SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

Pigment epithelium-derived factor (PEDF) is upregulated in obese rodents and is involved in the development of insulin resistance (IR). We aim to explore the relationships between PEDF, adiposity, insulin sensitivity, and cardiovascular risk factors in obese women with polycystic ovary syndrome (PCOS) and weight-matched controls and to examine the impact of endurance exercise training on PEDF. This prospective cohort intervention study was based at a tertiary medical center. Twenty obese PCOS women and 14 non-PCOS weight-matched women were studied at baseline. PEDF, cardiometabolic markers, detailed body composition, and euglycemic—hyperinsulinemic clamps were performed and measures were repeated in 10 PCOS and 8 non-PCOS women following 12 weeks of intensified aerobic exercise. Mean glucose infusion rate (GIR) was 31.7% lower (P = 0.02) in PCOS compared to controls (175.6 ± 96.3 and 257.2 ± 64.3 mg.m−2.min−1) at baseline, yet both PEDF and BMI were similar between groups. PEDF negatively correlated to GIR (r = −0.41, P = 0.03) and high-density lipoprotein (HDL) (r = −0.46, P = 0.01), and positively to cardiovascular risk factors, systolic (r = 0.41, P = 0.02) and diastolic blood pressure (r = 0.47, P = 0.01) and triglycerides (r = 0.49, P = 0.004). The correlation with GIR was not significant after adjusting for fat mass (P = 0.07). Exercise training maintained BMI and increased GIR in both groups; however, plasma PEDF was unchanged. In summary, PEDF is not elevated in PCOS, is not associated with IR when adjusted for fat mass, and is not reduced by endurance exercise training despite improved insulin sensitivity. PEDF was associated with cardiovascular risk factors, suggesting PEDF may be a marker of cardiovascular risk status.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

Polycystic ovary syndrome (PCOS) affects 6–18% of women of reproductive age (1), depending on diagnostic criteria and populations studied (2). PCOS is diagnosed based on oligo or amenorrhea, clinical or biochemical hyperandrogenism, and polycystic ovaries on ultrasound (3). Insulin resistance (IR) plays a central pathophysiological role in the majority of women with PCOS, independent of body weight; however, IR in PCOS is further exacerbated by the high prevalence of associated obesity (4). IR underpins significant metabolic complications in PCOS including dyslipidemia, impaired glucose tolerance, and type 2 diabetes (5,6,7), yet the aetiology of IR in PCOS remains unclear.

Pigment epithelium-derived factor (PEDF) is a glycoprotein that belongs to the superfamily of serine protease inhibitors. PEDF promotes neuronal differentiation and survival (8) and is a potent inhibitor of angiogenesis (9) and endothelial cell injury in vitro, suggesting a role in atherosclerosis (10). Our group recently reported that plasma PEDF is elevated in rodent models of obesity and reduced upon weight loss and insulin sensitization (11). We further showed that PEDF administration in lean mice stimulated adipose tissue lipolysis and caused IR, whereas neutralizing PEDF's actions in obese mice improved insulin sensitivity (11). Evidence for a causal role of PEDF in the development of human IR is limited. PEDF correlated with visceral adiposity in a Japanese cohort (12) and PEDF was upregulated in insulin-resistant individuals with metabolic syndrome (10,13), impaired glucose tolerance, and type 2 diabetes (14,15). However, a major limitation of these studies is determining whether PEDF primarily relates to obesity-induced IR or whether it is related to IR independent of obesity (12,16). A recent study in a Chinese cohort demonstrated correlation of PEDF to insulin sensitivity measured during clamp studies, independent of BMI in both lean and overweight PCOS and non-PCOS women; however, interpretation of this data was limited as no clamps were performed on the overweight non-PCOS women (17).

The etiology of IR in PCOS is poorly understood and existing research into this area is limited to humans, with no ideal animal models. Current etiological theories suggest that intrinsic IR (purportedly genetic, inherent, and unique to PCOS) (18), is exacerbated by extrinsic IR (lifestyle/obesity related) (4,19,20). As PEDF appears to have a causal role in obesity-related IR in animal studies (11), we hypothesized that PEDF may be involved in the etiology of extrinsic lifestyle-related IR in PCOS and as such may be improved with exercise intervention.

