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Keywords:

  • population studies;
  • neural factors/leptin;
  • bone QCT;
  • clinical/pediatrics;
  • body composition;
  • bone densitometry

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The association between leptin and areal BMD has been controversial, and the predictive role of leptin on cortical volumetric BMD and bone size has not previously been studied. We show that leptin is a negative independent predictor of aBMD (DXA), at several measured sites, and of cortical bone size (pQCT) in a large population of young men.

Introduction: Recent findings suggest that both adipose tissue (AT) and bone mass are regulated by leptin. Previous reports studying the association between leptin and areal BMD (aBMD) have yielded conflicting results. The role of leptin on volumetric BMD (vBMD) and bone size of the cortical and trabecular bone compartments has not previously been studied.

Materials and Methods: The Gothenburg Osteoporosis and Obesity Determinants (GOOD) study is a population-based study of 1068 men (age, 18.9 ± 0.6 [SD] years). aBMD of the total body, lumbar spine, femoral neck, both radii, and trochanter, as well as total body AT and lean mass (LM) were measured using DXA, whereas cortical and trabecular vBMD and bone size were measured by pQCT.

Results: Total body LM could explain a larger magnitude of the difference in the variation in aBMD and cortical bone size than what total body AT could (total body aBMD: LM 37.4% versus AT 8.7%; tibia cross-sectional area [CSA]: LM 46.8% versus AT 5.6%). The independent role of leptin on bone parameters was studied using a multiple linear regression model, including age, total body LM and AT, height, present physical activity, calcium intake, and smoking as covariates. Leptin was found to be a negative independent predictor of aBMD (total body: β =−0.08, p =0.01; lumbar spine: β =−0.13, p < 0.01; trochanter: β =−0.09, p =0.01), as well as of the cortical bone size (CSA and thickness) of both the radius (CSA: β =−0.12, p < 0.001) and tibia (CSA: β =−0.08, p < 0.01), but not of the cortical or trabecular vBMD of these bones.

Conclusion: Our results indicate that LM has a greater impact on bone mass than AT. Our findings further show that leptin is a negative independent predictor of aBMD at several measured sites and of bone parameters reflecting cortical bone size, but not vBMD, in a large population of young Swedish men.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Osteoporosis-related fractures constitute a major public health concern in women and men.(1 The fracture risk is highly dependent on BMD.(2,3 Each SD decrease in BMD has been associated with about a 2-fold increase in the age-adjusted hip fracture risk in postmenopausal women(4 and with a 3-fold risk increase in elderly men.(5

It is well established that obesity is a major risk factor for several common and severe diseases, including cardiovascular disease, diabetes, and cancer.(6 The link between obesity and osteoporosis is less clear.(7 A plethora of evidence supports the notion that body weight is positively associated with areal BMD (aBMD) in both sexes and at all ages throughout adulthood(8–10 and negatively associated with fracture incidence.(3,11 However, it remains a controversy whether it is lean mass or adipose tissue(12–15 that mediates the bone stimulatory effect exerted by weight. Recent findings suggest that both adipose tissue and bone mass are regulated by the small polypeptide adipocyte-derived hormone leptin.(16 This hormone has been shown to have a central role not only in regulating appetite and energy expenditure, but also in regulating bone metabolism, as shown by the “high bone mass” phenotype in the leptin-deficient (ob/ob) mice.(17 In humans, some cross-sectional studies have failed to show any association between serum leptin levels and aBMD in women(18,19 or in men,(20 whereas others have reported a positive association between leptin and aBMD.(21 Most likely, a great deal of the inconsistency in the published data can be attributed to the arbitrary way the various authors have chosen to evaluate and present either adjusted (for body weight) or unadjusted data. In a few recent studies in men, leptin was inversely correlated to aBMD, an association that became apparent only after adjustment of aBMD for body weight.(22–24 Previous studies investigating the association between adipose tissue, leptin, and bone mass have been limited by the use of 2D measurements (aBMD) of the bone, using DXA, which does not provide information about volumetric BMD (vBMD) or size of the different bone compartments (i.e., cortical and trabecular bone). Hence, because of the limitations of the DXA methodology, it remains unclear whether lean mass, adipose tissue, and leptin are associated with vBMD of the cortical and trabecular bone or with the bone size of these bone compartments. To measure the true vBMD and the bone size of the cortical and trabecular bone, a 3D technique, such as pQCT, must be used.

