Endocrine DOI 10.1007/s12020-014-0318-7
ORIGINAL ARTICLE
Comparative analysis of vaspin in pregnant women with and without gestational diabetes mellitus and healthy non-pregnant women Xiaojiao Jia • Shuyi Wang • Ning Ma Xiaojing Li • Likui Guo • Xiaoli Liu • Tao Dong • Yali Liu • Qiang Lu
•
Received: 26 December 2013 / Accepted: 23 May 2014 Ó Springer Science+Business Media New York 2014
Abstract To explore serum vaspin, leptin, and adiponectin levels and their correlation with insulin resistance (IR) in pregnant women with and without gestational diabetes mellitus (GDM) and healthy non-pregnant women. A total of 262 individuals, including pregnant women with GDM (n = 86), those without GDM (n = 92), and age-matched healthy non-pregnant women (n = 84) were enrolled in this case–control study. Vaspin, leptin, adiponectin, glucose, insulin, hemoglobin A1C (HbA1c), and lipid parameters were measured. The homeostasis model assessment–insulin resistance (HOMA–IR), quantitative insulin sensitivity check index, and body mass index were calculated. Data inferred higher concentrations of vaspin (2.72 ± 2.20 vs. 1.84 ± 1.57 vs. 0.81 ± 1.02) in GDM than during normal pregnancy and in non-pregnant women, higher leptin (23.42 ± 12.18 vs. 22.19 ± 10.55 vs. 12.10 ± 11.26), and
X. Jia Department of Endocrinology, Hebei Medical University, Shijiazhuang, China X. Jia N. Ma X. Liu Q. Lu (&) Department of Endocrinology, The First Hospital of Qinhuangdao, No.258, Wenhua Road, Qinhuangdao 066000, Hebei, China e-mail: [email protected] S. Wang Department of Clinical Laboratory, The First Hospital of Qinhuangdao, Qinhuangdao, China X. Li L. Guo Department of Obstetrics and Gynecology, The First Hospital of Qinhuangdao, Qinhuangdao, China T. Dong Y. Liu Department of Physical Examination Center, The First Hospital of Qinhuangdao, Qinhuangdao, China
lower adiponectin (4,164.83 ± 2,650.39 vs. 4,871.66 ± 2,803.51 vs. 7,202.85 ± 4,893.13) in GDM and normal pregnancy as compared to non-pregnant women (p \ 0.05). Vaspin was positively correlated to leptin (r = 0.273, p = 0.012), HOMA–IR (r = 0.387, p = 0.000), and triglycerides (TG, r = 0.218, p = 0.046) in GDM. In addition, leptin was negatively correlated to adiponectin in GDM (r = -0.336, p = 0.002) and normal pregnancy (r = -0.256, p = 0.014). Furthermore, vaspin was significantly correlated to GDM and HOMA–IR, and the weight gain might play a vital role in the occurrence of GDM. During pregnancy, high vaspin concentration is significantly associated with IR in GDM. Keywords Vaspin Adipokines Gestational diabetes mellitus Homeostatic model assessment–insulin resistance
Introduction Gestational diabetes mellitus (GDM) is a pregnancy complication with elevated plasma glucose levels which will influence maternal-child health, due to fetal malformation, premature delivery, late-onset diabetes, and metabolic syndrome (MS) [1], Therefore, timely intervention is particularly important. In recent years, the reported prevalence of GDM in different ethnic groups and based on various diagnostic criteria ranged from 1 to 15 % [2, 3]. To the best of our knowledge, fasting insulin levels can be increased by up to two-fold at the third trimester of pregnancy compared with pre-pregnancy, while insulin sensitivity declines by 50–70 % in pregnancy [4]. Lapolla et al. [5] reported women with impaired insulin sensitivity in early pregnancy may be easy to diagnose with GDM in late pregnancy. It is
123
Endocrine
well known that IR is an important characteristic of GDM, it is complicated and closely associated with genetic factors, higher body mass index (BMI), and adipokineinduced inflammation [6, 7]. Recently, studies reported that adipose tissue was not only a depot of energy but also an active endocrine organ. Since the first adipocytokine–leptin was discovered, our understanding of adipose tissue has fundamentally changed. Even though study results have varied, a change in the concentrations of adipocytokines has been observed in GDM. In addition, high leptin concentrations were associated with increased risk of developing GDM [8], and may be useful for early diagnosis of GDM. Moreover, studies showed lower adiponectin in GDM as compared to normal pregnant controls [9, 10], and women with reduced circulating adiponectin levels in the first trimester of pregnancy were more likely to be diagnosed with GDM [11]. To our knowledge, disorders of adipocytokines played an important role in the occurrence, development, and prognosis of IR [12] and GDM characterized by IR [13, 14]. IR is complex and may be regulated by as yet unrecognized factors—the exact mechanisms are not entirely understood. Visceral adipose tissue-derived serpin (vaspin) has been regarded as a novel adipokine with potential insulin-sensitizing properties. Elevated circulating vaspin levels have been associated with obesity, impaired insulin sensitivity [15–17], lipid metabolism [18], and MS related diseases [19, 20]. However, in contrast to these data, several studies did not find an association between circulating vaspin and insulin sensitivity [21, 22] or parameters of obesity and fat distribution [22]. Vaspin is probably a valuable serological marker in GDM, but there is a lack of evidence regarding the relationship between vaspin and GDM, and there are no uniform opinions amongst researchers [23, 24]. We studied the serum levels of leptin, adiponectin, and vaspin to determine the relationship between adipocytokines, IR, and GDM. Based on current studies [25, 26], we hypothesized that circulating levels of vaspin would be increased and more closely correlated with IR in GDM than in other groups.
Subjects and methods Subjects After obtaining informed consent from all participants and approval from the local Ethics Committee, a cross-sectional study was conducted. From July 2012 to April 2013, we enrolled 262 women, aged 18–35 years old, who presented to the First Hospital of Qinhuangdao for obstetrical examination or health examination. Serum samples were
123
obtained at 24–28 weeks of gestation in pregnant women. Samples were stored at -80 °C until analysis. Non-pregnant women were required to be in good health. To avoid the interference of other confounding factors on the possible relation between adipocytokines and IR, multipara, diabetes, liver or renal insufficiency, rheumatologic disease, thyroid diseases, polycystic ovary syndrome (PCOS), tumor, use of corticosteroids or metformin, and acute or chronic inflammation were excluded. Measurements Anthropometric measurements, including height, weight, and blood pressure were taken. Blood pressure was measured twice with a mercury sphygmomanometer after 10 min of rest while the subjects were seated, and the average of the two measurements was used for analysis. Pre-pregnancy weight and family history (i.e., hypertension, obesity, and diabetes) were recorded. Definitions The subjects were divided into three groups. GDM was defined according to the results of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study: if fasting venous plasma glucose exceeds 92 mg/dL or 1 h 180 mg/ dL or 2 h 153 mg/dL after glucose loading (a 75 g 2-h oral glucose tolerance test, OGTT) [27]. GDM patients were all newly diagnosed and had not received lifestyle interventions or insulin treatment. In addition, BMI-1, BMI-2, BMI-3, and weight gain were defined as follows: BMI-1 (BMI at pre-pregnancy in GDM and normal pregnancy); BMI-2 (BMI at 24–28 weeks of gestation in GDM and normal pregnancy, and at the moment of blood acquisition in healthy non-pregnant women); BMI-3 (multiply D value of BMI-2 and BMI-1 by 100 % in GDM and normal pregnancy), and weight gain (D value of weight at 24–28 weeks of gestation and pre-pregnancy). Laboratory examinations Each patient underwent an OGTT with 75 g of oral anhydrous glucose that was initiated at 8:00 am, and blood samples were taken at the same time. Plasma glucose levels were measured using the glucose oxidase method, and serum lipid levels were measured using an autoanalyzer (Hitachi, Tokyo, Japan). HbA1c was determined by high performance liquid chromatography (HPLC), which was standard in the Diabetes Control and Complications Trial (DCCT) and National Glycohemoglobin Standardization Program (NGSP). Insulin concentrations were measured by radioimmunological assay using a commercially available kit (North Institute of Biological Technology, Beijing,
Endocrine
China). Serum levels of leptin, adiponectin, and vaspin were measured by enzyme-linked immunosorbent assay using available kits (BioVendor, intra-assay coefficients of variation (CV) are 4.2 and 7.6 %, inter-assay are 6.7 and 4.4 %, the limit of Detection is 0.2 ng/mL; R&D systems, intra-assay Precision CV are 2.5, 3.4, and 4.7 %, interassay Precision are 6.8, 5.8, and 6.9 %, the minimum detectable dose (MDD) about adiponectin ranged from 0.079 to 0.891 ng/mL and the mean MDD was 0.246 ng/ mL; AdipoGen, intra-assay Precision CV are 1.310, 3.846, 3.272, 3.630, and 1.743 %, inter-assay Precision are 5.929, 3.267, 3.693, 9.0645, and 8.3165 %, the lowest levels of vaspin that can be detected are 12 pg/mL. The following equations were used for the HOMA–IR index and QUICKI: [fasting insulin level (mIU/L) 9 fasting glucose level (mmol/L)]/22.5 and 1/[log(fasting insulin) ? log(log fasting insulin)], respectively. IR was represented by HOMA–IR. Statistical analysis All analyses were performed using the SPSS 13.0 statistical software. Values were expressed as mean ± standard deviation, and when not normally distributed, they were transformed for analysis using t test, non-parametric equivalent test, ANOVA, or Chi square for comparisons, as appropriate. To measure the strength of the association between two variables, a simple scatter plot and Pearson correlation coefficient were used. Three multiple linear regression models (stepwise method) were used to evaluate the relationships between various parameters and IR. A binary logistic regression analysis (enter method) was performed to decide relationships between various parameters and GDM. HOMA–IR was the dependent variable, and age, BMI-1, BMI-2, BMI-3, weight gain, vaspin, leptin, adiponectin, triglycerides (TG), and total cholesterol (TC) were used as independent variables in the GDM group (model 1) and normal pregnancy (model 2). Age, BMI-2, vaspin, leptin, adiponectin, TG, and TC were used as independent variables in the healthy non-pregnant group (model 3). P \ 0.05 was considered statistically significant.