IR is central to the metabolic and reproductive disturbances in PCOS and thus lifestyle modification including exercise is a first-line therapy in PCOS management. There are limited studies examining the effects of exercise in PCOS. Previous studies assessing the impact of exercise therapy in PCOS report improved IR following exercise using indirect measures of IR (21). A recent systematic review on exercise in PCOS demonstrates clear gaps in knowledge in this area (21). Recent findings by our group demonstrate that intensified exercise enhances insulin sensitivity in women with and without PCOS independent of weight loss (22); however, it is unclear whether PEDF is affected by improved IR following exercise in the context of PCOS.

Therefore, the primary aim of this study was to assess the relationship between PEDF, adiposity, and IR in two groups of obese women: a non-PCOS control group and an insulin-resistant PCOS group. In addition, we aimed to assess the relationship between PEDF and known cardiometabolic risk factors. We also assessed the impact of exercise on IR and PEDF.

Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

Subjects

Women were recruited from community advertisements for a larger study (23). Thirty-four women were eligible (n = 20 PCOS and n = 14 non-PCOS controls) and had completed 3 months run-in and baseline data collection as previously described (23). In this PEDF substudy, we analyzed baseline data from 32 women (n = 18 with PCOS and n = 14 without PCOS) and post-exercise data from 18 women (n = 10 with PCOS and n = 8 without PCOS) based on sample availability for PEDF analysis.

As previously described, PCOS was diagnosed (1990 National Institutes of Health (NIH) criteria) by a qualified endocrinologist (S.K.H.) based on perimenarchal onset of irregular cycles (>35 days), combined with clinical (hirsutism, acne) or biochemical (elevation of at least one circulating ovarian androgen) hyperandrogenism (3,24). Hyperprolactinemia, thyroid dysfunction, and specific adrenal disorders were excluded clinically and where indicated, biochemically. All women without PCOS had regular menses and no evidence of clinical or biochemical hyperandrogenism. Exclusion criteria were smoking, diabetes, participation in regular physical activity, recent weight change, and pregnancy.

The Southern Health Research Advisory and Ethics Committee approved the study and all participants gave written informed consent. The clinical trial registration number is ISRCTN84763265.

Study design

At screening (3 months before baseline), standard diet and lifestyle advice were delivered (Heart Foundation of Australia recommendations (http:www.heartfoundation.org.au)) as previously described (22,23). Medications affecting end-points including insulin sensitizers, antiandrogens, and hormonal contraceptives were ceased for 3 months. End-point data was collected at 3 months (baseline) and again following 12 weeks of exercise intervention. Data was collected in the follicular phase of the menstrual cycle wherever feasible. A subset of PCOS (n = 10) and control (n = 8) women completed a 12-week intensified aerobic exercise program as described previously (22,23).

Anthropometric measurements

Participants were weighed lightly clothed without shoes (TBF310; Tanita, Tokyo, Japan). BMI was calculated, (weight (kilogram)/height squared (metre2)), (Stadiometer; Holtain, Wales, UK). Waist circumference was measured at the umbilicus by an experienced operator.

Euglycemic—hyperinsulinemic clamp

Insulin sensitivity was measured using the euglycemic—hyperinsulinemic clamp technique as previously described (22,23,25). Fasting venous blood samples were collected, centrifuged, and stored for assessment of glucose, insulin, PEDF, testosterone, sex hormone-binding globulin, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein, and triglycerides as previously described (22,23). Testosterone was measured on Beckman Coulter Unicel DXI 800 analyzer (Beckman Coulter Diagnostics Australia, Gladesville, Australia) using an automated competitive binding immunoenzymatic assay and the free androgen index was calculated from free androgen index = (testosterone/sex hormone-binding globulin) × 100 as previously reported (23). The glucose infusion rates (GIRs) were calculated during the last 30 min of the euglycemic—hyperinsulinemic clamp and expressed as glucose (ml) per hour per body surface area (m2) per minute.

