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INTRODUCTION
Women at reproductive age are at a lower risk of obesity-related
comorbidities, compared with postmenopausal women [1]. However, a
plethora of metabolic disturbances accompanied with an increased
visceral obesity, such as dyslipidemia, insulin resistance,
hypertension are observed in women after menopause [2-5].
Having in mind that adipose tissue redistributionhas been increasing
towards visceral region, along with an increased adipokines
secretion, it is speculated that postmenopausal women display higher
level of adipokines than premenopausal ones [6-9]. Many of these
adipokines may impair insulin signaling leading to metabolic
disorders, making them as one of the major culprits for diabetes
mellitus type 2 and cardiovascular diseases [6, 10, 11].
One such adipokine is retinol-binding protein 4 (RBP4), which has
been widely studied in the recent years [10-12]. Although primarily
secreted by the liver, adipose tissue also represents the highest
expression of this protein [6]. A majority of studies confirmed an
independent relationship between RBP4 and cardiometabolic states
closely related to insulin resistance (IR) [9, 10, 12, 13], thus
suggesting obesity-induced IR as a hallmark of increased RBP4
levels.The proposed mechanism of such relationship may act through
down-regulation of the insulin responsive glucose transporter-4,
which represents the trigger for RBP4 adipocytes secretion [6, 11].
Additionally, a sexual dimorphism is typical for RBP4 secretion,
which can be partly explained by the influence of sex hormones and
indirectly, by body fat distribution [14].
On the other hand, _our knowledge about the influence of menopausal
status on RBP4 is scarce and the underlying mechanism of this
relationship is not well elucidated. In line with this, the aim of
the current study was to examine whether RBP4 levels are associated
with menopausal status, independent of insulin resistance.
MATERIALS AND METHODS
Study population
The current research derived from our previous studies examining the
utility of inflammation and metabolic markers in postmenopausal
women [1-5, 11, 15, 16].
A total of 30 premenopausal and 100 postmenopausal women non-treated
with medications were included in the current cross-sectional study.
All women volunteered for biochemical analyses check-up in the
Center of Laboratory Diagnostics of the Primary Health Care Center
in Podgorica, Montenegro, in a period from October 2012 to May 2013.
Women were considered to be premenopausal if they self-reported
regular menstrual cycle, while the self-reported absence of
menstrual bleeding for more than one year was the criterion for
postmenopausal status.
Inclusion criteria for participants to enter the study were:
premenopausal and postmenopausal otherwise healthy women, with no
signs and symptoms of acute inflammatory disease.
Exclusion criteria were: diabetes mellitus, hypothyroidism or
hyperthyroidism, liver disease other than steatosis, renal
dysfunction, cardiovascular disorders, malignant diseases, high
sensitivity C-reactive protein (hsCRP) >10 mg/L, smoking, hormone
replacement therapy or any other medicament therapy used in the last
six months.
All women that entered the study provided written informed consent.
The research was carried out in compliance with the Declaration of
Helsinki, and with approval of the Ethical Committee of Primary
Health Care Center in Podgorica, Montenegro.
Anthropometric measurements
Basic anthropometric measurements, such as waist circumference (WC)
and body mass index (BMI) were obtained, as described previously
[3].
Biochemical analyses
Blood samples were taken and biochemical parameterswere measured
after an overnight fast of at least 8 hours, as described previously
[3]. Serum levels of glucose, creatinine, and lipid parameters
[e.g., total cholesterol (TC), high density lipoprotein cholesterol
(HDL-c), low density lipoprotein cholesterol (LDL-c), triglycerides
(TG)], were determined spectrophotometrically (Roche Cobas 400,
Mannheim, Germany). Levels of hsCRP were determined using an
immunonephelometric assay (Behring Nephelometer Analyzer, BN II,
Marburg, Germany).Insulin concentration was determined by
chemiluminescent assay (Immulite 2000, Siemens, Muenchen, Germany).
HOMA-IR and estimated glomerular filtration rate (eGFR) were
calculated, as described elsewhere [2, 11].
Blood pressure was measured as described elsewhere [2].
Statistical analysis
Testing distributions of examined variables were performed by
Kolmogorov-Smirnov test. Data were shown as a mean±standard
deviation for normally distributed variables. Log-normally
distributed variables were presented as geometric mean (95%
Confidence Interval) [17]. A comparison of normal and log-normal
continuous variables were done by Student’s t-test. Skewed
distributed data were given as median (interquartile range) and
compared by Mann-Whitney test. Spearman's correlation analysis was
used to estimate correlations between the examined parameters in
pre- and postmenopausal women. Data from correlation analysis were
presented as coefficient correlation, rho (ρ). If probability values
(p) for ρ were less than 0.1, those variables (independent) were
tested in further multiple linear regression analysis. As well,
skewed distributed data were not included as independent variables.
