regression line. The mean daily rate of CO2 production (rCO2, mol/day) was calculated as proposed by the revised equations of Speakman et al. (32). The daily energy expenditure rate for men was calculated by multiplying the rCO2 value by 127.5 kcal/mol CO2, the energy equivalent of the typical Western diet, which produces a respiratory quotient of 0.85 with 15% of the energy from protein oxidation. Physical activity energy expenditure (AEE) was calculated as total energy expenditure minus the BMR.

Body composition. Body composition was estimated by a criterion four-compartment model (16). Validation of the use of this model in our laboratory was recently reported (27). Body volume was measured by underwater weighing and corrected for residual volume by nitrogen washout. The body density was corrected for the TBW as described above, and the bone mineral content was corrected by dual-energy X-ray absorptiometry with a Hologic QDR 2000 bone densitometer (Hologic, Waltham, MA). The estimated percentage of body fat from the four-compartment model was used to calculate the fat mass (FM) and fat-free mass (FFM) by subtraction.

Magnetic resonance imaging. Abdominal subcutaneous fat and abdominal visceral fat areas at the level of the lumbar 4-lumbar 5 (L4-L5) intervertebral space were measured with magnetic resonance imaging (MRI) by use of a Siemens Vision 1.5T scanner. Adipose tissue at the L4-L5 levels was assessed using a Dixon imaging sequence phase corrected for magnetic field inhomogeneities. A standard spin-echo pulse sequence was used for the in-phase image. The out-of-phase image was acquired by shifting the 180° refocusing pulse by 1.12 ms. Images were acquired with a slice thickness of 6 mm, matrix of 256 × 256, and a ratio of repetition time to echo time of 575/15 ms. No oversampling or raw filters were used in the data acquisition, and two acquisitions were used per slice. The images were acquired with a 100% gap, followed by a shift in slices that led to a set of contiguous two-dimensional images. For postacquisition processing, a magnetic field inhomogeneity map was calculated from the in-phase and out-of-phase images, as previously described (6), which assumes that there are unequal amounts of fat and water in each pixel. This map was then used to unwrap phase shifts induced by the inhomogeneities by use of a region-growing technique and used to correct for phase error in the opposed phase image (34). Adding or subtracting the in-phase and opposed-phase images resulted in the water and fat images, respectively. The fat- and water-based tissue areas were determined using MedX software (Sensor Systems, Sterling, VA).

Anthropometry. All of the auxological measures were completed by a single trained anthropometrist (J. N. Roemmich). Height, trunk skinfolds (subscapular, chest, mid-axillary, suprailiac, abdominal), and peripheral skinfolds (triceps, biceps, thigh, and medial calf) were measured as recommended (11).

Peak O2 consumption. Peak O2 consumption (VO2 peak) was measured using a treadmill (Quinton Q65, Seattle, WA) exercise test. After a walking warm-up, the subjects began at an initial velocity of 3.4-6 mph depending on the size of the child. The initial velocity was then held constant, and the grade was increased from 0 by 2.5% every 2 min until volitional exhaustion. Metabolic data were collected every 20 s during the exercise bout via standard indirect calorimetry procedures by use of a SensorMedics 2700-Z metabolic cart (Yorba Linda, CA). Heart rates were monitored by echocardiograph. Subjects were given verbal encouragement throughout the test.

Assays. Serum leptin concentration was measured by RIA, as previously described (20). Serum total testosterone, free testosterone, estradiol, and progesterone concentrations were measured by RIA with kits from Diagnostic Products (Los Angeles, CA). The sensitivity of the testosterone assay was 10.0 ng/dl, with an intra-assay coefficient of variation (CV) of 5-6% within the range of 100-800 ng/dl. The interassay CV ranged from 9.2 to 12.9% within the range of 70-840 ng/dl. The free testosterone assay has a sensitivity of 0.15 pg/ml, with an intra-assay CV of 4-3% within the range of 4.6-40.3 pg/ml and an interassay CV of 5-3% within the range of 4.7-42.4 pg/ml. The sensitivity of the estradiol assay was 10.0 pg/ml, with an intra-assay CV of 4-7% within the range of 50-1,100 pg/ml. The interassay CV ranged from 4.2 to 8.1% within the range of 50-1,025 pg/ml. The progesterone assay sensitivity was 0.03 ng/ml, with an intra-assay CV of 6-3% within the range of 1.1-16.3 ng/ml and an interassay CV of 10-5% within the range of 1.3-15.9 ng/ml.

