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From the Clinical Research Centers |
Bone and Mineral Metabolism Laboratory, Departments of Physical Medicine, Medicine, and Nutrition, Davis Medical Research Center (V.M., J.Z.I., M.S., N.E.B., A.C., D.K., J.D.L.); and the Department of Statistics (P.G., R.W.N.), Ohio State University, Columbus, Ohio 43210
Address all correspondence and requests for reprints to: V. Matkovic, M.D., Ph.D., Bone and Mineral Metabolism Laboratory, Davis Medical Research Center, Ohio State University, 480 West 9th Avenue, Columbus, Ohio 43210.
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Abstract |
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A critical blood leptin level is necessary to trigger reproductive ability in women, suggesting a threshold effect. Leptin is a mediator between adipose tissue and the gonads. Leptin may also mediate the effect of obesity on bone mass by influencing the periosteal envelope. This may have implications for the development of osteoporosis and osteoarthritis.
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Introduction |
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With the recent discovery of the obesity gene (ob) and its product, leptin (11), it is possible to reexamine the relationship between body fatness and the timing of menarche from a new perspective. In support of this are recent discoveries in ob/ob mice treated with leptin showing signs of early onset of ovarian maturation and reproductive function (12, 13, 14). Similar data for humans do not exist.
We, therefore, measured body composition and serum leptin levels every 6–12 months and recorded menarche in a cohort of young females entering puberty over a 4-yr period of follow-up. We also examined the relationship between leptin and bone mass of pubertal girls, knowing the role body weight has in predicting bone mass and in osteoporosis prevention.
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Subjects and Methods |
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Three hundred and forty-three healthy Caucasian girls were recruited from the school districts in central Ohio to participate in a 4-yr longitudinal study of skeletal development during adolescence. All subjects were premenarcheal at baseline, aged 8.3–13.1 yr, and in pubertal stage 2, based on either breast or pubic hair development [mean of the two expressed as sexual maturity index (SMI)]. They were all ambulatory, free of any acute or chronic disease, and did not take medications known to affect body weight. Baseline metabolic and skeletal characteristics of the entire population were previously presented (15, 16). All participants and their parents gave informed consent according to guidelines of the human subjects committee at Ohio State University. Menstrual history, anthropometry, nutritional status, energy expenditure, body composition, and blood samples were obtained every 6–12 months over a 4-yr period.
Anthropometry, nutritional status, and energy expenditure
The subject’s weight was measured to the nearest 0.1 kg in normal indoor clothing without shoes. Standing height was recorded without shoes on a wall-mounted stadiometer to the nearest 0.1 cm with mandible plane parallel to the floor. Pubertal stage based on breast development and pubic hair distribution was self-assessed by marking corresponding figures of sexual development (15, 16, 17). The estimates of energy intake were obtained from the 3-day dietary food records taken over 2 weekdays and 1 weekend. Energy intake from the food record was analyzed by Nutritionist III software package, version 8.5 (The Hearst Corp., San Bruno, CA). Energy expenditure was estimated every 6 months by using a 2-day (1 week day and 1 weekend day) activity record (18). The process requires participants to record their dominant activity in 15-min periods throughout 24 h. Recording was simplified by having subjects use an activity list. Each activity record was analyzed separately, and the mean activity, measured as the total daily energy expenditure, was calculated.
Assessment of body composition
Body composition was measured by a dual x-ray absorptiometry technique with a pencil beam Lunar DPX-L machine with 1.3q software (Lunar, Madison, WI). All measurements were performed using the medium speed scan mode with 8 cm/s detector speed and sample size 4.8 over 9.6 mm, with the subject in the supine position along the middle axis of the scanning table and within the field of view of the detector. The data for total body bone mineral content (TBBMC), body fat, and lean body mass (LBM) were recorded. The precision errors [coefficients of variation (CVs)] for the measurements of TBBMC, body fat, and LBM in our laboratory were 0.9%, 2.6%, and 1.1%, respectively (15, 16).
Serum leptin, gonadotropins, and estradiol
After obtaining a blood sample, serum was stored at -80° C. Serum leptin was measured using the new sensitive RIA described by Ma et al. (19) at Linco Research (St. Charles, MO). The percent CVs within and between runs for leptin ranged from 3.4–8.3% and from 3.6–6.2%, respectively. FSH was measured by a standard sandwich immunoassay procedures; the within-run CV ranged from 1.6–2.4%, and the between-run CV ranged from 2.8–3.2% (Technicon, Immuno 1 System, Miles, Tarrytown, NY). LH and estradiol were measured by Coat-A-Count RIA kits (Diagnostic Products Corp., Los Angeles, CA). Within-run and between-run CVs for LH were 1.0–1.6% and 2.2–7.1%, respectively; and within-run and between-run CVs for E2 were 4.3–7.0% and 4.2–8.1%, respectively.
