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The Journal of Clinical Endocrinology & Metabolism Vol. 82, No. 9 2904-2910
Copyright © 1997 by The Endocrine Society


Original Studies

Plasma Leptin Levels in Healthy Children and Adolescents: Dependence on Body Mass Index, Body Fat Mass, Gender, Pubertal Stage, and Testosterone1

Werner F. Blum, Piera Englaro, Sigrid Hanitsch, Anders Juul, Niels T. Hertel, Jorn Müller, Niels E. Skakkebæk, Mark L. Heiman, Martin Birkett, Andrea M. Attanasio, Wieland Kiess and Wolfgang Rascher

Lilly Research Laboratories (W.F.B., M.L.H., M.B., A.M.A.); University Children’s Hospital (W.F.B., P.E., S.H., W.K., W.R.), Giessen, Germany; Rigshospitalet (A.J., N.T.H., J.M., N.E.S.), Copenhagen, Denmark

Address correspondence and requests for reprints to: Dr. Werner F. Blum, Lilly Germany GmbH, Saalburgstrasse 153, D-61350 Bad Homburg, Germany.


    Abstract
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Leptin, the product of the ob gene, is thought to play a key role in the regulation of body fat mass. Beyond this function, it appears to be an integral component of various hypothalamo-pituitary-endocrine feedback loops. Because childhood and puberty are periods of major metabolic and endocrine changes, leptin levels and various hormonal parameters were investigated in a large cohort of healthy children and adolescents (312 males, 401 females, age 5.8–19.9 yr). For this purpose, a specific and sensitive RIA was developed that allowed the accurate measurement of low leptin levels in young lean children. With this assay, leptin proved to be a comparatively stable protein under common conditions of blood sampling and storage.

Leptin levels increased in girls with age (r = 0.47, P < 0.0001), but decreased in boys (r = -0.34, P < 0.0001). An analysis according to pubertal stage showed a steady increase in girls between 2.51 µg/L (median) at Tanner stage 1 to 6.24 µg/L at Tanner stage 5. In boys, leptin levels were highest at Tanner stage 2 (2.19 µg/L) and declined thereafter to 0.71 µg/L at Tanner stage 5.

A strong exponential relationship was observed for leptin levels with body mass index (BMI) and percentage body fat as determined by bioelectric impedance measurements in a subgroup of subjects. This relationship was similar between boys and girls at Tanner stages 1 and 2. In boys, there was a significant decline of leptin at a given BMI with further progression of puberty that was much less pronounced in girls. Although the relative increase of leptin with BMI and percent body fat was the same in both genders, the absolute values at a given BMI or percent body fat were significantly lower in boys in late puberty and in adolescents. In boys, but not in girls, there was an inverse correlation with testosterone concentrations (r = -0.43, P < 0.0001), which explained 10.5% of the variation of leptin levels in a multiple regression model. Since BMI proved to be the major influencing variable, reference ranges were constructed using a best-fit regression line of the form leptin = a*e(b*BMI) and stratifying ranges according to gender and pubertal stage.

In conclusion, these data suggest that 1) plasma leptin levels increase in girls and decrease in boys after Tanner stage 2 as the pubertal development proceeds; 2) they show a significant gender difference especially in late puberty and adolescence, even after adjustment for BMI or percent body fat; 3) the lower levels in males may be explained at least in part by a suppressive effect of androgens; 4) reference ranges with BMI as the independent variable should be stratified according to gender and pubertal stage.


