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Oxford Centre for Diabetes, Endocrinology, and Metabolism (T.M.B., J.A.H.W., F.K., M.I.M.), Churchill Hospital, Oxford OX3 7LJ, United Kingdom; Department of Radiology (C.A., S.J.G.), John Radcliffe Hospital, Oxford OX3 9DU, 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, Headington, Oxford OX3 7LJ, United Kingdom. E-mail: tom.barber{at}drl.ox.ac.uk.
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Abstract |
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Objective: The objective of the study was to compare distributions of visceral, abdominal sc, and gluteofemoral sc adipose tissue in PCOS cases vs. control women.
Design: This was a cross-sectional study.
Setting and Participants: Fat depot measurements from axial magnetic resonance imaging scans taken at anatomically predefined sites were compared between 22 body mass index (BMI)/fat mass-matched pairs of PCOS cases and controls; whole-group comparisons included 50 PCOS cases vs. 28 female controls. All subjects were of UK British/Irish origin.
Main Outcome Measure(s): We measured cross-sectional areas of adipose tissue within visceral (mid-L4), abdominal (mid-L4) sc, and gluteofemoral (greater trochanteric and midfemoral) sc fat depots. Other measurements included fat mass, BMI, testosterone, SHBG, and homeostasis model assessment of insulin resistance (a measure of insulin sensitivity). Whole-group analyses were adjusted for fat mass and age.
Results: There were no significant differences in fat-depot measurements between BMI/fat mass-matched pairs of PCOS cases and controls: mid-L4 visceral (P = 0.40), abdominal sc (P = 0.22), gluteal sc (P = 0.67), and midfemoral sc (P = 0.37) depots. Whole-group comparisons gave similar results after adjustments for fat mass and age. Fasting serum insulin concentrations (P = 0.03) and homeostasis model assessment of insulin resistance (P = 0.03) were significantly higher in the PCOS group than BMI/fat mass-matched controls.
Conclusions: PCOS cases and BMI/fat mass-matched control women are indistinguishable with respect to distribution of fat within visceral, abdominal sc, and gluteofemoral sc depots, despite significant differences in insulin resistance between these two groups.
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Introduction |
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Previous studies in PCOS used a variety of imaging techniques for the assessment of BFD, including lipometer (12), ultrasound (13), and dual-energy x-ray absorptiometry, each of which has its limitations (14, 15, 16). Magnetic resonance imaging (MRI) has significant advantages over these other imaging techniques, including minimal operator dependence and the generation of high-resolution images, which enables accurate delineation of specific fat depots (including visceral vs. abdominal sc fat). MRI has not been used previously to compare BFD in women with PCOS vs. controls.
The aim of our study was to compare body fat distribution using MRI between BMI/fat mass-matched pairs of PCOS cases and healthy control women.
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Subjects and Methods |
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All recruited PCOS cases and control women were white and of British/Irish origin, aged between 18 and 50 yr, premenopausal, postmenarchal, and nonpregnant. All cases (n = 50) had a definitive diagnosis of PCOS made using the Rotterdam diagnostic criteria (17, 18). All had MRI-confirmed polycystic ovarian (PCO) morphology (17, 18, 19), and 44 PCOS cases also met both the other Rotterdam criteria for PCOS [oligoamenorrhea (intermenstrual interval greater than 42 d) and hyperandrogenism (clinical and/or biochemical)]. In the presence of PCO morphology, only one of these other two diagnostic criteria was required to confirm a diagnosis of PCOS (17, 18) in the remaining six cases, five of whom had hyperandrogenemia but normal menses, and one had oligoamenorrhea but normoandrogenemia. Other endocrine or neoplastic causes of hyperandrogenemia (including congenital adrenal hyperplasia, androgen-secreting tumors, and Cushing’s syndrome) were excluded (17, 18) on the basis of normal serum 17-hydroxyprogesterone; 0900 h serum cortisol and ACTH levels; normal 24-h urinary dehydroepiandrosterone sulfate, androstenedione, and total cortisol metabolite excretion; and absence of ovarian tumor on MRI scan. All the cases were recruited from general endocrine and PCOS clinics at the Churchill and John Radcliffe hospitals, Oxford.
Controls (n = 28) were healthy women recruited from the Oxford Biobank, none of whom met any of the diagnostic criteria for PCOS (17, 18). All controls had a history of regular menstrual cycles and none had any clinical or biochemical evidence of hyperandrogenism (17, 18). All of the controls had MRI-confirmed normal ovarian morphology (17, 18, 19). The control group were selected from a larger group of control women (n = 40), none of whom had any symptoms of PCOS (oligoamenorrhea or hyperandrogenism). Consistent with previous observations of the high prevalence of PCO morphology in the general female population (20), 12 women in the larger control group had MRI-proven PCO morphology and were therefore excluded from the study on that basis. None of the cases or controls had been taking any hormonal preparations (including oral contraceptive pill) or other confounding medications within 3 months of being recruited into the study. A minority of the PCOS cases (n = 21) was taking metformin, but this was stopped for 1 wk before the blood tests and MRI scan. None of the PCOS cases or controls had diabetes mellitus.