Results Clinical and laboratory characteristics in the study subjects are shown in Table 1. Age, diastolic blood pressure(DBP), QUICKI, family history of diabetes, and obesity were similar among the three groups. Furthermore, BMI-1 and BMI-2 in pregnancy with and without GDM were similar (p [ 0.05). However, family history of hypertension was significantly different between the GDM (21.4 %) and
healthy non-pregnant group (40.5 %; p \ 0.017). Serum vaspin, glucose (1, 2 h), HbA1c, and HOMA–IR levels were significantly higher in the GDM than in the other groups (p \ 0.05). Higher levels of leptin and insulin(0 h), and lower adiponectin concentrations were observed in pregnant women (both GDM and normal pregnancy) as compared to healthy non-pregnant women (p \ 0.05). In addition, BMI-2 in the non-pregnant group was significantly lower as compared to pregnant women, and there was a higher weight gain in normal pregnancy than in GDM. Figure 1 shows the scatter plot of vaspin and HOMA–IR in GDM. In addition, the correlation coefficients indicate that vaspin was positively associated with leptin (r = 0.273, p = 0.012), HOMA–IR (r = 0.387, p = 0.000) and TG (r = 0.218, p = 0.046) in GDM, but not in the other groups. Leptin was negatively correlated to adiponectin in GDM (r = -0.336, p = 0.002) and in normal pregnancy (r = -0.256, p = 0.014), but not in healthy non-pregnant group. Table 2 shows partial data of the correlation analyses for adipocytokines. In the multiple linear regression model (model 1), HOMA–IR was independently associated with BMI-2, vaspin, and leptin in GDM (Table 3). In model 2, HOMA– IR was independently associated with adiponectin and TG. In model 3, HOMA–IR was independently associated with BMI-2. Similarly, in binary logistic regression (Table 4), weight gain, vaspin, HOMA–IR, and TC were independently associated with GDM. Hence, vaspin is an important determinant of IR in GDM but not in other groups, and weight gain is more closely related with GDM.
Discussion Adipose tissue is a highly active endocrine organ secreting a number of bioactive molecules called adipocytokines [7, 16, 28]. Vaspin was identified as an adipokine, which is predominantly secreted from visceral adipose tissue. Interestingly, vaspin might be an adipokine with potential insulin-sensitizing properties [25, 29], and vaspin serum concentrations have been associated with glucolipid metabolism [18, 30, 31]. In addition, adiponectin is considered to be an insulin-sensitizing adipokine; during the course of pregnancy, maternal adiponectin secretion declines progressively, and circulating adiponectin levels are reduced in GDM as compared to normal pregnancy [9, 10]. Low serum adiponectin levels might further aggravate insulin resistance, and down regulation of adiponectin in the first trimester of pregnancy is an independent predictor for GDM. In contrast to previous studies [23, 24], we found higher levels of vaspin [25, 26] in GDM, and higher leptin [32] and lower adiponectin [10] concentrations in
123
Endocrine Table 1 Baseline characteristics of the study population GDM
Normal pregnancy
Healthy non-pregnant
n
84
92
80
Vaspin (ng/mL)
2.72 ± 2.20
1.84 ± 1.57*
0.81 ± 1.02*,#
Leptin (ng/mL)
23.42 ± 12.18
22.19 ± 10.55
12.10 ± 11.26*,#
Adiponectin (ng/mL)
4,164.83 ± 2,650.39
4,871.66 ± 2,803.51
7,202.85 ± 4,893.13*,# 29.44 ± 4.51
a
Age (years)
29.19 ± 3.91
28.43 ± 3.35
Gestational Ageb (weeks)
25.29 ± 1.60
25.87 ± 1.50*
–
BMI-1c (kg/m2)
23.38 ± 3.72
22.15 ± 3.04
–
BMI-2d (kg/m2)
26.75 ± 3.53
26.60 ± 5.50
22.41 ± 4.63*,#
BMI-3e (kg/m2)
15.18 ± 9.79
19.68 ± 9.27*
–
f
Weight gain (kg)
8.86 ± 5.39
11.11 ± 4.82*
–
SBP (mmHg) DBP (mmHg)
107.99 ± 12.22 69.37 ± 8.62
110.66 ± 12.89* 70.04 ± 8.87
104.39 ± 12.13# 66.85 ± 9.35
Glucose 0 h (mmol/L)
5.02 ± 0.82
4.28 ± 0.34*
4.88 ± 0.52#
Glucose 1 h (mmol/L)
9.61 ± 1.89
7.07 ± 1.21*
7.24 ± 1.92*
Glucose 2 h (mmol/L)
8.05 ± 2.02
6.25 ± 0.96*
6.18 ± 1.13*
HbA1c (%)
5.47 ± 0.28
5.19 ± 0.45*
5.07 ± 0.41*
Insulin 0 h (mIU/L)
10.79 ± 6.61
9.74 ± 4.10
7.45 ± 4.73*,#
HOMA–IR
2.44 ± 1.61
1.86 ± 0.82*
1.63 ± 1.16*
QUICKI
0.64 ± 0.17
0.63 ± 0.06
0.66 ± 0.06
TG (mmol/L)
2.22 ± 0.94
2.41 ± 0.94
0.94 ± 0.43*,#
TC (mmol/L)
5.40 ± 1.18
6.14 ± 1.13*
4.53 ± 0.65*,#
Family history of diabetes (%)
21.4
16.3
27.5
Family history of obesity (%)
22.6
29.3
18.8
Family history of hypertension (%)
21.4
28.3
40.5*
BMI body mass index, DBP diastolic blood pressure, GDM gestational diabetes mellitus, HOMA–IR homeostatic model assessment–insulin resistance, QUICKI quantitative insulin sensitivity check index, SBP systolic blood pressure, TG triglycerides, TC total cholesterol * p \ 0.05 as compared with GDM; #p \ 0.05 as compared with normal pregnancy a
Age, age at blood acquisition
b
Gestational age, gestational age at blood acquisition
c
BMI-1, BMI at pre-pregnancy in GDM and normal pregnancy
d
BMI-2, BMI at 24–28 weeks of gestation in GDM and normal pregnancy, and at the moment of blood acquisition in healthy non-pregnant women e BMI-3, Multiply D value of BMI-2 and BMI-1 by 100 % in GDM and normal pregnancy f
Weight gain, D value of weight at 24–28 weeks of gestation and pre-pregnancy
pregnancy. These findings may be related to different controls, races, or periods of blood acquisition in each study. In our study, both vaspin and adiponectin levels were significantly different between pregnancy (GDM and non-GDM) and healthy non-pregnant women. Vaspin levels were also different between GDM and normal pregnant women, indicating vaspin was more closely related to the levels of insulin and IR in GDM than during normal pregnancy and in non-pregnant women. In this study, the higher levels of vaspin in GDM which might be explained by a compensative increase of insulin-sensitizing vaspin in attempt to ameliorate increased IR in GDM. It might increase at the early stage of diabetes, whereas it decreases with the worsening of the diabetes [29]. Vaspin also
123
inhibited the expressions of pro-inflammatory adipocytokines, suggesting that it might exert an anti-inflammatory role [33]. Furthermore, compared to the report by Giomisi et al. [34], our results showed that vaspin was positively correlated to leptin, HOMA–IR [26], and TG in GDM but not in the others groups [21]. Regression analyses showed that vaspin was independently associated with GDM and HOMA–IR in pregnant women with or without GDM, but not in non-pregnant women. Based on the logistic regression analysis, vaspin, weight gain, HOMA–IR, and TC were independently associated with GDM, it seems that preventing excessive weight gain might be beneficial for pregnant women [35, 36], but the women with GDM had
Endocrine
lower weight gain than normal pregnancy in our study, we still cannot conclude that gestational weight gain is associated with increased risk of GDM [37]. Overall, higher
Fig. 1 Scatter plot of vaspin and HOMA–IR in gestational diabetes mellitus HOMA–IR, homeostasis model assessment–insulin resistance Table 2 Correlation analysis for leptin, adiponectin, and vaspin BMI-2 r
HOMA–IR p
r
p
Leptin GDM
0.253
0.020
0.419
\0.001
Normal pregnancy Healthy non-pregnant
0.378 0.788
\0.001 \0.001
0.213 0.504
0.041 \0.001
Adiponectin GDM
-0.350
0.001
-0.258
0.018
Normal pregnancy
-0.256
0.014
-0.286
0.006
Healthy non-pregnant
-0.314
0.005
-0.240
0.032
0.085
0.442
0.387
\0.001
Vaspin GDM Normal pregnancy
0.077
0.463
0.105
0.318
Healthy non-pregnant
0.036
0.754
0.001
0.994
BMI-2, BMI at 24–28 weeks of gestation in GDM and normal pregnancy, and at the moment of blood acquisition in healthy nonpregnant women BMI body mass index, GDM gestational diabetes mellitus, HOMA–IR homeostatic model assessment–insulin resistance
circulating vaspin is independently associated with the occurrence of GDM. Even though, previous studies also showed obesity was correlated with many metabolic disorders, BMI-2 was significantly lower in non-pregnant women than in the pregnant groups, it was probably responsible for the differences in adipocytokines, HOMA– IR, and lipid levels between pregnant and non-pregnant women. After adjusting for BMI-2, vaspin was also significantly associated with GDM. In addition, there was higher weight gain but lower vaspin concentrations in normal pregnancy than in GDM, these may also indicate an important role of vaspin in GDM. However, the exact mechanisms linking vaspin secretion to glucose metabolism and insulin sensitivity in pregnant women with GDM are unknown. Several previous studies have reported that circulating levels of leptin were higher in pregnant women (both GDM and non-GDM group), and the strongest independent determinant of leptin was progestational BMI [32]. Our data also showed that higher leptin levels were positively correlated with IR, TC, and negatively correlated with adiponectin in GDM. Moreover, BMI-2, vaspin, and leptin