    Introduction
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
LEPTIN, the product of the ob gene (1, 2), is a recently discovered proteohormone with a molecular weight of 16 kDa that is thought to play a key role in the regulation of body weight. Although its amino acid sequence exhibits no major homologies with other proteins, prediction of its tertiary structure shows similarities with class I cytokines (3, 4). This is not surprising in that leptin receptors (alternatively spliced forms exist that differ in length) belong to the cytokine class I receptor family (5, 6, 7). Leptin receptors are found ubiquitously in the body (5, 6, 8, 9) indicating a general role. Leptin is produced by differentiated adipocytes (10, 11, 12). It acts on the hypothalamus, thereby suppressing food intake and stimulating energy expenditure (2, 13, 14, 15, 16). Besides its metabolic effects, leptin affects a number of endocrine axes. In male mice, it blunted the starvation-induced marked decline of LH, testosterone, and thyroxine, and the increase of ACTH and corticosterone. In female mice, leptin prevented the starvation-induced delay in ovulation (17). Ob/ob mice, which are leptin deficient because of an ob gene mutation, are infertile. This defect could be corrected by administration of leptin, but not through weight loss by fasting (18), suggesting that leptin is pivotal for reproductive functions, at least in female mice.

All these actions may, at least in part, be explained by the suppressive effect of leptin on neuropeptide Y (NPY) expression and secretion by neurons in the arcuate nucleus (13, 19, 20). Further, there is evidence that leptin also functionally antagonizes NPY action (19, 21). NPY is a strong stimulator of appetite (21, 22) and is known to be involved in the regulation of various pituitary hormones, e.g. suppression of GH through stimulation of somatostatin (23, 24), suppression of gonadotropins (24), or stimulation of the pituitary-adrenal axis (22).

The most important variable that determines circulating leptin levels is body fat mass (25, 26, 27). Obviously, under conditions of regular eating cycles, leptin reflects the proportion of adipose tissue (28). This constitutive synthesis of leptin is modulated by a number of hormones. Strong stimulators in both rodents and humans are insulin (10, 12, 29, 30, 31, 32) and glucocorticoids (12, 33, 34, 35, 36). GH exerts short-term a stimulating and long-term a suppressing effect (37). Suppression has also been shown for cAMP and ß3-adrenoceptor agonists (34). From these findings it becomes clear that leptin is an integral component of various metabolic (21, 22) and endocrine feedback loops.

Because childhood and especially puberty are periods of pronounced changes in the endocrine milieu, we investigated whether various hormonal regulators of growth and sexual development are associated with changes of circulating plasma leptin levels. Because our preliminary findings suggested that leptin levels in normal young children are at the limit of sensitivity of previously employed immunoassays, we developed a new radioimmunoassay that allowed accurate measurement of low plasma leptin concentrations. To provide a basis for the question of what is normal and what is pathologic, leptin was studied in a large cohort of healthy children and adolescents, aiming at the construction of reference ranges with respect to the major influencing variables. Based on reference values, obese subjects may be classified more precisely in those with low leptin levels (relative or absolute leptin deficiency) or with high leptin levels (potential leptin resistance). Thus, leptin measurements may aid to unveil different pathophysiologic causes of obesity.


    Subjects and Methods
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Subjects

713 healthy children and adolescents (312 males, age 6.0–19.9 yr, mean age 13.5 yr; 401 females, age 5.8–19.7 yr, mean age 13.1 yr) were investigated. All children or their parents were asked for written informed consent and agreed to participate in the study. None of the individuals had obvious signs of acute or chronic illness. Standing height was measured with a portable Harpender stadiometer (Holtain Ltd., Crymych, United Kingdom) to the nearest 0.1 cm. Weight was determined using a digital weight scale with a precision of 0.1 kg (SECAdelta, model 707). BMI was calculated as weight (kg) divided by the square of height (m). The pubertal stage (development of breast, genitalia, and pubic hair) was documented in 311 males and 333 females according to the classification by Tanner. For the analysis of subgroups, the classification was based on pubic hair development. Blood samples were drawn from the antecubital vein between 0800 and 1300 h. After centrifugation, serum was stored at -20 C, until measurement of the various parameters.

In 179 subjects (71 males, age 6.4–16.5 yr, mean age 11.3 yr; 108 females, age 6.1–16.8 yr, mean 11.3 yr), the body composition was determined by bioelectric impedance measurement (BIA) using a Holtain Body Composition Analyser (Holtain Ltd.). Total body water and fat free mass were calculated using the equations reported by Davies et al. (38). For comparison, an alternative equation by Wabitsch et al. was used (39). The percentage of body fat was calculated by the following equation:

Methods

Leptin radioimmunoassay Assay components.