Statistics. ANOVA [(2) gender × (2) maturation] was used to test for group differences in body composition, body fat distribution, energy expenditure, and serum leptin concentrations. Regression analysis was used to examine the strength of the relationship between leptin concentration and body composition, body fat distribution, and energy expenditure variables. Multiple linear regression analyses were used to determine the independent effects of key predictor variables on serum leptin concentrations. Multiple linear regression was also used to test whether the slopes and intercepts of the leptin-adiposity relationships differed in the male and female subject groups or the prepubertal and pubertal subject groups. The regression parameters were compared by pooling the data and performing a regression with either "gender" or "maturation" as an additional (dummy) independent variable and then testing the significance of the dummy terms. The model took the form
<IT>Y</IT> = &bgr;<SUB>0</SUB> + &bgr;<SUB>1</SUB><IT>X</IT> + &bgr;<SUB>2</SUB><IT>Z</IT> + &bgr;<SUB>3</SUB><IT>ZX</IT>
where Y is the dependent variable [log(10) leptin], X is the independent variable (adiposity), and Z is either 0 or 1, depending on the gender or maturation of the subject. If the intercept is the same in both groups, beta 2 is equal to zero. If the slope is the same in both groups, beta 3 is equal to zero (14). Forward stepwise regression was used to determine the combination of variables that most accurately predicted serum leptin concentration, with careful attention paid to multicolinearity between variables. A maximum of three steps were examined to maintain an adequate subject-to-predictor ratio. The leptin concentrations were log transformed, because the absolute values were not normally distributed.

    RESULTS
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Abstract
Introduction
Methods
Results
Discussion
References

Physical characteristics are shown in Table 1. Gender differences were observed with boys having lower serum leptin concentrations (P = 0.002), %body fat (P = 0.0008), FM (P = 0.01), sum of skinfolds (P = 0.05), and abdominal subcutaneous fat area (P = 0.08) and a greater VO2 peak (P < 0.0001). Pubertal boys and girls were older (P < 0.0001), more skeletally mature (P < 0.0001), taller (P < 0.0001), and heavier (P < 0.0001) and had greater amounts of FM (P = 0.0007), FFM (P < 0.0001), and abdominal visceral fat (P = 0.01) and greater TEE (P = 0.008) than prepubertal boys and girls. The BMR was significant for the interaction effect (P = 0.03) in that the pubertal boys had a greater BMR than the pubertal females.

                              
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Table 1.   Physical characteristics, leptin concentration, four-compartment model body composition, abdominal visceral fat, subcutaneous abdominal fat, sum of skinfolds, subcutaneous fat distribution, and total energy expenditure of subject groups

The slopes of the leptin-adiposity relationships were not dependent on pubertal maturation. The coefficient and P value for the slope term in the multiple linear regression analyses were the sum of skinfolds × maturation (beta 3 = 0.0004, P = 0.92), FM × maturation (beta 3 = 0.0275, P = 0.49), abdominal subcutaneous fat × maturation (beta 3 = 0.0013, P = 0.51), and abdominal visceral fat × maturation (beta 3 = -0.009, P = 0.28). Thus, for Figs. 1 and 2, the data from the prepubertal and pubertal subjects were collapsed and the regression lines were drawn as "all boys" and "all girls." As shown in Fig. 1, the log(10) leptin concentration and sum of skinfolds increased in a curvilinear relationship. The coefficient of determination (R2) values of the second-order regressions are shown in Fig. 1. The R2 values of the first-order (linear) regressions for all subjects, all girls, and all boys were 0.62, 0.62, and 0.56, respectively. The slope of the first-order log(10) leptin sum of skinfold regression did not differ between genders (beta 3 = 0.002, P = 0.41). The sum of four peripheral skinfolds (second-order R2: for all subjects = 0.61, all girls = 0.66, and all boys = 0.66) and sum of five trunk skinfolds (second-order R2: for all subjects = 0.67, all girls = 0.71, and all boys = 0.59) also had significant (P < 0.001) curvilinear relationships with log(10) leptin concentrations. Total FM and log(10) leptin concentrations increased in a linear fashion, and the total FM did not account for as much variance in log(10) leptin concentrations as the sum of skinfolds (Fig. 1). The slope of the log(10) leptin-FM regression line was not significantly different in girls and boys (beta 3 = -0.004, P = 0.86).