Table 4 Binary logistic regression analysis for gestational diabetes mellitus Variables
Unstandardized coefficients
Weight gain
-0.088
0.916
0.013
0.855–0.982
0.230
1.258
0.017
1.041–1.521
Vaspin HOMA–IR TC
Exp (B)
p
95 % CI for Exp (B)
0.338
1.402
0.039
1.018–1.931
-0.571
0.565
\0.001
0.414–0.772
2.840
17.124
0.004
Constant
–
Normal pregnancy was rated as 0 and GDM group as 1 within dependent variable; age, BMI-1, BMI-2, BMI-3, weight gain, vaspin, leptin, adiponectin, HOMA–IR, TG, and TC as independents. Weight gain, D value of weight at 24–28 weeks of gestation and prepregnancy BMI body mass index, HOMA–IR homeostatic model assessment– insulin resistance, TC total cholesterol Test for the equation (v2 = 39.249, p \ 0.05)
Table 3 Multiple linear regression analysis (GDM group, n = 84) Variables
Unstandardized coefficients b
SE
Standardized coefficients b
t
95 CI % for b
p
BMI-2
0.191
0.040
0.418
4.742
\0.001
0.111 to 0.271
Vaspin
0.211
0.065
0.287
3.244
0.002
0.081 to 0.340
0.031
0.012
0.234
-3.975
1.055
–
Leptin Constant
2.567
0.012
-3.766
\0.001
0.007 to 0.055 -6.075 to -1.874
BMI-2, BMI during 24–28 weeks of gestation BMI body mass index, GDM gestational diabetes mellitus
123
Endocrine
were significantly associated with HOMA–IR in GDM. Therefore, we can also see the significance of leptin [38] in pregnant women. Similarly, there were significantly reduced plasma concentrations of adiponectin in pregnant women [10], and lower adiponectin levels were associated with IR, GDM, and macrosomia [39, 40]. However, data showed that adiponectin was negatively correlated with BMI-2 and HOMA–IR in all three groups. Recently, a USbased nested case–control study indicated that in pregnancy low adiponectin concentrations may identify women at high risk for GDM, and the risk of developing GDM in these women is 5 times higher than for other pregnant women [41]. However, there is no significant difference in adiponectin between GDM and normal pregnant women, and it is unrelated to the diagnosis of GDM [42]. Still, we believe that adiponectin is associated with GDM. However, the reason for the higher levels of TG and TC in normal pregnant women is not clear but it is probably associated with adipocytokines or BMI. In addition, QUICKI was similar among the three groups in this study. Although there were higher HOMA–IR levels in the GDM group. To the best of our knowledge, different indices for the assessment of IR vary widely in their reliability. The QUICKI index is similar to HOMA, except that it interprets the data by taking both logarithms and the reciprocal of the fasting glucose and insulin levels, HOMA– IR and QUICKI cannot completely replace each other [43]. Metabolic disorders are complex. Although the initial factor in the pathophysiology of metabolic disorders is unknown, adipocytokines might provide an extensive network of communication within adipose tissue, and play a role in hyperglycemia, obesity, and IR. Studies have showed that leptin [32] and adiponectin [39, 41] were involved in a wide range of physiological processes including lipid metabolism and insulin sensitivity [8]. Previous studies suggested that plasma vaspin levels are associated with IR and are significantly reduced following short-term Continuous Subcutaneous Insulin Infusion (CSII) treatment [25]. Chang et al. [28] also reported that a short-term weight reduction caused significantly decreased vaspin levels. Metformin has demonstrated a beneficial effect in decreasing vaspin concomitant with improvement in insulin sensitivity and a decrease in IR [17]. In our study, we found significantly different levels of vaspin and IR but similar baseline (BMI-1 and -2) between GDM and normal pregnancy, in addition, vaspin was also significantly associated with GDM after adjusting for BMI-2. This study has some limitations. First, this is just a case– control and small sample study, the phenomenon we observed still needs to be further studied. Second, it is necessary to develop a paired design, increase the number of type 2 diabetic women with and without gestation, and divide the gestation period into more detailed phases to
123
achieve a better control. Third, it will be a greatly significant to monitor the circulating vaspin levels in GDM and pGDM patients, and it is necessary for us to conduct basic research on adipocytokines and GDM in future. Fourth, pregnancy with higher weight gain should be excluded in future study to avoid its interference on circulating dipocytokines. In addition, the family history of hypertension is a limitation in this paper. In conclusion, circulating vaspin concentrations are significantly associated with IR in GDM, and it might be of great significance in GDM. Moreover, weight gain might play a vital role in GDM. Further work needs to be done to illustrate the specific significance of vaspin in GDM and other related diseases. All of these may provide us with a new perspective on GDM.
Conflict of interest All authors have no conflicts of interest to disclose, and this study was self-financed.
References 1. L. Bellamy, J.P. Casas, A.D. Hingorani, D. Williams, Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet 373, 1773–1779 (2009) 2. P. Kalra, C.P. Kachhwaha, H.V. Singh, Prevalence of gestational diabetes mellitus and its outcome in western Rajasthan. Indian J. Endocrinol. Metab. 17, 677–680 (2013) 3. D. Dabelea, J.K. Snell-Bergeon, C.L. Hartsfield, K.J. Bischoff, R.F. Hamman, R.S. McDuffie, Kaiser Permanente of Colorado GDM Screening Program: increasing prevalence of gestational diabetes mellitus (GDM) over time and by birth cohort: Kaiser Permanente of Colorado GDM Screening Program. Diabetes Care 28, 579–584 (2005) 4. L.A. Barbour, C.E. McCurdy, T.L. Hernandez, J.P. Kirwan, P.M. Catalano, J.E. Friedman, Cellular mechanisms for insulin resistance in normal pregnancy and gestational diabetes. Diabetes Care 30, S112–S119 (2007) 5. A. Lapolla, M.G. Dalfra`, G. Mello, E. Parretti, R. Cioni, C. Marzari, M. Masin, A. Ognibene, G. Messeri, D. Fedele, A. Mari, G. Pacini, Early detection of insulin sensitivity and beta-cell function with simple tests indicates future derangements in late pregnancy. J. Clin. Endocrinol. Metab. 93, 876–880 (2008) 6. M. Blu¨her, A. Rudich, N. Klo¨ting, R. Golan, Y. Henkin, E. Rubin, D. Schwarzfuchs, Y. Gepner, M.J. Stampfer, M. Fiedler, J. Thiery, M. Stumvoll, I. Shai, Two patterns of adipokine and other biomarker dynamics in a long-term weight loss intervention. Diabetes Care 35, 342–349 (2012) 7. Z. Goktas, N. Moustaid-Moussa, C.L. Shen, M. Boylan, H. Mo, S. Wang, Effects of bariatric surgery on adipokine-induced inflammation and insulin resistance. Front. Endocrinol. (Lausanne) 4, 69 (2013) 8. K. Miehle, H. Stepan, M. Fasshauer, Leptin, adiponectin and other adipokines in gestational diabetes mellitus and preeclampsia. Clin. Endocrinol. (Oxf). 76, 2–11 (2012) 9. R. Retnakaran, A.J. Hanley, N. Raif, P.W. Connelly, M. Sermer, B. Zinman, Reduced adiponectin concentration in women with gestational diabetes: a potential factor in progression to type 2 diabetes. Diabetes Care 27, 799–800 (2004)
Endocrine 10. D. Cortelazzi, S. Corbetta, S. Ronzoni, F. Pelle, A. Marconi, V. Cozzi, I. Cetin, R. Cortelazzi, P. Beck-Peccoz, A. Spada, Maternal and foetal resistin and adiponectin concentrations in normal and complicated pregnancies. Clin. Endocrinol. (Oxf). 66, 447–453 (2007) 11. K.Y. Lain, A.R. Daftary, R.B. Ness, J.M. Roberts, First trimester adipocytokine concentrations and risk of developing gestational diabetes later in pregnancy. Clin. Endocrinol. (Oxf). 69, 407–411 (2008) 12. K. Rabe, M. Lehrke, K.G. Parhofer, U.C. Broedl, Adipokines and insulin resistance. Mol. Med. 14, 741–751 (2008) 13. G. Murdolo, M. Piroddi, F. Luchetti, C. Tortoioli, B. Canonico, C. Zerbinati, F. Galli, L. Iuliano, Oxidative stress and lipid peroxidation by-products at the crossroad between adipose organ dysregulation and obesity-linked insulin resistance. Biochimie 95, 585–594 (2013) 14. K. Bergmann, G. Sypniewska, Diabetes as a complication of adipose tissue dysfunction. Is there a role for potential new biomarkers? Clin. Chem. Lab. Med. 51, 177–185 (2013) 15. M. Blu¨her, Vaspin in obesity and diabetes: pathophysiological and clinical significance. Endocrine 41, 176–182 (2012) 16. B.S. Youn, N. Klo¨ting, J. Kratzsch, N. Lee, J.W. Park, E.S. Song, K. Ruschke, A. Oberbach, M. Fasshauer, M. Stumvoll, M. Blu¨her, Serum vaspin concentrations in human obesity and type 2 diabetes. Diabetes 57, 372–377 (2008) 17. B.K. Tan, D. Heutling, J. Chen, S. Farhatullah, R. Adya, S.D. Keay, C.R. Kennedy, H. Lehnert, H.S. Randeva, Metformin decreases the adipokine vaspin in overweight women with polycystic ovary syndrome concomitant with improvement in insulin sensitivity and a decrease in insulin resistance. Diabetes 57, 1501–1507 (2008) 18. E. Herrera, H. Ortega-Senovilla, Disturbances in lipid metabolism in diabetic pregnancy—are these the cause of the problem? Best. Pract. Res. Clin. Endocrinol. Metab. 