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Leptin Levels, Leptin Receptor Gene Polymorphisms, and Energy Metabolism in Women Machteld Wauters,* Robert V. Considine,† Monique Chagnon,‡ Ilse Mertens,* Tuomo Rankinen,‡ Claude Bouchard,‡ and Luc F. Van Gaal*

Abstract WAUTERS, MACHTELD, ROBERT V. CONSIDINE, MONIQUE CHAGNON, ILSE MERTENS, TUOMO RANKINEN, CLAUDE BOUCHARD, AND LUC F. VAN GAAL. Leptin levels, leptin receptor gene polymorphisms, and energy metabolism in women. Obes Res. 2002;10: 394 – 400. Objective: Resting metabolic rate (RMR) is mainly determined by fat-free mass and additionally by age, sex, hormones, and possibly genetic differences. We evaluated whether leptin levels and polymorphisms in the leptin receptor (LEPR) gene were associated with energy expenditure phenotypes. Methods: RMR, body composition, and leptin levels were measured in 125 overweight and obese women. Three LEPR polymorphisms, Lys109Arg, Gln223Arg, and Lys656Asn, were typed on genomic DNA of another group of 192 women in whom RMR was measured. Fat, protein, and carbohydrate oxidation were calculated for 103 of these subjects. In 38 subjects, glucose-induced thermogenesis was measured over 3 hours. Results: In the first study group, a negative correlation between RMR and leptin levels was found after controlling for fat and fat-free mass. In multiple regression analysis, leptin contributed significantly to RMR, independent of body composition. In the second study group, RMR was not associated with LEPR polymorphisms. Differences in sub-

Submitted for publication September 24, 2001. Accepted for publication in final form January 30, 2002. *Department of Diabetology, Metabolism and Clinical Nutrition, University Hospital Antwerp, Antwerp, Belgium; †Division of Endocrinology and Metabolism, Indiana University School of Medicine, Indianapolis, Indiana; and ‡Human Genomics Laboratory, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana. Address correspondence to Prof. Dr. Luc F. Van Gaal, University Hospital Antwerp, Department of Diabetology, Metabolism and Clinical Nutrition, Wilrijkstraat 10, 2650 Edegem, Antwerp, Belgium. E-mail: [email protected] Copyright © 2002 NAASO

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strate oxidation rates were found among genotypes at the Lys656Asn site. In fasting conditions, Lys656Lys showed a trend to oxidize more carbohydrates and less fat than Asn656 carriers, a trend which became significant after the glucose load when carbohydrate oxidation rate in Lys656Lys was 15% higher than in Asn656 carriers (p ⫽ 0.04), and fat oxidation rate was 44% lower (p ⫽ 0.02). Discussion: These results suggest that DNA sequence variations in the LEPR gene could affect substrate oxidation. We hypothesize that this might be caused by differences in glucose levels, leading to differences in glucose oxidation rates. Key words: leptin, energy expenditure, substrate oxidation rates, genetics

Introduction Resting energy expenditure, or resting metabolic rate (RMR), is determined to a major extent by the metabolically active fat-free mass. Other factors playing a role in the variability in energy expenditure between subjects include age, sex, hormonal aspects, and, possibly, genetic differences (1). Leptin is a peptide involved in body weight regulation. As it is secreted by adipocytes, it is potentially a signal for the amount of energy stored to the brain, which reacts by adjusting food intake and/or energy expenditure (2). In mice, it was shown that leptin acts on both sides of the energy balance equation, reducing food intake and, at the same time, increasing energy expenditure. This is most obvious in ob/ob mice that exhibit hyperphagia and decreased energy expenditure, which can both be corrected by exogenous leptin (3). Leptin administration to ob/ob mice increases energy expenditure and sympathetic outflow to brown adipose tissue (4,5). Also, in normal non-obese mice and rats, intracerebroventricular injection of leptin decreases food intake and, at the same time, increases energy

Leptin and Energy Metabolism, Wauters et al.