The aim of this population-based study was to determine if lean mass, adipose tissue, and leptin were associated with aBMD, vBMD, and cortical bone size in a large population (n =1068) of young men.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Subjects

The Gothenburg Osteoporosis and Obesity Determinants (GOOD) study was initiated with the aim to determine both environmental and genetic factors involved in the regulation of bone and fat mass. Study subjects were randomly identified using national population registers, contacted by telephone, and asked to participate in this study. A total of 1068 men 18.9 ± 0.02 years of age, from the greater Gothenburg area, were included. To be included in the GOOD study, subjects had to be between 18 and 20 years of age and willing to participate in the study. There were no other exclusion criteria; 48.6% of the contacted study subject candidates agreed to participate and were included in this study. A standardized questionnaire was used to collect information about amount of present physical activity (h/week), age, nutritional intake (dairy products), and smoking. Calcium intake was estimated from dairy product intake. We previously presented baseline data on aBMD and bone parameters measured with pQCT in this cohort.(25

Anthropometrical measurements

Height and weight were measured using standardized equipment. The CV values were <1% for these measurements.

DXA

Total body lean mass, adipose tissue, and aBMD (g/cm2) of the whole body, femoral neck and trochanter (of the left leg), lumbar spine, and the dominant and nondominant radius were assessed using the Lunar Prodigy DXA (GE Lunar Corp., Madison, WI, USA). The CVs for the aBMD measurements were 0.4% for the total body, 0.8% for the spine, 0.6% for the femoral neck, and 2.5% for the radius. The CVs for total body adipose tissue and lean mass were 3.4% and 1.8%, respectively.

pQCT

A pQCT device, using single-energy X-ray (XCT-2000; Stratec Medizintechnik, Pforzheim, Germany) was used to scan the distal leg (tibia) and the distal arm (radius) of the nondominant leg and arm, respectively. The pQCT was calibrated every week using a standard phantom and once every 30 days using a cone phantom provided by the manufacturer. A 2-mm-thick single tomographic slice was scanned with a voxel size of 0.50 mm. The cortical vBMD (mg/cm3), cortical BMC (mg/mm), cortical cross-sectional area (CSA, mm2), and cortical thickness (mm) were measured using a scan through the diaphysis (at 25% of the bone length in the proximal direction of the distal end of the bone) of the radius and tibia.

The cortical vBMD is the true cortical vBMD, not including the marrow compartment. Trabecular vBMD (mg/cm3) was measured using a scan through the metaphysis (at 4% of the bone length in the proximal direction of the distal end of the bone) of these bones. All the pQCT analyses were performed by the same technician using one pQCT. The CVs were <1% for all pQCT measurements.

Leptin analysis

Serum was obtained from whole blood using standard procedures, frozen without delay, and stored at −70 C. Leptin was analyzed in serum samples (that had not undergone additional freeze-thaw cycles) using a commercially available kit (Active Human Leptin ELISA; Diagnostic Systems Laboratories, Webster, TX, USA) with a detection limit of 0.05 ng/ml. Intra- and interassay CVs were 6.2% and 5.3%, respectively.

Serum analyses of testosterone and sex hormone binding globulin

Analyses of serum levels of total testosterone and sex hormone binding globulin (SHBG) were performed as previously described.(26 Free testosterone was calculated according to the method previously described by Vermulen et al.(27 and Van den Beld et al.(28

Statistical analysis

Values are given as mean ± SD. Correlations of normally distributed and non-normally distributed variables were tested using Pearson's and Spearman's coefficients of correlation, respectively. The independent predictors of the various bone parameters were tested using multiple linear regression analysis. Variables that were not normally distributed (leptin, adipose tissue, and age) were log-transformed before entered into the regression analysis. The percentage of the variation of each bone parameter explained (R2) by total body lean mass or adipose tissue alone was calculated using the linear regression model. The proportion of the variation in bone parameters explained by the whole regression model was calculated using age, height, smoking, physical activity, calcium intake, total body lean mass and adipose tissue, and leptin as covariates. The percentage of the variation in bone parameters explained by leptin alone was calculated as the observed difference in the percentage of the variation explained by the whole regression model (including leptin) and by the whole regression model not including leptin as a covariate.