24, 515–525 (2010) 19. S.H. Choi, S.H. Kwak, Y. Lee, M.K. Moon, S. Lim, Y.J. Park, H.C. Jang, M.S. Kim, Plasma vaspin concentrations are elevated in metabolic syndrome in men and are correlated with coronary atherosclerosis in women. Clin. Endocrinol. (Oxf). 75, 628–635 (2011) 20. H.S. Cura, H.H. Ozdemir, C.F. Demir, S. Bulut, N. Ilhan, M.F. Inci, Investigation of vaspin level in patients with acute ischemic stroke. J. Stroke Cerebrovasc. Dis. 23, 453–456 (2014) 21. C. von Loeffelholz, M. Mo¨hlig, A.M. Arafat, F. Isken, J. Spranger, K. Mai, H.S. Randeva, A.F. Pfeiffer, M.O. Weickert, Circulating vaspin is unrelated to insulin sensitivity in a cohort of nondiabetic humans. Eur. J. Endocrinol. 162, 507–513 (2010) 22. S. Akbarzadeh, I. Nabipour, S.M. Jafari, A. Movahed, N. Motamed, M. Assadi, N. Hajian, Serum visfatin and vaspin levels in normoglycemic first-degree relatives of Iranian patients with type 2 diabetes mellitus. Diabetes Res. Clin. Pract. 95, 132–138 (2012) 23. A. Gkiomisi, K.G. Makedou, A.D. Anastasilakis, S.A. Polyzos, A. Kourtis, S. Gerou, E. Gavana, T. Dagklis, D. Rousso, C. Giannoulis, Serum vaspin levels in women with and without gestational diabetes mellitus during pregnancy and postpartum. Cytokine 61, 127–132 (2013) 24. H. Stepan, S. Kralisch, K. Klostermann, S. Schrey, C. Reisenbu¨chler, M. Verlohren, H.J. Verlohren, K. Drynda, M. Blu¨her, M. Stumvoll, J. Kratzsch, P. Kovacs, M. Fasshauer, Preliminary report: circulating levels of the adipokine vaspin in gestational diabetes mellitus and preeclampsia. Metabolism 59, 1054–1056 (2010) 25. K. Li, L. Li, M. Yang, H. Liu, D. Liu, H. Yang, G. Boden, G. Yang, Short-term continuous subcutaneous insulin infusion decreases the plasma vaspin levels in patients with type 2 diabetes mellitus concomitant with improvement in insulin sensitivity. Eur. J. Endocrinol. 164, 905–910 (2011)
26. S. Teshigawara, J. Wada, K. Hida, A. Nakatsuka, J. Eguchi, K. Murakami, M. Kanzaki, K. Inoue, T. Terami, A. Katayama, I. Iseda, Y. Matsushita, N. Miyatake, J.F. McDonald, K. Hotta, H. Makino, Serum vaspin concentrations are closely related to insulin resistance, and rs77060950 at SERPINA12 genetically defines distinct group with higher serum levels in Japanese population. J. Clin. Endocrinol. Metab. 97, E1202–E1207 (2012) 27. HAPO Study Cooperative Research Group, B.E. Metzger, L.P. Lowe, A.R. Dyer, E.R. Trimble, U. Chaovarindr, D.R. Coustan, D.R. Hadden, D.R. McCance, M. Hod, H.D. McIntyre, J.J. Oats, B. Persson, M.S. Rogers, D.A. Sacks, Hyperglycemia and adverse pregnancy outcomes. N. Engl. J. Med. 358, 1991–2002 (2008) 28. H.M. Chang, H.J. Lee, H.S. Park, J.H. Kang, K.S. Kim, Y.S. Song, Y.J. Jang, Effects of weight reduction on serum vaspin concentrations in obese subjects: modification by insulin resistance. Obesity 18, 2105–2110 (2010) 29. K. Hida, J. Wada, J. Eguchi, H. Zhang, M. Baba, A. Seida, I. Hashimoto, T. Okada, A. Yasuhara, A. Nakatsuka, K. Shikata, S. Hourai, J. Futami, E. Watanabe, Y. Matsuki, R. Hiramatsu, S. Akagi, H. Makino, Y.S. Kanwar, Visceral adipose tissue-derived serine protease inhibitor: a unique insulin-sensitizing adipocytokine in obesity. Proc. Natl. Acad. Sci. USA 102, 10610–10615 (2005) 30. M.M. Roca-Rodrı´guez, C. Lo´pez-Tinoco, A. Ferna´ndez-Deudero, M. Murri, M.V. Garcı´a-Palacios, M.A. Garcı´a-Valero, F.J. Tinahones-Maduen˜o, M. Aguilar-Diosdado, Adipokines and metabolic syndrome risk factors in women with previous gestational diabetes mellitus. Diabetes Metab. Res. Rev. 28, 542–548 (2012) 31. N. Klo¨ting, P. Kovacs, M. Kern, J.T. Heiker, M. Fasshauer, M.R. Scho¨n, M. Stumvoll, A.G. Beck-Sickinger, M. Blu¨her, Central vaspin administration acutely reduces food intake and has sustained blood glucose-lowering effects. Diabetologia 54, 1819–1823 (2011) 32. C. Qiu, M.A. Williams, S. Vadachkoria, I.O. Frederick, D.A. Luthy, Increased maternal plasma leptin in early pregnancy and risk of gestational diabetes mellitus. Obstet. Gynecol. 103, 519–525 (2004) 33. S. Liu, Y. Dong, T. Wang, S. Zhao, K. Yang, X. Chen, C. Zheng, Vaspin inhibited proinflammatory cytokine induced activation of nuclear factor-kappa B and its downstream molecules in human endothelial EA.hy926 cells. Diabetes Res. Clin. Pract. 103, 482–488 (2014) 34. A. Giomisi, A. Kourtis, K.A. Toulis, A.D. Anastasilakis, K.G. Makedou, M. Mouzaki, S. Gerou, E. Gavana, T. Agorastos, C. Giannoulis, Serum vaspin levels in normal pregnancy in comparison with non-pregnant women. Eur. J. Endocrinol. 164, 579–583 (2011) 35. J.G. Ray, H. Berger, L.L. Lipscombe, M. Sermer, Gestational prediabetes: a new term for early prevention? Indian J. Med. Res. 132, 251–255 (2010) 36. C. Sommer, K. Mørkrid, A.K. Jenum, L. Sletner, A. Mosdøl, K.I. Birkeland, Weight gain, total fat gain and regional fat gain during pregnancy and the association with gestational diabetes: a population-based cohort study. Int. J. Obes. (Lond). 38, 76–81 (2014) 37. A.E. Ruifrok, M.N. van Poppel, M. van Wely, E. Rogozin´ska, K.S. Khan, C.J. de Groot, S. Thangaratinam, B.W. Mol, Association between weight gain during pregnancy and pregnancy outcomes after dietary and lifestyle interventions: a meta-analysis. Am. J. Perinatol. 31, 353–364 (2014) 38. M.P. Malee, A. Verma, G. Messerlian, R. Tucker, B.R. Vohr, Association between maternal and child leptin levels 9 years after pregnancy complicated by gestational diabetes. Horm. Metab. Res. 34, 212–216 (2002) 39. M. Lacroix, M.C. Battista, M. Doyon, J. Me´nard, J.L. Ardilouze, P. Perron, M.F. Hivert, Lower adiponectin levels at first trimester
123
Endocrine of pregnancy are associated with increased insulin resistance and higher risk of developing gestational diabetes mellitus. Diabetes Care 36, 1577–1583 (2013) 40. R. Retnakaran, Y. Qi, P.W. Connelly, M. Sermer, A.J. Hanley, B. Zinman, Low adiponectin concentration during pregnancy predicts postpartum insulin resistance, beta cell dysfunction and fasting glycaemia. Diabetologia 53, 268–276 (2010) 41. M.M. Hedderson, J. Darbinian, P.J. Havel, C.P. Quesenberry, S. Sridhar, S. Ehrlich, A. Ferrara, Low prepregnancy adiponectin concentrations are associated with a marked increase in risk for development of gestational diabetes mellitus. Diabetes Care 36, 3930–3937 (2013)
123
42. M. Ballesteros, I. Simo´n, J. Vendrell, V. Ceperuelo-Mallafre´, R.M. Miralles, G. Albaiges, F. Tinahones, A. Megia, Maternal and cord blood adiponectin multimeric forms in gestational diabetes mellitus: a prospective analysis. Diabetes Care 34, 2418–2423 (2011) 43. A. Borai, C. Livingstone, I. Kaddam, G. Ferns, Selection of the appropriate method for the assessment of insulin resistance. BMC Med. Res. Methodol. 11, 158 (2011)
ORIGINAL ARTICLE
Comparative analysis of vaspin in pregnant women with and without gestational diabetes mellitus and healthy non-pregnant women Xiaojiao Jia • Shuyi Wang • Ning Ma Xiaojing Li • Likui Guo • Xiaoli Liu • Tao Dong • Yali Liu • Qiang Lu
•
Received: 26 December 2013 / Accepted: 23 May 2014 Ó Springer Science+Business Media New York 2014
Abstract To explore serum vaspin, leptin, and adiponectin levels and their correlation with insulin resistance (IR) in pregnant women with and without gestational diabetes mellitus (GDM) and healthy non-pregnant women. A total of 262 individuals, including pregnant women with GDM (n = 86), those without GDM (n = 92), and age-matched healthy non-pregnant women (n = 84) were enrolled in this case–control study. Vaspin, leptin, adiponectin, glucose, insulin, hemoglobin A1C (HbA1c), and lipid parameters were measured. The homeostasis model assessment–insulin resistance (HOMA–IR), quantitative insulin sensitivity check index, and body mass index were calculated. Data inferred higher concentrations of vaspin (2.72 ± 2.20 vs. 1.84 ± 1.57 vs. 0.81 ± 1.02) in GDM than during normal pregnancy and in non-pregnant women, higher leptin (23.42 ± 12.18 vs. 22.19 ± 10.55 vs. 12.10 ± 11.26), and
X. Jia Department of Endocrinology, Hebei Medical University, Shijiazhuang, China X. Jia N. Ma X. Liu Q. Lu (&) Department of Endocrinology, The First Hospital of Qinhuangdao, No.258, Wenhua Road, Qinhuangdao 066000, Hebei, China e-mail: [email protected] S. Wang Department of Clinical Laboratory, The First Hospital of Qinhuangdao, Qinhuangdao, China X. Li L. Guo Department of Obstetrics and Gynecology, The First Hospital of Qinhuangdao, Qinhuangdao, China T. Dong Y. Liu Department of Physical Examination Center, The First Hospital of Qinhuangdao, Qinhuangdao, China