expenditure (6,7). Exogenous leptin has also been shown to increase uncoupling protein-mediated thermogenesis in rat brown adipose tissue (8). The exact mechanism by which leptin exerts its effects on energy expenditure is unknown: neither whether, nor to what extent, it affects resting metabolic rate, thermogenesis, or energy expenditure of physical activity. A recent report suggests an important role for the pro-opiomelanocortin pathway, with a dual action of leptininduced melanocyte-stimulating hormone: a central inhibition of appetite by interaction with melanocortin receptor 4 – expressing neurons, complemented by a peripheral, catabolic effect on fat metabolism, which increases metabolic rate (9). It is not clear whether leptin also exerts this dual action in humans. In human leptin deficiency, treatment with leptin clearly reduced hyperphagia (10). At the same time, a decreased RMR but increased physical activity level due to improved mobility was seen, resulting in an overall increase in total energy expenditure (10). In normal healthy people, the effect is not easy to evaluate. Studies with leptin treatment are limited, and data on food intake and energy expenditure during leptin administration are not available at the moment. To evaluate a possible effect of leptin on resting energy expenditure, we measured circulating leptin levels and RMR together with other factors known to influence RMR (age, sex, fat and fat-free mass, and thyroid hormones) in a group of overweight and obese women. In addition, we also typed three polymorphisms in the leptin receptor (LEPR) gene. We hypothesized that if leptin effectively has an effect on energy expenditure, it will probably exert this action through the leptin receptors present in the hypothalamus. Therefore, we evaluated whether leptin levels, on one hand, and polymorphisms in the leptin receptor (LEPR) gene, on the other, were associated with some indicators of energy expenditure: RMR, respiratory quotient (RQ), glucose-induced thermogenesis (GIT), and substrate (carbohydrate, fat, and protein) oxidation rates.

Research Methods and Procedures Protocol 1: Circulating Leptin Levels and Resting Energy Expenditure Subjects were 125 overweight and obese women, aged 18 to 65 years, with a body mass index (BMI) between 25 and 50 kg/m2. Patients with type 2 diabetes (defined as fasting glucose ⬎126 mg/dL) were excluded from this study. None of the subjects were taking any medication known to influence appetite behavior or were being treated for other specific endocrine diseases such as Cushing’s disease or hypothyroidism. RMR and body composition were measured as described below. A fasting blood sample was drawn to measure circulating leptin and thyroxine (T4) and thyroidstimulating hormone (TSH) levels.

Protocol 2: LEPR Polymorphisms and Energy Expenditure Subjects were 192 women, aged 18 to 60 years, with a BMI ⬎20 kg/m2. Patients with type 2 diabetes (defined as fasting glucose ⬎126 mg/dL) were excluded from this study as were subjects taking medication known to influence appetite behavior or who were being treated for other specific endocrine diseases such as Cushing’s disease or hypothyroidism. RMR was measured and RQ was calculated as VCO2/VO2. In the 103 subjects for whom urinary nitrogen excretion data were available, fat, protein, and carbohydrate oxidation were calculated. In 38 subjects, this fasting measurement was followed by a measurement of energy expenditure after an oral glucose load of 75 g over a period of 3 hours. GIT was calculated as the mean difference between energy expenditure after the glucose load and energy expenditure at rest (RMR) and was expressed as percent increase from RMR by dividing this difference by the RMR. Weight and height, fat mass, and fat-free mass were measured. A fasting blood sample was drawn to determine fasting leptin and for DNA extraction. Anthropometric Measurements All anthropometric measurements were performed in the morning with the patients undressed and in fasting condition. Height and weight were measured to calculate BMI. Fat mass (in kilograms and percentage of total body fat) was determined by a bioimpedance measurement with a body composition analyzer (BIA-10; RJL Systems, Detroit, MI) with the formula of Deurenberg et al. (11). Energy Expenditure RMR was measured by indirect calorimetry with a ventilated hood system (Deltatrac; Datex, Helsinki, Finland). Subjects stayed overnight at the metabolic ward of the University Hospital Antwerp, and RMR was measured in the morning on awakening after an overnight fast. Oxygen consumption and carbon dioxide production in expired air were measured each minute for 30 minutes after a 10minute equilibration period. Energy expenditure was calculated with the equation of de Weir (12). In addition to energy expenditure, substrate oxidation was calculated with the Lusk equations (13). Laboratory Analyses For leptin measurement, serum samples were frozen and stored at ⫺20 °C until analyzed in batch. Serum leptin levels were measured with a radioimmunoassay, as described previously (14). Circulating levels of free T4 and TSH were measured with Vitros Immunodiagnostic products (Ortho-Clinical Diagnostics, Amersham, UK). The three LEPR polymorphisms, Lys109Arg, Gln223Arg, and Lys656Asn, were typed by polymerase chain reaction as described previously (15). OBESITY RESEARCH Vol. 10 No. 5 May 2002