Body composition and adipose tissue distribution

Fat mass, abdominal fat mass, and fat-free mass were measured by dual-energy X-ray absorptiometry as described elsewhere (23). Single-slice computed tomography images were acquired at the level of L4—L5 intervertebral disc space and abdominal visceral fat (AVF) and abdominal subcutaneous fat cross-sectional areas (centimeters squared) were calculated as previously described (23). Biopsies were performed on all participants to obtain thigh adipose tissue samples for analysis.

Exercise intervention

Participants completed a 12-week intensified aerobic exercise program on a motorized treadmill (Biodex 500/Life Fitness 95T; Life Fitness, Lawrence, NY) as described (22). Participants attended three, 1 h sessions each week which sequentially alternated between moderate intensity (walking or jogging at 70% of VO2 max or 75–85% HRmax) and high-intensity interval training (6 × 5-min intervals with 2-min recovery period at ∼95–100% of VO2 max or ∼95–100% HRmax). Participants progressed to eight repetitions in the high-intensity training sessions by week 4, and reduced recovery time to 1 min by week 8 of training. Target exercise intensity (percentage VO2 max) and heart rates for each participant were achieved by altering speed (kph) and workload (gradient; %) on the treadmill with individual increases in fitness.

Plasma PEDF

Plasma PEDF was determined using a commercial ELISA according to the manufacturers' procedure (BioVender Human PEDF ELISA; Evropska, Modrice, Czech Republic) using a single assay. The within assay coefficient of variation was 8.1 ± 1.5% (n = 8 samples in duplicate, values are mean ± s.e.m.).

Quantitative reverse transcription-PCR

RNA was extracted from thigh adipose tissue using the RNeasy Lipid Tissue Mini Kit (Qiagen, Valencia, CA) and 1 µg mRNA was reverse transcribed (iScript cDNA Synthesis Kit; Bio-Rad Laboratories, Hercules, CA). Quantitative real-time PCR was performed on a realplex Mastercycler (Eppendorf, North Ryde, Australia) using the TaqMan Universal PCR Master Mix and TaqMan Gene Expression Assays (Applied Biosystems, Foster City, CA). The relative quantification was calculated using the ΔΔCt method (18S as the housekeeping gene) and results are normalized to values of the control group.

Statistics

All data were analyzed using STATA software version 11.0 (Stata, College Station, TX). PEDF levels were assessed for normality and found to be well-approximated by a normal distribution. A comparison between obese PCOS and non-PCOS subjects was conducted using Student's t-test for normally distributed variables and Mann—Whitney U-test for variables that are not normally distributed. Linear regression was used for assessment of factors associated with plasma PEDF levels. Age adjusted estimates were also derived due to a statistically significant difference in age between the two groups. Results from the regression analysis are reported as parameter estimates (s.e.), with an R2 statistic to indicate the amount of variation explained. Correlation of PEDF with lipids and cardiovascular risk factors was assessed using Pearson or Spearman rank correlation, wherever appropriate. The effect of exercise within groups was assessed using paired t-tests. Continuous data are presented as mean ± s.d. or median (interquartile range) as appropriate. Statistical significance was set at α-level of 0.05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

Results are presented for 32 subjects with samples available for further analysis including PEDF at baseline. Eighteen women with PCOS and 14 women without PCOS who were eligible at screening, completed the 3-month run-in phase with a steady diet, undertook no additional regular physical activity, were compliant with withdrawal of relevant medications and completed baseline data collection. Ten PCOS and eight non-PCOS women completed the 12-week exercise intervention and completed baseline data collection.

PCOS vs. non-PCOS women: clinical, metabolic, and hormonal status and PEDF levels

All baseline metabolic and clinical characteristics are presented in Table 1. The women with PCOS were younger than controls (29.8 ± 5.7 vs. 35.0 ± 4.3 years, P = 0.01). The experimental groups had similar adiposity as determined by BMI, waist hip ratio, fat mass assessment by dual-energy X-ray absorptiometry, and visceral abdominal fat content determined by computed tomography.

Table 1.  Baseline characteristics: demographics, biochemistry, and measures of adiposity
inline image

As expected, the women with PCOS had higher androgen levels. HDL levels were lower in PCOS; other cardiovascular risk factors were not different between groups. PCOS subjects were more insulin resistant with higher fasting insulin and homeostasis model assessment and lower GIR during euglycemic—hyperinsulinemic clamp studies (Table 1).

