Arch Gynecol Obstet DOI 10.1007/s00404-015-3656-7
GYNECOLOGIC ENDOCRINOLOGY AND REPRODUCTIVE MEDICINE
Association between osteocalcin and metabolic syndrome in postmenopausal women Suk Woo Lee • Hyun Hee Jo • Mee Ran Kim Jang Heub Kim • Young Oak You
•
Received: 10 March 2014 / Accepted: 6 February 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Objectives Undercarboxylated osteocalcin (ucOC) has been proved as a regulator of glucose and fat mass in an animal model. This study examined the association between osteocalcin and metabolic syndrome (MetS) in postmenopausal women. Methods We selected 135 postmenopausal women and determined anthropometric values [waist-hip ratio (WHR), visceral fat area (VFA), body fat mass (BFM), and skeletal muscle mass (SMM)], the lipid profile, fasting plasma glucose (FPG), insulin, high-sensitivity C-reactive protein (hs-CRP), homeostasis model assessment of insulin resistance (HOMA-IR), serum leptin and adiponectin level, and serum tOC and ucOC level. Results There were 52 postmenopausal women in the MetS group. After adjusting for age and years since menopause, ucOC was negatively correlated with WHR, VFA, BFM, triglyceride, fasting insulin, HOMA-IR, and serum leptin and was positively correlated with serum S. W. Lee Department of Obstetrics and Gynecology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, 22, Gwanpyeong-ro 170beon-gil, Dongan-gu, Anyang-si, Gyeonggi-do 431-796, Korea e-mail: [email protected] H. H. Jo M. R. Kim J. H. Kim Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul St. Mary’s Hospital, 222 Banpo-daero, Seocho-gu, Seoul 137-701, Korea Y. O. You (&) Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, St. Vincent Hospital, 93 Jungbu-daero, Ji-dong, Paldal-gu, Suwon, Gyeonggi-do 442-723, Korea e-mail: [email protected]
adiponectin. The odds ratio for MetS was significantly lower in the highest quartile than the lowest quartile after adjusting for age, years since menopause, and BMI. In multiple regression analysis, serum leptin and HOMA-IR were the most important predictors of the independent variables that affect serum ucOC. Conclusion ucOC showed an inverse correlation with markers of insulin resistance, central obesity, and the presence of MetS in postmenopausal women and appears to protect against MetS. Further large-scale clinical and experimental studies are needed to clarify the potential of ucOC as a predictor of MetS in postmenopausal women. Keywords Adipokine Insulin resistance Metabolic syndrome Osteocalcin Postmenopause
Introduction Bone is an active organ that continuously undergoes remodeling involving bone resorption and formation, and bone mass is maintained by the balance between these two processes. Increase in bone resorption and decrease in bone formation due to estrogen deficiency are associated with increased prevalence of osteoporosis in postmenopausal women [1]. Metabolic syndrome (MetS) is defined as a cluster of metabolic risk factors, including abdominal obesity, atherogenic dyslipidemia, elevated blood pressure, insulin resistance, and increased levels of proinflammatory cytokines, including IL-1, IL-6, and TNF-a [2]. Weight gain, increases in abdominal fat, and dyslipidemia are common during menopause, and large amounts of abdominal fat are associated with increased risk of insulin resistance and MetS [3].
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Leptin and adiponectin, representative adipokines secreted by adipocytes, play opposite roles in MetS. Leptin is positively correlated with central obesity, stimulates proinflammatory cytokines, and contributes to an increase in insulin resistance [4, 5]. Adiponectin increases insulin sensitivity by increasing fatty acid oxidation and glucose uptake in muscle and antiatherogenic action by inhibiting infiltration of monocytes and foam cell formation in endothelial cells. Leptin and adiponectin are also well known to affect bone formation and resorption, either directly or indirectly. Previous studies have indicated that bone and adipose tissue act as endocrine organs that modulate energy metabolism [6]. Osteocalcin is a vitamin K-dependent protein produced mainly by osteoblasts and is used as a biochemical marker for bone formation [7]. Osteocalcin is c-carboxylated by vitamin K. Carboxylated osteocalcin (cOC) has high affinity for calcium and hydroxyapatite in the bone matrix while undercarboxylated osteocalcin (ucOC) has been shown to act as a hormone in the body, causing beta cells in the pancreas to release more insulin and increase insulin sensitivity in both fat and muscle [8, 9]. ucOC also stimulates adiponectin in adipocytes, and leptin inhibits the activity of osteocalcin, thus enhancing insulin resistance [10]. Taken together, these studies support a regulatory role for bone in glucose and fat metabolism, which appears to be mediated by ucOC [11]. Although there have been several clinical studies of the association between fat and glucose metabolism, MetS, and osteocalcin in both sexes, and there is interest in the increasing incidence of MetS in postmenopausal women, no definitive conclusions regarding the association between osteocalcin and MetS in postmenopausal women have yet been reached. The present study was performed to examine the association between osteocalcin and MetS in postmenopausal women.
Materials and methods Participants Between September 2009 and August 2010, a total of 194 postmenopausal women who were cared for at Saint Vincent’s Hospital were recruited. This prospective and cross-sectional study was approved by the Institutional Review Board of The Catholic University of Korea and informed consent was obtained from each participant. The exclusion criteria were as follows: current cancer; laboratory evidence of kidney, liver, or thyroid disease; diabetes; bone-altering conditions (bilateral oophorectomy, hyperparathyroidism, nephrolithiasis, renal disease,
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or therapy with biphosphonates, calcitonin, estrogen, steroids, tamoxifen, or chemotherapy in the past year); use of anti-obesity agents or non-compliance with diet and behavioral therapy for weight control. Postmenopausal women had at least 12 consecutive months of amenorrhea with no other medical cause for amenorrhea and a follicle-stimulating hormone level [40 mIU/mL at the time of enrollment. After the application of exclusion criteria, 135 women were enrolled in the present study. Clinical and anthropometric data Data on age, years since menopause, health behaviors, including smoking and alcohol consumption, and personal history of diabetes and hypertension were provided by the participants through questionnaires. Alcohol consumers were defined as those with at least weekly consumption of alcohol. Subjects were classified as having a smoking habit if they smoked at the time of the study. Body size and composition were measured by bioelectrical impedance analysis (BIA) using a body composition analyzer (Inbody 720, Biospace Inc., Seoul, Korea). The data collected included waist–hip ratio (WHR), visceral fat area (VFA), skeletal muscle mass (SMM), percent body fat (PBF), and body fat mass (BFM). The degree of accuracy of body size and composition measurements had a 1.0 % coefficient of variation. Blood pressure was measured twice with a mercury sphygmomanometer after a 10-min seated rest, and the average of the two measurements was used for statistical analysis. Biochemical analyses Blood was collected by venipuncture after an overnight fast, and the total cholesterol, triglycerides, HDL cholesterol, fasting plasma glucose (FPG), and high-sensitivity C-reactive protein (hs-CRP) levels were measured using a Hitachi 7600-110Ò Automatic Analyzer (Hitachi Co., Tokyo, Japan). LDL cholesterol was calculated according to Friedewald’s formula [total cholesterol (mg/dL)—HDL cholesterol (mg/dL)—total triglyceride (mg/dL)/5]. The coefficients of variation of total cholesterol, triglycerides, HDL cholesterol, fasting glucose, and hs-CRP were 2.0, 2.2, 2.6, 2.3, and 6.75 % (intra-assay) and 1.6, 2.6, 0.9, 1.6, and 7.91 % (inter-assay), respectively. Serum fasting insulin was measured by a chemiluminescent immunometric assay with ImmuliteÒ 2000 Insulin (Siemens Healthcare, Washington DC, WA, USA). The coefficients of variation for insulin were 3.7 % (intra-assay) and 8.1 % (inter-assay). Insulin resistance was estimated by homeostasis model assessment of insulin resistance (HOMA-IR) index [insulin (mIU/ml) 9 fasting blood glucose (mg/dL)/405].