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Table 1. Characteristics of the 125 women in protocol 1

Table 2. Characteristics of the 192 women in protocol 2

Phenotype

Mean ⴞ SD

Phenotype

Mean ⴞ SD

Age (years) Height (m) Weight (kg) BMI (kg/m2) Fat mass (kg) Fat mass (%) Fat-free mass (kg) Leptin (ng/mL) TSH (mU/L) Free T4 (pM) RMR (kcal/24 hours) RMR/FFM (kcal/kg per day) RQ Nutrient oxidation Carbohydrate oxidation (g/d)* Fat oxidation (g/d)* Protein oxidation (g/d)*

38 ⫾ 11 1.65 ⫾ 0.06 103.3 ⫾ 16.8 38.1 ⫾ 5.9 54.1 ⫾ 13.6 51.7 ⫾ 6.0 49.2 ⫾ 5.8 30.6 ⫾ 16.2 1.58 ⫾ 0.86 14.5 ⫾ 2.4 1780 ⫾ 250 36.3 ⫾ 4.2 0.78 ⫾ 0.05

Age (years) Height (m) Weight (kg) BMI (kg/m2) Fat mass (kg) Fat-free mass (kg) RMR (kcal/24 h) RMR/FFM (kcal/kg/24 h) RQ Nutrient oxidation* Fat oxidation (g/d) Carbohydrate oxidation (g/d) Protein oxidation (g/d) GIT (% increase)† RQ during GIT Nutrient oxidation during GIT Fat oxidation (g/d) Carbohydrate oxidation (g/d) Protein oxidation (g/d)

40 ⫾ 10 1.64 ⫾ 0.06 101.0 ⫾ 18.0 37.6 ⫾ 6.4 52.3 ⫾ 15.0 48.8 ⫾ 5.5 1660 ⫾ 250 34.2 ⫾ 4.2 0.83 ⫾ 0.04

100 ⫾ 72 125 ⫾ 44 75 ⫾ 29

BMI, body mass index; TSH, thyroid stimulating hormone; T4, thyroxine; RMR, resting metabolic rate; FFM, fat-free mass; RQ, respiratory quotient. * Nutrient oxidation rates were calculated for 83 subjects.

Statistical Analyses Pearson correlations were calculated between leptin, after logarithmic transformation, and energy metabolism phenotypes. Partial correlations controlling for fat mass and fatfree mass were calculated. A stepwise multiple regression analysis was performed to determine the most important independent parameters contributing to RMR. A general linear model procedure was used to test for differences between the different genotypes at each polymorphism, and results were considered significant if p ⬍ 0.05. Analyses were performed on phenotypes adjusted for age and fat-free mass as covariates in the model.

Results Protocol 1: RMR and Circulating Leptin Levels Subjects were 125 overweight and obese women of whom 87 were premenopausal. The characteristics of the participants in this study are presented in Table 1. No correlations were found between leptin and RMR or RQ. Leptin was significantly correlated with percent fat mass (r ⫽ 0.35; p ⬍ 0.001), whereas RMR showed strongest correlations with fat mass and fat-free mass (both r ⫽ 396


87 ⫾ 38 160 ⫾ 65 72 ⫾ 29 11 ⫾ 8 0.88 ⫾ 0.06 59 ⫾ 35 269 ⫾ 85 62 ⫾ 22

GIT, glucose-induced thermogenesis. * Nutrient oxidation in fasted state was calculated for 103 subjects. † Thermogenesis after a 75-g glucose load was measured in 38 subjects.

0.63; p ⬍ 0.001). When controlling for these two main determinants and for age, a negative correlation between leptin and RMR was found (r ⫽ ⫺0.26; p ⫽ 0.004). In addition, an inverse association between leptin and protein oxidation rates was found (r ⫽ ⫺0.23; p ⫽ 0.03). Multiple regression analyses with RMR as the dependent variable and with fat mass, fat-free mass, age, sex, and T4 and leptin levels as independent variables showed that leptin contributed independently to the variation in RMR in overweight women, explaining an additional 4% (p ⫽ 0.0014), after fat-free mass, fat mass, and age, which together explained 60% of the variance (all p ⬍ 0.001). A similar result was found for protein oxidation, with leptin explaining 5% of the variance in protein oxidation rates in this group of women. Protocol 2: LEPR Polymorphisms and Energy Expenditure Subject characteristics are shown in Table 2. The mean age of the 192 participants was 40 ⫾ 10 years, and mean BMI was 37.6 ⫾ 6.4 kg/m2. No differences in weight, BMI,