Fasting plasma and adipose tissue PEDF mRNA content were not different between groups (P = 0.22 and P = 0.24 respectively) (Table 1).

PEDF relationships with clinical, metabolic, and hormonal status

Relationship between plasma PEDF levels and cardiometabolic factors are presented in Table 2. Plasma PEDF levels were negatively related to insulin sensitivity as assessed by GIR during euglycemic—hyperinsulinemic clamps. Other predictors of PEDF on univariate analyses were systolic and diastolic blood pressure, HDL, plasma triglycerides, and AVF. Adjusting for age did not impact on these results (Table 2). We also adjusted the regression analysis for fat mass to assess the effect on IR, independent on adiposity (Table 2). The relationship of PEDF to IR just failed to reach statistical significance after adjustment for fat mass (P = 0.07).

Table 2.  Relationship of plasma PEDF levels to metabolic risk factors
inline image

As adipose tissue is postulated to be the major source of plasma PEDF and adipocyte PEDF is increased in rodent obesity (11), a univariate analysis of PEDF mRNA in adipose tissue was performed; however this did not find any statistically significant relationships.

Correlations

Significant correlations were found at baseline between plasma PEDF and BMI (r = 0.39, P = 0.03), systolic blood pressure (r = 0.41, P = 0.02), diastolic blood pressure (r = 0.47, P = 0.01), plasma triglycerides (r = 0.49, P = 0.004), and HDL (r = −0.46, P = 0.01) (Figure 1). PEDF correlated with AVF (r = 0.46, P = 0.01), but not with abdominal subcutaneous fat (r = 0.21, P = 0.27). GIR correlated negatively with PEDF (r = −0.41, P = 0.03). There was no significant correlation with PEDF and age (r = 0.06, P = 0.73).

image

Figure 1. Relationship of PEDF to adiposity measures, insulin sensitivity, blood pressure, and triglycerides. (a) Relationship of PEDF to BMI, r = 0.39, P = 0.03. (b) Relationship of PEDF to abdominal visceral fat, r = 0.46, P = 0.01. (c) Relationship of PEDF to fat mass, r = 0.31, P = 0.09. (d) Relationship of PEDF to glucose infusion rate (GIR), r = −0.41, P = 0.03. (e) Relationship of PEDF to systolic blood pressure, r = 0.41, P = 0.02. (f) Relationship of PEDF to diastolic blood pressure, r = 0.47, P = 0.01. (g) Relationship of PEDF to triglycerides, r = 0.49, P = 0.004. BP, blood pressure; PEDF, pigment epithelium-derived factor.

Download figure to PowerPoint

Effects of aerobic exercise training on PEDF, clinical, metabolic, and hormonal status

Following exercise, a subgroup analysis was performed on 10 women with PCOS and 8 women without PCOS who completed end-point data collection following exercise intervention. There was a 44% drop out following exercise intervention. Adherence to the exercise intervention was >90% in both groups with no difference between groups as published elsewhere (22). Exercise training reduced whole group BMI (P = 0.02), but with no difference between or within groups. Insulin sensitivity was improved by exercise training in the group as a whole, as reflected by an increased GIR (P = 0.01); however, exercise training did not affect plasma PEDF in either group, nor overall (Figure 2).

image

Figure 2. Change in BMI, insulin sensitivity, and PEDF with endurance exercise training. Error bars represent s.e.m. (a) BMI pre- and post-exercise. (b) PEDF levels pre- and post-exercise. (c) Glucose infusion rates (GIRs) pre- and post-exercise. PEDF, pigment epithelium-derived factor; PCOS, polycystic ovary syndrome.

Download figure to PowerPoint

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

We report here that despite similar fat mass and greater IR in women with PCOS, plasma PEDF did not differ between groups. Although PEDF correlated with insulin sensitivity, this relationship, despite a trend, failed to reach significance after adjusting for fat mass. Furthermore, plasma PEDF was not reduced after prolonged exercise training, despite reduced adiposity and enhanced insulin sensitivity. A further novel finding from this study is that plasma PEDF levels correlate with both systolic and diastolic blood pressure and we confirmed the correlation of PEDF with dyslipidemia.