Standardized β-values are given. A p value <0.05 was considered significant. All statistical analysis was performed using SPSS (version 13.0.1; SPSS, Chicago, IL, USA).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Anthropometric data, calcium intake, amount of present physical activity, total body adipose tissue and lean mass, serum leptin levels, testosterone and SHBG, and bone variables as measured using DXA and pQCT are given in Table 1.

Table Table 1.. Anthropometric Characteristics, aBMD (DXA), vBMD, and Bone Size (pQCT) of the 1068 Men in the GOOD Cohort
  inline image

Univariate correlations between total body adipose tissue, lean mass, leptin, and cortical bone size (pQCT)

Serum leptin levels were strongly correlated to total body adipose tissue (r =0.66, p < 0.0001) and moderately to total body lean mass (r =0.11, p < 0.001). Serum free testosterone was not significantly correlated to leptin levels (r =−0.03, p =0.33).

Total body lean mass was more strongly positively correlated to parameters of cortical bone size (CSA, cortical thickness, periosteal circumference [PC], and endosteal circumference [EC]) than what total body adipose tissue was (Table 2). Both total body lean mass and adipose tissue were inversely correlated to cortical vBMD and positively correlated to trabecular vBMD of the tibia, whereas only total body lean mass displayed similar correlations for the radius. Total body lean mass and adipose tissue could explain 46.8% and 5.6%, respectively, of the variation in tibia CSA.

Table Table 2.. Univariate Correlations Between Adipose Tissue, Lean Mass, Leptin, and Parameters of Bone Size and vBMD (pQCT) of the Radius and Tibia
  inline image

Leptin was positively correlated in the univariate analyses to EC and PC of the tibia but not of the radius (Table 2).

Univariate correlations between total body adipose tissue, lean mass, leptin, and aBMD (DXA)

Total body lean mass was more strongly positively correlated to aBMD of the total body, femoral neck, trochanter, radii, and lumbar spine than what total body adipose tissue was (lean mass: r =0.61–0.39 versus adipose tissue: r =0.28–0.07; Table 3). Total body lean mass could explain a larger magnitude of the difference in the variation in aBMD than what total body adipose tissue could (total body aBMD: lean mass 37.4% versus adipose tissue 8.7%; femoral neck aBMD: lean mass 23.1% versus adipose tissue 2.2%; dominant radius: lean mass 15.3% versus adipose tissue 7.7%; nondominant radius: lean mass 14.9% versus adipose tissue 6.7%).

Table Table 3.. Univariate Correlations Between Adipose Tissue, Lean Mass, Leptin, and aBMD (DXA)
  inline image

Leptin was correlated to aBMD of the total body and radii but not to the other aBMD sites (Table 3).

Total body adipose tissue and lean mass as independent predictors of cortical bone size (pQCT)

Because the two major constituents of body weight (i.e., total body lean mass and adipose tissue) were both correlated to aBMD and to several bone parameters measured with pQCT, a multiple linear regression model, using age, height, present physical activity, calcium intake, and smoking as covariates, was used to determine the independent predictive role of total body adipose tissue and lean mass for bone parameters. Total body adipose tissue was a positive independent predictor of cortical bone size (cortical CSA, PC, and EC) of the tibia (Table 4). Total body lean mass was a strong positive independent predictor of cortical bone size (CSA, thickness, PC, and EC) of both the radius and tibia. Total body lean mass was a positive independent predictor of both radius and tibia trabecular vBMD, whereas total body adipose tissue only predicted tibia trabecular vBMD. Total body adipose tissue was a negative predictor of the cortical vBMD of the tibia but not of the radius (Table 4).

Table Table 4.. Total Body Adipose Tissue and Total Body Lean Mass as Independent Predictors of aBMD (DXA), Cortical vBMD, and Cortical Bone Size (pQCT)
  inline image

Total body adipose tissue and lean mass as independent predictors of aBMD (DXA)

In the regression analysis, total body adipose tissue was an independent predictor of aBMD of the total body, femoral neck, and the radii, whereas total body lean mass was an independent predictor of aBMD at all bone sites studied (Table 4).