Table 3. Associations between leptin receptor gene polymorphisms and energy expenditure in 192 women Phenotype RMR (kcal/d)

RQ

GIT (%increase)

Genotype

Mean ⴞ SE

N

p

Lys109Lys Lys109Arg ⫹ Arg109Arg Gln223Gln Gln223Arg ⫹ Arg223Arg Lys656Lys Lys656Asn ⫹ Asn656Asn Lys109Lys Lys109Arg ⫹ Arg109Arg Gln223Gln Gln223Arg ⫹ Arg223Arg Lys656Lys Lys656Asn ⫹ Asn656Asn Lys109Lys Lys109Arg ⫹ Arg109Arg Gln223Gln Gln223Arg ⫹ Arg223Arg Lys656Lys Lys656Asn ⫹ Asn656Asn

1666 ⫾ 17 1653 ⫾ 18 1663 ⫾ 24 1659 ⫾ 15 1656 ⫾ 15 1666 ⫾ 22 0.83 ⫾ 0.01 0.83 ⫾ 0.01 0.82 ⫾ 0.01 0.83 ⫾ 0.01 0.83 ⫾ 0.01 0.82 ⫾ 0.01 11.3 ⫾ 1.8 10.5 ⫾ 2.0 9.7 ⫾ 2.3 11.6 ⫾ 1.7 11.7 ⫾ 1.9 10.1 ⫾ 2.0

96 93 52 138 126 63 96 88 52 133 122 62 21 17 13 25 20 18

0.60 0.97 0.60 0.73 0.53 0.41 0.77 0.51 0.59

RMR, resting metabolic rate; RQ, respiratory quotient; GIT, glucose-induced thermogenesis.

or fat mass were found among the different genotypes. RMR reached 1660 kcal/24 hours and was raised by 11% after the glucose load. The mean fasting RQ at rest was 0.83, rising to 0.88 during the GIT. No associations were found between these measurements of energy expenditure and the three LEPR polymorphisms (Table 3). The nutrient oxidation rates at rest and during GIT are given in Table 2. After the glucose load, carbohydrate oxidation increased from a mean fasting value of 160 ⫾ 65 g/d (representing 38% of metabolic rate) to 269 ⫾ 85 g/d (58% of total oxidation). Fat oxidation dropped from 87 ⫾ 38 to 59 ⫾ 35 g/d and protein oxidation from 72 ⫾ 29 to 62 ⫾ 22 g/d. Significant differences were found with substrate oxidation among genotypes at the Lys656Asn polymorphism (Table 4). Under fasting conditions, Lys656Lys homozygotes showed a trend to oxidize ⬃5% more carbohydrates (p ⫽ 0.12) and less fat (p ⫽ 0.15) than carriers of the Arg656 allele (Figure 1A). This became more obvious during the glucose load test (Figure 1B), when carbohydrate oxidation rose to 298 ⫾ 22 g/d in Lys656Lys homozygotes, which was 15% higher than in carriers of the Asn656 allele (p ⫽ 0.06). Concomitantly, fat oxidation in this group fell to 46 ⫾ 8 g/d, which was significantly lower than the Asn656 carriers (p ⫽ 0.03). In this group of women in whom the GIT was measured, associations with glucose metabolism were further investi-

gated. The Lys656Asn polymorphism was associated with the acute glucose response after an oral glucose load (glucose at 15⬘): Lys homozygotes showed significantly higher glucose levels compared with Asn carriers (6.9 ⫾ 0.3 vs. 5.9 ⫾ 0.3 mM, p ⫽ 0.04). No significant associations with glucose levels at other time points during the oral glucose tolerance test were found. A trend was found for the insulin response after 2 hours, with higher insulin levels in Lys homozygotes compared with Asn carriers (933 ⫾ 129 pM vs. 610 ⫾ 129 pM; p ⫽ 0.08)

Figure 1: (A) Substrate oxidation for the Lys656Asn genotypes in fasting conditions. (B) Substrate oxidation for the Lys656Asn genotypes after an oral glucose load. * indicates a significant difference between Lys/Lys and Asn carriers.