New Zealand white rabbits were immunized with recombinant human leptin (Eli Lilly and Company, Indianapolis, IN). The serum with the highest affinity was used for further studies. Tracer was prepared with 2.5 µg leptin as described in detail using the chloramine T method (40). The radiolabeled protein was further purified by exclusion chromatography on a 1.5 x 90 cm column of Sephadex G-50 (Pharmacia, Freiburg, Germany) and was stored at -20 C. Standards were prepared by geometrical dilutions of recombinant human leptin in assay buffer (0.05 mol/L sodium phosphate, pH 7.4, 0.1 mol/L NaCl, 0.1% (vol/vol) gelatine from teleost fish (Sigma, Munich, Germany), 0.1% (vol/vol) triton x 100 (Serva, Heidelberg, Germany), 0.05% (wt/vol) NaN3) between 12.5 and 0.049 µg/L.

Assay procedure. Standards or diluted samples (100 µL; 1:3 to 1:10 in assay buffer) were pipetted into polystyrene tubes, and 100 µL each of first antibody [1:10,000 in assay buffer, containing 150 µg/mL rabbit gammaglobulin (Sigma)] and radioiodinated leptin (150,000–200,000 cpm/mL in assay buffer) were added. After incubation overnight at room temperature, separation of free and bound tracer was achieved by adding 500 µL of cold 4% (wt:vol) polyethylene glycol 6000 (Serva) containing a goat-antirabbit IgG serum (DSL, Webster, MA; 1:150). After 30 min at 4 C, the bound tracer was precipitated by centrifugation (15 min x 2000 g) and the radioactivity was measured in a gamma counter.

Assay performance. Maximal binding in the absence of unlabeled leptin (B0) was 37–45%. Nonspecific binding with normal rabbit serum was 0.61 ± 0.08% (n = 10). Half-maximal binding (50% B/B0) occurred at 0.092 ± 0.007 ng per tube (n = 10). Sensitivity with undiluted samples was 0.03 µg/L, corresponding to 0.003 ng per tube. The intra- and interassay coefficients of variation were 0.8 and 8.5% respectively (n = 10). Excellent parallelism with the standard curve was obtained with serial dilutions of human sera. Spiking experiments with 0.1 ng per tube yielded a recovery of 97 ± 2.1%. Prolonged incubation of the assay mixture (1, 2, 4, and 8 days) at room temperature yielded identical results. Serum leptin levels by RIA were stable upon repeated freezing and thawing, up to 10 cycles, and also during incubation at 4 C and at room temperature up to 8 days. At 37 C leptin levels started to decline steadily after 24 h and had almost disappeared after 8 days.

Other hormones

Insulin-like growth factor (IGF)-I and IGF-II were measured by RIA after acid-ethanol extraction as described previously (41, 42). IGF binding protein (IGFBP)-1 (43), IGFBP-2 (44), and IGFBP-3 (45) were measured by specific RIAs. Estradiol (RIA; Immunodiagnostic System Ltd., Boldon, United Kingdom), testosterone (RIA; Diagnostic Products Corp., Los Angeles, CA), DHEA-S (RIA; Immunotech International, Marseille, France), and SHBG (Delfia; Wallac Oy, Turku, Finland) were measured with commercial assay kits.

Statistics

The distribution of leptin levels in various age or BMI groups was log normal. Therefore, the values were transformed to their logarithms before calculating means and standard deviations, and Student’s t test was used to test for significance of differences between groups. Nonlinear regression analysis was used to calculate ranges that include 90% of the values related to BMI. Correlations between log leptin and the various other parameters are given by the Pearson correlation coefficient r. To test which variables contribute to the variation of leptin levels, multiple step-wise backward regression analysis was performed.


    Results
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
When leptin levels were related to age, a wide scatter was obvious, with in general, higher levels in girls than in boys, particularly after the age of 12 yr (Fig. 1Go). This difference in age-dependence became especially clear after logarithmic transformation of leptin values (Fig. 1bGo). While in girls levels increased with age (r = 0.47, P < 0.0001), serum leptin decreased in boys (r = -0.34, P < 0.0001). As a consequence of this finding, the following analyses were performed separately for both genders.



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Figure 1. Serum leptin concentrations in boys ({square}) and girls (•) vs. age. a) Linear scale of the ordinate; b) logarithmic scale of the ordinate. The regression lines in panel a) are given by leptin = 3.1624*e(-0.0792*age) in males and leptin = 1.1777*e(0.0963*age) in females.

 
In both boys and girls there was a significant increase in BMI with age and pubertal development (Table 1Go). In contrast, leptin levels increased in girls continuously with progression of puberty, while they decreased significantly in boys from Tanner stage 3 on despite a further increase in BMI. This opposite pattern resulted eventually in more than 8-fold higher levels in females at Tanner stage 5, although BMI values were comparable.


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Table 1. BMI (mean ± SD) and serum leptin levels in boys and girls according to pubertal stage

 
When serum leptin was related to BMI, a strong exponential relationship was observed in girls (leptin = 0.10501e(0.10471BMI) µg/L, r = 0.79, P < 0.0001), whereas only a weak association was found in boys (leptin = 0.43031e(0.04871BMI) µg/L, r = 0.16, P = 0.0048). This finding, together with the age-dependence, prompted us to stratify the analysis according to pubertal stage. In boys, the relation between leptin levels and BMI was identical in Tanner stages 1 and 2 (Fig. 2aGo). In Tanner stages 3, 4, and 5, however, average leptin levels decreased at a given BMI with progression of the pubertal development. This phenomenon was much less pronounced in girls (Fig. 2bGo). The comparison of boys and girls, classified according to pubertal stage, revealed that the relative increase of serum leptin with BMI is identical in both genders as indicated by parallel lines in the semilogarithmic plots (Fig. 3Go). However, while absolute values showed a less pronounced difference in pre- and early puberty (Figure 3aGo), a large difference was observed in Tanner stage 5. This stratified analysis according to pubertal stages clearly improved the associations between leptin levels and BMI especially in males (Table 2Go).



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Figure 2. Serum leptin concentrations in boys (left panel) and girls (right panel) according to pubertal stage vs. BMI. The symbols for the various Tanner stages (TS) are as indicated. The best-fit regression lines were of the form leptin = a*e(b*BMI) and are indicated by the following styles: TS 1 and 5: solid lines; TS 2 and 4: dashed lines; TS 3: broken line.

 


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Figure 3. Serum leptin concentrations in boys ({square}) and girls (•) vs. BMI. a) Combined Tanner stages 1 and 2; b) Tanner stage 5. The best-fit regression lines (solid lines) are given by the equation leptin = a*e(b*BMI). The range comprising 90% of the values in each cohort according to gender and pubertal stage is given by the following equations: leptin = a*e(b*BMI+c) and leptin = a*e(b*BMI-c). The broken lines relate to males and the dashed lines to females. The values of a, b and c are given in Table 2Go.

 

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Table 2. Correlations between log-transformed serum leptin levels and BMI in subgroups separated according to gender and pubertal stage