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The serum and plasma were separated from samples of whole blood by centrifugation at 300 rpm for 5 min, and aliquots were stored at -80 °C until analysis. Subsequently, we used the samples together and determined the serum leptin, adiponectin, total osteocalcin (tOC), and ucOC levels. Serum leptin and adiponectin levels were measured with a Quantikine Human Leptin Immunoassay (R&D Systems, Inc., Minneapolis, MN, USA) and Human Adiponectin ELISA Kit (Life Technologies Corp., Darmstadt, Frankfrut, Germany). The coefficients of variation for leptin and adiponectin were 3.2 and 3.8 % (intra-assay), and 3.0 and 5.1 % (inter-assay), respectively. Serum tOC and ucOC levels were measured using N-MIDÒ Osteocalcin ELISA (Roche Diagnostic Products Corp., Indianapolis, IN, USA) and Human Undercarboxylated Osteocalcin ELISA Kits (Cusabio Biotech Co., Wuhan, Hubei, USA), respectively. The coefficients of variation for tOC and ucOC were 4.2 and B8.0 % (intra-assay), and 4.0 and B10 % (inter-assay), respectively. MetS was diagnosed, according to the Third Adult Treatment Panel (ATP III) criteria, based on C3 of the following five risk determinants: abdominal obesity (waist circumference [88 cm); increased serum triglycerides (C150 mg/dL); decreased HDL cholesterol (\50 mg/dL); increased fasting glucose (C110 mg/dL); and increased blood pressure (C130/85 mmHg) [2]. For assessment of abdominal obesity, waist circumference was replaced by increased WHR ([0.85) [12]. Statistical analysis Statistical analysis was performed using SPSS (version 15.0; SPSS Inc., Chicago, IL, USA). All data are described as mean ± standard deviation (SD) or numbers (%). Variables, such as WHR, blood pressure, fasting insulin, HOMA-IR, hs-CRP, and serum leptin and adiponectin, were logarithmically transformed prior to statistical analyses to approximate a normal distribution. Clinical, anthropometric, and laboratory characteristics were compared between the MetS and non-MetS groups using the t test or v2 test, or Fisher’s exact v2 test if the expected count was \5. The associations between MetS and serum tOC and ucOC levels were determined by analysis of covariance (ANCOVA). The correlations between the anthropometric profile, lipid profile, glucose and insulin levels, blood pressure, serum adipokine, and serum osteocalcin were examined using Pearson’s correlation test and partial coefficients of correlations. The distribution of osteocalcin levels according to the number of MetS components was evaluated using the Kruskal–Wallis test. The odds ratio (OR) for the presence of MetS according to the quartiles of serum osteocalcin level were evaluated using a binary logistic regression model. As variables are interrelated,
multiple regression analysis was performed to determine the most important explanatory variables for osteocalcin. The variables entered in the model were as follows: age; years since menopause; WHR; VFA; BFM; total cholesterol; total triglycerides; HDL cholesterol; LDL cholesterol; FPG; HOMA-IR; hs-CRP; systolic blood pressure (SBP); diastolic blood pressure (DBP); serum leptin and adiponectin; current smoking status; current alcohol consumption; treatment for hypertension; and lipid-lowering therapy. In all analyses, p value B0.05 was taken to indicate statistical significance.
Results The baseline characteristics of the women are presented in Table 1. The MetS and non-MetS groups consisted of 52 and 83 postmenopausal women, respectively. The prevalence of MetS was 38.5 %. Serum tOC and ucOC levels were 15.0 ± 6.0 and 5.1 ± 2.8 ng/mL, respectively, in the MetS group and 17.4 ± 6.5 and 6.5 ± 3.0 ng/mL, respectively, in the non-MetS group (p = 0.032, p = 0.009, respectively). Serum leptin and adiponectin levels were 11.0 ± 4.6 and 13.0 ± 5.9 ng/mL in the MetS group and 7.5 ± 4.3 and 24.4 ± 6.3 ng/mL in the non-MetS group. Serum adiponectin level was significantly higher, and the serum leptin level was significantly lower in the non-MetS group than the MetS group (all p \ 0.0001; Table 1). After adjusting for age and years since menopause, significant differences in tOC and ucOC were maintained between the two groups (p = 0.015 and p = 0.025, respectively; Fig. 1). Figure 2 shows serum tOC and ucOC levels according to the number of components of MetS. A significant decrease in ucOC level was observed with a greater number of MetS components (p = 0.042). A similar trend was observed with the tOC; however this did not reach statistical significance (p = 0.096). Serum tOC was negatively correlated with WHR, VFA, and hs-CRP (p \ 0.05). Serum ucOC was negatively correlated with VFA, BFM, FPG, SBP (p \ 0.05), PBF, fasting insulin, HOMA-IR, and serum leptin (p \ 0.01), and was positively correlated with serum adiponectin (p = 0.021). After adjusting for age and years since menopause, serum tOC was negatively correlated with WHR, fasting insulin, HOMA-IR, and hs-CRP (p \ 0.05). Serum ucOC was negatively correlated with WHR, VFA, BFM, triglyceride (p \ 0.05), PBF, fasting insulin, HOMA-IR, and serum leptin (p \ 0.01), and was positively correlated with SMM and serum adiponectin (p \ 0.05). However, neither tOC nor ucOC showed a significant correlation with BMI (p = 0.104 and p = 0.100; Table 2).
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Arch Gynecol Obstet Table 1 Clinical characteristics of postmenopausal women
Data are presented as the mean ± SD or number (%) FSH follicle-stimulating hormone, BMI body mass index, WHR waist-to-hip ratio, PBF percent body fat, VFA visceral fat area, BFM body fat mass, SMM skeletal muscle mass, HDL high-density lipoprotein, LDL low-density lipoprotein, FPG fasting plasma glucose, HOMA-IR homeostasis model assessment of insulin resistance, hs-CRP high-sensitivity C-reactive protein, SBP systolic blood pressure, DBP diastolic blood pressure, tOC total osteocalcin, ucOC undercarboxylated osteocalcin a
Values were analyzed after logarithmic transformation
Variables
Non-MetS (N = 83)
p
Age (year)
56.4 ± 5.7
54.6 ± 5.1
0.077
Years since menopause (year)
7.3 ± 5.2
6.5 ± 4.8
0.417
Height (cm)
155.2 ± 4.8
156.5 ± 5.2
0.148
Weight (kg)
61.5 ± 6.5
62.4 ± 6.3
0.899
FSH (mIU/mL)
52.3 ± 17.9
53.1 ± 16.2
0.822
Estradiol (pg/mL)
14.4 ± 6.1
19.9 ± 23.3
0.102
BMI (kg/m2)
25.5 ± 2.5
22.7 ± 2.5
\0.0001
WHRa
0.92 ± 0.04
0.87 ± 0.05
\0.0001
PBF (%)
37.0 ± 4.3
31.2 ± 5.6
\0.0001
VFA (cm2)
113.5 ± 17.3
90.1 ± 19.9
\0.0001 \0.0001
BFM (kg)
22.9 ± 4.5
17.5 ± 4.6
SMM (kg)
20.8 ± 2.2
20.7 ± 2.9
0.774
Total cholesterol (mg/dL)
205.0 ± 37.5
203.6 ± 36.9
0.826
Total triglycerides (mg/dL)
184.1 ± 63.7
84.7 ± 35.6
\0.0001
HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)
43.6 ± 10.4 124.6 ± 36.5
54.5 ± 12.6 131.4 ± 33.5
\0.0001 0.277
FPGa (mg/dL)
99.3 ± 18.7
92.3 ± 7.5
0.004
Fasting insulina (lIU/mL)
5.0 ± 5.26
2.99 ± 3.01
0.006
HOMA-IRa
1.26 ± 1.46
0.69 ± 0.69
0.003
hs-CRPa (mg/dL)
0.12 ± 0.11
0.09 ± 0.10
0.100
SBPa (mmHg)
131.5 ± 17.3
118.3 ± 12.9
\0.0001 \0.0001
a
DBP (mmHg)
82.9 ± 9.2
74.0 ± 9.4
Serum tOC (ng/mL)
15.0 ± 6.0
17.4 ± 6.5
0.032
Serum ucOC (ng/mL)
5.1 ± 2.8
6.5 ± 3.0
0.009
Serum adiponectina (ng/mL)
13.0 ± 5.9
24.4 ± 6.3
\0.0001
Serum leptina (ng/mL)
11.0 ± 4.6
7.5 ± 4.3
\0.0001
Current alcohol consumption (%)
8 (15.4)
16 (19.3)
0.648
Current smoking status (%)
2 (3.8)
1 (1.2)
0.559
Treatment for hypertension (%)
20 (38.5)
14 (16.9)
0.008
Lipid-lowering therapy
14 (26.9)
6 (7.2)
0.003
When participants were categorized into one of four groups by serum tOC and ucOC level quartiles, the prevalences of MetS were 51.5, 32.4, 44.1, and 26.5 % in the serum tOC and 57.6, 35.3, 35.3, and 26.5 % in the serum ucOC from lowest to highest groups. In binary logistic regression analyses, The OR for MetS was significantly lower in the highest quartile (Quartile 4) than the lowest quartile (Quartile 1) after adjusting for age, years since menopause, and BMI [OR 0.30, CI (0.08–0.94), p = 0.40; Table 3]. However, tOC showed no association in each group. Multiple regression analysis was performed to identify independent variables that affect serum ucOC level. Among the independent variables, serum leptin and HOMA-IR were the most important predictors of serum ucOC level (p = 0.008 and p = 0.046, respectively; Table 4). However, no independent variables were found to affect serum tOC level.