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Table 4. Associations between leptin receptor gene polymorphisms and nutrient oxidation in rest and after a glucose load During RMR (n ⴝ 103) Genotype

Mean ⴞ SE

n

p

Mean ⴞ SE

n

p

Lys109Lys Lys109Arg ⫹ Arg109Arg Gln223Gln Gln223Arg ⫹ Arg223Arg Lys656Lys Lys656Asn ⫹ Asn656Asn Lys109Lys Lys109Arg ⫹ Arg109Arg Gln223Gln Gln223Arg ⫹ Arg223Arg Lys656Lys Lys656Asn ⫹ Asn656Asn Lys109Lys Lys109Arg ⫹ Arg109Arg Gln223Gln Gln223Arg ⫹ Arg223Arg Lys656Lys Lys656Asn ⫹ Asn656Asn

86 ⫾ 5 86 ⫾ 5 90 ⫾ 6 85 ⫾ 4 82 ⫾ 4 92 ⫾ 6 167 ⫾ 9 154 ⫾ 10 164 ⫾ 12 160 ⫾ 8 169 ⫾ 8 147 ⫾ 11 68 ⫾ 4 76 ⫾ 4 69 ⫾ 5 73 ⫾ 3 72 ⫾ 4 72 ⫾ 5

54 47 29 72 64 36 54 47 29 72 64 36 54 47 29 72 64 36

0.92

66 ⫾ 9 49 ⫾ 10 49 ⫾ 12 63 ⫾ 8 46 ⫾ 8 78 ⫾ 10 259 ⫾ 24 282 ⫾ 26 281 ⫾ 31 264 ⫾ 22 298 ⫾ 22 228 ⫾ 27 60 ⫾ 6 66 ⫾ 7 66 ⫾ 8 61 ⫾ 6 65 ⫾ 6 59 ⫾ 7

15 12 9 18 16 11 15 12 9 18 16 11 15 12 9 18 16 11

0.23

Phenotype Fat oxidation (g/d)

Carbohydrate oxidation (g/d)

Protein oxidation (g/d)

During GIT (n ⴝ 38)

0.52 0.15 0.33 0.78 0.12 0.12 0.50 0.96

0.36 0.03 0.53 0.66 0.06 0.48 0.59 0.59

RMR, resting metabolic rate, GIT, glucose-induced thermogenesis.

Discussion The novelty of this study is the finding that a polymorphism in the leptin receptor gene seems to be associated with relative oxidation rates of glucose. To our knowledge, this is the first study examining the relations between leptin receptor gene polymorphisms and energy metabolism. Resting energy expenditure is known to be determined mainly by the metabolically active lean body mass, but also by fat mass. Besides this, other factors that contribute to the variance in RMR are age, sex, sympathetic tonus, and thyroid hormones. Most of the energy expended at rest is for the metabolic needs of the heart, liver, brain, kidneys, and skeletal muscle. In the first part of this study, we analyzed whether, in addition to these factors, leptin levels added further to the variance in RMR. In this group of overweight and obese women, a significant inverse correlation was found after correcting for age, fat mass, and fat-free mass. Several previous studies have reported on the relationships between leptin and resting energy expenditure. However, results are inconsistent because of the heterogeneity of subjects in the various studies (obese and non-obese, men and women, three in children, and two in specific ethnic groups such as Pima Indians or African Americans), different statistical adjustments (some controlled only for fat 398


mass, others for body composition, age, and sex), and the limited number of subjects. Four studies found associations between leptin and energy expenditure at rest when adjusting for body composition; two of these controlled for fatfree mass, of which one reported a correlation in women but not in men (16), whereas the other found leptin to be correlated to RMR in men only (17). The third study controlled for fat mass, age, and sex and found an inverse association between leptin and RMR (18). Liuzzi et al. (19) also found this inverse relation when controlling for fat mass and sex but not when controlling for fat-free mass. Toth et al. (20) found that fat-free mass and leptin levels accounted for 66% of the variation in RMR. Another study in children (21) found a correlation between leptin and RMR but not after adjusting for fat mass, fat-free mass, and sex. Other reports (22–25) found no significant associations between leptin and RMR. Overall, all studies that appropriately adjusted for fat mass and fat-free mass found no significant correlations between leptin and RMR (19,21–23). In our study, in women only, we found an inverse association between circulating leptin levels and RMR after controlling for age and body composition, i.e., fat mass and fat-free mass, the two strongest correlates of leptin and RMR, respectively. With multiple regression analysis, lep-