Multiple linear regression analysis was performed to estimate the
independent contribution of clinical parameters, and presence of
menopausal status on RBP4 level. Categorical data referring to
menopausal status were included in the Model and coded as
1-premenopausal status and 2-postmenopausal status. The F-ratio of
the ANOVA test in multiple linear regression analysis was used to
determine whether the overall regression model is a good fit of the
data. Multicollinearity among independent variables was also tested.
Statistical analyses were performed using PASW® Statistic version 18
(Chicago, Illinois, USA) and MedCalc version 15.8 softwares. All
statistical tests were considered significant when p was less than
0.05.
RESULTS
Baseline clinical and laboratorycharacteristics according to
menopausal status are summarized in Table 1. Postmenopausal women
were older and displayed higher DBP than premenopausal. There were
none significant differences in BMI, WC and SBP between tested
groups (Table 1).
Furthermore, postmenopausal women had higher TC, LDL-c, TG
concentrations and HOMA-IR than premenopausal women (Table 1). Also,
statistically higher levels of RBP4 were determined in
postmenopausal women. Estimated GFR was significantly lower in
postmenopausal women, but as it can be seen from the Table 1, both
groups of women had preserved kidney function.
Table 1. Baseline clinical and laboratory characteristics
of women according to menopausal status
Tabela 1. Klinički i laboratorijski parametri ispitanica u
odnosu na menopauzu
| |
Premenopausal women |
Postmenopausal women |
p |
| N |
30 |
100 |
|
| Age, years |
47.56 (46.74-48.39) |
56.52 (55.68-57.38) |
<0.001 |
| |
|
|
|
| BMI, kg/m2 |
25.52 (23.49-27.72) |
26.41 (25.65-27.19) |
0.342 |
| |
|
|
|
| WC, cm |
85.40 (79.78-91.43) |
89.25 (87.12-91.43) |
0.146 |
| |
|
|
|
| SBP, mmHg |
125.00 (118.00-132.00) |
128.00 (124.00-134.00) |
0.480 |
| |
|
|
|
| DBP, mmHg |
76.00 (73.00-81.00) |
83.00 (80.00-86.00) |
0.021 |
| HDL-c, mmol/L |
1.68±0.42 |
1.66±0.42 |
0.820 |
| LDL-c, mmol/L |
3.59 ±1.17 |
4.41 ±1.05 |
<0.001 |
| TG, mmol/L |
1.09 (0.94-1.26) |
1.37 (1.26-1.49) |
0.015 |
| Glucose, mmol/L* |
5.40 (5.10-5.80) |
5.30 (5.00-5.70) |
0.606 |
| Insulin, μIU/L** |
6.40 (5.05-8.10) |
6.71 (6.13-7.35) |
0.668 |
| HOMA-IR** |
1.53 (1.20-1.97) |
1.61 (1.46-1.77) |
0.001 |
| Creatinine, µmol/L* |
56.50 (53.36-59.57) |
57.00 (51.00-62.00) |
0.861 |
| eGFR, mL/min/1.73 m²** |
105.65 (100.58-10.97) |
99.72 (98.50-100.96) |
0.001 |
| HsCRP, mg/L** |
0.80 (0.52-1.23) |
0.99 (0.83-1.18) |
0.311 |
| RBP4, mg/L* |
34.47 (35.16-39.94) |
43.24 (41.95-44.58) |
<0.001 |
Data are presented as an arithmetic mean ± SD and compared to
Student’s t-test
*Skewed distributed data are presented as median (interquartile
range) and compared with the Mann-Whitney U test
**Log-normal distributed data are presented as geometric mean (95%
CI) and compared with Student’s t-test after logarithmic
transformation
BMI-Body mass index; WC-Waist circumference; SBP-Systolic blood
pressure; DBP-Diastolic blood pressure; TC-Total cholesterol; HDL-c-High
density lipoprotein cholesterol; LDL-c-Low density lipoprotein
cholesterol; TG-Triglycerides; HOMA-IR-Homeostasis model assessment
of insulin resistance; eGFR-Estimated glomerular filtration rate;
hsCRP-High-sensitivity C-reactive protein; RBP4-Retinol-binding
protein 4
Associations of examined parameters with RBP4 were tested with
Spearman’s correlation analysis. Significant positive correlations
were determined between RBP4 and age, BMI, WC, SBP, DBP, TC, LDL-c,
TG, glucose, insulin, HOMA-IR, creatinine (Table 2). On the
contrary, RBP4 significantly negatively correlated with HDL-c and
eGFR.