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MetS (N = 52)
Discussion In the present study, serum ucOC was negatively correlated with VFA, body fat, fasting insulin, HOMA-IR, hs-CRP, and serum leptin and positively correlated with serum adiponectin. Higher ucOC levels had lower OR for the presence of MetS. Serum leptin and HOMA-IR were independent predictors of serum ucOC. Osteocalcin is the most abundant non-collagenous bone matrix protein and a c-carboxyglutamate protein expressed by osteoblasts [13]. Although osteocalcin is well known as a marker of bone formation, the mechanism of bone metabolism has not yet been established. Osteocalcin has been suggested to act as a regulator of bone mineralization, osteoblasts, and osteoclast activity [14]. The c-carboxylation of osteocalcin confers the greater affinity for calcium and hydroxyapatite in the bone extracellular matrix, and
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Fig. 1 Mean total osteocalcin and undercarboxylated osteocalcin levels in metabolic syndrome and non-metabolic syndrome group. After adjustment for age and years since menopause, the difference of serum total osteocalcin and undercarboxylated osteocalcin between
two groups showed a statistical significance (p = 0.015 and p = 0.025, respectively). Statistical analyses by analysis of covariance (ANCOVA)
Fig. 2 Serum total and undercarboxylated osteocalcin levels in relation to the number of metabolic syndrome components. A significant decrease in undercarboxylated osteocalcin levels was observed with a higher number of metabolic syndrome components
(p = 0.042). A Similar trend was observed with the total osteocalcin but this did not reach statistical significance (p = 0.096). Statistical analyses by Kruskal–Wallis test
osteocalcin has either skeletal or non-skeletal effects depending on whether the carboxylation of osteocalcin [15]. Recent evidence from studies in experimental animals indicated that osteocalcin regulates glucose and fat metabolism and provided evidence of the crosstalk between bone and glucose metabolism. Lee et al. [9] showed that osteocalcin knockout mice (Ocn-/-) had increased serum
glucose and triglyceride levels, fat mass, and adipocyte number and decreased secretion of adiponectin, while the opposite results were observed in Esp knockout mice (Esp-/-); thus, osteocalcin induces the proliferation of pancreatic b cells and increases insulin and adiponectin secretion in adipocytes. Ferron et al. [16] reported that insulin signaling in osteoblasts reduces the expression of
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Arch Gynecol Obstet Table 2 Correlations between serum total osteocalcin and undercarboxylated osteocalcin, and anthropometric parameters, lipid profile, insulin sensitivity-related parameters, hs-CRP, blood pressure, and
serum adipokine (A1), and partial coefficients of correlations after adjustment for age and years since menopause (A2)
tOC
ucOC
tOC
ucOC
A1
A1
A2
A2
r
p
r
p
BMI (kg/cm2)
-0.128
0.069
-0.102
WHR
-0.184*
0.016
-0.134
VFA (cm2)
-0.159*
0.033
-0.142*
PBF (%)
-0.071
0.208
-0.219** *
r
p
r
p
0.121
-0.110
0.104
-0.112
0.100
0.061
-0.172*
0.024
-0.167*
0.028
0.049
-0.131
0.067
-0.215*
0.013
0.005
-0.061
0.243
-0.257**
0.003
*
0.012
0.147*
0.046
BFM (kg)
-0.096
0.133
-0.191
0.013
-0.083
0.173
SMM (kg)
-0.005
0.478
0.119
0.084
-0.038
0.334
TC (mg/dL)
-0.013
0.442
-0.030
0.365
-0.022
0.402
-0.038
0.333
TG (mg/dL)
-0.109
0.103
-0.140
0.053
-0.105
0.115
-0.169*
0.026
0.131
0.065
0.079
0.182
0.062
0.239
0.101
0.125
HDL-C (mg/dL) LDL-C (mg/dL)
-0.217
0.016
0.427
-0.036
0.340
0.003
0.486
-0.019
0.413
FPG (mg/dL) Insulin (lIU/mL)
-0.019 -0.137
0.416 0.056
-0.148* -0.273**
0.043 0.001
0.003 -0.166*
0.487 0.028
-0.106 -0.269**
0.114 0.001
HOMA-IR
-0.139
0.054
-0.256**
0.001
-0.161*
0.033
-0.274**
0.001
*
-0.172
0.023
-0.111
0.100
-0.173
0.024
-0.190*
0.015
SBP (mmHg)
0.033
0.353
-0.139*
0.043
0.040
0.323
-0.150
0.085
DBP (mmHg)
-0.015
0.436
-0.141
-0.171
0.043
0.311
0.176*
-0.117
0.088
-0.298**
hs-CRP (mg/dL)
Adiponectin (ng/mL) Leptin (ng/mL)
*
0.051
0.015
0.430
0.021
0.008
0.466
0.203*
\0.001
-0.075
0.197
-0.309**
0.050 0.020 \0.001
tOC total osteocalcin, ucOC undercarboxylated osteocalcin, BMI body mass index, WHR waist-to-hip ratio, VFA visceral fat area, PBF percent body fat, BFM body fat mass, SMM skeletal muscle mass, TC total cholesterol, TG total triglyceride, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, FPG fasting plasma glucose, HOMA-IR homeostasis model assessment of insulin resistance, hs-CRP high-sensitivity C-reactive protein, SBP systolic blood pressure, DBP diastolic blood pressure * p \ 0.05, ** p \ 0.01
Table 3 Association of serum total and undercarboxylated osteocalcin with the presence of metabolic syndrome: logistic regression analyses were performed to determine the odds ratios (ORs) of Parameters
metabolic syndrome with regard to total and undercarboxylated osteocalcin quartiles after adjustment for age, years since menopause, and body mass index
Odds ratio (95 % confidence interval), p value Quartile 1 (n = 33)
Quartile 2 (n = 34)
Quartile 3 (n = 34)
Quartile 4 (n = 34)
Total osteocalcin (ng/mL)
B11.84
11.90–15.06
15.38–19.41
C19.43
Unadjusted
1
0.46 (0.17–1.26), 0.131
0.75 (0.26–2.15), 0.595
0.34 (0.12–0.94), 0.038
Age, years since menopause, and BMI adjusted
1
0.74 (0.23–2.37), 0.614
1.43 (0.41–5.01), 0.572
0.47 (0.15–1.48), 0.196
Undercarboxylated osteocalcin (ng/mL)
B3.75
3.77–5.83
5.85–7.54
C7.68
Unadjusted
1
0.66 (0.23–1.86), 0.432
0.66 (0.23–1.86), 0.432
0.27 (0.01–0.74), 0.011
Age, years since menopause, and BMI adjusted
1
0.79 (0.23–2.66), 0.699
0.48 (0.14–1.58), 0.227
0.30 (0.09–0.98), 0.046
BMI body mass index
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Arch Gynecol Obstet Table 4 Multiple regression analysis with serum undercarboxylated osteocalcin as dependent variables Variables
B
Standard error
Standardized b
p
Leptin
-2.320
0.907
-0.230
0.008
HOMA-IR
-0.904
0.454
-0.179
0.046
HOMA-IR homeostasis model assessment of insulin resistance
osteoprotegerin, a negative regulator of osteoclast function, and promotes the ability of osteoclasts to acidify the bone extracellular matrix. An acid pH in the bone extracellular cellular matrix can enhance decarboxylation of osteocalcin and ucOC that promotes glucose metabolism. Fluzele et al. [17] reported that insulin receptors in osteoblasts control osteoblast development and ucOC, and mice lacking insulin receptors in osteoblast have low levels of ucOC, decreased bone formation, and increased peripheral adiposity, glucose intolerance, and insulin resistance. Leptin upregulates the sympathetic nervous system and activated sympathetic tone increases expression of the Esp gene in osteoblasts via ß2 adrenergic receptors. Increased Esp gene expression inactivates the bioactivity of ucOC and decreases insulin expression and secretion in pancreatic ß cells. Therefore, hyperleptinemia is associated with insulin resistance via inhibition of osteocalcin expression [10]. According to these studies, hyperleptinemia is associated with MetS, and leptin and osteocalcin exert opposite effects on insulin secretion. Briefly, insulin signaling promotes the differentiation of osteoblasts via insulin receptors in osteoblasts, enhanced osteoclast activity promotes decarboxylation of osteocalcin, and increased ucOC enhances insulin secretion and sensitivity. However, leptin inhibits activation of osteocalcin via enhanced sympathetic tone. These complex mechanisms indicate the existence of a bone-fat-pancreas endocrine loop, and bone and energy metabolism exert reciprocal regulation [18]. Several studies reported differences in serum osteocalcin level according to MetS. Serum osteocalcin levels were significantly lower in the MetS group than the non-MetS group in postmenopausal Korean and Chinese women [19, 20]. However, Liu et al. reported that serum ucOC level increased with MetS in middle-aged women in contrast to carboxylated osteocalcin (8.1 ± 7.2 vs. 5.9 ± 4.6 ng/ml, p = 0.036). They hypothesized that hyperinsulinemia secondary to insulin resistance underlies most of the metabolic derangement in MetS, and that higher serum ucOC can enhance the synthesis and secretion of insulin, which in part contributes to hyperinsulinemia, and increased insulin receptor signaling in osteoblasts leads to accelerated osteocalcin decarboxylation. However, the limitation of this study was the small sample size [21]. The
results of the present study were consistent with those of previous investigations in postmenopausal Korean and Chinese women. Several studies have indicated the inverse association between metabolic risks, including markers of insulin resistance, proinflammatory cytokines, leptin, and osteocalcin in postmenopausal women [22–24]. However, there is still debate regarding the associations between fat mass, central obesity, and osteocalcin. Yang et al. [20] reported that the OR for central obesity was significantly lower in the highest quartile compared to the lowest quartile of osteocalcin level (p \ 0.01). Movahed et al. [25] reported that lower serum osteocalcin was inversely associated with waist circumference [OR 2.53; CI (1.13–5.67), p = 0.024]. However, Kanazawa et al. [26] reported that although ucOC was negatively correlated with %fat, %trunk, and visceral fat area in postmenopausal women, they found no significant association in multiple regression analysis. Our study showed that ucOC was negatively correlated with markers of central obesity, including WHR and VFA, body fat mass, as well as HOMA-IR, hs-CRP, and leptin. However, there was no significant correlation between ucOC and BMI. It is well known that visceral fat is a strong predictor of insulin resistance and abdominal obesity, and insulin resistance is a risk factor for cardiovascular disease (CVD) [27]. Although the prevalence of MetS increases with age and BMI, MetS can be present in lean individuals; in addition, a proportion of obese subjects does not have MetS [28]. Several studies have focused on the association between MetS and osteocalcin in postmenopausal women. Saleem et al. [22] reported that the ORs for MetS were 0.33 in black and 0.43 in Hispanic white women in the highest quartile of osteocalcin level (p \ 0.001). In a study of Korean postmenopausal women, the OR for MetS was 5.25 in the lowest quartile of osteocalcin level (p \ 0.001) [19]. Yang et al. [20] reported that postmenopausal women with the highest osteocalcin levels had lower OR for MetS (OR = 0.123, p \ 0.01). In these previous studies, the association between MetS and osteocalcin was limited to tOC rather ucOC. Our study showed that ucOC is inversely associated with the presence of MetS. Previous animal experiments have shown that ucOC rather than cOC is mainly involved in the regulation of glucose and fat metabolism. Although our results were consistent with previous findings, we failed to search for the studies focusing on the association between ucOC and glucose and fat metabolism in postmenopausal women. We measured both ucOC and tOC to evaluate the association between osteocalcin and MetS. This study had several limitations. First, due to its crosssectional design, we failed to determine the cause and effect relationship between ucOC and MetS. Second, serum
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osteocalcin may be influenced by physical activity and dietary habits. We did not include physical activity and dietary habits in our analysis but excluded subjects who were dieting and exercising for weight control. We included all subjects engaged in moderate physical activity. Third, for the diagnostic criteria of MetS, the WHR was substituted for waist circumference. The waist circumference and the WHR were both used as measures of abdominal obesity; indeed, a previous case–control study indicated that WHR is a risk factor for CVD [29]. A number of questions remain to be resolved. First, the presence of osteocalcin receptors in pancreatic b cells and adipocytes and the definitive action of osteocalcin in humans have yet to be clarified. Second, factors that influence the osteocalcin level, including vitamin K agents, hormone therapy, and agents for promoting bone formation, such as bisphosphonates and teriparatide, may affect the prevalence of MetS.
Conclusion The increase in prevalence of MetS in postmenopausal women may increase the risk of CVD, and the prevention and treatment of MetS are important. Further large-scale clinical and experimental studies are required to clarify the potential of ucOC as a predictor of MetS and treatment of diabetes mellitus. Conflict of interest The authors have stated explicitly that there are no conflicts of interest in connection with this article.
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8. Hauschka PV, Lian JB, Cole DE, Gundberg CM (1989) Osteocalcin and matrix Gla protein: vitamin K-dependent proteins in bone. Physiol Rev 69(3):990–1047 9. Lee NK, Sowa H, Hinoi E, Ferron M, Ahn JD, Confavreux C, Dacquin R, Mee PJ, McKee MD, Jung DY, Zhang Z, Kim JK, Mauvais-Jarvis F, Ducy P, Karsenty G (2007) Endocrine regulation of energy metabolism by the skeleton. Cell 130(3): 456–469 10. Hinoi E, Gao N, Jung DY, Yadav V, Yoshizawa T, Myers MG Jr, Chua SC Jr, Kim JK, Kaestner KH, Karsenty G (2008) The sympathetic tone mediates leptin’s inhibition of insulin secretion by modulating osteocalcin bioactivity. J Cell Biol 183(7): 1235–1242 11. Clemens TL, Karsenty G (2011) The osteoblast: an insulin target cell controlling glucose homeostasis. J Bone Miner Res 26(4):677–680 12. Alberti KG, Zimmet PZ (1998) Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 15(7):539–553 13. Wolf G (1996) Function of the bone protein osteocalcin: definitive evidence. Nutr Rev 54(10):332–333 14. Ducy P, Desbois C, Boyce B, Pinero G, Story B, Dunstan C, Smith E, Bonadio J, Goldstein S, Gundberg C, Bradley A, Karsenty G (1996) Increased bone formation in osteocalcindeficient mice. Nature 382(6590):448–452 15. Neve A, Corrado A, Cantatore FP (2013) Osteocalcin: skeletal and extra-skeletal effects. J Cell Physiol 228(6):1149–1153 16. Ferron M, Wei J, Yoshizawa T, Del Fattore A, DePinho RA, Teti A, Ducy P, Karsenty G (2010) Insulin signaling in osteoblasts integrates bone remodeling and energy metabolism. Cell 142(2):296–308 17. Fulzele K, Riddle RC, DiGirolamo DJ, Cao X, Wan C, Chen D, Faugere MC, Aja S, Hussain MA, Bruning JC, Clemens TL (2010) Insulin receptor signaling in osteoblasts regulates postnatal bone acquisition and body composition. Cell 142(2): 309–319 18. Ducy P (2011) The role of osteocalcin in the endocrine cross-talk between bone remodelling and energy metabolism. Diabetologia 54(6):1291–1297 19. Bae SJ, Choe JW, Chung YE, Kim BJ, Lee SH, Kim HY, Koh JM, Kim HK, Kim GS (2011) The association between serum osteocalcin levels and metabolic syndrome in Koreans. Osteoporos Int 22(11):2837–2846 20. Yang R, Ma X, Pan X, Wang F, Luo Y, Gu C, Bao Y, Jia W (2013) Serum osteocalcin levels in relation to metabolic syndrome in Chinese postmenopausal women. Menopause 20(5): 548–553 21. Liu JJ, Toy WC, Wong MD, Tan CS, Tavintharan S, Wong MS, Sum CF, Lim SC (2013) Elevated undercarboxylated and reduced carboxylated osteocalcin are associated with metabolic syndrome in middle age Asian females. Exp Clin Endocrinol Diabetes 121(6):329–333 22. Saleem U, Mosley TH Jr, Kullo IJ (2010) Serum osteocalcin is associated with measures of insulin resistance, adipokine levels, and the presence of metabolic syndrome. Arterioscler Thromb Vasc Biol 30(7):1474–1478 23. Lu C, Ivaska KK, Alen M, Wang Q, Tormakangas T, Xu L, Wiklund P, Mikkola TM, Pekkala S, Tian H, Vaananen HK, Cheng S (2012) Serum osteocalcin is not associated with glucose but is inversely associated with leptin across generations of nondiabetic women. J Clin Endocrinol Metab 97(11):4106–4114 24. Chen L, Li Q, Yang Z, Ye Z, Huang Y, He M, Wen J, Wang X, Lu B, Hu J, Liu C, Ling C, Qu S, Hu R (2013) Osteocalcin, glucose metabolism, lipid profile and chronic low-grade