Leptin as a negative independent predictor of cortical bone size (pQCT) and aBMD (DXA)

To determine if leptin independently predicted any bone parameters, leptin was added to the multiple linear regression model. In this analysis, leptin was found to be a negative independent predictor of cortical bone size (CSA and thickness) of both the radius and tibia but not of the cortical or trabecular vBMD of these bones (Table 5).

Table Table 5.. Total Body Adipose Tissue and Leptin as Independent Predictors of aBMD (DXA), Cortical vBMD, and Cortical Bone Size (pQCT)
  inline image

Leptin was also a negative independent predictor of aBMD at the total body, lumbar spine, and trochanter (Table 5).

To investigate if physical activity or lean mass influenced the association between leptin and bone parameters, the regression analysis was also performed without physical activity or lean mass. Neither removal of physical activity (total body aBMD: β =−0.09, p =0.004; lumbar spine aBMD: β =−0.14, p < 0.001; trochanter aBMD: β =−0.10, p =0.004; CSA radius: β =−0.12, p < 0.001; CSA tibia: β =−0.12, p =0.002) nor removal of lean mass (total body aBMD: β =−0.10, p =0.009; lumbar spine aBMD: β =−0.14, p =0.001; trochanter aBMD: β =−0.10, p =0.009; CSA radius: β =−0.14, p < 0.001; CSA tibia: β =−0.10, p =0.006) substantially altered the impact of leptin as a negative independent predictor of aBMD or cortical bone size.

The proportion of the variation in aBMDs explained by the whole regression model (including age, height, smoking, physical activity, calcium intake, total body lean mass and adipose tissue, and leptin) was 44.4% for the total body, 24.5% for the lumbar spine, 30.4% for the femoral neck, 30.3% for the trochanter, 25.3% of the dominant radius, and 24.1% for the nondominant radius. The same regression model could explain 37.7% and 49.6% of the variation in CSA of the radius and tibia, respectively. The variation in aBMD explained by leptin alone was 0.3% of the total body, 0.9% of the lumbar spine, and 0.4% of the trochanter. Leptin alone could explain between 0.3% (tibia) and 0.8% (radius) of the variation in CSA.

We also studied if serum total or free testosterone levels could influence the associations between serum leptin levels, aBMD, and cortical bone size. Inclusion of total or free testosterone levels in the regression analysis (including age, height, smoking, physical activity, calcium intake, total body lean mass and adipose tissue, and leptin) did not change the found associations between leptin and aBMD or cortical bone size (data not shown).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

It has long been a controversy whether lean mass or adipose tissue is the strongest predictor of aBMD.(12–15,29 Recent reports indicated that, in young female populations, lean mass is a positive predictor,(30,31 whereas adipose tissue is a weaker positive(32 or, after adjustment for body weight,(33–35 a negative predictor of BMD. In this study, we showed that total body lean mass explained a much larger proportion of the variance in aBMD than what adipose tissue did (37.4% versus 8.7% for total body aBMD).

Because of the limitations in the DXA technique, the association between adipose tissue, lean mass, bone size, and vBMD of the different bone compartments (i.e., trabecular and cortical bone) has not been revealed. A recent small study has indicated a relationship between lean mass percent and cortical area in men (n =36) and women (n =36).(36 In this study, we showed, with the use of pQCT, that total body lean mass is a strong positive independent predictor of the cortical bone size of both weight-bearing (tibia) and non—weight-bearing bones (radius) in our large cohort of young men. A possible explanation for these associations is that the mechanical loading exerted by muscle contraction could result in cortical bone expansion. Thus, the effect of lean mass on cortical bone size is of similar magnitude in non—weight-bearing bones and in weight-bearing bones. Interestingly, total body lean mass was a negative predictor of the cortical vBMD of the radius. We have previously shown that the cortical vBMD of the radius and tibia has most likely not reached its peak in the men of this cohort.(25 One could speculate that a growth stimulatory effect of lean mass on the cortical bone size could hinder an adequate cortical mineralization to take place. In agreement with what was found for total body lean mass, adipose tissue was a positive independent predictor of the cortical bone size of the weight-loaded tibia. One could speculate that the mechanical loading effect (by the weight) of the adipose tissue stimulates the cortical bone growth of the weight-loaded bones, an effect that is absent in the non—weight-loaded bones. This study is limited to measurements of CSA of the nondominant arm and leg, hindering comparisons of associations between adipose tissue, leptin, and bone geometry measurements between dominant and nondominant paired bones (e.g., the radii). We have previously shown in this cohort that aBMD of the radius in the dominant arm is greater than that in the nondominant arm.(37 Using the DXA measurements, we could, in this study, not detect any substantial discrepancies between the associations between adipose tissue, leptin, and aBMD of the dominant and of the nondominant radius. Because of the limitations of the DXA technique, being 2D, it could not be determined how these DXA data translate into associations regarding cortical bone size. Furthermore, we studied whether the relationship between leptin and bone parameters was modulated by physical activity or lean mass, by removing either of these predictors from the regression model. When removing lean mass or physical activity from the regression model, the role of leptin as a negative predictor of cortical bone size, as well as of aBMD, was mainly unaltered, suggesting that the impact of leptin on these bone parameters was not dependent on lean mass.