Table 2. Spearman’s correlation analysis between RBP4 and
clinical and laboratory parameters in all women
Tabela 2. Spirmanova korelacija između RBP4, kliničkih i
laboratorijskih parametara u celoj grupi ispitanica
| |
RBP4, mg/L |
| |
ρ |
p |
| Age, years |
0.255 |
0.002 |
| BMI, kg/m² |
0.252 |
0.002 |
| WC, cm |
0.255 |
0.002 |
| SBP, mmHg |
0.389 |
<0.001 |
| DBP, mmHg |
0.381 |
<0.001 |
| TC, mmol/L |
0.212 |
0.009 |
| HDL-c, mmol/L |
-0.290 |
<0.001 |
| LDL-c, mmol/L |
0.256 |
0.002 |
| TG, mmol/L |
0.452 |
<0.001 |
| Glucose, mmol/L |
0.215 |
0.008 |
| Insulin, μIU/L |
0.165 |
0.041 |
| HOMA-IR |
0.188 |
0.022 |
| Creatinine, µmol/L |
0.250 |
0.002 |
| eGFR, mL/min/1.73 m² |
-0.361 |
<0.001 |
| HsCRP, mg/L |
0.081 |
0.324 |
Data are presented as correlation coefficient Rho (ρ)
BMI-Body mass index; WC-Waist circumference; SBP-Systolic blood
pressure; DBP-Diastolic blood pressure; TC-Total cholesterol; HDL-c-High
density lipoprotein cholesterol; LDL-c-Low density lipoprotein
cholesterol; TG-Triglycerides; HOMA-IR-Homeostasis model assessment
of insulin resistance; eGFR-Estimated glomerular filtration rate;
hsCRP-High-sensitivity C-reactive protein; RBP4-Retinol-binding
protein 4
Further statistical testing included multiple linear regression
analysis in order to identify the demographic and clinical
parameters independently associated with RBP4 (Table 3). Independent
variables that correlated with RBP4 levels in Spearman’s correlation
analysis with the significance of p<0.1 (Table 2) and which were not
skewed distributed after tested by Kolmogorov-Smirnov test, entered
into the Model. Although, insulin concentration was used in HOMA-IR
calculation, it was not included into the Model. Also, because of
glucose and WC skewed distributions, these parameters were not
included into the Model. According to the ANOVA test of multiple
linear regression analysis, tested independent variables
statistically significantly predicted RBP4 concentration, F=6,522,
p<0.001. This also demonstrated the Model is a good fit of the data.
An adjusted R2=0.310 for the Model demonstrated that 31% variation
in RBP4 concentration could be explained by this Model. SBP was
independently associated with an increase in RBP4 levels (β=0.418,
p=0.028), as well as TG levels (β=0.315, p=0.002). On the other
hand, eGFR was independently associated with decrease in RBP4 levels
(β= - 0.258, p=0.004). The independent positive association of
menopausal status and RBP4 concentration, with standardized
coefficient β=0.240, p=0.016 was of the greatest importance.The
multiple regression unstandardized coefficient (B), its standard
error (SE), standardized coefficient (β) and p levels are presented
in Table 3.