IR, independent of obesity, is a feature present in the majority of women with PCOS (26). Lean women with PCOS are more insulin resistant than lean controls without PCOS (18). There is emerging evidence that the underlying mechanisms of IR differ in the intrinsic and extrinsic components of IR in PCOS. This intrinsic PCOS-related IR is independent of adiposity and appears to be related to insulin-signaling abnormalities (4). Intrinsic IR is exacerbated by obesity-related extrinsic IR (4). We report here significantly greater IR in PCOS, yet no difference in plasma PEDF levels between obese insulin-resistant PCOS women compared to overweight controls. We did show a relationship between PEDF and IR measured by GIR; however, this failed to reach significance after correction for adiposity. Insulin sensitivity improved after the exercise intervention, yet there was no significant change in plasma PEDF. These observations are of interest, suggesting that PEDF may not be causal for, or a specific marker of IR in humans.

A recent study from China analyzed serum PEDF levels in lean (BMI <24.0 kg/m2), overweight (BMI 24.0–27.9 kg/m2), and obese (BMI ≥ 28.0 kg/m2) women based on BMI guidelines for Chinese adults (17) in women with PCOS (diagnosed using the 2003 Rotterdam criteria) and women without PCOS. Measurements included participants' BMI and waist circumference, while our study used more detailed anthropometric measures. The Chinese study found that PEDF levels were higher in women with PCOS; however, on subgroup analysis while PEDF was significantly higher in lean PCOS women, PEDF levels were not different between groups in overweight women, similar to our study. PEDF levels in this group may be modulated by adiposity and may relate more to visceral fat. The study by Yang et al. reported a negative correlation between PEDF and insulin sensitivity, as measured by clamp studies; however, none of the overweight/obese control women underwent clamp studies (17). Our study extends knowledge in this area as it was in a different ethnic population, included clamp studies in both obese control and PCOS women and also assessed the effects of an exercise intervention. We failed to confirm a correlation to PEDF and insulin sensitivity on clamp studies, once corrected for fat mass and also showed no change in PEDF with exercise, suggesting that PEDF is not primarily related to insulin sensitivity.

Previous studies have found that plasma levels of PEDF correlate with BMI in patients with metabolic syndrome (10,13) and type 2 diabetes (12,14). Our study noted a correlation of PEDF with BMI in overweight nondiabetic women and a correlation of PEDF with AVF, but not with abdominal subcutaneous fat. Consistent with our current study, Wang et al. noted an independent relationship of visceral adiposity and BMI to plasma PEDF (16). Other studies have shown correlation of PEDF to waist circumference (10,12). Overall PEDF appears to relate to obesity, with the strongest relationships to visceral rather than subcutaneous fat.

Our study found that metabolic risk factors such as systolic and diastolic blood pressure, HDL, and triglycerides relate to plasma levels of PEDF. Previous studies have found variable relationships between PEDF and blood pressure with some reporting no correlation (10,12), and others finding a positive correlation with diastolic blood pressure alone (13,16). Positive associations have also been reported between PEDF and both HDL and triglycerides (10) and triglycerides alone (27), whereas others found an inverse relationship between PEDF and low-density lipoprotein cholesterol levels and no change with lipid-lowering agents (14). PEDF is highly expressed in hepatocytes and recent studies propose that PEDF is involved in hepatic triglyceride homeostasis by binding to and activating adipose triglyceride lipase (ATGL) in the liver (28,29). However, whether this would result in increased plasma triglycerides in humans remains controversial as adenoviral overexpression of activating adipose triglyceride lipase does not affect triglyceride secretion in mice (30,31). Further research into the mechanistic relationships between PEDF and metabolic risk factors is needed.

