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Serum Levels of Retinol-Binding Protein 4 and Adiponectin in Women with Polycystic Ovary Syndrome: Associations with Visceral Fat But No Evidence for Fat Mass-Independent Effects on Pathogenesis in This Condition

Oxford Centre for Diabetes, Endocrinology, and Metabolism (T.M.B., C.C., J.A.H.W., M.I.M.), Churchill Hospital, Oxford OX3 7LJ, United Kingdom; School of Life Sciences (M.H., N.P.G.), Oxford Brookes University, Oxford OX3 0BP, United Kingdom; Department of Radiology (S.J.G., C.A.), John Radcliffe Hospital, Oxford OX3 9DU, United Kingdom; Department of Clinical Biochemistry (K.B., A.V.-P.), Addenbrooke’s Hospital, Cambridge CB2 0QQ, United Kingdom; and Institute of Reproductive and Developmental Biology (S.F.), Imperial College (Hammersmith Campus), London W12 0NN, United Kingdom

Address all correspondence and requests for reprints to: Dr. Tom Barber, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology, and Metabolism, Churchill Hospital, Old Road, Head-ington, Oxford OX3 7LJ, United Kingdom. E-mail: tom.barber{at}drl.ox.ac.uk.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Context: Insulin resistance, which associates with levels of retinol-binding protein 4 (RBP4) and adiponectin, is implicated in the development of polycystic ovary syndrome (PCOS).

Objective: The objective of the study was to explore the potential contribution of RBP4 and adiponectin in the etiology of PCOS and their relationships with specific fat depot measurements.

Design: This was a cross-sectional study.

Setting and Participants: Serum RBP4 and adiponectin levels were compared between 50 PCOS cases and 28 female controls (including 22 body mass index/fat mass-matched pairs) and correlated with specific fat depot (including visceral) axial magnetic resonance imaging cross-sectional area measurements. All subjects were of U.K. British/Irish origin.

Main Outcome Measure(s): Serum levels of RBP4 (automated immunonephelometric assay) and adiponectin [immunoassay: total and high molecular weight (HMW)]. Data are reported as geometric mean (SD, range) and optionally adjusted for fat mass and age.

Results: Between the 50 PCOS cases and 28 controls, serum RBP4 levels were indistinguishable [39.0 µg/ml (31.0, 49.0) vs. 41.6 µg/ml (32.7, 52.9), respectively, unadjusted P = 0.24; adjusted P = 0.55]. Total (and HMW) adiponectin levels were lower in PCOS cases [total adiponectin 19.9 µg/ml (14.2, 27.8) vs. 25.8 µg/ml (17.7, 37.7), respectively, unadjusted P = 2.4 x 10^–3; adjusted P = 0.10]. For the paired-sample analyzes, there were no differences in RBP4 (P = 0.09), total adiponectin (P = 0.06), HMW adiponectin (P =0.19), or HMW to total adiponectin ratio (P = 0.98). In PCOS cases, L4-visceral fat area was associated positively with RBP4 (r² = 0.34, P = 0.01) and negatively with HMW to total adiponectin ratio (r² = –0.44, P = 1.3 x 10^–3). Controls showed similar relationships.

Conclusions: Although associated with visceral fat, serum RBP4 and adiponectin levels do not play important, fat-mass-independent primary roles in the development of PCOS.

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Insulin resistance and obesity play a central role in the pathogenesis of polycystic ovary syndrome (PCOS) (1, 2, 3, 4, 5). Given that women with PCOS are more insulin resistant than would be expected from their body mass index (BMI) (5), an important consideration is whether adipokines such as retinol-binding protein 4 (RBP4) and adiponectin, both thought to be important mediators of insulin resistance (6, 7), are also implicated in PCOS pathogenesis.