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Fig. 1.   Relationship between serum log(10) leptin concentration and sum of skinfolds (top) and fat mass (FM, bottom). Slope of linear regression line was similar (see RESULTS) for both genders for leptin vs. sum of skinfolds {for girls, [log(10) leptin = 0.0072 (sum of skinfolds) + 0.1573]; for boys, [log(10) leptin = 0.0078 (sum of skinfolds) -0.1056]} and for leptin vs. FM {for girls, [log(10) leptin = 0.0626 (FM) + 0.3081]; for boys, [log(10) leptin = 0.0466 (FM) + 0.2723]}. Solid line, regression for all subjects; long dashed line, regression for girls; short dashed line, regression for boys. bullet , Prepubertal boys; black-triangle, pubertal boys; open circle , prepubertal girls; triangle , pubertal girls.

The abdominal subcutaneous fat area and log(10) leptin concentration increased in a direct relationship (Fig. 2) for all subjects, all girls, and all boys. The slope of regression lines for boys and girls was not different (beta 3 = 0.001, P = 0.66). Weaker relationships were observed between log(10) leptin concentration and abdominal visceral fat area than for FM and subcutaneous fat (Figs. 1 and 2). The relationship was stronger in boys than in girls. The slope of the log(10) leptin-abdominal visceral fat regression line was similar in girls and boys (beta 3 = 0.008, P = 0.31). From multiple linear regression, the ratio of abdominal subcutaneous to visceral fat was directly related to the log(10) leptin concentration, even after correction for the total FM (R2 = 0.54, P = 0.03).


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Fig. 2.   Relationship between serum log(10) leptin concentration and abdominal subcutaneous fat area (top) and abdominal visceral fat area (bottom) measured at level of lumbar 4-lumbar 5 intervertebral space. Slope of regression line was similar (see RESULTS) for both genders for leptin vs. abdominal subcutaneous fat {for girls, [log(10) leptin = 0.0040 (abdominal subcutaneous fat) + 0.5618]; for boys, [log(10) leptin = 0.0045 (abdominal subcutaneous fat) + 0.2629]} and for leptin vs. abdominal visceral fat {for girls, [log(10) leptin = 0.0047 (abdominal visceral fat) + 0.7920]; for boys, [log(10) leptin = 0.0080 (abdominal visceral fat) + 0.2166]}. Solid line, regression for all subjects; long dashed line, regression for girls; short dashed line, regression for boys. bullet , Prepubertal boys; black-triangle, pubertal boys; open circle , prepubertal girls; triangle , pubertal girls.

An inverse linear relationship was observed between VO2 peak and log(10) leptin concentrations in all subjects (R2 = -0.18, P = 0.004), but not in all girls (R2 = -0.08, P = 0.16) or all boys (R2 = 0.01, P = 0.77). The inverse relationship between VO2 peak and log(10) leptin concentrations was maintained after correction for the sum of skinfolds (P = 0.02), FM (P = 0.04), and FFM (P = 0.003) but not after correction for the TEE (P = 0.08) or AEE (P = 0.09).

When analyzed for all subjects (R2 = -0.002) or for all boys (R2 = 0.01) or all girls (R2 = -0.003), log(10) leptin concentration and the BMR were not related, even after the confounding effects of FFM on BMR were removed with multiple linear regression (data not shown). The respiratory exchange ratio and log(10) leptin concentrations were not significantly related (R2 = 0.02, P = 0.31). The TEE was inversely, but not significantly, related to log(10) leptin concentrations for all subjects (R2 = -0.06, P = 0.11), all boys (R2 = -0.05, P = 0.35), and all girls (R2 = -0.04, P = 0.34). After the FFM was statistically controlled for, the TEE was inversely related to log(10) leptin concentrations in all subjects and all girls (Table 2). The AEE was inversely related to the leptin concentrations for all subjects (R2 = -0.10, P = 0.05) but was not significant for all boys (R2 = -0.10, P = 0.21) or all girls (R2 = -0.07, P = 0.24). Statistical correction of the AEE for the FFM enhanced the inverse relationship with leptin concentrations for all subjects and all girls, but not for all boys (Table 2).