Arch Gynecol Obstet inflammation in middle-aged and elderly Chinese. Diabet Med 30(3):309–317 25. Movahed A, Larijani B, Nabipour I, Kalantarhormozi M, Asadipooya K, Vahdat K, Akbarzadeh S, Farrokhnia M, Assadi M, Amirinejad R, Bargahi A, Sanjdideh Z (2012) Reduced serum osteocalcin concentrations are associated with type 2 diabetes mellitus and the metabolic syndrome components in postmenopausal women: the crosstalk between bone and energy metabolism. J Bone Miner Metab 30(6):683–691 26. Kanazawa I, Yamaguchi T, Yamauchi M, Yamamoto M, Kurioka S, Yano S, Sugimoto T (2011) Serum undercarboxylated osteocalcin was inversely associated with plasma glucose level and fat mass in type 2 diabetes mellitus. Osteoporos Int 22(1):187–194 27. Usui C, Asaka M, Kawano H, Aoyama T, Ishijima T, Sakamoto S, Higuchi M (2010) Visceral fat is a strong predictor of insulin
resistance regardless of cardiorespiratory fitness in non-diabetic people. J Nutr Sci Vitaminol (Tokyo) 56(2):109–116 28. Hanley AJ, Karter AJ, Festa A, D’Agostino R Jr, Wagenknecht LE, Savage P, Tracy RP, Saad MF, Haffner S (2002) Factor analysis of metabolic syndrome using directly measured insulin sensitivity: the Insulin Resistance Atherosclerosis Study. Diabetes 51(8):2642–2647 29. Czernichow S, Kengne AP, Huxley RR, Batty GD, de Galan B, Grobbee D, Pillai A, Zoungas S, Marre M, Woodward M, Neal B, Chalmers J (2011) Comparison of waist-to-hip ratio and other obesity indices as predictors of cardiovascular disease risk in people with type-2 diabetes: a prospective cohort study from ADVANCE. Eur J Cardiovasc Prev Rehabil 18(2):312–319
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GYNECOLOGIC ENDOCRINOLOGY AND REPRODUCTIVE MEDICINE
Association between osteocalcin and metabolic syndrome in postmenopausal women Suk Woo Lee • Hyun Hee Jo • Mee Ran Kim Jang Heub Kim • Young Oak You
•
Received: 10 March 2014 / Accepted: 6 February 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Objectives Undercarboxylated osteocalcin (ucOC) has been proved as a regulator of glucose and fat mass in an animal model. This study examined the association between osteocalcin and metabolic syndrome (MetS) in postmenopausal women. Methods We selected 135 postmenopausal women and determined anthropometric values [waist-hip ratio (WHR), visceral fat area (VFA), body fat mass (BFM), and skeletal muscle mass (SMM)], the lipid profile, fasting plasma glucose (FPG), insulin, high-sensitivity C-reactive protein (hs-CRP), homeostasis model assessment of insulin resistance (HOMA-IR), serum leptin and adiponectin level, and serum tOC and ucOC level. Results There were 52 postmenopausal women in the MetS group. After adjusting for age and years since menopause, ucOC was negatively correlated with WHR, VFA, BFM, triglyceride, fasting insulin, HOMA-IR, and serum leptin and was positively correlated with serum S. W. Lee Department of Obstetrics and Gynecology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, 22, Gwanpyeong-ro 170beon-gil, Dongan-gu, Anyang-si, Gyeonggi-do 431-796, Korea e-mail: [email protected] H. H. Jo M. R. Kim J. H. Kim Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul St. Mary’s Hospital, 222 Banpo-daero, Seocho-gu, Seoul 137-701, Korea Y. O. You (&) Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, St. Vincent Hospital, 93 Jungbu-daero, Ji-dong, Paldal-gu, Suwon, Gyeonggi-do 442-723, Korea e-mail: [email protected]
adiponectin. The odds ratio for MetS was significantly lower in the highest quartile than the lowest quartile after adjusting for age, years since menopause, and BMI. In multiple regression analysis, serum leptin and HOMA-IR were the most important predictors of the independent variables that affect serum ucOC. Conclusion ucOC showed an inverse correlation with markers of insulin resistance, central obesity, and the presence of MetS in postmenopausal women and appears to protect against MetS. Further large-scale clinical and experimental studies are needed to clarify the potential of ucOC as a predictor of MetS in postmenopausal women. Keywords Adipokine Insulin resistance Metabolic syndrome Osteocalcin Postmenopause
Introduction Bone is an active organ that continuously undergoes remodeling involving bone resorption and formation, and bone mass is maintained by the balance between these two processes. Increase in bone resorption and decrease in bone formation due to estrogen deficiency are associated with increased prevalence of osteoporosis in postmenopausal women [1]. Metabolic syndrome (MetS) is defined as a cluster of metabolic risk factors, including abdominal obesity, atherogenic dyslipidemia, elevated blood pressure, insulin resistance, and increased levels of proinflammatory cytokines, including IL-1, IL-6, and TNF-a [2]. Weight gain, increases in abdominal fat, and dyslipidemia are common during menopause, and large amounts of abdominal fat are associated with increased risk of insulin resistance and MetS [3].
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Leptin and adiponectin, representative adipokines secreted by adipocytes, play opposite roles in MetS. Leptin is positively correlated with central obesity, stimulates proinflammatory cytokines, and contributes to an increase in insulin resistance [4, 5]. Adiponectin increases insulin sensitivity by increasing fatty acid oxidation and glucose uptake in muscle and antiatherogenic action by inhibiting infiltration of monocytes and foam cell formation in endothelial cells. Leptin and adiponectin are also well known to affect bone formation and resorption, either directly or indirectly. Previous studies have indicated that bone and adipose tissue act as endocrine organs that modulate energy metabolism [6]. Osteocalcin is a vitamin K-dependent protein produced mainly by osteoblasts and is used as a biochemical marker for bone formation [7]. Osteocalcin is c-carboxylated by vitamin K. Carboxylated osteocalcin (cOC) has high affinity for calcium and hydroxyapatite in the bone matrix while undercarboxylated osteocalcin (ucOC) has been shown to act as a hormone in the body, causing beta cells in the pancreas to release more insulin and increase insulin sensitivity in both fat and muscle [8, 9]. ucOC also stimulates adiponectin in adipocytes, and leptin inhibits the activity of osteocalcin, thus enhancing insulin resistance [10]. Taken together, these studies support a regulatory role for bone in glucose and fat metabolism, which appears to be mediated by ucOC [11]. Although there have been several clinical studies of the association between fat and glucose metabolism, MetS, and osteocalcin in both sexes, and there is interest in the increasing incidence of MetS in postmenopausal women, no definitive conclusions regarding the association between osteocalcin and MetS in postmenopausal women have yet been reached. The present study was performed to examine the association between osteocalcin and MetS in postmenopausal women.
Materials and methods Participants Between September 2009 and August 2010, a total of 194 postmenopausal women who were cared for at Saint Vincent’s Hospital were recruited. This prospective and cross-sectional study was approved by the Institutional Review Board of The Catholic University of Korea and informed consent was obtained from each participant. The exclusion criteria were as follows: current cancer; laboratory evidence of kidney, liver, or thyroid disease; diabetes; bone-altering conditions (bilateral oophorectomy, hyperparathyroidism, nephrolithiasis, renal disease,
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or therapy with biphosphonates, calcitonin, estrogen, steroids, tamoxifen, or chemotherapy in the past year); use of anti-obesity agents or non-compliance with diet and behavioral therapy for weight control. Postmenopausal women had at least 12 consecutive months of amenorrhea with no other medical cause for amenorrhea and a follicle-stimulating hormone level [40 mIU/mL at the time of enrollment. After the application of exclusion criteria, 135 women were enrolled in the present study. Clinical and anthropometric data Data on age, years since menopause, health behaviors, including smoking and alcohol consumption, and personal history of diabetes and hypertension were provided by the participants through questionnaires. Alcohol consumers were defined as those with at least weekly consumption of alcohol. Subjects were classified as having a smoking habit if they smoked at the time of the study. Body size and composition were measured by bioelectrical impedance analysis (BIA) using a body composition analyzer (Inbody 720, Biospace Inc., Seoul, Korea). The data collected included waist–hip ratio (WHR), visceral fat area (VFA), skeletal muscle mass (SMM), percent body fat (PBF), and body fat mass (BFM). The degree of accuracy of body size and composition measurements had a 1.0 % coefficient of variation. Blood pressure was measured twice with a mercury sphygmomanometer after a 10-min seated rest, and the average of the two measurements was used for statistical analysis. Biochemical analyses Blood was collected by venipuncture after an overnight fast, and the total cholesterol, triglycerides, HDL cholesterol, fasting plasma glucose (FPG), and high-sensitivity C-reactive protein (hs-CRP) levels were measured using a Hitachi 7600-110Ò Automatic Analyzer (Hitachi Co., Tokyo, Japan). LDL cholesterol was calculated according to Friedewald’s formula [total cholesterol (mg/dL)—HDL cholesterol (mg/dL)—total triglyceride (mg/dL)/5]. The coefficients of variation of total cholesterol, triglycerides, HDL cholesterol, fasting glucose, and hs-CRP were 2.0, 2.2, 2.6, 2.3, and 6.75 % (intra-assay) and 1.6, 2.6, 0.9, 1.6, and 7.91 % (inter-assay), respectively. Serum fasting insulin was measured by a chemiluminescent immunometric assay with ImmuliteÒ 2000 Insulin (Siemens Healthcare, Washington DC, WA, USA). The coefficients of variation for insulin were 3.7 % (intra-assay) and 8.1 % (inter-assay). Insulin resistance was estimated by homeostasis model assessment of insulin resistance (HOMA-IR) index [insulin (mIU/ml) 9 fasting blood glucose (mg/dL)/405].
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The serum and plasma were separated from samples of whole blood by centrifugation at 300 rpm for 5 min, and aliquots were stored at -80 °C until analysis. Subsequently, we used the samples together and determined the serum leptin, adiponectin, total osteocalcin (tOC), and ucOC levels. Serum leptin and adiponectin levels were measured with a Quantikine Human Leptin Immunoassay (R&D Systems, Inc., Minneapolis, MN, USA) and Human Adiponectin ELISA Kit (Life Technologies Corp., Darmstadt, Frankfrut, Germany). The coefficients of variation for leptin and adiponectin were 3.2 and 3.8 % (intra-assay), and 3.0 and 5.1 % (inter-assay), respectively. Serum tOC and ucOC levels were measured using N-MIDÒ Osteocalcin ELISA (Roche Diagnostic Products Corp., Indianapolis, IN, USA) and Human Undercarboxylated Osteocalcin ELISA Kits (Cusabio Biotech Co., Wuhan, Hubei, USA), respectively. The coefficients of variation for tOC and ucOC were 4.2 and B8.0 % (intra-assay), and 4.0 and B10 % (inter-assay), respectively. MetS was diagnosed, according to the Third Adult Treatment Panel (ATP III) criteria, based on C3 of the following five risk determinants: abdominal obesity (waist circumference [88 cm); increased serum triglycerides (C150 mg/dL); decreased HDL cholesterol (\50 mg/dL); increased fasting glucose (C110 mg/dL); and increased blood pressure (C130/85 mmHg) [2]. For assessment of abdominal obesity, waist circumference was replaced by increased WHR ([0.85) [12]. Statistical analysis Statistical analysis was performed using SPSS (version 15.0; SPSS Inc., Chicago, IL, USA). All data are described as mean ± standard deviation (SD) or numbers (%). Variables, such as WHR, blood pressure, fasting insulin, HOMA-IR, hs-CRP, and serum leptin and adiponectin, were logarithmically transformed prior to statistical analyses to approximate a normal distribution. Clinical, anthropometric, and laboratory characteristics were compared between the MetS and non-MetS groups using the t test or v2 test, or Fisher’s exact v2 test if the expected count was \5. The associations between MetS and serum tOC and ucOC levels were determined by analysis of covariance (ANCOVA). The correlations between the anthropometric profile, lipid profile, glucose and insulin levels, blood pressure, serum adipokine, and serum osteocalcin were examined using Pearson’s correlation test and partial coefficients of correlations. The distribution of osteocalcin levels according to the number of MetS components was evaluated using the Kruskal–Wallis test. The odds ratio (OR) for the presence of MetS according to the quartiles of serum osteocalcin level were evaluated using a binary logistic regression model. As variables are interrelated,
multiple regression analysis was performed to determine the most important explanatory variables for osteocalcin. The variables entered in the model were as follows: age; years since menopause; WHR; VFA; BFM; total cholesterol; total triglycerides; HDL cholesterol; LDL cholesterol; FPG; HOMA-IR; hs-CRP; systolic blood pressure (SBP); diastolic blood pressure (DBP); serum leptin and adiponectin; current smoking status; current alcohol consumption; treatment for hypertension; and lipid-lowering therapy. In all analyses, p value B0.05 was taken to indicate statistical significance.
Results The baseline characteristics of the women are presented in Table 1. The MetS and non-MetS groups consisted of 52 and 83 postmenopausal women, respectively. The prevalence of MetS was 38.5 %. Serum tOC and ucOC levels were 15.0 ± 6.0 and 5.1 ± 2.8 ng/mL, respectively, in the MetS group and 17.4 ± 6.5 and 6.5 ± 3.0 ng/mL, respectively, in the non-MetS group (p = 0.032, p = 0.009, respectively). Serum leptin and adiponectin levels were 11.0 ± 4.6 and 13.0 ± 5.9 ng/mL in the MetS group and 7.5 ± 4.3 and 24.4 ± 6.3 ng/mL in the non-MetS group. Serum adiponectin level was significantly higher, and the serum leptin level was significantly lower in the non-MetS group than the MetS group (all p \ 0.0001; Table 1). After adjusting for age and years since menopause, significant differences in tOC and ucOC were maintained between the two groups (p = 0.015 and p = 0.025, respectively; Fig. 1). Figure 2 shows serum tOC and ucOC levels according to the number of components of MetS. A significant decrease in ucOC level was observed with a greater number of MetS components (p = 0.042). A similar trend was observed with the tOC; however this did not reach statistical significance (p = 0.096). Serum tOC was negatively correlated with WHR, VFA, and hs-CRP (p \ 0.05). Serum ucOC was negatively correlated with VFA, BFM, FPG, SBP (p \ 0.05), PBF, fasting insulin, HOMA-IR, and serum leptin (p \ 0.01), and was positively correlated with serum adiponectin (p = 0.021). After adjusting for age and years since menopause, serum tOC was negatively correlated with WHR, fasting insulin, HOMA-IR, and hs-CRP (p \ 0.05). Serum ucOC was negatively correlated with WHR, VFA, BFM, triglyceride (p \ 0.05), PBF, fasting insulin, HOMA-IR, and serum leptin (p \ 0.01), and was positively correlated with SMM and serum adiponectin (p \ 0.05). However, neither tOC nor ucOC showed a significant correlation with BMI (p = 0.104 and p = 0.100; Table 2).