Leptin has been proposed to be a mediator of the adipose tissue hormonal effects on bone mass.(7 The role of leptin in bone metabolism is not fully elucidated, but results from animal studies showed that mice deficient in leptin signaling (ob/ob or db/db) had higher trabecular bone mass, despite hypogonadism and hypercortisolism.(38

In a few recent studies in men, leptin has been inversely correlated to aBMD, but only after adjustment for body weight.(22–24 In agreement with these reports, we showed that leptin was an independent negative predictor of aBMD at several measured sites. This study is the first study to reveal the independent role of leptin on aBMD in young men.

The association between leptin and cortical bone size and trabecular and cortical vBMD has not previously been studied. In our cohort of young men, serum leptin levels were not independent predictors of cortical or trabecular vBMD, indicating that leptin is not involved in the mineralization of the young male skeleton. Interestingly, leptin was a negative independent predictor of cortical bone size of both the non—weight-loaded bone (radius) and the weight-loaded bone (tibia), suggesting a general inhibitory role of leptin on cortical bone size. Based on our results, one can speculate that leptin is a mediator of a systemic inhibitory effect of adipose tissue on cortical bone size. A reduced cortical bone size has been reported to be associated with reduced mechanical strength of the radius (39 and an increased risk of fractures of the femoral neck.(40

Our findings from this study suggest that lean mass is more strongly associated with aBMD and cortical bone size than adipose tissue, suggesting that a body constitution with a high proportion of lean mass could protect against fracture. Furthermore, our results indicate that excessive leptin levels, as seen in obesity, could result in a reduced cortical bone size at non—weight-bearing bone sites (also after adjustment for physical activity level) and might increase fracture risk. In agreement with this hypothesis, Skaggs et al.(34 showed that girls who sustained forearm fractures after minor trauma tended to be overweight and had a smaller CSA of the distal radius than girls without fractures. It should, however, be noted that the associations obtained in this study apply to a young and primarily healthy population with normal body mass indexes and that these associations may not be true in elderly subjects who sustain the most fractures or in overweight or obese populations.

We have previously shown that testosterone levels are positive independent predictors of cortical bone size in men in this cohort.(26 Other studies have reported inverse correlations between serum testosterone and leptin levels in men.(41,42 We studied if serum free testosterone levels could influence the association between serum leptin levels and cortical bone size. However, in our cohort, inclusion of serum testosterone levels in the regression analysis did not change the found associations between leptin and cortical bone size.

In conclusion, the results from this study indicate that lean mass has a greater impact on bone mass than adipose tissue. Our findings further show that leptin is a negative independent predictor of aBMD at several measured sites and of bone parameters reflecting cortical bone size, in a large population of young Swedish men.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

This study was supported by the Swedish Research Council, the Swedish Foundation for Strategic Research, European Commission Grant QLK4-CT-2002-02528, the Lundberg Foundation, the Torsten and Ragnar Söderberg's Foundation, Petrus and Augusta Hedlunds Foundation, the ALF/LUA grant from the Sahlgrenska University Hospital, and the Novo Nordisk Foundation.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES