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Pediatric Endocrinology |
Bone and Mineral Metabolism Laboratory, Departments of Physical Medicine, Medicine, and Nutrition, Ohio State University, Columbus, Ohio 43210
Address all correspondence and requests for reprints to: Dr. V. Matkovic, 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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There was a significant rise in serum leptin at midnight and 0400 h, suggesting a diurnal variation in serum leptin concentrations (ANOVA F ratio = 6.2; P < 0.0001). There was also a strong association between relative total body fat and the average daytime serum leptin level (r = 0.78; P < 0.0001). The percent increase in the nocturnal leptin concentration was inversely related to the percent gain in total body fat (r = -0.45; P < 0.024). Forward stepwise regression analysis selected the change in total body fat over a 6-month interval as the most powerful determinant of the percent increase in the nocturnal leptin concentration (partial R2 = 0.203; ß = -0.450; SE of ß = 0.186; t = -2.418; P < 0.024). If the lack of a nocturnal rise in serum leptin persists over a longer period of time, it may have implications for the development of obesity, presumably by inadequate suppression of nighttime appetite.
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Introduction |
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Both genetic and environmental factors contribute to adolescent obesity. Evidence of a genetic basis for obesity development is substantial (2), although the exact mechanism of action has yet to be identified. An obesity gene has been recently cloned in mice and humans. Its product is a 167-amino acid peptide called leptin, which is produced and released from adipose tissue (3). In homozygous mice the mutations of the obesity (ob) gene resulted in increased food intake, reduced energy expenditure, elevated insulin level, and subsequent obesity and the development of noninsulin-dependent diabetes mellitus (3). Administration of leptin to leptin-deficient homozygous ob/ob mice created the opposite effects (4, 5, 6). These observations support the idea that the accumulation of body fat increases leptin synthesis and its release from the adipose tissue. The hypothesis is that leptin binds to specific receptors in the hypothalamus, which eventually leads to reduced appetite and increased energy expenditure (3, 6, 7, 8, 9). This action of leptin as a satiety factor is attributed primarily to its 35-amino acid fragment (10). The assumption is that some kind of resistance to leptin could lead to obesity in humans (11, 12).
At present, there are no data to support the concept of abnormal mutations of the obesity gene in humans (13). A few cross-sectional studies conducted in adults did show a significant correlation among body mass index (BMI), relative and absolute body fat, and serum leptin levels. The serum leptin level was several times higher in obese individuals than that in lean subjects (14, 15, 16, 17). A nocturnal rise in leptin in lean and obese adults and obese noninsulin dependent adult-onset diabetes mellitus patients was recently reported (18). The significance of this circadian rhythmicity of leptin to the pathogenesis of obesity is not clear at the present time. To what extent a similar phenomenon exists during growth is not known. The purpose of this study, therefore, was to document diurnal variation in serum leptin in adolescents and to assess the impact of the change in body fat over time on the circadian rhythmicity of leptin.
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Subjects and Methods |
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Twenty-five healthy young Caucasian females, aged 11.4–14.6 yr, participated in this study. They were selected from a larger group of participants in a longitudinal study of skeletal development through adolescence based on BMI and total body bone mineral density (all within ±1 SD of the group mean). They were all in pubertal stage 2 at the time of enrollment into the study (aged 9.4–12.6 yr). Body composition, nutrient intake from the subjects’ self-selected diets, and energy expenditure data were obtained at baseline and after 6 months; the diurnal variation study was conducted in the middle of this interval at the General Clinical Research Center of Ohio State University. Basic anthropometry was performed at all three visits. For the diurnal variation study, after an overnight fast blood samples were obtained at 0800 h and every fourth hour subsequently throughout a 24-h period. Blood samples were obtained before each meal. After 30 min of clotting, serum was separated and stored at -80 C until assayed for leptin. All participants and their parents gave informed consent according to guidelines of the human subjects committee at Ohio State University.
Assessment of nutrition, activity, and anthropometry
Caloric intake was estimated from 3-day dietary records,
covering 2 weekdays and 1 weekend day, using Nutritionist III, version
8.5, for Macintosh (N-Squared Computing, The Hearst Corp., San Bruno,
CA). During the in-patient study, subjects consumed a diet matched to
the prestudy calories (
1850 Cal/day) and nutrients. Activity level
was assessed using a 2-day (1 week day and 1 weekend day) activity
record. The process requires participants to record their dominant
activity in 15-min time periods throughout 24 h. Recording has
been simplified by the use of an activity list (19). Each activity
record was analyzed separately and presented as the total daily energy
expenditure. Each subject (and the parents) was instructed on an
individual basis by the registered dietitian on how to complete the
dietary and activity records. 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 portable stadiometer to the nearest 0.1
cm with the mandible plane parallel to the floor. BMI was calculated
from the basic anthropometry data. Pubertal stage, based on breast
development and pubic hair distribution, was self-assessed by marking
corresponding figures of sexual development (20, 21)
Body composition
Body composition was measured on each participant by dual x-ray absorptiometry with a Lunar DPX-L machine (1.3q software, Lunar, Madison, WI). All measurements were performed using medium speed scan mode with 8 cm/s detector speed and sample size 4.8 over 9.6 mm, with the subject in a supine position along the middle axis of the scanning table and within the field of view of the detector. The subject’s arms were positioned along the sides of the body, with hands supinated. The knees and ankles of the subject were immobilized by velcro straps, and the feet were separated by foam to avoid overlapping of the osseous structures. All attenuating materials were removed before the scanning. The data for total body bone mineral content (TBBMC), total body fat (TBF), and lean body mass (LBM) were recorded. The precision errors (percent coefficient of variation) for TBBMC, TBF, and LBM in our laboratory were 0.9%, 2.6%, and 1.1%, respectively (20, 22, 23).
Leptin assay
Serum leptin was measured using the new sensitive RIA, as described by Ma et al. (24), at Linco Research (St. Charles, MO). Within- and between-run coefficients of variation for leptin ranged from 3.4–8.3% and from 3.6–6.2%, respectively.
Statistics
Basic descriptive statistics were used to describe each variable. The difference in serum leptin levels between various time points during a 24-h period was tested by ANOVA. The association between serum leptin level and the parameters of body fatness was evaluated by a simple linear regression analysis. To evaluate the determinants of nocturnal rise in serum leptin concentration, a forward stepwise regression analysis was used. For the above statistics, the average daytime (the mean of 8, 12, 16, and 20 h samples) and the nighttime (the mean of 24 and 4 h samples) serum leptin levels were used. All calculations were performed using Data Desk Professional version 5.01 (Data Description, Ithaca, NY) and Statistica/Mac version 4.1 (StatSoft, Tulsa, OK) (25). P < 0.05 was considered significant throughout.
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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. There was a rise in serum
leptin at midnight and 0400 h, suggesting a diurnal variation in
serum leptin concentrations. Those changes were significant as tested
by ANOVA (F ratio = 6.2; P < 0.0001). The
relationship between the average nocturnal and daytime serum leptin
levels is presented in Fig. 2. There was a linear
relation between daytime and nighttime serum leptin levels, suggesting
that all subjects contribute to the nocturnal increase (r = 0.79;
P < 0.0001). The equation of the relation is as
follows: nocturnal leptin = 0.36 + 1.67 x daytime
leptin.
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shows descriptive statistics of the basic
anthropometry and body composition variables of the participants in the
study at baseline (mean age, 12.9 yr) and after 6 months of follow-up.
All variables significantly increased with age except BMI and relative
total body fat. The average daily consumptions of calories among
subjects at baseline and after 6 months of follow-up were 1858 ±
68 and 1889 ± 112 (mean ± SE), respectively.