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Arch Gynecol Obstet Table 1 Clinical characteristics of postmenopausal women
Data are presented as the mean ± SD or number (%) FSH follicle-stimulating hormone, BMI body mass index, WHR waist-to-hip ratio, PBF percent body fat, VFA visceral fat area, BFM body fat mass, SMM skeletal muscle mass, HDL high-density lipoprotein, LDL low-density lipoprotein, FPG fasting plasma glucose, HOMA-IR homeostasis model assessment of insulin resistance, hs-CRP high-sensitivity C-reactive protein, SBP systolic blood pressure, DBP diastolic blood pressure, tOC total osteocalcin, ucOC undercarboxylated osteocalcin a
Values were analyzed after logarithmic transformation
Variables
Non-MetS (N = 83)
p
Age (year)
56.4 ± 5.7
54.6 ± 5.1
0.077
Years since menopause (year)
7.3 ± 5.2
6.5 ± 4.8
0.417
Height (cm)
155.2 ± 4.8
156.5 ± 5.2
0.148
Weight (kg)
61.5 ± 6.5
62.4 ± 6.3
0.899
FSH (mIU/mL)
52.3 ± 17.9
53.1 ± 16.2
0.822
Estradiol (pg/mL)
14.4 ± 6.1
19.9 ± 23.3
0.102
BMI (kg/m2)
25.5 ± 2.5
22.7 ± 2.5
\0.0001
WHRa
0.92 ± 0.04
0.87 ± 0.05
\0.0001
PBF (%)
37.0 ± 4.3
31.2 ± 5.6
\0.0001
VFA (cm2)
113.5 ± 17.3
90.1 ± 19.9
\0.0001 \0.0001
BFM (kg)
22.9 ± 4.5
17.5 ± 4.6
SMM (kg)
20.8 ± 2.2
20.7 ± 2.9
0.774
Total cholesterol (mg/dL)
205.0 ± 37.5
203.6 ± 36.9
0.826
Total triglycerides (mg/dL)
184.1 ± 63.7
84.7 ± 35.6
\0.0001
HDL cholesterol (mg/dL) LDL cholesterol (mg/dL)
43.6 ± 10.4 124.6 ± 36.5
54.5 ± 12.6 131.4 ± 33.5
\0.0001 0.277
FPGa (mg/dL)
99.3 ± 18.7
92.3 ± 7.5
0.004
Fasting insulina (lIU/mL)
5.0 ± 5.26
2.99 ± 3.01
0.006
HOMA-IRa
1.26 ± 1.46
0.69 ± 0.69
0.003
hs-CRPa (mg/dL)
0.12 ± 0.11
0.09 ± 0.10
0.100
SBPa (mmHg)
131.5 ± 17.3
118.3 ± 12.9
\0.0001 \0.0001
a
DBP (mmHg)
82.9 ± 9.2
74.0 ± 9.4
Serum tOC (ng/mL)
15.0 ± 6.0
17.4 ± 6.5
0.032
Serum ucOC (ng/mL)
5.1 ± 2.8
6.5 ± 3.0
0.009
Serum adiponectina (ng/mL)
13.0 ± 5.9
24.4 ± 6.3
\0.0001
Serum leptina (ng/mL)
11.0 ± 4.6
7.5 ± 4.3
\0.0001
Current alcohol consumption (%)
8 (15.4)
16 (19.3)
0.648
Current smoking status (%)
2 (3.8)
1 (1.2)
0.559
Treatment for hypertension (%)
20 (38.5)
14 (16.9)
0.008
Lipid-lowering therapy
14 (26.9)
6 (7.2)
0.003
When participants were categorized into one of four groups by serum tOC and ucOC level quartiles, the prevalences of MetS were 51.5, 32.4, 44.1, and 26.5 % in the serum tOC and 57.6, 35.3, 35.3, and 26.5 % in the serum ucOC from lowest to highest groups. In binary logistic regression analyses, The OR for MetS was significantly lower in the highest quartile (Quartile 4) than the lowest quartile (Quartile 1) after adjusting for age, years since menopause, and BMI [OR 0.30, CI (0.08–0.94), p = 0.40; Table 3]. However, tOC showed no association in each group. Multiple regression analysis was performed to identify independent variables that affect serum ucOC level. Among the independent variables, serum leptin and HOMA-IR were the most important predictors of serum ucOC level (p = 0.008 and p = 0.046, respectively; Table 4). However, no independent variables were found to affect serum tOC level.
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MetS (N = 52)
Discussion In the present study, serum ucOC was negatively correlated with VFA, body fat, fasting insulin, HOMA-IR, hs-CRP, and serum leptin and positively correlated with serum adiponectin. Higher ucOC levels had lower OR for the presence of MetS. Serum leptin and HOMA-IR were independent predictors of serum ucOC. Osteocalcin is the most abundant non-collagenous bone matrix protein and a c-carboxyglutamate protein expressed by osteoblasts [13]. Although osteocalcin is well known as a marker of bone formation, the mechanism of bone metabolism has not yet been established. Osteocalcin has been suggested to act as a regulator of bone mineralization, osteoblasts, and osteoclast activity [14]. The c-carboxylation of osteocalcin confers the greater affinity for calcium and hydroxyapatite in the bone extracellular matrix, and
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Fig. 1 Mean total osteocalcin and undercarboxylated osteocalcin levels in metabolic syndrome and non-metabolic syndrome group. After adjustment for age and years since menopause, the difference of serum total osteocalcin and undercarboxylated osteocalcin between
two groups showed a statistical significance (p = 0.015 and p = 0.025, respectively). Statistical analyses by analysis of covariance (ANCOVA)
Fig. 2 Serum total and undercarboxylated osteocalcin levels in relation to the number of metabolic syndrome components. A significant decrease in undercarboxylated osteocalcin levels was observed with a higher number of metabolic syndrome components
(p = 0.042). A Similar trend was observed with the total osteocalcin but this did not reach statistical significance (p = 0.096). Statistical analyses by Kruskal–Wallis test
osteocalcin has either skeletal or non-skeletal effects depending on whether the carboxylation of osteocalcin [15]. Recent evidence from studies in experimental animals indicated that osteocalcin regulates glucose and fat metabolism and provided evidence of the crosstalk between bone and glucose metabolism. Lee et al. [9] showed that osteocalcin knockout mice (Ocn-/-) had increased serum
glucose and triglyceride levels, fat mass, and adipocyte number and decreased secretion of adiponectin, while the opposite results were observed in Esp knockout mice (Esp-/-); thus, osteocalcin induces the proliferation of pancreatic b cells and increases insulin and adiponectin secretion in adipocytes. Ferron et al. [16] reported that insulin signaling in osteoblasts reduces the expression of
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Arch Gynecol Obstet Table 2 Correlations between serum total osteocalcin and undercarboxylated osteocalcin, and anthropometric parameters, lipid profile, insulin sensitivity-related parameters, hs-CRP, blood pressure, and
serum adipokine (A1), and partial coefficients of correlations after adjustment for age and years since menopause (A2)
tOC
ucOC
tOC
ucOC
A1
A1
A2
A2
r
p
r
p
BMI (kg/cm2)
-0.128
0.069
-0.102
WHR
-0.184*
0.016
-0.134
VFA (cm2)
-0.159*
0.033
-0.142*
PBF (%)
-0.071
0.208
-0.219** *
r
p
r
p
0.121
-0.110
0.104
-0.112
0.100
0.061
-0.172*
0.024
-0.167*
0.028
0.049
-0.131
0.067
-0.215*
0.013
0.005
-0.061
0.243
-0.257**
0.003
*
0.012
0.147*
0.046
BFM (kg)
-0.096
0.133
-0.191
0.013
-0.083
0.173
SMM (kg)
-0.005
0.478
0.119
0.084
-0.038
0.334
TC (mg/dL)
-0.013
0.442
-0.030
0.365
-0.022
0.402
-0.038
0.333
TG (mg/dL)
-0.109
0.103
-0.140
0.053
-0.105
0.115
-0.169*
0.026
0.131
0.065
0.079
0.182
0.062
0.239
0.101
0.125
HDL-C (mg/dL) LDL-C (mg/dL)
-0.217
0.016
0.427
-0.036
0.340
0.003
0.486
-0.019
0.413
FPG (mg/dL) Insulin (lIU/mL)
-0.019 -0.137
0.416 0.056
-0.148* -0.273**
0.043 0.001
0.003 -0.166*
0.487 0.028
-0.106 -0.269**
0.114 0.001
HOMA-IR
-0.139
0.054
-0.256**
0.001
-0.161*
0.033
-0.274**
0.001
*
-0.172
0.023
-0.111
0.100
-0.173
0.024
-0.190*
0.015
SBP (mmHg)
0.033
0.353
-0.139*
0.043
0.040
0.323
-0.150
0.085
DBP (mmHg)
-0.015
0.436
-0.141
-0.171
0.043
0.311
0.176*
-0.117
0.088
-0.298**
hs-CRP (mg/dL)
Adiponectin (ng/mL) Leptin (ng/mL)
*
0.051
0.015
0.430
0.021
0.008
0.466
0.203*
\0.001
-0.075
0.197
-0.309**
0.050 0.020 \0.001
tOC total osteocalcin, ucOC undercarboxylated osteocalcin, BMI body mass index, WHR waist-to-hip ratio, VFA visceral fat area, PBF percent body fat, BFM body fat mass, SMM skeletal muscle mass, TC total cholesterol, TG total triglyceride, HDL-C high-density lipoprotein cholesterol, LDL-C low-density lipoprotein cholesterol, FPG fasting plasma glucose, HOMA-IR homeostasis model assessment of insulin resistance, hs-CRP high-sensitivity C-reactive protein, SBP systolic blood pressure, DBP diastolic blood pressure * p \ 0.05, ** p \ 0.01
Table 3 Association of serum total and undercarboxylated osteocalcin with the presence of metabolic syndrome: logistic regression analyses were performed to determine the odds ratios (ORs) of Parameters