 
In a subgroup of children, fat mass was determined by BIA measurements. Because of the lower number, it appeared inappropriate to perform a similar stratified analysis according to both gender and Tanner stage. Therefore, males and females were compared irrespective of their pubertal development. The proportion of body fat (BF) (mean ± SD) was 14.70 ± 7.58% in males and 18.95 ± 8.37% in females, showing significant correlations with BMI (r = 0.56, P < 0.0001 in males and r = 0.80, P < 0.0001 in females). When leptin levels were related to percent body fat (%BF), exponential relationships were again obtained. The best-fit nonlinear regression curve in males was leptin = 0.48361e(0.073151%BF) µg/L (r = 0.72, P < 0.0001), and in females it was leptin = 0.89521e(0.068771%BF) µg/L (r = 0.77, P < 0.0001). In a semilogarithmic plot, these curves give almost parallel lines (Fig. 4Go), indicating that the relative increase of leptin with body fat is the same in both sexes. However, for a given percentage of body fat, females had higher absolute leptin levels than males. At a mean value of 16.26% BF, the average leptin level was 2.74 µg/L in girls vs. 1.59 µg/L in boys. Using the errors of the nonlinear regression model in both sexes, this difference proved significant (P = 0.002). Corresponding results were obtained when, alternatively, the model of Wabitsch et al. (39) was employed for calculating percent BF. Although the correlation of BF values with those obtained with the model of Davies et al. was high (r = 0.97), absolute values were lower by about 30%.



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Figure 4. Serum leptin concentrations in boys ({square}) and girls (•) vs. percent body fat as determined by bioelectric impedance measurements. The best-fit regression lines are given by leptin = 0.4836*e(0.07315*%BF) in males (solid line) and 0.8952*e(0.06877*%BF) in females (dashed line).

 
Besides BMI (or fat mass), a series of hormones was examined for any associations with serum leptin (Table 3Go). Significant correlations were found with logarithmically transformed leptin levels, which were, surprisingly, mostly opposite when comparing genders. This may be related to the opposite age-dependence of leptin levels. When a multiple step-wise backward regression analysis was performed, the total contribution of all parameters, including age and BMI, accounted for 52.3% of the leptin variation in males. Besides age and BMI, only testosterone (10.5%) and IGFBP-2 (3.2%) contributed significantly to this variation. In females, 69.5% of the variation was explained by all parameters, with BMI as the major influencing variable and only a minor contribution by age and by IGFBP-2 (5.4%).


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Table 3. Correlations between logarithmically transformed serum leptin concentrations and various endocrine parameters

 
Because leptin levels appeared to be largely determined by BMI, normal leptin reference ranges were constructed by referring leptin levels to BMI. The findings of this study suggested that these reference ranges should be stratified according to gender and pubertal development. To obtain reliably large numbers per group, Tanner stages 1 and 2, and 3 and 4 were combined. This appeared to be appropriate, as the differences between these groups with respect to the dependence of leptin on BMI were minor. The best-fit regression line for the relationship between leptin values and BMI was an exponential curve of the form leptin = a1e(b1BMI). For a sufficiently large number of individuals, this curve corresponds to the 50th percentile. The range comprising 90% of all leptin values is given by the lines leptin = a1e(b1BMI-c) and leptin = a1e(b1BMI+c), which correspond to the 5th and 95th percentile, respectively. The values for a, b, and c for the various subgroups are given in Table 2Go. These reference ranges can be used to adjust leptin levels for BMI in a given comparator group by calculating standard deviation scores (SDS, Z-scores). Accounting for the logarithmic distribution, the deviation from the mean reference value is given by the following equation:

The d-values of the various subgroups are also shown in Table 2Go.


    Discussion
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Using recombinant human leptin, a sensitive RIA for this protein was developed that proved to be specific, precise, accurate, and robust. Its sensitivity is higher by an order of magnitude compared with currently commercially available assays, which allowed the precise measurement of low leptin levels especially in lean young children and male adolescents. The investigation of the stability of immunoreactive leptin demonstrated that serum leptin is a comparatively stable protein, which makes sample handling unproblematic. Recently, it was reported that leptin is partially bound to specific binding proteins in the circulation (46). Therefore, it was important to examine whether our assay detects only free or total leptin. From systematic studies of human sera from lean and obese subjects by exclusion chromatography, it became clear that our RIA detects primarily total leptin and that leptin binding proteins do not interfere in the assay, most probably because of the high affinity of the antibody (data not shown).