lower adiponectin (4,164.83 ± 2,650.39 vs. 4,871.66 ± 2,803.51 vs. 7,202.85 ± 4,893.13) in GDM and normal pregnancy as compared to non-pregnant women (p \ 0.05). Vaspin was positively correlated to leptin (r = 0.273, p = 0.012), HOMA–IR (r = 0.387, p = 0.000), and triglycerides (TG, r = 0.218, p = 0.046) in GDM. In addition, leptin was negatively correlated to adiponectin in GDM (r = -0.336, p = 0.002) and normal pregnancy (r = -0.256, p = 0.014). Furthermore, vaspin was significantly correlated to GDM and HOMA–IR, and the weight gain might play a vital role in the occurrence of GDM. During pregnancy, high vaspin concentration is significantly associated with IR in GDM. Keywords Vaspin Adipokines Gestational diabetes mellitus Homeostatic model assessment–insulin resistance
Introduction Gestational diabetes mellitus (GDM) is a pregnancy complication with elevated plasma glucose levels which will influence maternal-child health, due to fetal malformation, premature delivery, late-onset diabetes, and metabolic syndrome (MS) [1], Therefore, timely intervention is particularly important. In recent years, the reported prevalence of GDM in different ethnic groups and based on various diagnostic criteria ranged from 1 to 15 % [2, 3]. To the best of our knowledge, fasting insulin levels can be increased by up to two-fold at the third trimester of pregnancy compared with pre-pregnancy, while insulin sensitivity declines by 50–70 % in pregnancy [4]. Lapolla et al. [5] reported women with impaired insulin sensitivity in early pregnancy may be easy to diagnose with GDM in late pregnancy. It is
123
Endocrine
well known that IR is an important characteristic of GDM, it is complicated and closely associated with genetic factors, higher body mass index (BMI), and adipokineinduced inflammation [6, 7]. Recently, studies reported that adipose tissue was not only a depot of energy but also an active endocrine organ. Since the first adipocytokine–leptin was discovered, our understanding of adipose tissue has fundamentally changed. Even though study results have varied, a change in the concentrations of adipocytokines has been observed in GDM. In addition, high leptin concentrations were associated with increased risk of developing GDM [8], and may be useful for early diagnosis of GDM. Moreover, studies showed lower adiponectin in GDM as compared to normal pregnant controls [9, 10], and women with reduced circulating adiponectin levels in the first trimester of pregnancy were more likely to be diagnosed with GDM [11]. To our knowledge, disorders of adipocytokines played an important role in the occurrence, development, and prognosis of IR [12] and GDM characterized by IR [13, 14]. IR is complex and may be regulated by as yet unrecognized factors—the exact mechanisms are not entirely understood. Visceral adipose tissue-derived serpin (vaspin) has been regarded as a novel adipokine with potential insulin-sensitizing properties. Elevated circulating vaspin levels have been associated with obesity, impaired insulin sensitivity [15–17], lipid metabolism [18], and MS related diseases [19, 20]. However, in contrast to these data, several studies did not find an association between circulating vaspin and insulin sensitivity [21, 22] or parameters of obesity and fat distribution [22]. Vaspin is probably a valuable serological marker in GDM, but there is a lack of evidence regarding the relationship between vaspin and GDM, and there are no uniform opinions amongst researchers [23, 24]. We studied the serum levels of leptin, adiponectin, and vaspin to determine the relationship between adipocytokines, IR, and GDM. Based on current studies [25, 26], we hypothesized that circulating levels of vaspin would be increased and more closely correlated with IR in GDM than in other groups.
Subjects and methods Subjects After obtaining informed consent from all participants and approval from the local Ethics Committee, a cross-sectional study was conducted. From July 2012 to April 2013, we enrolled 262 women, aged 18–35 years old, who presented to the First Hospital of Qinhuangdao for obstetrical examination or health examination. Serum samples were
123
obtained at 24–28 weeks of gestation in pregnant women. Samples were stored at -80 °C until analysis. Non-pregnant women were required to be in good health. To avoid the interference of other confounding factors on the possible relation between adipocytokines and IR, multipara, diabetes, liver or renal insufficiency, rheumatologic disease, thyroid diseases, polycystic ovary syndrome (PCOS), tumor, use of corticosteroids or metformin, and acute or chronic inflammation were excluded. Measurements Anthropometric measurements, including height, weight, and blood pressure were taken. Blood pressure was measured twice with a mercury sphygmomanometer after 10 min of rest while the subjects were seated, and the average of the two measurements was used for analysis. Pre-pregnancy weight and family history (i.e., hypertension, obesity, and diabetes) were recorded. Definitions The subjects were divided into three groups. GDM was defined according to the results of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study: if fasting venous plasma glucose exceeds 92 mg/dL or 1 h 180 mg/ dL or 2 h 153 mg/dL after glucose loading (a 75 g 2-h oral glucose tolerance test, OGTT) [27]. GDM patients were all newly diagnosed and had not received lifestyle interventions or insulin treatment. In addition, BMI-1, BMI-2, BMI-3, and weight gain were defined as follows: BMI-1 (BMI at pre-pregnancy in GDM and normal pregnancy); BMI-2 (BMI at 24–28 weeks of gestation in GDM and normal pregnancy, and at the moment of blood acquisition in healthy non-pregnant women); BMI-3 (multiply D value of BMI-2 and BMI-1 by 100 % in GDM and normal pregnancy), and weight gain (D value of weight at 24–28 weeks of gestation and pre-pregnancy). Laboratory examinations Each patient underwent an OGTT with 75 g of oral anhydrous glucose that was initiated at 8:00 am, and blood samples were taken at the same time. Plasma glucose levels were measured using the glucose oxidase method, and serum lipid levels were measured using an autoanalyzer (Hitachi, Tokyo, Japan). HbA1c was determined by high performance liquid chromatography (HPLC), which was standard in the Diabetes Control and Complications Trial (DCCT) and National Glycohemoglobin Standardization Program (NGSP). Insulin concentrations were measured by radioimmunological assay using a commercially available kit (North Institute of Biological Technology, Beijing,
Endocrine
China). Serum levels of leptin, adiponectin, and vaspin were measured by enzyme-linked immunosorbent assay using available kits (BioVendor, intra-assay coefficients of variation (CV) are 4.2 and 7.6 %, inter-assay are 6.7 and 4.4 %, the limit of Detection is 0.2 ng/mL; R&D systems, intra-assay Precision CV are 2.5, 3.4, and 4.7 %, interassay Precision are 6.8, 5.8, and 6.9 %, the minimum detectable dose (MDD) about adiponectin ranged from 0.079 to 0.891 ng/mL and the mean MDD was 0.246 ng/ mL; AdipoGen, intra-assay Precision CV are 1.310, 3.846, 3.272, 3.630, and 1.743 %, inter-assay Precision are 5.929, 3.267, 3.693, 9.0645, and 8.3165 %, the lowest levels of vaspin that can be detected are 12 pg/mL. The following equations were used for the HOMA–IR index and QUICKI: [fasting insulin level (mIU/L) 9 fasting glucose level (mmol/L)]/22.5 and 1/[log(fasting insulin) ? log(log fasting insulin)], respectively. IR was represented by HOMA–IR. Statistical analysis All analyses were performed using the SPSS 13.0 statistical software. Values were expressed as mean ± standard deviation, and when not normally distributed, they were transformed for analysis using t test, non-parametric equivalent test, ANOVA, or Chi square for comparisons, as appropriate. To measure the strength of the association between two variables, a simple scatter plot and Pearson correlation coefficient were used. Three multiple linear regression models (stepwise method) were used to evaluate the relationships between various parameters and IR. A binary logistic regression analysis (enter method) was performed to decide relationships between various parameters and GDM. HOMA–IR was the dependent variable, and age, BMI-1, BMI-2, BMI-3, weight gain, vaspin, leptin, adiponectin, triglycerides (TG), and total cholesterol (TC) were used as independent variables in the GDM group (model 1) and normal pregnancy (model 2). Age, BMI-2, vaspin, leptin, adiponectin, TG, and TC were used as independent variables in the healthy non-pregnant group (model 3). P \ 0.05 was considered statistically significant.