The strengths of this study include the use of strict criteria to define PCOS and non-PCOS women, gold-standard techniques to measure IR and body composition, and the use of an exercise intervention. Weaknesses include a relatively small sample size and a 44% drop out rate following the exercise intervention, reflecting the high intensity of the intervention. Thirty subjects overall were required to detect a correlation coefficient of 0.5, 80% power, and an α-value of 5%, but did not allow correlation assessment in individual PCOS and control groups. Patients and controls are not age matched and while this is corrected for in the statistical analyses, this is not an optimal design.

In conclusion, our exploratory study reveals that obese PCOS women had greater IR than similar weight non-PCOS control women, when assessed by euglycemic—hyperinsulinemic clamp. Plasma PEDF levels were not different between the PCOS and control groups. Overall, plasma PEDF levels correlated with IR; however, this failed to reach significance after correction for fat mass. Finally, despite improved IR after 12 weeks of endurance exercise, plasma PEDF did not change. PEDF concentrations related to systolic and diastolic blood pressure, low HDL, and high triglyceride levels. This data suggests that in obese IR women with PCOS, PEDF relates to cardiovascular risk factors but does not clearly relate to IR.

ACKNOWLEDGMENTS

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

This work was supported as an investigator-initiated trial funded by a competitive grant from Monash University and through a Jean Hailes Foundation grant. H.J.T. and N.K.S. are supported by a research grant from the National Health and Medical Research Council of Australia (NHMRC) and H.J.T. is also a NHMRC Research Fellow. M.J.W. is supported by research grants from and is a Senior Research Fellow of the NHMRC.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information
  • 1
    March WA, Moore VM, Willson KJ et al. The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Hum Reprod 2010;25:544551.
  • 2
    Asunción M, Calvo RM, Millán San JL et al. A prospective study of the prevalence of the polycystic ovary syndrome in unselected Caucasian women from Spain. J Clin Endocrinol Metab 2000;85:24342438.
  • 3
    Norman RJ, Dewailly D, Legro RS, Hickey TE. Polycystic ovary syndrome. Lancet 2007;370:685697.
  • 4
    Diamanti-Kandarakis E, Papavassiliou AG. Molecular mechanisms of insulin resistance in polycystic ovary syndrome. Trends Mol Med 2006;12:324332.
  • 5
    Dabadghao P, Roberts BJ, Wang J, Davies MJ, Norman RJ. Glucose tolerance abnormalities in Australian women with polycystic ovary syndrome. Med J Aust 2007;187:328331.
  • 6
    Ehrmann DA, Barnes RB, Rosenfield RL, Cavaghan MK, Imperial J. Prevalence of impaired glucose tolerance and diabetes in women with polycystic ovary syndrome. Diabetes Care 1999;22:141146.
  • 7
    Legro RS, Kunselman AR, Dodson WC, Dunaif A. Prevalence and predictors of risk for type 2 diabetes mellitus and impaired glucose tolerance in polycystic ovary syndrome: a prospective, controlled study in 254 affected women. J Clin Endocrinol Metab 1999;84:165169.
  • 8
    Tombran-Tink J, Chader G, Johnson L. PEDF: a pigment epithelium-derived factor with potent neuronal differentiative activity. Exp Eye Res 1991:411414.
  • 9
    Dawson DW, Volpert OV, Gillis P et al. Pigment epithelium-derived factor: a potent inhibitor of angiogenesis. Science 1999;285:245248.
  • 10
    Yamagishi S, Adachi H, Abe A et al. Elevated serum levels of pigment epithelium-derived factor in the metabolic syndrome. J Clin Endocrinol Metab 2006;91:24472450.
  • 11
    Crowe S, Wu LE, Economou C et al. Pigment epithelium-derived factor contribute to insulin resistance in obesity. Cell Metab 2009:4047.
  • 12
    Nakamura K, Yamagishi S, Adachi H et al. Serum levels of pigment epithelium-derived factor (PEDF) are positively associated with visceral adiposity in Japanese patients with type 2 diabetes. Diabetes Metab Res Rev 2009;25:5256.