Statistical analysis
Basic descriptive statistics were used to describe each variable
at three time points (cross-sectional models: early premenarche, before
menarche, and at menarche; Table 1
). The
data for menarche and leptin before menarche (highest r2)
were initially smoothed by using a LOWESS smoother (making no a
priori assumptions about the model) to assess the overall shape of
the plot. The plot indicated that the variables of interest could be
modeled as a segmented linear and plateau regression. SAS Proc NONLINR
(SAS, Cary, NC) and S-Plus (StatSci, MathSoft, Seattle, WA) were used
to fit the model running on a HP6000/615 work station. For this model,
we also determined the 95% confidence interval (CI) at the change
point (serum leptin level) between the regression lines. The
association between leptin and menarche was also evaluated according to
the different timing of menarche used as a categorical variable
(menarche groups: group 1 = still premenarcheal after 4 yr of
follow-up, to group 5 = developed menarche during the first year
of follow-up; results presented as box plots).
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Results |
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, A and B. The association between serum
leptin and body fat is best represented by the linear regression model;
r = 0.81, P < 0.0001, equation: leptin (ng/mL) =
-0.27 + 0.00078 x body fat (g). The scatter plot of serum leptin
and percent body fat was best described by an exponential growth model;
variance explained = 68%, equation: leptin (ng/mL) = 0.22 +
exp(0.61 + 0.057 x percent body fat), P <
0.0001. Leptin also strongly correlated with BMI, with r = 0.75,
P < 0.0001, equation: leptin (ng/mL) = -21.09 +
1.27 x BMI. The relation between the change (
) in serum leptin
level and body fat over time in young females is presented in Fig. 1C;
r = 0.58, P < 0.0001, linear equation: leptin
(ng/mL/3 yr) = -0.15 + 0.001 x body fat (g/3 yr).
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Body composition and serum leptin measurements obtained before menarche
were used for this analysis. The scatterplot shown with linear-plateau
least squares fit model with equations: menarche (yr) =
13.43–0.082 x leptin (ng/mL) for serum leptin less than 12.2
ng/mL as menarche (yr) = 12.2 + 0 x leptin (ng/mL) otherwise. The
95% CI for the slope in the lower region, showing the inverse relation
between menarche and leptin, is -0.12 to -0.05 (yr). The 95% CI for
the change point (serum leptin; x x 0) is 7.6–16.7
ng/mL. The negative association between menarche and leptin is even
better depicted with Log-transformed leptin data (Fig. 2B); equation:
menarche (yr) = 13.1–0.4 x log-leptin, r = -0.184,
P < 0.001. The timing of menarche (years) and the
change () in body fat over time were negatively related; r =
-0.18, P < 0.0017, linear equation: menarche (yr) =
13.01–0.000035 x body fat (g/3 yr). Table 2 shows the summary of the forward
stepwise regression procedures with regression weights for menarche as
the dependent variable in the models with different obesity,
anthropometry, and energy balance parameters as predictor variables
measured before menarche (-6 months). Independent variables with
corresponding model r2 were as follows: model A:
log-leptin, height, SMI, LBM, TBBMC, energy intake, energy expenditure,
r2 = 0.26; model B: log-percent body fat, height, SMI, LBM,
TBBMC, energy intake, energy expenditure, r2 = 0.24; model
C: log-body fat, height, SMI, LBM, TBBMC, energy intake, energy
expenditure, r2 = 0.24 (n of cases = 291). The
corresponding intercepts were 7.1, 7.7, and 8.4, respectively. F to
enter 3.0. Sexual maturity index, height, and log-leptin, log-percent
body fat, and log-body fat were selected as determinants of menarche in
the models. Logarithmic transformations of serum leptin concentration
and absolute and relative body fat were always negatively associated
with menarche in the respective models, each controlled for sexual
maturation and body size. This negative association between menarche
and absolute and relative body fat remained significant with
corresponding correlation coefficients (r = -0.133 and r =
-0.136, and P values of 0.013 and 0.014, respectively).
Individuals with early-onset menarche were shorter in stature than
subjects with late-onset menarche.
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). Group 1
(n = 11; 3.2%) did not have a menstrual period by the end of the
fourth year of follow-up, group 2 (n = 39; 11.4%) had a first
menstrual period during the fourth year, group 3 (n = 93; 27.1%)
had a first menstrual period during the third year, group 4 (n =
132; 38.5%) had a first menstrual period during the second year, and
group 5 (n = 68; 19.8%) started menstruating during the first
year of the study. Box plots of serum leptin according to menarche
groups at yr 1 of the study are presented in Fig. 3A. The group effect
is significant by ANOVA at P < 0.05. Serum leptin by
yr 4 of the study in different menarche groups is presented in Fig. 3B.
The difference in serum leptin between group 1 and pooled groups 2–5
is significant by t test at P < 0.008.
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shows the three-dimensional
plane surface model (z = a + bx +
cy) developed by the least squares criterion of the
relationship among the timing of menarche (z), energy intake
(y), and serum leptin level (x) in young females.