Results Clinical and laboratory characteristics in the study subjects are shown in Table 1. Age, diastolic blood pressure(DBP), QUICKI, family history of diabetes, and obesity were similar among the three groups. Furthermore, BMI-1 and BMI-2 in pregnancy with and without GDM were similar (p [ 0.05). However, family history of hypertension was significantly different between the GDM (21.4 %) and
healthy non-pregnant group (40.5 %; p \ 0.017). Serum vaspin, glucose (1, 2 h), HbA1c, and HOMA–IR levels were significantly higher in the GDM than in the other groups (p \ 0.05). Higher levels of leptin and insulin(0 h), and lower adiponectin concentrations were observed in pregnant women (both GDM and normal pregnancy) as compared to healthy non-pregnant women (p \ 0.05). In addition, BMI-2 in the non-pregnant group was significantly lower as compared to pregnant women, and there was a higher weight gain in normal pregnancy than in GDM. Figure 1 shows the scatter plot of vaspin and HOMA–IR in GDM. In addition, the correlation coefficients indicate that vaspin was positively associated with leptin (r = 0.273, p = 0.012), HOMA–IR (r = 0.387, p = 0.000) and TG (r = 0.218, p = 0.046) in GDM, but not in the other groups. Leptin was negatively correlated to adiponectin in GDM (r = -0.336, p = 0.002) and in normal pregnancy (r = -0.256, p = 0.014), but not in healthy non-pregnant group. Table 2 shows partial data of the correlation analyses for adipocytokines. In the multiple linear regression model (model 1), HOMA–IR was independently associated with BMI-2, vaspin, and leptin in GDM (Table 3). In model 2, HOMA– IR was independently associated with adiponectin and TG. In model 3, HOMA–IR was independently associated with BMI-2. Similarly, in binary logistic regression (Table 4), weight gain, vaspin, HOMA–IR, and TC were independently associated with GDM. Hence, vaspin is an important determinant of IR in GDM but not in other groups, and weight gain is more closely related with GDM.
Discussion Adipose tissue is a highly active endocrine organ secreting a number of bioactive molecules called adipocytokines [7, 16, 28]. Vaspin was identified as an adipokine, which is predominantly secreted from visceral adipose tissue. Interestingly, vaspin might be an adipokine with potential insulin-sensitizing properties [25, 29], and vaspin serum concentrations have been associated with glucolipid metabolism [18, 30, 31]. In addition, adiponectin is considered to be an insulin-sensitizing adipokine; during the course of pregnancy, maternal adiponectin secretion declines progressively, and circulating adiponectin levels are reduced in GDM as compared to normal pregnancy [9, 10]. Low serum adiponectin levels might further aggravate insulin resistance, and down regulation of adiponectin in the first trimester of pregnancy is an independent predictor for GDM. In contrast to previous studies [23, 24], we found higher levels of vaspin [25, 26] in GDM, and higher leptin [32] and lower adiponectin [10] concentrations in
123
Endocrine Table 1 Baseline characteristics of the study population GDM
Normal pregnancy
Healthy non-pregnant
n
84
92
80
Vaspin (ng/mL)
2.72 ± 2.20
1.84 ± 1.57*
0.81 ± 1.02*,#
Leptin (ng/mL)
23.42 ± 12.18
22.19 ± 10.55
12.10 ± 11.26*,#
Adiponectin (ng/mL)
4,164.83 ± 2,650.39
4,871.66 ± 2,803.51
7,202.85 ± 4,893.13*,# 29.44 ± 4.51
a
Age (years)
29.19 ± 3.91
28.43 ± 3.35
Gestational Ageb (weeks)
25.29 ± 1.60
25.87 ± 1.50*
–
BMI-1c (kg/m2)
23.38 ± 3.72
22.15 ± 3.04
–
BMI-2d (kg/m2)
26.75 ± 3.53
26.60 ± 5.50
22.41 ± 4.63*,#
BMI-3e (kg/m2)
15.18 ± 9.79
19.68 ± 9.27*
–
f
Weight gain (kg)
8.86 ± 5.39
11.11 ± 4.82*
–
SBP (mmHg) DBP (mmHg)
107.99 ± 12.22 69.37 ± 8.62
110.66 ± 12.89* 70.04 ± 8.87
104.39 ± 12.13# 66.85 ± 9.35
Glucose 0 h (mmol/L)
5.02 ± 0.82
4.28 ± 0.34*
4.88 ± 0.52#
Glucose 1 h (mmol/L)
9.61 ± 1.89
7.07 ± 1.21*
7.24 ± 1.92*
Glucose 2 h (mmol/L)
8.05 ± 2.02
6.25 ± 0.96*
6.18 ± 1.13*
HbA1c (%)
5.47 ± 0.28
5.19 ± 0.45*
5.07 ± 0.41*
Insulin 0 h (mIU/L)
10.79 ± 6.61
9.74 ± 4.10
7.45 ± 4.73*,#
HOMA–IR
2.44 ± 1.61
1.86 ± 0.82*
1.63 ± 1.16*
QUICKI
0.64 ± 0.17
0.63 ± 0.06
0.66 ± 0.06
TG (mmol/L)
2.22 ± 0.94
2.41 ± 0.94
0.94 ± 0.43*,#
TC (mmol/L)
5.40 ± 1.18
6.14 ± 1.13*
4.53 ± 0.65*,#
Family history of diabetes (%)
21.4
16.3
27.5
Family history of obesity (%)
22.6
29.3
18.8
Family history of hypertension (%)
21.4
28.3
40.5*
BMI body mass index, DBP diastolic blood pressure, GDM gestational diabetes mellitus, HOMA–IR homeostatic model assessment–insulin resistance, QUICKI quantitative insulin sensitivity check index, SBP systolic blood pressure, TG triglycerides, TC total cholesterol * p \ 0.05 as compared with GDM; #p \ 0.05 as compared with normal pregnancy a
Age, age at blood acquisition
b
Gestational age, gestational age at blood acquisition
c
BMI-1, BMI at pre-pregnancy in GDM and normal pregnancy
d
BMI-2, BMI at 24–28 weeks of gestation in GDM and normal pregnancy, and at the moment of blood acquisition in healthy non-pregnant women e BMI-3, Multiply D value of BMI-2 and BMI-1 by 100 % in GDM and normal pregnancy f
Weight gain, D value of weight at 24–28 weeks of gestation and pre-pregnancy
pregnancy. These findings may be related to different controls, races, or periods of blood acquisition in each study. In our study, both vaspin and adiponectin levels were significantly different between pregnancy (GDM and non-GDM) and healthy non-pregnant women. Vaspin levels were also different between GDM and normal pregnant women, indicating vaspin was more closely related to the levels of insulin and IR in GDM than during normal pregnancy and in non-pregnant women. In this study, the higher levels of vaspin in GDM which might be explained by a compensative increase of insulin-sensitizing vaspin in attempt to ameliorate increased IR in GDM. It might increase at the early stage of diabetes, whereas it decreases with the worsening of the diabetes [29]. Vaspin also
123
inhibited the expressions of pro-inflammatory adipocytokines, suggesting that it might exert an anti-inflammatory role [33]. Furthermore, compared to the report by Giomisi et al. [34], our results showed that vaspin was positively correlated to leptin, HOMA–IR [26], and TG in GDM but not in the others groups [21]. Regression analyses showed that vaspin was independently associated with GDM and HOMA–IR in pregnant women with or without GDM, but not in non-pregnant women. Based on the logistic regression analysis, vaspin, weight gain, HOMA–IR, and TC were independently associated with GDM, it seems that preventing excessive weight gain might be beneficial for pregnant women [35, 36], but the women with GDM had
Endocrine
lower weight gain than normal pregnancy in our study, we still cannot conclude that gestational weight gain is associated with increased risk of GDM [37]. Overall, higher
Fig. 1 Scatter plot of vaspin and HOMA–IR in gestational diabetes mellitus HOMA–IR, homeostasis model assessment–insulin resistance Table 2 Correlation analysis for leptin, adiponectin, and vaspin BMI-2 r
HOMA–IR p
r
p
Leptin GDM
0.253
0.020
0.419
\0.001
Normal pregnancy Healthy non-pregnant
0.378 0.788
\0.001 \0.001
0.213 0.504
0.041 \0.001
Adiponectin GDM
-0.350
0.001
-0.258
0.018
Normal pregnancy
-0.256
0.014
-0.286
0.006
Healthy non-pregnant
-0.314
0.005
-0.240
0.032
0.085
0.442
0.387
\0.001
Vaspin GDM Normal pregnancy
0.077
0.463
0.105
0.318
Healthy non-pregnant
0.036
0.754
0.001
0.994
BMI-2, BMI at 24–28 weeks of gestation in GDM and normal pregnancy, and at the moment of blood acquisition in healthy nonpregnant women BMI body mass index, GDM gestational diabetes mellitus, HOMA–IR homeostatic model assessment–insulin resistance