                              
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Table 2.   Results from multiple linear regression analyses with log(10) leptin concentration as dependent variable

Gender remained related to log(10) leptin concentrations after differences in FM or the sum of skinfolds were accounted for but not after correction for both the adiposity and the FFM (Table 3). Likewise, gender was not a significant predictor of log(10) leptin concentrations after FM and TEE or the sum of skinfolds and TEE was controlled for (Table 3). The stage of pubertal maturation was a significant predictor of log(10) leptin concentrations only in the gender-FM model.

                              
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Table 3.   Results from multiple linear regression analyses with log(10) leptin concentration as dependent variable and with correction for body composition, body fat distribution, or energy expenditure

Investigation of the relationship between sex steroids and leptin concentration was limited to those subjects whose sex steroid concentrations were above the lower sensitivity of the assay. For the girls, progesterone (R2 = 0.19, P = 0.02) and estradiol (R2 = 0.15, P = 0.08) were modestly related to log(10) leptin concentration. Neither testosterone (R2 = -0.05, P = 0.30) nor free testosterone (R2 = -0.10, P = 0.29) was significantly related to log(10) leptin concentrations in the pubertal boys. Estrogen concentrations remained related to log(10) leptin concentrations after correction for the sum of skinfolds (R2 = 0.72, P = 0.02) or the FM (R2 = 0.65, P = 0.05). Progesterone and log(10) leptin concentrations were not related after correction for the sum of skinfolds (P = 0.31) or FM (P = 0.29). When log(10) leptin concentrations were adjusted for either the serum total or free testosterone or estradiol concentration, gender no longer had a significant independent effect on serum leptin concentration (Table 4).

                              
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Table 4.   Results from multiple linear regression analyses with log(10) leptin concentration as dependent variable and with correction for sex steroid concentrations

Two forward stepwise regression analyses were completed (Table 5). The first included sex steroids as dependent variables. The second did not include sex steroid variables so as to allow comparison of our data with previous investigations of children (5, 22). In the first stepwise regression, the sum of skinfolds was a positive predictor of log(10) leptin concentrations, accounting for 59% of the variance in log(10) leptin concentrations. The free testosterone concentration (negative predictor) and estrogen concentration (positive predictor) accounted for an additional 9 and 5% of the variance, respectively. In the second regression, the sum of skinfolds accounted for 59% and the TEE (negative predictor) accounted for an additional 6.5% of the variance in log(10) leptin concentrations.

                              
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Table 5.   Results from forward stepwise regression analysis with log(10) leptin concentration as dependent variable

    DISCUSSION
Top
Abstract
Introduction
Methods
Results
Discussion
References

We have utilized a sum of nine skinfolds as a measure of the total subcutaneous fat to show that serum leptin concentrations are more highly related to the total subcutaneous fat than to the total FM or the abdominal subcutaneous fat or abdominal visceral fat depots (Figs. 1 and 2, Table 5). Previous studies (3, 22) have assumed that the abdominal subcutaneous fat is representative of the total subcutaneous fat depot. However, this may not be valid because of the gender and maturational influences on subcutaneous fat patterning during puberty (18, 19). We found that the total subcutaneous fat and abdominal subcutaneous fat were not similarly associated with the serum log(10) leptin concentration. The sum of all skinfolds (Fig. 1), sum of trunk skinfolds, and sum of peripheral skinfolds (see RESULTS) increased in a curvilinear relationship with log(10) leptin concentrations. The total FM (Fig. 1), abdominal subcutaneous fat, and abdominal visceral fat (Fig. 2) increased in linear relationships with log(10) leptin concentrations. The sum of skinfolds was the only adiposity-related variable that entered in a forward stepwise regression to predict serum leptin concentrations, which suggests that the sum of skinfolds is a better predictor of the influence of the subcutaneous fat depot on log(10) leptin concentrations than is the abdominal subcutaneous fat (Table 5).