RBP4 has recently been identified as an adipocyte-secreted protein that mediates insulin resistance in mice by enhancing hepatic gluconeogenesis and impairing insulin signaling in skeletal muscle (6). Most studies have shown that serum RBP4 levels are also elevated in insulin-resistant humans with obesity, impaired glucose tolerance, and type 2 diabetes and correlate inversely with insulin sensitivity and directly with components of the metabolic syndrome (8, 9). Furthermore, lifestyle, exercise, and pharmacological (thiazolidinediones) and surgical (bariatric surgery) interventions, which improve insulin sensitivity, also usually, although not invariably, lead to a reduction in serum RBP4 levels (10). RBP4 is therefore widely regarded as one of the key mediators of insulin resistance. However, there have been few studies that have assessed serum levels of RBP4 in women with PCOS, and these have yielded conflicting results (11, 12, 13).

Adiponectin, a 244-amino acid protein expressed exclusively in white adipose tissue (14), is a key adipokine in the mediation of the relationship between body weight and insulin sensitivity (7). Serum adiponectin plays an important role in the pathogenesis and amplification of insulin-resistant states in humans (15, 16), levels being reduced in insulin-resistant patients with type 2 diabetes (17) and obese humans (18). Unlike other adipokines, there is an inverse correlation between serum adiponectin levels and body weight (19) [resulting from down-regulation of the expression of adiponectin within adipose tissue (20)], and adiponectin has insulin-sensitizing properties [in addition to antiatherogenic (21) and antiinflammatory (22) effects]. The structure of adiponectin belongs to the complement C1q family and consists of an NH₂-terminal collagen-repeat domain and a COOH-terminal globular head domain (23). Recently it has been demonstrated that circulating adiponectin is present as several multimers (24). These consist of low-, middle-, and high-molecular-weight (HMW) forms of adiponectin. HMW adiponectin comprises 12–18 protomers (25). Recent evidence from humans and rodents suggests that the ratio of HMW to total adiponectin is more closely associated with measures of insulin sensitivity than the absolute amount of (total) adiponectin (26, 27). However, the few studies on adiponectin in PCOS to date have mainly reported on total adiponectin levels (28, 29, 30). It is therefore timely to study the ratio of HMW to total adiponectin in PCOS.

The aim of our study was to explore the relationships between the adipokines, RBP4, and adiponectin (total, HMW, and HMW to total ratio) and PCOS, particularly regarding fat mass-independent effects. A further aim was to explore the relationships of serum RBP4 and adiponectin with specific fat depot measurements and components of the metabolic syndrome in PCOS.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Subjects

All subjects were premenopausal, postmenarchal, nondiabetic, and nonpregnant. All cases (n = 50) had a definitive diagnosis of PCOS based on Rotterdam diagnostic criteria (31). More specifically, all PCOS cases had polycystic ovarian (PCO) morphology on magnetic resonance imaging (MRI) scan (31, 32), and 44 cases also met both the other Rotterdam criteria for PCOS [oligoamenorrhea (intermenstrual interval greater than 42 d) and hyperandrogenism (clinical and/or biochemical)] and so also fulfilled the 1990 National Institutes of Health criteria for definition of PCOS (33). In addition to the presence of PCO morphology, the remaining six PCOS cases each fulfilled one of the other two Rotterdam diagnostic criteria: five had hyperandrogenism but regular menses, and one had oligoamenorrhea but normoandrogenemia (Fig. 1). Other causes of hyperandrogenemia had been excluded in all PCOS cases as per Rotterdam criteria (31). Clinical definition of hyperandrogenism was a Ferriman-Gallwey score of 8 or greater and/or presence of androgenic alopecia. Biochemical hyperandrogenism was defined as a serum testosterone concentration of 2.36 nmol/liter or greater and/or free androgen index of 8.98 or greater. [Cutoff values were derived from the distribution (mean + 2 SD) for testosterone and SHBG measured with the same assays in the control group.] Cases were recruited from general endocrine and PCOS clinics at the Churchill and John Radcliffe Hospitals (Oxford, UK). All subjects were white and of British/Irish origin.