circulating vaspin is independently associated with the occurrence of GDM. Even though, previous studies also showed obesity was correlated with many metabolic disorders, BMI-2 was significantly lower in non-pregnant women than in the pregnant groups, it was probably responsible for the differences in adipocytokines, HOMA– IR, and lipid levels between pregnant and non-pregnant women. After adjusting for BMI-2, vaspin was also significantly associated with GDM. In addition, there was higher weight gain but lower vaspin concentrations in normal pregnancy than in GDM, these may also indicate an important role of vaspin in GDM. However, the exact mechanisms linking vaspin secretion to glucose metabolism and insulin sensitivity in pregnant women with GDM are unknown. Several previous studies have reported that circulating levels of leptin were higher in pregnant women (both GDM and non-GDM group), and the strongest independent determinant of leptin was progestational BMI [32]. Our data also showed that higher leptin levels were positively correlated with IR, TC, and negatively correlated with adiponectin in GDM. Moreover, BMI-2, vaspin, and leptin
Table 4 Binary logistic regression analysis for gestational diabetes mellitus Variables
Unstandardized coefficients
Weight gain
-0.088
0.916
0.013
0.855–0.982
0.230
1.258
0.017
1.041–1.521
Vaspin HOMA–IR TC
Exp (B)
p
95 % CI for Exp (B)
0.338
1.402
0.039
1.018–1.931
-0.571
0.565
\0.001
0.414–0.772
2.840
17.124
0.004
Constant
–
Normal pregnancy was rated as 0 and GDM group as 1 within dependent variable; age, BMI-1, BMI-2, BMI-3, weight gain, vaspin, leptin, adiponectin, HOMA–IR, TG, and TC as independents. Weight gain, D value of weight at 24–28 weeks of gestation and prepregnancy BMI body mass index, HOMA–IR homeostatic model assessment– insulin resistance, TC total cholesterol Test for the equation (v2 = 39.249, p \ 0.05)
Table 3 Multiple linear regression analysis (GDM group, n = 84) Variables
Unstandardized coefficients b
SE
Standardized coefficients b
t
95 CI % for b
p
BMI-2
0.191
0.040
0.418
4.742
\0.001
0.111 to 0.271
Vaspin
0.211
0.065
0.287
3.244
0.002
0.081 to 0.340
0.031
0.012
0.234
-3.975
1.055
–
Leptin Constant
2.567
0.012
-3.766
\0.001
0.007 to 0.055 -6.075 to -1.874
BMI-2, BMI during 24–28 weeks of gestation BMI body mass index, GDM gestational diabetes mellitus
123
Endocrine
were significantly associated with HOMA–IR in GDM. Therefore, we can also see the significance of leptin [38] in pregnant women. Similarly, there were significantly reduced plasma concentrations of adiponectin in pregnant women [10], and lower adiponectin levels were associated with IR, GDM, and macrosomia [39, 40]. However, data showed that adiponectin was negatively correlated with BMI-2 and HOMA–IR in all three groups. Recently, a USbased nested case–control study indicated that in pregnancy low adiponectin concentrations may identify women at high risk for GDM, and the risk of developing GDM in these women is 5 times higher than for other pregnant women [41]. However, there is no significant difference in adiponectin between GDM and normal pregnant women, and it is unrelated to the diagnosis of GDM [42]. Still, we believe that adiponectin is associated with GDM. However, the reason for the higher levels of TG and TC in normal pregnant women is not clear but it is probably associated with adipocytokines or BMI. In addition, QUICKI was similar among the three groups in this study. Although there were higher HOMA–IR levels in the GDM group. To the best of our knowledge, different indices for the assessment of IR vary widely in their reliability. The QUICKI index is similar to HOMA, except that it interprets the data by taking both logarithms and the reciprocal of the fasting glucose and insulin levels, HOMA– IR and QUICKI cannot completely replace each other [43]. Metabolic disorders are complex. Although the initial factor in the pathophysiology of metabolic disorders is unknown, adipocytokines might provide an extensive network of communication within adipose tissue, and play a role in hyperglycemia, obesity, and IR. Studies have showed that leptin [32] and adiponectin [39, 41] were involved in a wide range of physiological processes including lipid metabolism and insulin sensitivity [8]. Previous studies suggested that plasma vaspin levels are associated with IR and are significantly reduced following short-term Continuous Subcutaneous Insulin Infusion (CSII) treatment [25]. Chang et al. [28] also reported that a short-term weight reduction caused significantly decreased vaspin levels. Metformin has demonstrated a beneficial effect in decreasing vaspin concomitant with improvement in insulin sensitivity and a decrease in IR [17]. In our study, we found significantly different levels of vaspin and IR but similar baseline (BMI-1 and -2) between GDM and normal pregnancy, in addition, vaspin was also significantly associated with GDM after adjusting for BMI-2. This study has some limitations. First, this is just a case– control and small sample study, the phenomenon we observed still needs to be further studied. Second, it is necessary to develop a paired design, increase the number of type 2 diabetic women with and without gestation, and divide the gestation period into more detailed phases to
123
achieve a better control. Third, it will be a greatly significant to monitor the circulating vaspin levels in GDM and pGDM patients, and it is necessary for us to conduct basic research on adipocytokines and GDM in future. Fourth, pregnancy with higher weight gain should be excluded in future study to avoid its interference on circulating dipocytokines. In addition, the family history of hypertension is a limitation in this paper. In conclusion, circulating vaspin concentrations are significantly associated with IR in GDM, and it might be of great significance in GDM. Moreover, weight gain might play a vital role in GDM. Further work needs to be done to illustrate the specific significance of vaspin in GDM and other related diseases. All of these may provide us with a new perspective on GDM.
Conflict of interest All authors have no conflicts of interest to disclose, and this study was self-financed.
References 1. L. Bellamy, J.P. Casas, A.D. Hingorani, D. Williams, Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet 373, 1773–1779 (2009) 2. P. Kalra, C.P. Kachhwaha, H.V. Singh, Prevalence of gestational diabetes mellitus and its outcome in western Rajasthan. Indian J. Endocrinol. Metab. 17, 677–680 (2013) 3. D. Dabelea, J.K. Snell-Bergeon, C.L. Hartsfield, K.J. Bischoff, R.F. Hamman, R.S. McDuffie, Kaiser Permanente of Colorado GDM Screening Program: increasing prevalence of gestational diabetes mellitus (GDM) over time and by birth cohort: Kaiser Permanente of Colorado GDM Screening Program. Diabetes Care 28, 579–584 (2005) 4. L.A. Barbour, C.E. McCurdy, T.L. Hernandez, J.P. Kirwan, P.M. Catalano, J.E. Friedman, Cellular mechanisms for insulin resistance in normal pregnancy and gestational diabetes. Diabetes Care 30, S112–S119 (2007) 5. A. Lapolla, M.G. Dalfra`, G. Mello, E. Parretti, R. Cioni, C. Marzari, M. Masin, A. Ognibene, G. Messeri, D. Fedele, A. Mari, G. Pacini, Early detection of insulin sensitivity and beta-cell function with simple tests indicates future derangements in late pregnancy. J. Clin. Endocrinol. Metab. 93, 876–880 (2008) 6. M. Blu¨her, A. Rudich, N. Klo¨ting, R. Golan, Y. Henkin, E. Rubin, D. Schwarzfuchs, Y. Gepner, M.J. Stampfer, M. Fiedler, J. Thiery, M. Stumvoll, I. Shai, Two patterns of adipokine and other biomarker dynamics in a long-term weight loss intervention. Diabetes Care 35, 342–349 (2012) 7. Z. Goktas, N. Moustaid-Moussa, C.L. Shen, M. Boylan, H. Mo, S. Wang, Effects of bariatric surgery on adipokine-induced inflammation and insulin resistance. Front. Endocrinol. (Lausanne) 4, 69 (2013) 8. K. Miehle, H. Stepan, M. Fasshauer, Leptin, adiponectin and other adipokines in gestational diabetes mellitus and preeclampsia. Clin. Endocrinol. (Oxf). 76, 2–11 (2012) 9. R. Retnakaran, A.J. Hanley, N. Raif, P.W. Connelly, M. Sermer, B. Zinman, Reduced adiponectin concentration in women with gestational diabetes: a potential factor in progression to type 2 diabetes. Diabetes Care 27, 799–800 (2004)