Our investigation is the only one that utilizes a valid method to estimate total FM in children and adolescents (27). Thus the present investigation most accurately describes the FM-serum leptin concentration relationship and most accurately corrects serum leptin concentrations for the FM. The present investigation also utilizes criterion methods to assess the TEE and is the first to compare the separate and combined influences of criterion measures of total FM, specific fat depots, energy expenditure, and sex steroids on serum leptin concentrations in the same subjects. We determined that individual differences in total FM could not account for the gender difference in serum leptin concentration and the wide variation in serum leptin concentration at a given adiposity. Rather, the body fat distribution, TEE, and sex hormone concentrations modify the serum leptin-adiposity relationships.

Several of our findings suggest that the body fat distribution is associated with the gender difference in serum leptin concentrations. The total subcutaneous fat was most highly related to log(10) leptin concentrations (Figs. 1 and 2; Table 5). The abdominal subcutaneous fat area was more strongly correlated with serum leptin concentrations than abdominal visceral fat area from the same MRI slice (Fig. 2) (3, 7, 21, 22). These data support cellular findings that leptin mRNA expression is greater in adipocytes from the subcutaneous fat depot than from the visceral fat depot (21). Together, these data suggest that the greater amount of subcutaneous fat in the girls (Table 1) could increase leptin production and the serum leptin concentration (17). The ratio of subcutaneous to visceral leptin mRNA expression is greater in females than in males (21). In the current investigation, as the ratio of abdominal subcutaneous to visceral fat increased, the log(10) leptin concentration also increased, even after correction for the total FM (see RESULTS). Furthermore, serum leptin concentrations correlated with abdominal visceral fat in boys but not girls (Fig. 2), even though the abdominal visceral fat area did not differ between genders (Table 1). The stronger relationship between serum leptin concentration and abdominal visceral fat in males may be due to their significantly lower sum of skinfolds (amount of subcutaneous fat) compared with the females (Table 1). That is, in the males, the overriding influence of subcutaneous fat on serum leptin concentration may be lessened so that the leptin contribution from the visceral fat depot is more apparent, and the visceral fat depot of males may supply a greater percentage of the total serum leptin than that of females.

The gender difference in serum leptin concentration was not fully accounted for by differences in subcutaneous fat or criterion measures of total FM (Table 3). The girls had greater serum leptin concentrations at a given amount of adiposity (Figs. 1 and 2), although the slope of the regression lines was not significantly different (see RESULTS). Similar to findings of Nagy et al. (22), the combination of FM and FFM or our model of the sum of skinfolds and FFM could account for the gender difference in log(10) leptin concentrations (Table 3). In all models, the FFM was negatively related to the log(10) leptin concentration. Several reports (5, 22) have mentioned that some factor related to the FFM reduces leptin production in children. We hypothesize that this factor may be the TEE. Regression models that combined adiposity and TEE (Table 3) accounted for the gender difference in log(10) leptin concentration in similar fashion to the models combining adiposity and FFM (Table 3). When corrected for the amount of metabolically active tissue (FFM), the TEE and serum leptin concentration are inversely related, especially in girls (Table 2). The sexual dimorphism may exist because the TEE (corrected for the FFM) is more highly inversely related to the sum of skinfolds in girls (girls: R2 = -0.26, P = 0.01; boys: R2 = -0.04, P = 0.43) and abdominal visceral fat in boys (girls: R2 = -0.01, P = 0.68; boys: R2 = -0.24, P = 0.05). Thus girls who expend the most energy for a given amount of FFM may have lower amounts of subcutaneous fat, the primary leptin-producing fat depot. Under the same constraints, males may have less visceral fat, a fat depot that produces less leptin. When sex steroids are not considered, energy expenditure may indirectly influence serum leptin concentrations by reducing the amount of subcutaneous fat (Table 5). Of course we cannot prove causality from our correlations.

Androgens reduce leptin production in vitro (36) and are negatively related to serum leptin concentrations in vivo (1, 8, 20, 36). Perhaps because of the small sample size, we did not find a significant inverse relationship between log(10) leptin concentrations and androgen concentrations in the boys (see RESULTS). However, other evidence demonstrates that sex steroids are related to the gender difference in serum log(10) leptin concentrations. Estradiol concentrations of the girls were positively related to serum leptin concentrations after correction for adiposity, suggesting that estrogens enhance leptin production (8, 31). When serum leptin concentrations were adjusted for either the serum total or free testosterone or estradiol concentration, gender no longer had a significant effect on serum leptin concentration (Table 4). Results of the forward stepwise regression (Table 5) support the notion that a combination of variables, including the total subcutaneous fat (primary factor), androgens, and estrogens, best predicts serum leptin concentrations in boys and girls.