tin level was an independent determinant of RMR. Leptin was a significant predictor even after controlling for fat-free mass and fat mass, although it added little to the variance (⬍10%). The physiological significance of this relationship is not clear at this time. In addition to evaluating resting metabolic rate, we also investigated possible relationships of leptin with substrate oxidation. We found an inverse association with protein oxidation rate that disappeared when controlling for body composition. Participants with higher leptin levels, in general those more obese, had lower protein oxidation rates. However, the association was very weak and was observed in a small group, thus emphasizing that no firm conclusions can be drawn. Two previous human studies (18,20) found significant inverse associations of leptin with carbohydrate oxidation rates, with serum leptin levels the most important independent variable in regression analysis, explaining from 21% to 26% of the variation in carbohydrate oxidation rates. Another recent study (26) found leptin to be inversely correlated with non-protein respiratory quotient in obese subjects. In the second study, we found no associations between three LEPR polymorphisms and RMR, GIT, or RQ. However, we found a significant difference in fat and carbohydrate oxidation rates, especially in response to a glucose load, among carriers and non-carriers of the Asn allele at the Lys656Asn polymorphism. These results suggest that the leptin receptor gene could be an effector of nutrient use. Rodent studies have shown that leptin administration to ob/ob mice has a profound effect on fuel selection, reducing RQ, an indication of a reduction in relative carbohydrate oxidation rate and of a rise in the fat oxidation rate (5). Several studies have found that a high fasting or postabsorptive RQ reflects low rates of fat oxidation and is a predictor of weight gain (27–29). It has been hypothesized that carbohydrate oxidizers with a high 24-hour RQ and a low rate of fat oxidation are at a higher risk for weight gain, independent of RMR, because of a chronic imbalance between fat intake and fat oxidation (30). The rationale is that the positive fat balance resulting from lower fat oxidation rates leads to more fat stored and hence to weight gain. The present study suggests that the Lys656Lys homozygotes are more prone to exhibit the latter phenotype. However, we did not find any difference in weight, BMI, or fat mass between the two genotypic groups. Nevertheless, it is possible that a small effect results in a higher overall weight gain over a long period of time. Longitudinal follow-up studies would be necessary to document this phenomenon. Moreover, gene-diet interactions may be important: the LEPR genotype was associated with substrate oxidation measured after glucose load and not in the fasting state, suggesting that quantity and quality of the diet as well as meal frequency may interact with the LEPR genotype effect on postprandial glucose and fat oxidation and thereby on weight gain over time.

The potential mechanism by which the leptin receptor might affect nutrient oxidation rates is not clear. Substrate use is normally regulated by circulating levels of substrates (i.e., blood levels of glucose, free fatty acids, and amino acids) and hormones (i.e., insulin, glucagon, catecholamines, growth hormone, thyroid hormones), and by the sympathetic nervous system (31,32). Leptin could theoretically affect this through several pathways. First, leptin stimulates sympathetic outflow, and hypoleptinemia or leptin resistance may lead to reduced activity of the sympathetic nervous system and thus to reduced RMR and higher RQ (32). However, if the effect of leptin on nutrient oxidation was mediated through the hypothalamic leptin receptor and the sympathetic nervous system, one would also expect a concomitant increase in RMR, which we did not find. Second, leptin has been shown to affect insulin and glucose homeostasis via several mechanisms: modulation of insulin secretion through leptin receptors on pancreatic ␤-cells, modulation of glucose use through peripheral receptors (e.g., on liver, muscle, and adipocytes), and modulation of insulin action through central nervous system pathways. In rodents, leptin infusion has been shown to increase overall glucose use. Here, we found a significant association with the acute glucose response (glucose levels 15⬘ after the glucose load) for the LEPR Lys656Asn polymorphism in the same subjects in which the association with carbohydrate oxidation rate was found. Thus, the Asn carriers exhibited both lower glucose levels and lower carbohydrate oxidation rates. This suggests that the leptin effect is a peripheral effect, with a lower carbohydrate oxidation rate resulting from the lower plasma glucose levels.

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