  • 13
    Stejskal D, Karpísek M, Svesták M et al. Pigment epithelium-derived factor as a new marker of metabolic syndrome in Caucasian population. J Clin Lab Anal 2010;24:1719.
  • 14
    Jenkins A, Zhang SX, Gosmanova A et al. Increased serum pigment epithelium derived factor levels in Type 2 diabetes patients. Diabetes Res Clin Pract 2008;82:e5e7.
  • 15
    Sabater M, Moreno-Navarrete JM, Ortega FJ et al. Circulating pigment epithelium-derived factor levels are associated with insulin resistance and decrease after weight loss. J Clin Endocrinol Metab 2010;95:47204728.
  • 16
    Wang P, Smit E, Brouwers MC et al. Plasma pigment epithelium-derived factor is positively associated with obesity in Caucasian subjects, in particular with the visceral fat depot. Eur J Endocrinol 2008;159:713718.
  • 17
    Yang S, Li Q, Zhong L et al. Serum pigment epithelium-derived factor is elevated in women with polycystic ovary syndrome and correlates with insulin resistance. J Clin Endocrinol Metab 2011;96:831836.
  • 18
    Salley KE, Wickham EP, Cheang KI et al. Glucose intolerance in polycystic ovary syndrome—a position statement of the Androgen Excess Society. J Clin Endocrinol Metab 2007;92:45464556.
  • 19
    Dunaif A. Insulin resistance and the polycystic ovary syndrome: mechanism and implications for pathogenesis. Endocr Rev 1997;18:774800.
  • 20
    Corbould A, Kim YB, Youngren JF et al. Insulin resistance in the skeletal muscle of women with PCOS involves intrinsic and acquired defects in insulin signaling. Am J Physiol Endocrinol Metab 2005;288:E1047E1054.
  • 21
    Harrison CL, Lombard CB, Moran LJ, Teede HJ. Exercise therapy in polycystic ovary syndrome: a systematic review. Hum Reprod Update 2011;17:171183.
  • 22
    Harrison CL, Stepto NK, Hutchison SK, Teede HJ. The impact of intensified exercise training on insulin resistance and fitness in overweight and obese women with and without polycystic ovary syndrome. Clin Endocrinol (Oxf) 2012;76:351357.
  • 23
    Hutchison SK, Stepto NK, Harrison CL et al. Effects of exercise on insulin resistance and body composition in overweight and obese women with and without polycystic ovary syndrome. J Clin Endocrinol Metab 2011;96:E48E56.
  • 24
    Zawadzki J, Dunaif A. Diagnostic Criteria for Polycystic Ovary Syndrome: Towards a Rational Approach. Blackwell: Boston, 1992.
  • 25
    DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 1979;237:E214E223.
  • 26
    DeUgarte CM, Bartolucci AA, Azziz R. Prevalence of insulin resistance in the polycystic ovary syndrome using the homeostasis model assessment. Fertil Steril 2005;83:14541460.
  • 27
    Ogata N, Matsuoka M, Matsuyama K et al. Plasma concentration of pigment epithelium-derived factor in patients with diabetic retinopathy. J Clin Endocrinol Metab 2007;92:11761179.
  • 28
    Chung C, Doll JA, Gattu AK et al. Anti-angiogenic pigment epithelium-derived factor regulates hepatocyte triglyceride content through adipose triglyceride lipase (ATGL). J Hepatol 2008;48:471478.
  • 29
    Borg ML, Andrews ZB, Duh EJ et al. Pigment epithelium-derived factor regulates lipid metabolism via adipose triglyceride lipase. Diabetes 2011;60:14581466.
  • 30
    Turpin SM, Hoy AJ, Brown RD et al. Adipose triacylglycerol lipase is a major regulator of hepatic lipid metabolism but not insulin sensitivity in mice. Diabetologia 2011;54:146156.
  • 31
    Reid BN, Ables GP, Otlivanchik OA et al. Hepatic overexpression of hormone-sensitive lipase and adipose triglyceride lipase promotes fatty acid oxidation, stimulates direct release of free fatty acids, and ameliorates steatosis. J Biol Chem 2008;283:1308713099.

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods and Procedures
  5. Results
  6. Discussion
  7. ACKNOWLEDGMENTS
  8. DISCLOSURE
  9. References
  10. Supporting Information

Supporting Information

FilenameFormatSizeDescription
oby_2784_sm_oby2012135_coi.pdf1031KSupporting info item

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.