Table 3. Multiple linear regression analysis of the
association of RBP4 with examined parameters
Tabela 3. Višestruka linearna regresija povezanosti RBP4 sa
ostalim ispitivanim parametrima
| Predictors |
Unstandardized |
Standardized
coefficient |
|
| |
B |
Standard error |
β |
p |
| Age, years |
-0.155 |
0.175 |
-0.091 |
0.376 |
| BMI, kg/m² |
-0.073 |
0.096 |
-0.072 |
0.446 |
| SBP, mmHg |
0.385 |
0.174 |
0.418 |
0.028 |
| DBP, mmHg |
-0.299 |
0.199 |
-0.291 |
0.135 |
| HDL-c, mmol/L |
-0.004 |
0.018 |
-0.020 |
0.843 |
| LDL-c, mmol/L |
0.002 |
0.005 |
0.024 |
0.760 |
| TG, mmol/L |
0.123 |
0.040 |
0.315 |
0.002 |
| HOMA-IR |
-0.007 |
0.029 |
-0.021 |
0.817 |
| eGFR, mL/min/1.73 m² |
-0.536 |
0.181 |
-0.258 |
0.004 |
| Menopausal status |
0.047 |
0.019 |
0.240 |
0.016 |
BMI-Body mass index; SBP-Systolic blood pressure; DBP-Diastolic
blood pressure; HDL-c-High density lipoprotein cholesterol; LDL-c-Low
density lipoprotein cholesterol; TG-Triglycerides;
HOMA-IR-Homeostasis model assessment of insulin resistance; eGFR-Estimated
glomerular filtration rate; RBP4-Retinol-binding protein 4
DISCUSSION
The main result of our study is that menopause per se has an
independent influence on higher RBP4 levels (Table 3). Also,
postmenopausal women in the current study displayed significantly
higher levels of this adipokine than premenopausal counterparts
(Table 1). Similarly, some previous researchers also reported higher
RBP4 in postmenopausal women [7-9].
The higher RBP4 concentration in postmenopausal women in our study
may in part be explained by estrogen deficiency. In line with this,
an inverse relationship between serum RBP4 and estradiol levels in a
cohort of obese women, was recently reported [18]. The indirect
effect of estrogen may be exerted through the influenceof the body
fat distribution on serum RBP4. Estrogen levels are related to
reduced fat storage and increasedenergy expenditure[14]. In line
with that, it was shown that ovariectomy was accompanied with an
increase weight gain in response to a high-fat diet in female mice
in comparison with mice on a normal-fat diet [14]. On the contrary,
supplementation of 17-β estradiol (E2) had no effect on male mice,
but only on female mice [19], suggesting sex difference in body fat
distribution, mainly due to estrogen influence.
In addition, animal and human studies showed that lack of endogenous
estrogen production leads to IR [14]. Furthermore, E2 replacement
therapy in postmenopausal women is related to enhanced insulin
signaling through suppression of lipolysis [20]. Namely, it is well
established that obesity is accompanied with increased IR and
unfavorable lipid profile [15]. Although in the current study there
were no significant difference in anthropometric parameters between
pre- and postmenopausal women, the latter ones showed higher HOMA-IR,
TC, LDL-c, and TG than premenopausal ones (Table 1).
In our study, in addition to SBP, TG and eGFR, menopausal status
exerted the independent influence on RBP4 (Table 3). This may in
part be explained by diminished effect of estrogen to suppress the
lipolysis through activation of estrogen receptor alpha (ER-α) in
adipose tissue [19], thus suggesting the contribution of increased
lipolysis and subsequent free fatty acid secretion from adipose
tissue in insulin resistance occurrence and progression in
postmenopausal women.
Additionally, in Spearman’s non-parametric correlation analysis,
RBP4 correlated with anthropometric and cardiometabolic parameters
(Table 2). However, we failed to show the direct influence of
anthropometric parameters on RBP4 levels. Our results are in line
with the study of Tan et al. [21] who showed that RBP4 mRNA
expression was significantly increased in human adipocytes of
overweight women with polycystic ovary syndrome, but they excluded
the influence of anthropometric indices on higher RBP4 mRNA
expression and higher RBP4 levels in circulation.
Our study has some limitations, such as the relatively small sample
size of examined cohorts and its cross-sectional design. In
addition, we were not able to determine sex hormones in our study
group. However, our cohort comprised of premenopausal and
postmenopausal otherwise healthy women, without hormone replacement
therapy or any medication usage in the last six months, so we
excluded such confounding factors when estimating cardiometabolic
profile of examined groups. In addition, we also excluded
cardiometabolic diseases that may also affect serum RBP4 level.
Future longitudinal studies with larger sample size are needed to
further explore pathophysiological mechanisms concerning the impact
of menopause on RBP4 level in order to find the best therapeutic
target approach for the decrease of this adipokine in postmenopause.
CONCLUSION
Postmenopausal women displayed higher retinol-binding protein 4
and unfavorable cardiometabolic profile, compared to premenopausal
ones. Menopause per se is an independent predictor of high serum
retinol-binding protein 4levels which should be taken into account
when examining the role of this adipokine in cardiometabolic disease
occurrence.
Acknowledgement
This work was financially supported in part by a grant from the
Ministry of Education, Science and Technological Development,
Republic of Serbia (Project number 175035).
Conflict of Interest Statement
The authors have declared no conflicts of interest.
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