View larger version (14K): [in this window] [in a new window]   FIG. 1. Fulfilled PCOS diagnostic criteria for whole group of PCOS cases. a, Rotterdam diagnostic criteria (31 ) for PCOS (at least two of PCO morphology, hyperandrogenism, and oligoamenorrhea). b, National Institutes of Health diagnostic criteria (33 ) for PCOS (both hyperandrogenism and oligoamenorrhea).

Because it was not possible to match perfectly for BMI and age between the whole groups of PCOS cases and controls, the PCOS case group was more obese and younger than the controls [geometric mean BMI (SD, range) 31.4 kg/m² (24.8, 39.7) vs. 28.0 kg/m² (22.7, 34.4), respectively, P = 0.03; mean age (SD) 30.0 yr (6.6) vs. 39.5 yr (6.3), respectively, P = 2.5 x 10^–8, Table 1]. To limit the possible confounding effect of disparate BMI/fat mass between PCOS cases and controls, we performed two sets of analyses: one was based on the whole-group comparisons (50 PCOS cases vs. 28 female controls), which could be optionally adjusted for age and BMI, and the other was based on comparisons between the 22 BMI/fat mass-matched pairs of PCOS cases and controls that had been selected from the whole groups. To limit the metabolic heterogeneity associated with multiple PCOS phenotypic groups (35), each of the pair-matched PCOS cases fulfilled all three Rotterdam-proscribed PCOS diagnostic criteria (PCO morphology, oligoamenorrhea, and hyperandrogenism) (31). Matching of PCOS cases and controls for BMI/fat mass was performed on an individual, post hoc basis, and none of the matched-pairs differed by more than 1 kg/m^–2 (BMI). Both BMI (r² = 0.97, P = 8.9 x 10^–14) and fat mass (r² = 0.87, P = 1.4 x 10^–7) correlated highly between the pair-matched PCOS cases and controls. All clinical investigations were conducted in accordance with the guidelines in the Declaration of Helsinki, and the study was approved by the Oxfordshire Research Ethics Committee (United Kingdom). All subjects provided fully informed consent.

Fat mass was estimated using foot-to-foot measures of bioelectrical impedance obtained using a TBF-305 body composition analyzer (Tanita U.K. Ltd., Middlesex, UK, www.tanita.com). This is an established, well-validated technique for measurement of fat mass (36). In our study, BMI and bioimpedance-measured fat mass were highly correlated (r² = 0.95, P < 0.0001). Serum RBP4 levels were measured using an automated immunonephelometric assay. This method was performed on a Dade Behring Nephelometer II (Deerfield, IL) using Dade-Behring reagents and calibrants [intraassay coefficient of variation (CV) of 2.2%]. Serum levels of adiponectin (total and HMW) were measured with an immunoassay using monoclonal antibodies (intraassay CV < 7%), which has been shown to correlate highly with other commercially available assays for adiponectin [B-Bridge (San Jose, CA) (r² = 0.97); Alpco Diagnostics (Windham, NH) (r² = 0.98)]. Further assay details are available from the authors.

Serum (specific) insulin and plasma glucose were analyzed with automated immunometric (intraassay CV < 6%) and hexokinase assays, respectively. Plasma nonesterified fatty acid (NEFA) was measured using an enzymatic colorimetric method (NEFA C kit from Wako Chemicals, Eastleigh, Hampshire, UK). Measures of insulin sensitivity were calculated as homeostasis model assessment of insulin resistance (HOMA2 IR) values using the Oxford Diabetes Trials Unit calculator (www.dtu.ox.ac.uk). Serum testosterone and SHBG were analyzed using direct (competitive) chemiluminescent and immunometric assays, respectively. All blood samples were taken at 0900 h after an overnight fast. For the control women and five regularly cycling PCOS cases, blood samples were taken during d 2–5 of the menstrual cycle (follicular phase). However, this was not possible for the remaining oligoamenorrheic PCOS cases. MRI scans were performed within 2 wk of the blood samples being taken.