VO2 peak and serum leptin concentrations are influenced by many of the same factors, including age, gender, body composition, and genetics. Leptin injections increase the activity and VO2 of the ob/ob mouse (28), suggesting a potential link between VO2 peak and leptin production. The VO2 peak was inversely related to serum leptin concentrations before (see RESULTS) and after adjustment for adiposity, but not after correction for the AEE. Perhaps greater amounts of physical activity (energy expenditure) increase the aerobic fitness and, as discussed above, reduce the adiposity, resulting in lower serum leptin concentrations. Alternatively, a common genetic factor may be responsible for increasing the physical activity and downregulating serum leptin concentrations. The inverse relationship between the amount of FFM and serum leptin concentration may also be relevant here, but we cannot prove that youth exercise more because they have a genetically predetermined large FFM or that they have a large FFM because they exercise. Although our data disagree with previous studies of adults that found no relation between aerobic fitness and serum leptin concentration after adjustment for adiposity (12, 23), our study is the only one to adjust the data with accurate measures of adiposity.

In summary, this is the first investigation to use criterion methods of body composition, body fat distribution, and energy expenditure to examine the independent and combined influences of the total FM, various fat depots, energy expenditure, sex steroids, and aerobic fitness on serum leptin concentrations in children and adolescents. As such, this is the first study to accurately describe these relationships in youth. The results of the present study indicate the following conclusions. 1) Serum leptin concentrations are more strongly related to the total subcutaneous fat than to the total FM or the abdominal subcutaneous fat or visceral fat depots. 2) The abdominal subcutaneous fat and total subcutaneous fat masses may not have similar relationships with serum leptin concentrations. 3) Serum leptin concentrations are greater in girls than in boys, and the gender difference cannot be accounted for by criterion measures of FM or body fat distribution. 4) The gender difference in serum leptin concentration was related to differences in subcutaneous fat and sex steroid concentrations or subcutaneous fat and energy expenditure. 5) Serum leptin concentrations are indirectly related to aerobic fitness, perhaps through the influence of physical activity to increase VO2 peak and energy expenditure, which may reduce the adiposity. Childhood and adolescence are critical periods for the establishment of the adult human body and obesity. The hormonal signals influencing the pubertal alterations in body composition and body fat distribution remain unclear. Alterations in adiposity and its distribution are likely caused by the interaction of sex steroids, growth hormone, leptin, nutrition, and genetics. Future longitudinal studies must consider all of these factors to determine their separate and combined influences on the timing and tempo of puberty and pubertal changes in body fat distribution.

    ACKNOWLEDGEMENTS

The authors are indebted to Sandra Jackson and the nursing staff at the University of Virginia General Clinical Research Center (GCRC), who provided patient care; Judy Weltman, M.S., and Laurie Wideman, Ph.D., for collecting the peak oxygen consumption and basal metabolic rate data; Milagros Huerta, M.D., and Deepali Sharma for assistance with data collection; and John Christopher for help with the MRI methodology. We also acknowledge the subjects for their enthusiasm for the research program for the past two years.

    FOOTNOTES

This work was supported in part by National Institutes of Health Grants HD-32631 (to A. D. Rogol) and DK-28082 (to J. S. Flier), GCRC Grants RR-00847 (to the University of Virginia) and RR-010302 (to Beth Israel Hospital), a grant from Genentech Foundation for Growth and Development (to P. A. Clark), and a grant from the University of Virginia Children's Medical Center (to J. N. Roemmich).

Address for reprint requests: J. N. Roemmich, Univ. of Virginia Health Sciences Center, Dept. of Pediatrics, Division of Endocrinology, Box 386, Charlottesville, VA 22908.

Received 27 October 1997; accepted in final form 4 June 1998.

    REFERENCES
Top
Abstract
Introduction
Methods
Results
Discussion
References

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