Data for energy intake and leptin were obtained before menarche.
Subjects with lower energy intake and lower serum leptin levels had
late-onset menarche in this model and vice versa.
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, and the change in total body bone
area and serum leptin over time (n = 270; r = 0.274;
P < 0.0001) is presented in Fig. 5B. Table 3 shows multiple regression analysis with
total body bone area (square centimeters) as the dependent variable,
and age, SMI, height, LBM, TBBMC, and log-leptin as independent
variables in the model (n = 311; adjusted r2 = 0.95).
Height, LBM, TBBMC, and log-leptin partially predict total body bone
area after being adjusted by other variables. Table 4 shows multiple regression analysis,
with the change () in total body bone area (cm2/2 y) as
the dependent variable and the changes in SMI, height, LBM, TBBMC, and
serum leptin level over 2-yr period as independent variables in the
model (n = 270; adjusted r2 = 0.93). Changes in
height, LBM, TBBMC, and serum leptin partially predict the change in
total body bone area over time after being adjusted by other
variables.
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Serum FSH, LH, and estradiol did not provide any additional predictive capability for the timing of menarche in the multivariate statistics. Only serum leptin was selected by the forward stepwise regression procedure as a significant predictor variable in the model (n = 201; partial r2 = 0.036; t = -2.7; P < 0.007; F to enter 3.0). The only relationship between leptin and gonadotropins was present when the serum FSH concentration before menarche was regressed on the change in serum leptin level during puberty (nanograms per mL/3 yr; n = 193; r = 0.176; P < 0.014). It is most likely that leptin acts as a hormone and provides a direct stimulus to gonads by triggering a reproductive cycle in human females. The exact understanding of the mechanism involved will require a clinical trial with leptin in premenarcheal girls of low body fatness. A persistent defect of the hypothalamic-pituitary-gonadal axis was described in ob/ob mice (23); these abnormalities were corrected by leptin administration (12, 13), although the exact sequence of the events in the restoration of the axis still remains unknown. Absolute and relative body fat were also negatively related to menarche as well as to the change in body fat over time. Young females who did not develop menarche by the fourth year of follow-up in this study have lower body fat than their peers who started menstruating earlier. A serum leptin level of 12.2 ng/mL corresponds to a relative body fat of 29.7%, a BMI of 22.3, and body fat of 16.0 kg among our participants. A gain in body fat of 1 kg lowers the timing of menarche by approximately 13 days.
It is anticipated, therefore, that leptin deficiency is a primary reason for delayed puberty and menarche in individuals and in populations accustomed to absolute or relative dietary energy deficiency. In menstruating women, a negative energy balance caused by either fasting and/or exercise could cause secondary amenorrhea (24, 25, 26), presumably due to low levels of circulating leptin. Low serum leptin levels were found in young amenorrheic athletes (27) and in women suffering from anorexia nervosa (28). A decrease in the serum leptin concentration was documented in older women in response to exercise (29).
As late onset of menarche and leanness are considered risk factors for osteoporosis (3, 30, 31, 32), we evaluated the association between leptin and bone mass of young females during peak growth. The association between body weight and bone mass has previously been attributed to either mechanical forces exerted on the skeleton and/or to a more favorable estrogen status associated with obesity (33). This study showed a positive relation between serum leptin and whole body bone mineral areal density (r = 0.204; P < 0.0002); however, in a multiple regression model, leptin did not show any influence on bone mineral content when bone area was among the predictor variables. Instead, serum leptin was related to bone area, suggesting an influence on the periosteal envelope. We propose that obesity may have an additional protective effect on bone mass through its influence on cortical bone and its periosteal envelope, and that this could be mediated by leptin. Periosteal bone apposition increases bone volume, with a corresponding change in peak bone mass (3). It is the bone size that ultimately determines the risk of fracture, as documented for the spine (34). The definitive data in this regard, however, should come from intervention studies with leptin in an animal model by looking at the skeleton as the target organ. The above finding could help understanding the pathophysiology of osteoporosis and osteoarthritis. Most of the patients with generalized osteoarthritis are obese and have higher peak bone mass and a hyperactive periosteal envelope (35). Their serum leptin levels are higher than those in patients with osteoporosis (36).
In summary, this observational study conducted in young women showed an inverse relation between menarche and serum leptin up to 12.2 ng/mL, suggesting a threshold effect of serum leptin with regard to reproductive ability. Leptin is a hormone acting as a mediator between adipose tissue and the gonadal-hypothalamic axis in human females. Leptin may also mediate the effect of obesity on bone mass by influencing periosteal envelope expansion. This may have implications for the development of osteoporosis and osteoarthritis.
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Footnotes |
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Received May 15, 1997.
Revised June 27, 1997.
Accepted July 2, 1997.
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23 months before the onset of the first menstrual
period), before menarche (
