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
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ABSTRACT |
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 |
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.
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METHODS |
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
(
O2 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
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,
2
is equal to zero. If the slope is the same in both groups,
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 |
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
O2 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
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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 (
3 = 0.0004, P = 0.92), FM × maturation
(
3 = 0.0275, P = 0.49), abdominal subcutaneous fat × maturation (
3 = 0.0013, P = 0.51), and abdominal visceral fat × maturation (
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
(
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
(
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. , Prepubertal boys; , pubertal boys; , prepubertal
girls; , pubertal girls.
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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
(
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
(
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. , Prepubertal boys; ,
pubertal boys; , prepubertal girls; , pubertal girls.
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An inverse linear relationship was observed between
O2 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
O2 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
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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
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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
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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
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 |
DISCUSSION |
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.
O2 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
O2 of the
ob/ob mouse (28), suggesting a
potential link between
O2 peak and leptin
production. The
O2 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
O2 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.
 |
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