Endocrine 10. D. Cortelazzi, S. Corbetta, S. Ronzoni, F. Pelle, A. Marconi, V. Cozzi, I. Cetin, R. Cortelazzi, P. Beck-Peccoz, A. Spada, Maternal and foetal resistin and adiponectin concentrations in normal and complicated pregnancies. Clin. Endocrinol. (Oxf). 66, 447–453 (2007) 11. K.Y. Lain, A.R. Daftary, R.B. Ness, J.M. Roberts, First trimester adipocytokine concentrations and risk of developing gestational diabetes later in pregnancy. Clin. Endocrinol. (Oxf). 69, 407–411 (2008) 12. K. Rabe, M. Lehrke, K.G. Parhofer, U.C. Broedl, Adipokines and insulin resistance. Mol. Med. 14, 741–751 (2008) 13. G. Murdolo, M. Piroddi, F. Luchetti, C. Tortoioli, B. Canonico, C. Zerbinati, F. Galli, L. Iuliano, Oxidative stress and lipid peroxidation by-products at the crossroad between adipose organ dysregulation and obesity-linked insulin resistance. Biochimie 95, 585–594 (2013) 14. K. Bergmann, G. Sypniewska, Diabetes as a complication of adipose tissue dysfunction. Is there a role for potential new biomarkers? Clin. Chem. Lab. Med. 51, 177–185 (2013) 15. M. Blu¨her, Vaspin in obesity and diabetes: pathophysiological and clinical significance. Endocrine 41, 176–182 (2012) 16. B.S. Youn, N. Klo¨ting, J. Kratzsch, N. Lee, J.W. Park, E.S. Song, K. Ruschke, A. Oberbach, M. Fasshauer, M. Stumvoll, M. Blu¨her, Serum vaspin concentrations in human obesity and type 2 diabetes. Diabetes 57, 372–377 (2008) 17. B.K. Tan, D. Heutling, J. Chen, S. Farhatullah, R. Adya, S.D. Keay, C.R. Kennedy, H. Lehnert, H.S. Randeva, Metformin decreases the adipokine vaspin in overweight women with polycystic ovary syndrome concomitant with improvement in insulin sensitivity and a decrease in insulin resistance. Diabetes 57, 1501–1507 (2008) 18. E. Herrera, H. Ortega-Senovilla, Disturbances in lipid metabolism in diabetic pregnancy—are these the cause of the problem? Best. Pract. Res. Clin. Endocrinol. Metab. 24, 515–525 (2010) 19. S.H. Choi, S.H. Kwak, Y. Lee, M.K. Moon, S. Lim, Y.J. Park, H.C. Jang, M.S. Kim, Plasma vaspin concentrations are elevated in metabolic syndrome in men and are correlated with coronary atherosclerosis in women. Clin. Endocrinol. (Oxf). 75, 628–635 (2011) 20. H.S. Cura, H.H. Ozdemir, C.F. Demir, S. Bulut, N. Ilhan, M.F. Inci, Investigation of vaspin level in patients with acute ischemic stroke. J. Stroke Cerebrovasc. Dis. 23, 453–456 (2014) 21. C. von Loeffelholz, M. Mo¨hlig, A.M. Arafat, F. Isken, J. Spranger, K. Mai, H.S. Randeva, A.F. Pfeiffer, M.O. Weickert, Circulating vaspin is unrelated to insulin sensitivity in a cohort of nondiabetic humans. Eur. J. Endocrinol. 162, 507–513 (2010) 22. S. Akbarzadeh, I. Nabipour, S.M. Jafari, A. Movahed, N. Motamed, M. Assadi, N. Hajian, Serum visfatin and vaspin levels in normoglycemic first-degree relatives of Iranian patients with type 2 diabetes mellitus. Diabetes Res. Clin. Pract. 95, 132–138 (2012) 23. A. Gkiomisi, K.G. Makedou, A.D. Anastasilakis, S.A. Polyzos, A. Kourtis, S. Gerou, E. Gavana, T. Dagklis, D. Rousso, C. Giannoulis, Serum vaspin levels in women with and without gestational diabetes mellitus during pregnancy and postpartum. Cytokine 61, 127–132 (2013) 24. H. Stepan, S. Kralisch, K. Klostermann, S. Schrey, C. Reisenbu¨chler, M. Verlohren, H.J. Verlohren, K. Drynda, M. Blu¨her, M. Stumvoll, J. Kratzsch, P. Kovacs, M. Fasshauer, Preliminary report: circulating levels of the adipokine vaspin in gestational diabetes mellitus and preeclampsia. Metabolism 59, 1054–1056 (2010) 25. K. Li, L. Li, M. Yang, H. Liu, D. Liu, H. Yang, G. Boden, G. Yang, Short-term continuous subcutaneous insulin infusion decreases the plasma vaspin levels in patients with type 2 diabetes mellitus concomitant with improvement in insulin sensitivity. Eur. J. Endocrinol. 164, 905–910 (2011)
26. S. Teshigawara, J. Wada, K. Hida, A. Nakatsuka, J. Eguchi, K. Murakami, M. Kanzaki, K. Inoue, T. Terami, A. Katayama, I. Iseda, Y. Matsushita, N. Miyatake, J.F. McDonald, K. Hotta, H. Makino, Serum vaspin concentrations are closely related to insulin resistance, and rs77060950 at SERPINA12 genetically defines distinct group with higher serum levels in Japanese population. J. Clin. Endocrinol. Metab. 97, E1202–E1207 (2012) 27. HAPO Study Cooperative Research Group, B.E. Metzger, L.P. Lowe, A.R. Dyer, E.R. Trimble, U. Chaovarindr, D.R. Coustan, D.R. Hadden, D.R. McCance, M. Hod, H.D. McIntyre, J.J. Oats, B. Persson, M.S. Rogers, D.A. Sacks, Hyperglycemia and adverse pregnancy outcomes. N. Engl. J. Med. 358, 1991–2002 (2008) 28. H.M. Chang, H.J. Lee, H.S. Park, J.H. Kang, K.S. Kim, Y.S. Song, Y.J. Jang, Effects of weight reduction on serum vaspin concentrations in obese subjects: modification by insulin resistance. Obesity 18, 2105–2110 (2010) 29. K. Hida, J. Wada, J. Eguchi, H. Zhang, M. Baba, A. Seida, I. Hashimoto, T. Okada, A. Yasuhara, A. Nakatsuka, K. Shikata, S. Hourai, J. Futami, E. Watanabe, Y. Matsuki, R. Hiramatsu, S. Akagi, H. Makino, Y.S. Kanwar, Visceral adipose tissue-derived serine protease inhibitor: a unique insulin-sensitizing adipocytokine in obesity. Proc. Natl. Acad. Sci. USA 102, 10610–10615 (2005) 30. M.M. Roca-Rodrı´guez, C. Lo´pez-Tinoco, A. Ferna´ndez-Deudero, M. Murri, M.V. Garcı´a-Palacios, M.A. Garcı´a-Valero, F.J. Tinahones-Maduen˜o, M. Aguilar-Diosdado, Adipokines and metabolic syndrome risk factors in women with previous gestational diabetes mellitus. Diabetes Metab. Res. Rev. 28, 542–548 (2012) 31. N. Klo¨ting, P. Kovacs, M. Kern, J.T. Heiker, M. Fasshauer, M.R. Scho¨n, M. Stumvoll, A.G. Beck-Sickinger, M. Blu¨her, Central vaspin administration acutely reduces food intake and has sustained blood glucose-lowering effects. Diabetologia 54, 1819–1823 (2011) 32. C. Qiu, M.A. Williams, S. Vadachkoria, I.O. Frederick, D.A. Luthy, Increased maternal plasma leptin in early pregnancy and risk of gestational diabetes mellitus. Obstet. Gynecol. 103, 519–525 (2004) 33. S. Liu, Y. Dong, T. Wang, S. Zhao, K. Yang, X. Chen, C. Zheng, Vaspin inhibited proinflammatory cytokine induced activation of nuclear factor-kappa B and its downstream molecules in human endothelial EA.hy926 cells. Diabetes Res. Clin. Pract. 103, 482–488 (2014) 34. A. Giomisi, A. Kourtis, K.A. Toulis, A.D. Anastasilakis, K.G. Makedou, M. Mouzaki, S. Gerou, E. Gavana, T. Agorastos, C. Giannoulis, Serum vaspin levels in normal pregnancy in comparison with non-pregnant women. Eur. J. Endocrinol. 164, 579–583 (2011) 35. J.G. Ray, H. Berger, L.L. Lipscombe, M. Sermer, Gestational prediabetes: a new term for early prevention? Indian J. Med. Res. 132, 251–255 (2010) 36. C. Sommer, K. Mørkrid, A.K. Jenum, L. Sletner, A. Mosdøl, K.I. Birkeland, Weight gain, total fat gain and regional fat gain during pregnancy and the association with gestational diabetes: a population-based cohort study. Int. J. Obes. (Lond). 38, 76–81 (2014) 37. A.E. Ruifrok, M.N. van Poppel, M. van Wely, E. Rogozin´ska, K.S. Khan, C.J. de Groot, S. Thangaratinam, B.W. Mol, Association between weight gain during pregnancy and pregnancy outcomes after dietary and lifestyle interventions: a meta-analysis. Am. J. Perinatol. 31, 353–364 (2014) 38. M.P. Malee, A. Verma, G. Messerlian, R. Tucker, B.R. Vohr, Association between maternal and child leptin levels 9 years after pregnancy complicated by gestational diabetes. Horm. Metab. Res. 34, 212–216 (2002) 39. M. Lacroix, M.C. Battista, M. Doyon, J. Me´nard, J.L. Ardilouze, P. Perron, M.F. Hivert, Lower adiponectin levels at first trimester
123
Endocrine of pregnancy are associated with increased insulin resistance and higher risk of developing gestational diabetes mellitus. Diabetes Care 36, 1577–1583 (2013) 40. R. Retnakaran, Y. Qi, P.W. Connelly, M. Sermer, A.J. Hanley, B. Zinman, Low adiponectin concentration during pregnancy predicts postpartum insulin resistance, beta cell dysfunction and fasting glycaemia. Diabetologia 53, 268–276 (2010) 41. M.M. Hedderson, J. Darbinian, P.J. Havel, C.P. Quesenberry, S. Sridhar, S. Ehrlich, A. Ferrara, Low prepregnancy adiponectin concentrations are associated with a marked increase in risk for development of gestational diabetes mellitus. Diabetes Care 36, 3930–3937 (2013)
123
42. M. Ballesteros, I. Simo´n, J. Vendrell, V. Ceperuelo-Mallafre´, R.M. Miralles, G. Albaiges, F. Tinahones, A. Megia, Maternal and cord blood adiponectin multimeric forms in gestational diabetes mellitus: a prospective analysis. Diabetes Care 34, 2418–2423 (2011) 43. A. Borai, C. Livingstone, I. Kaddam, G. Ferns, Selection of the appropriate method for the assessment of insulin resistance. BMC Med. Res. Methodol. 11, 158 (2011)