It was not possible to obtain a perfect match for BMI and age between the whole groups of PCOS cases and controls. Consequently, the PCOS cases as a group were more obese and younger than 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 confounding effect of disparate BMI/fat mass between PCOS cases and controls, the main analyses were based on comparisons between 22 pairs of PCOS cases and controls selected from the whole groups, each pair having been matched (to within 1 kg/m–2) on an individual basis for BMI. All pair-matched PCOS cases fulfilled all three Rotterdam-proscribed PCOS diagnostic criteria (PCO morphology, oligoamenorrhea and hyperandrogenism) (17, 18) to limit the metabolic heterogeneity associated with multiple PCOS phenotypic groups (21). All clinical investigations were conducted in accordance with the guidelines in the Declaration of Helsinki, and the study was approved by the relevant ethics committee in the United Kingdom. All subjects provided fully informed consent.
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All participants were examined on a Signa 1.5 Tesla twin-speed super conducting MRI system (GE Medical Systems, Milwaukee, WI), using a phased-array torso coil system (22). Assessment of BFD in each subject was based on measurements of cross-sectional areas of specific fat depots, made from axial T1-weighted spin-echo images taken at the following anatomically predefined levels: midfourth lumbar (L4) vertebral body (Fig. 1) for measurement of visceral and sc abdominal fat depots; greater trochanters for measurement of the gluteal sc fat depot; and the midfemoral level (defined by the midpoint between the apex of the greater trochanter and the lateral femoral epicondyle) for measurement of the (mean) midthigh sc fat depot. A cursor area measurement facility on the diagnostic console was used for all fat depot measurements. This was implemented by a radiologist (S.J.G.) who was blinded to the clinical and laboratory findings.
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PCO morphology was defined as per Rotterdam criteria (17, 18) [ovarian volume calculated as 0.5 x ovarian length x width x height (23) using monitor cursors]. Android index (AI) was defined by the ratio of android (visceral) to gynoid (gluteofemoral sc) fat measurements with the equation, AI = [(mid-L4 visceral fat area)/(gluteal sc fat area + mean midfemoral sc fat area)]. AI is a modification of the established fat distribution index derived from dual-energy x-ray absorptiometry measurements of regional fat mass (14).
Anthropometric and biochemical evaluation
Fat mass in each subject was measured with a body composition analyzer (TBF-305), based on foot-to-foot measures using Tanita bioelectrical impedence analysis technology, an established well-validated technique for measurement of fat mass (Tanita UK Ltd., Middlesex, UK, www.tanita.com). Waist circumference was measured at the midpoint between the iliac crest and the lowest rib margin at the end of normal expiration [BMI and bioimpedance measured fat mass were highly correlated in our study (r2 = 0.95, P = 1.1 x 10–52)].
Fasting serum-specific insulin was measured with a chemiluminescent assay performed on a Immulite 2500 machine (Diagnostic Products Corp., Los Angeles, CA). Fasting plasma glucose was measured with a hexokinase assay (ADVIA 2400 analyzer; Bayer Corp., Newbury, 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). Plasma glucose and serum insulin were measured in all subjects both fasting and at 30 min (+30) after a standard (75 g) oral glucose load. Insulinogenic index (InsI) and insulin disposition index were calculated using the following equations: InsI = [(+30 insulin – fasting insulin)/(+30 glucose – fasting glucose)]; disposition index = [InsI x HOMA2 IR]. HOMA2 IR as a measure of insulin sensitivity has previously been shown to correlate well with the gold standard for insulin sensitivity measurement, the euglycemic-hyperinsulinemic clamp (24). Serum testosterone was measured with a direct (competitive) chemiluminescent assay (ADVIA Centaur analyzer; Bayer), and SHBG using a chemiluminescent assay (Immulite 2000 analyzer; Diagnostic Products).
Clinical hyperandrogenism was defined as a Ferriman-Gallwey score of 8 or greater and/or androgenic alopecia. Biochemical hyperandrogenism was defined as a serum testosterone concentration of 8.18 ng/ml or greater and/or free androgen index (FAI) of 8.98 or greater. FAI was calculated as the total testosterone (nanograms per milliliter) divided by SHBG (nanograms per milliliter) and multiplied by 100. The cutoff values for testosterone and FAI were derived as previously described (25) from the distribution (mean + 2 SD) for testosterone and SHBG measured with the same assays in the control group. All blood tests were taken at 0900 h after an overnight fast. For all of the control women and the five regularly cycling PCOS cases, blood was taken during the follicular phase of the menstrual cycle (d 2–5). This was not possible for the majority of cases who had oligoamenorrhea. MRI scans were performed within 2 wk of the blood samples being taken.