metabolic syndrome with regard to total and undercarboxylated osteocalcin quartiles after adjustment for age, years since menopause, and body mass index
Odds ratio (95 % confidence interval), p value Quartile 1 (n = 33)
Quartile 2 (n = 34)
Quartile 3 (n = 34)
Quartile 4 (n = 34)
Total osteocalcin (ng/mL)
B11.84
11.90–15.06
15.38–19.41
C19.43
Unadjusted
1
0.46 (0.17–1.26), 0.131
0.75 (0.26–2.15), 0.595
0.34 (0.12–0.94), 0.038
Age, years since menopause, and BMI adjusted
1
0.74 (0.23–2.37), 0.614
1.43 (0.41–5.01), 0.572
0.47 (0.15–1.48), 0.196
Undercarboxylated osteocalcin (ng/mL)
B3.75
3.77–5.83
5.85–7.54
C7.68
Unadjusted
1
0.66 (0.23–1.86), 0.432
0.66 (0.23–1.86), 0.432
0.27 (0.01–0.74), 0.011
Age, years since menopause, and BMI adjusted
1
0.79 (0.23–2.66), 0.699
0.48 (0.14–1.58), 0.227
0.30 (0.09–0.98), 0.046
BMI body mass index
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Arch Gynecol Obstet Table 4 Multiple regression analysis with serum undercarboxylated osteocalcin as dependent variables Variables
B
Standard error
Standardized b
p
Leptin
-2.320
0.907
-0.230
0.008
HOMA-IR
-0.904
0.454
-0.179
0.046
HOMA-IR homeostasis model assessment of insulin resistance
osteoprotegerin, a negative regulator of osteoclast function, and promotes the ability of osteoclasts to acidify the bone extracellular matrix. An acid pH in the bone extracellular cellular matrix can enhance decarboxylation of osteocalcin and ucOC that promotes glucose metabolism. Fluzele et al. [17] reported that insulin receptors in osteoblasts control osteoblast development and ucOC, and mice lacking insulin receptors in osteoblast have low levels of ucOC, decreased bone formation, and increased peripheral adiposity, glucose intolerance, and insulin resistance. Leptin upregulates the sympathetic nervous system and activated sympathetic tone increases expression of the Esp gene in osteoblasts via ß2 adrenergic receptors. Increased Esp gene expression inactivates the bioactivity of ucOC and decreases insulin expression and secretion in pancreatic ß cells. Therefore, hyperleptinemia is associated with insulin resistance via inhibition of osteocalcin expression [10]. According to these studies, hyperleptinemia is associated with MetS, and leptin and osteocalcin exert opposite effects on insulin secretion. Briefly, insulin signaling promotes the differentiation of osteoblasts via insulin receptors in osteoblasts, enhanced osteoclast activity promotes decarboxylation of osteocalcin, and increased ucOC enhances insulin secretion and sensitivity. However, leptin inhibits activation of osteocalcin via enhanced sympathetic tone. These complex mechanisms indicate the existence of a bone-fat-pancreas endocrine loop, and bone and energy metabolism exert reciprocal regulation [18]. Several studies reported differences in serum osteocalcin level according to MetS. Serum osteocalcin levels were significantly lower in the MetS group than the non-MetS group in postmenopausal Korean and Chinese women [19, 20]. However, Liu et al. reported that serum ucOC level increased with MetS in middle-aged women in contrast to carboxylated osteocalcin (8.1 ± 7.2 vs. 5.9 ± 4.6 ng/ml, p = 0.036). They hypothesized that hyperinsulinemia secondary to insulin resistance underlies most of the metabolic derangement in MetS, and that higher serum ucOC can enhance the synthesis and secretion of insulin, which in part contributes to hyperinsulinemia, and increased insulin receptor signaling in osteoblasts leads to accelerated osteocalcin decarboxylation. However, the limitation of this study was the small sample size [21]. The
results of the present study were consistent with those of previous investigations in postmenopausal Korean and Chinese women. Several studies have indicated the inverse association between metabolic risks, including markers of insulin resistance, proinflammatory cytokines, leptin, and osteocalcin in postmenopausal women [22–24]. However, there is still debate regarding the associations between fat mass, central obesity, and osteocalcin. Yang et al. [20] reported that the OR for central obesity was significantly lower in the highest quartile compared to the lowest quartile of osteocalcin level (p \ 0.01). Movahed et al. [25] reported that lower serum osteocalcin was inversely associated with waist circumference [OR 2.53; CI (1.13–5.67), p = 0.024]. However, Kanazawa et al. [26] reported that although ucOC was negatively correlated with %fat, %trunk, and visceral fat area in postmenopausal women, they found no significant association in multiple regression analysis. Our study showed that ucOC was negatively correlated with markers of central obesity, including WHR and VFA, body fat mass, as well as HOMA-IR, hs-CRP, and leptin. However, there was no significant correlation between ucOC and BMI. It is well known that visceral fat is a strong predictor of insulin resistance and abdominal obesity, and insulin resistance is a risk factor for cardiovascular disease (CVD) [27]. Although the prevalence of MetS increases with age and BMI, MetS can be present in lean individuals; in addition, a proportion of obese subjects does not have MetS [28]. Several studies have focused on the association between MetS and osteocalcin in postmenopausal women. Saleem et al. [22] reported that the ORs for MetS were 0.33 in black and 0.43 in Hispanic white women in the highest quartile of osteocalcin level (p \ 0.001). In a study of Korean postmenopausal women, the OR for MetS was 5.25 in the lowest quartile of osteocalcin level (p \ 0.001) [19]. Yang et al. [20] reported that postmenopausal women with the highest osteocalcin levels had lower OR for MetS (OR = 0.123, p \ 0.01). In these previous studies, the association between MetS and osteocalcin was limited to tOC rather ucOC. Our study showed that ucOC is inversely associated with the presence of MetS. Previous animal experiments have shown that ucOC rather than cOC is mainly involved in the regulation of glucose and fat metabolism. Although our results were consistent with previous findings, we failed to search for the studies focusing on the association between ucOC and glucose and fat metabolism in postmenopausal women. We measured both ucOC and tOC to evaluate the association between osteocalcin and MetS. This study had several limitations. First, due to its crosssectional design, we failed to determine the cause and effect relationship between ucOC and MetS. Second, serum
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osteocalcin may be influenced by physical activity and dietary habits. We did not include physical activity and dietary habits in our analysis but excluded subjects who were dieting and exercising for weight control. We included all subjects engaged in moderate physical activity. Third, for the diagnostic criteria of MetS, the WHR was substituted for waist circumference. The waist circumference and the WHR were both used as measures of abdominal obesity; indeed, a previous case–control study indicated that WHR is a risk factor for CVD [29]. A number of questions remain to be resolved. First, the presence of osteocalcin receptors in pancreatic b cells and adipocytes and the definitive action of osteocalcin in humans have yet to be clarified. Second, factors that influence the osteocalcin level, including vitamin K agents, hormone therapy, and agents for promoting bone formation, such as bisphosphonates and teriparatide, may affect the prevalence of MetS.
Conclusion The increase in prevalence of MetS in postmenopausal women may increase the risk of CVD, and the prevention and treatment of MetS are important. Further large-scale clinical and experimental studies are required to clarify the potential of ucOC as a predictor of MetS and treatment of diabetes mellitus. Conflict of interest The authors have stated explicitly that there are no conflicts of interest in connection with this article.
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