When leptin levels were related to BMI, an exponential relation was observed in accordance with reports in adults (26, 27) indicating that fat mass is the main regulator of leptin levels. However, there was also a clear dependence upon age and pubertal stage that was also observed in a smaller number of subjects by Hassink et al. (47). In particular, there was a decrease in males with age as compared to females. At first sight, this finding may be explained by the divergent pattern of development of fat and lean body mass during puberty. In males, the increase of BMI in late puberty may be mainly caused by the accumulation of muscle mass owing to the action of androgens. This view is supported by the fact that the difference between male and female leptin levels was much less pronounced when leptin was referred to percent BF instead of BMI. However, although the relative increase of leptin vs. BMI or percent BF as measured by BIA was identical in both genders, i.e. for a given increase in BMI or percent BF, leptin levels increased by the same factor, absolute values were significantly different, suggesting that an additional factor influences plasma leptin.

The question, whether sex steroids are causally involved in this gender difference, which has also been observed by others (47, 48, 49), cannot conclusively and directly be answered by the results of this study. As revealed by multiple regression analysis, however, about 10% of the variation of leptin levels could be contributed to testosterone in males, but not in females. Since absolute values of testosterone were on average about 20-fold higher in male adolescents, it cannot be excluded that a threshold effect plays a role. In a separate study with hypogonadal men receiving androgen replacement (50), and in in vitro studies with human adipocytes (51), we were able to clearly demonstrate that androgens suppress leptin levels and leptin expression. Therefore, the divergent pattern of absolute leptin levels during pubertal development of males and females may be explained by the rising levels of androgens in males that have a direct effect and also an indirect one by shifting the relative contribution of the increase of BMI towards muscle mass.

As suggested by multiple regression analysis, IGF-I as an important regulator of growth does not significantly contribute to the variation of leptin, which is consistent with in vitro experiments (Dr. M. Wabitsch, personal communication). Also, leptin did not significantly contribute to the variation of GH-dependent variables such as IGF-I or IGFBP-3. This was unexpected because, hypothetically, leptin should be expected to stimulate GH secretion through suppression of NPY (23, 24) and since it restores starvation-induced suppression of GH secretion in rats (Dr. M. Aubert, personal communication). Therefore, the question, whether leptin as a signal reflecting available energy stores is of any importance for growth, which would teleologically make sense, remains to be answered by more specifically designed studies.

To appropriately interpret measured leptin concentrations (e.g. to detect pathology), reference values are required. For this purpose, leptin should be referred to the predominant (independent) influencing variable. With respect to leptin levels, the major regulator proved to be fat mass. Absolute measured values of fat mass, however, depend largely on the methodology used, despite the fact that good correlations between methods may be obtained. Using the impedance values of the current study, absolute percent of BF values differed largely depending on the regression models used, although their relation to leptin levels was comparable. On the other hand, BMI reflects body fat mass somehow. It is easy to determine, it is retrospectively mostly available, and it is the most precise measure for short-term longitudinal changes of body fat in a single patient, e.g. during restricted food intake. Therefore, on this basis it appeared reasonable to provide reference ranges of leptin levels referring to BMI rather than relative fat mass or age.

Of course, these ranges (taken as normal ranges), are, in a strict sense, limited to the BMI ranges of the studied cohorts. Adjusting the leptin concentrations of patients that fall within this range according to gender, pubertal stage and BMI is straightforward. However, the extrapolation of these ranges to extremely low or high BMI values is not trivial. A BMI value of, say, 40 kg/m or less can be considered neither normal nor healthy. Therefore, the ranges provided by the functions derived from this study should be considered instead as expectation ranges. Nevertheless, these expectation ranges may be a useful tool for detecting discrepancies between a given BMI value and aberrant leptin levels. Removal of the influences of gender, pubertal stage, and BMI by calculating leptin SDS values as suggested in Table 2Go can thus be helpful in detecting both pathologic leptin production (or clearance) and the influence of additional regulating factors.


    Footnotes
 
1 Presented in part at the 35th Annual ESPE Meeting in Montpellier, France, September 1996. Back

Received March 20, 1997.

Revised May 29, 1997.

Accepted March 20, 1997.


    References
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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