The frequency histograms for the relative and absolute total body fat
at baseline are presented in Fig. 3 and show normal
distribution of the variables.
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). The relation
between the average daytime serum leptin level and the BMI calculated
from anthropometry measurements taken at the time of the diurnal study
also revealed a strong positive association (r = 0.653;
P < 0.0001).
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shows the relation between the percent
nocturnal increase in the average serum leptin concentration and the
relative change in TBF over a 6-month interval. The percent increase in
the nocturnal leptin concentration was inversely related to the percent
gain in TBF (r = -0.45; P < 0.024).
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The relationship between the percent increase in the nocturnal leptin
level (z), the percent change in body fat over the 6-month
period (x), and the relative change in kilocalorie
consumption per day over the 6-month interval (y) is
presented in Fig. 6 using the plane surface model
(z = a + bx + cy). The
fitted surface is determined based on the least squares criterion (25).
This three-dimensional linear surface plot shows a stronger influence
of the change in body fatness over kilocalorie intake on the nocturnal
rise in serum leptin.
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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A nocturnal rise in serum leptin was previously documented in lean and obese adults and in noninsulin-dependent diabetes mellitus patients (18). In all three groups, serum leptin levels were highest between midnight and the early morning hours and lowest around noon to midafternoon. The same pattern in circadian rhythmicity of serum leptin was observed among young participants in this study.
As leptin is encoded by the ob gene and produced only in the fat cells, its serum concentration indirectly reflects body fat stores (11, 12, 26). A nocturnal rise in the serum leptin level, regardless of the amount of fat mass in the body, therefore, suggests an increase in either the production rate of leptin in the fat cells and/or its secretion rate into the circulation. It could also be due to reduced clearance of the 167-amino acid sequence peptide from the circulation, although this is probably less likely. Recent reports indicated that leptin release could be affected by glucose and insulin as well as by changes in body fat mass (27). However, in the study of Sinha et al. (18), the circadian rhythmicity of leptin did not correlate to the plasma levels of glucose and insulin (not measured in the present study). The nocturnal rise in serum leptin observed in both adults and children resembles the circadian rhythmicity of some hormones (PRL and TSH), free fatty acids, and melatonin (18, 28, 29). The similarity with melatonin is strong, suggesting a potential interaction between the two variables. To what extent the nocturnal rise in serum leptin is related to nighttime bed rest (inactivity), whereas lower concentrations of leptin during the day are related to increased activity and energy expenditure is unknown and remains to be clarified. Sinha et al. suggested that the nocturnal increase in serum leptin in humans could be related to appetite suppression during sleep (18). If this hypothesis is correct, our finding that young women who accumulated more body fat over a 6-month interval had a lower nocturnal rise in serum leptin could have a special meaning with regard to the pathogenesis of obesity. This lack of appetite suppression during the night over a long period of time could ultimately lead to overeating and weight gain. Whether this finding applies to obese people in general or is specific for overweight individuals suffering from the night eating syndrome (30), remains to be determined. None of our subjects was morbidly obese or suffered from an eating disorder as far as we could determine; however, traits in obesity do start at an early age. A longer follow-up of body composition in those young individuals is necessary to clarify certain of the above trends.
In conclusion, our data show a positive association between serum leptin and body fat stores in young teenage females. The presence of a diurnal variation in the serum leptin level was confirmed for this age group as well. The serum leptin level is relatively stable during the daytime and progressively increases by midnight and the early morning hours, with a fall to the baseline level thereafter. In addition, this is the first study in humans to show an inverse relation between acquisition of body fat and the nocturnal rise in serum leptin. If the lack of a nocturnal rise in serum leptin persists over a longer period of time, it could contribute to the development of obesity by inadequate suppression of nighttime appetite.
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Footnotes |
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Received December 3, 1996.
Revised January 22, 1997.
Accepted January 27, 1997.
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References |
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