MRI evaluation

Axial T1-weighted spin echo MRI images of specific fat depots were obtained using a Signa 1.5 Tesla twin speed super conducting MRI system (GE Medical Systems, Milwaukee, WI). From these images, cross-sectional area measurements of specific fat depots were taken at anatomically predefined levels, including the mid-fourth lumbar vertebra (mid-L4; visceral and abdominal sc fat depot measurements), and the greater trochanteric/midfemoral levels (gluteofemoral sc fat depot measurements). All fat depot measurements were made by a single radiologist (S.J.G.) who was blinded to the clinical and laboratory findings. The fat depot cross-sectional area measurements were confirmed to be highly reproducible (r² > 0.98, P < 0.0001) through comparison with repeat fat depot measurements taken from the same scans in a subset of 20 subjects chosen at random, on a different day by the same radiologist (S.J.G.) who was blinded to the first set of measurements. Further imaging details and parameters are available from the authors.

Statistical analyses

For the whole-group comparisons (50 PCOS cases vs. 28 female controls), independent-sample t tests were used. Whole-group comparisons were also optionally adjusted for fat mass and age. For the comparisons between the 22 BMI/fat mass-matched pairs of PCOS cases and controls, paired-sample t tests were used. All variables were skewed and underwent logarithmic transformation before statistical analysis. Based on the Kolmogorov-Smirnov test, all variables were appropriately normally distributed after logarithmic transformation. P <0.05 was considered significant. All statistical analyses were conducted in SPSS (version 12.0 for Windows; SPSS Inc., Chicago, IL). We had greater than 80% power to detect a between-group difference exceeding 86 and 67% of a SD for RBP4 levels in the BMI/fat mass-matched PCOS case/control pairs and whole-group comparisons respectively ( = 0.05).

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The main results are shown in Table 1. For the whole-group analyses, serum levels of adiponectin were significantly lower in the PCOS cases than the control women [geometric mean total adiponectin (SD range) 19.9 µg/ml (14.2, 27.8) vs. 25.8 µg/ml (17.7, 37.7), respectively, unadjusted P = 2.4 x 10^–3; Table 1]. HMW adiponectin levels were similar (Table 1). There was no difference in HMW to total adiponectin ratio between PCOS cases and controls [geometric mean (SD range) 0.47 (0.37, 0.58) vs. 0.51 (0.37, 0.69), respectively, unadjusted P = 0.14; Table 1]. Similarly, there was no difference in serum RBP4 levels between PCOS cases and controls [geometric mean RBP4 (SD range) 39.0 µg/ml (31.0, 49.0) vs. 41.6 µg/ml (32.7, 52.9), respectively, unadjusted P = 0.24; Table 1]. After adjustments for fat mass and age, there were no differences in serum levels of total adiponectin (adjusted P = 0.10), HMW adiponectin (adjusted P = 0.24), HMW to total adiponectin ratio (adjusted P = 0.81,) and RBP4 (adjusted P = 0.55) between the PCOS cases and controls (Table 1).

Paired-sample comparisons between PCOS cases and controls essentially confirmed these findings. PCOS cases were significantly more insulin resistant than the BMI/fat mass-matched controls [geometric mean HOMA2 IR (SD range) 1.50 (0.68, 3.31) vs. 1.16 (0.62, 2.18), respectively, P = 0.03]. There were no differences in other metabolic (fasting) indices between PCOS cases and BMI/fat mass-matched controls [triglycerides (P = 0.34), high-density lipoprotein (HDL)-cholesterol (P = 0.16), NEFA (P = 0.69); Table 1]. Paired-sample comparisons between the BMI/fat mass-matched PCOS cases and controls showed that there were no significant differences in serum levels of RBP4 [geometric mean (SD range) 37.6 µg/ml (28.9, 49.0) vs. 42.2 µg/ml (32.7, 54.5), respectively, P = 0.09; Table 1] or adiponectin [geometric mean (SD range) total adiponectin: 22.1 µg/ml (15.1, 32.3) vs. 27.0 µg/ml (18.1, 40.1), respectively, P = 0.06; HMW adiponectin: 11.2 µg/ml (6.7, 18.9) vs. 13.6 µg/ml (7.1, 26.3), respectively, P = 0.19; HMW to total adiponectin ratio: 0.51 (0.42, 0.61) vs. 0.51 (0.36, 0.71), respectively, P = 0.98; Table 1]. Because there were no significant relationships between RBP4 and age (r² = 0.22, P = 0.12) or between HMW to total adiponectin ratio and age (r² = –0.001, P = 0.99) and no exponential relationships between these variables, the difference in age in the matched-pair subset was unlikely to be confounding.

The recent demonstration of a preferential expression of RBP4 in visceral rather than sc fat (37) prompted us to explore the relationships of RBP4 (and adiponectin) levels with cross-sectional area measurements of visceral, abdominal sc, and gluteofemoral sc fat depots and other measures of metabolic status. In the whole group of PCOS cases, serum RBP4 levels correlated significantly with visceral fat (r² = 0.34, P = 0.01), triglycerides (r² = 0.59, P < 0.0001), and SHBG (r² = –0.33, P = 0.03; Table 2). RBP4 also correlated positively with fat mass (r² = 0.25, P = 0.08) and HOMA2 IR (r² = 0.27, P = 0.07; Table 2), but these associations were not significant. Correlation analyses of RBP4 in the whole group of control women gave similar results (Table 2). In the whole group of PCOS cases, HMW to total adiponectin ratio correlated significantly and negatively with L4 visceral fat area (r² = –0.44, P = 0.001), L4 sc fat area (r² = –0.34, P = 0.01), triglycerides (r² = –0.42, P = 0.002), fat mass (r² = –0.44, P = 0.001), and HOMA2 IR (r² = –0.41, P = 0.004) and positively with SHBG (r² = 0.35, P = 0.02) and HDL-cholesterol (r² = 0.36, P = 0.01). In the PCOS cases, neither RBP4 nor HMW to total adiponectin ratio correlated with measures of gluteofemoral sc fat depots. Although testosterone has been demonstrated to have an inhibitory effect on the secretion of HMW adiponectin from rat adipocytes (25), we found no relationships between serum levels of testosterone and either HMW adiponectin (r² = –0.01, P = 0.94) or HMW to total adiponectin ratio (r² = 0.006, P = 0.97) in the PCOS cases. Similar results were obtained in the control women.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

We show significant fat mass-independent differences in HOMA2 IR measures of insulin resistance between the BMI/fat mass-matched pairs of PCOS cases and controls. These data are consistent with those from previous studies, which have shown that most women with PCOS (between 50 and 90%, depending on the diagnostic criteria used) are significantly more insulin resistant than BMI-matched control women (this disparity being more marked for higher BMIs) (3, 5). These observations combined with the indistinguishable serum levels of RBP4 and HMW to total adiponectin ratio argue against an important role for either adipokine in the development of fat mass-independent insulin resistance, a characteristic feature of women with PCOS. The association of insulin resistance with PCOS remains incompletely understood. Possible pathophysiological mechanisms include abnormal lipolysis, steroid metabolism, or intrahepatic fat content, although current evidence is limited (5).

Our RBP4 data confirm and extend those from a recent study that showed no difference in RBP4 levels between lean groups of PCOS cases and control women (13). Conversely, a further smaller study showed elevated serum RBP4 levels in PCOS cases (11). We show that in women with PCOS, serum RBP4 levels correlate with indices that reflect metabolic status, including fasting triglyceride and SHBG levels and (less strongly) with HOMA2 IR, a measure of insulin sensitivity. This is the first PCOS case/control study to analyze the relationships between serum levels of adiponectin and RBP4 with visceral fat depots. We showed a clear relationship between visceral fat cross-sectional area and serum levels of RBP4 (and adiponectin) in the PCOS cases group. This observation corroborates data from a recent study that showed preferential expression of RBP4 in visceral rather than sc fat in both men and women (37) and data from a further study that showed an association between RBP4 levels and intraabdominal fat in subjects with and without type 2 diabetes (38). In contrast, one other study showed no correlation between visceral fat and serum RBP4 levels (39). Differences in data obtained between studies may have been influenced by methodological differences in measurements of RBP4 levels.

Most previous studies on adiponectin in women with PCOS have been limited by measurements of total (without HMW) adiponectin. Data from these studies have been conflicting. Whereas levels of total adiponectin have been shown to be similar between BMI-matched PCOS cases and controls in some studies (28, 40), a comparison of obese and overweight PCOS cases with a low number of lean controls showed reduced serum adiponectin levels in obese women with PCOS (30, 41). A tendency toward lower adiponectin levels in PCOS cases vs. age-matched control women was also shown in a further study, although differences in adiponectin between groups failed to reach significance (29). Another comparison of 30 PCOS cases with 14 weight-matched control women did show significantly reduced total adiponectin levels in the PCOS cases, although HMW adiponectin levels were indistinguishable between the two groups (42). Recent evidence has shown that, rather than absolute amounts of total adiponectin, the ratio of HMW to total adiponectin is more closely associated with insulin sensitivity in humans (26, 27). Furthermore, it has recently been shown that testosterone inhibits the secretion of HMW adiponectin from rat adipocytes (25). We hypothesized that lower serum levels of HMW adiponectin mediates a link between hyperandrogenemia and insulin resistance in women with PCOS (due to the inhibitory effect of testosterone on HMW adiponectin secretion from adipocytes). Although we confirm a significant correlation between HMW to total adiponectin ratio and insulin resistance, we find no evidence to suggest that serum HMW to total adiponectin ratio (and levels of HMW adiponectin) are influenced appreciably by serum levels of testosterone in women with PCOS.

The whole groups differed for factors (fat mass and age) that could have potentially confounded our results. However, all of the maneuvers (adjustment and pair matching) indicated that the age disparity between PCOS cases and controls did not obscure significant differences between these groups. Although a residual effect of age on the paired-sample analyses is possible, this is unlikely, given that age did not correlate with either serum RBP4 or adiponectin levels in our study. Also, our study had 80% power to detect a between-group difference exceeding 67% of a SD for RBP4 (and adiponectin) levels ( = 0.05). Smaller between-group differences may have been missed, and we are therefore unable to exclude more subtle abnormalities in serum RBP4 and adiponectin levels that may exist in women with PCOS. However, the number of subjects in our study was similar to that in previous studies in the field (28, 29, 30, 39, 40, 41).

To summarize, we provide evidence to show that the differences in adiponectin (total and HMW) between PCOS cases and controls are attributable to differences in fat mass between these two groups. Our data are entirely consistent with the notion that adiponectin plays some role in the pathogenesis of PCOS, through mediation of obesity-related effects. However, our data (including indistinguishable levels of RBP4 and HMW to total adiponectin ratio between PCOS cases and control women) also argue against a primary role for either RBP4 or adiponectin (independent of fat mass) in the development of PCOS.

	Acknowledgments

 
We acknowledge the patients and nurses who contributed to the ascertainment of the various clinical samples used in this study. We acknowledge Dr. Fedrik Karpe for use of the Oxford Biobank for recruitment of female controls.

	Footnotes

 
This work was supported by a research fellowship awarded from NovoNordisk (to T.M.B.).

Declaration Summary: All authors have nothing to declare.

First Published Online April 29, 2008

Abbreviations: BMI, Body mass index; CV, coefficient of variation; HDL, high-density lipoprotein; HMW, high molecular weight; HOMA2 IR, homeostasis model assessment of insulin resistance; mid-L4, mid-fourth lumbar vertebra; MRI, magnetic resonance imaging; NEFA, nonesterified fatty acid; PCO, polycystic ovary; PCOS, polycystic ovary syndrome; RBP4, retinol-binding protein 4.

Received December 17, 2007.

Accepted April 17, 2008.

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