Statistical analyses
To remove important sources of confounding (the differences in BMI/fat mass and age between the PCOS cases and controls), we performed several different statistical analyses. These included use of paired-sample t tests for comparisons based on data from the 22 BMI/fat mass-matched pairs of PCOS cases and controls and independent-sample t tests (both unadjusted and adjusted for fat mass and age) for the whole-group comparisons of PCOS cases (n = 50) vs. controls (n = 28). All statistical analyses were conducted in SPSS (version 12.0 for Windows; SPSS Inc., Chicago, IL).
All variables (including data from MRI measurements) were skewed and underwent logarithmic transformation before statistical analysis. P <0.05 was considered significant. Power was calculated a priori and informed by the effect size estimate of BFD difference, seen in previous studies (13, 14, 26). On this basis, we had greater than 80% power to detect a between-group difference exceeding 86 and 67% of a SD for L4 visceral fat cross-sectional area in the BMI/fat mass-matched PCOS cases/control pairs and whole-group comparisons respectively (
= 0.05).
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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and 2, respectively. Paired-sample comparisons between the BMI/fat mass-matched pairs of PCOS cases and controls demonstrated that there were no significant differences in fat-depot measurements between these groups, including L4 visceral fat [geometric mean (SD range) 56.7 cm2 (27.0, 119.1) vs. 61.8 cm2 (39.0, 98.2), respectively; P = 0.40, Table 2]. Similar results were obtained for the other fat depot measurements, including cross-sectional area measurements taken from abdominal sc (P = 0.22), gluteal sc (P = 0.67), and midfemoral sc (P = 0.37) depots. Importantly, AI was also comparable between the matched pairs of PCOS cases and controls (P = 0.47, Table 2). Because there were no significant relationships between fat depot measurements and age (L4 visceral fat depot r2 = 0.04, P = 0.70), the age disparity between the BMI/fat mass-matched pairs of PCOS cases and controls was unlikely to be a confounding variable.
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]. There were no significant differences in visceral fat cross-sectional areas between PCOS cases and controls [L4 visceral fat geometric mean (SD range), 73.2 cm2 (38.0, 141.0) vs. 59.4 cm2 (37.6, 93.7) in PCOS cases and controls, respectively; P = 0.14 (unadjusted) and P = 0.25 (adjusted for fat mass and age), Table 2]. Similarly, whole-group comparisons, both unadjusted and adjusted for fat mass and age, revealed no significant differences between PCOS cases and controls for gluteal sc fat (adjusted P = 0.29), midfemoral sc fat (adjusted P = 0.35), and AI (adjusted P = 0.18, Table 2). Restricting these analyses to those PCOS cases naive to the prior use of metformin (n = 29) did not alter these findings. To explore the possible effect of fat mass on BFD in the whole groups of PCOS cases and controls, it was shown that fat mass and AI were positively correlated in both PCOS cases (r2 = 0.56, P = 4.3 x 10–5) and controls (r2 = 0.37, P = 0.02).
In the context of comparable BFD, and indistinguishable visceral fat cross-sectional areas between PCOS cases and BMI/fat mass-matched controls, we also compared metabolic parameters between these two groups. Further paired-sample comparisons between the 22 BMI/fat mass-matched pairs revealed that PCOS cases were significantly more insulin resistant and had significantly higher fasting serum insulin concentrations than controls [HOMA2 IR geometric mean (SD range), 1.50 (0.68, 3.31) and 1.16 (0.62, 2.18), respectively, P = 0.03; fasting serum insulin geometric mean (SD range), 10.1 µU/ml (4.6, 22.3) and 7.7 µU/ml (4.0, 14.6), respectively, P = 0.03; Table 1]. The association between visceral fat and insulin resistance [demonstrated previously in women with PCOS (1)] was explored further. There were significant positive correlations between HOMA2 IR and visceral fat cross-sectional area in the PCOS cases (r2 = 0.81, P = 1.5 x 10–5) and BMI/fat mass-matched controls (r2 = 0.82, P = 2.7 x 10–6; Fig. 2).
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Given the positive association of fat mass with AI in women, our data highlight the importance of matching for BMI and fat mass between PCOS cases and controls and performing appropriate adjustments for fat mass when making comparisons of BFD between these groups. The association of fat mass with AI may have influenced some previous BFD comparisons between groups of PCOS cases and controls with disparate BMIs (12) and body fat mass (14). Furthermore, this phenomenon might account for differences between our conclusions, drawn from data on mainly overweight and obese subjects (thereby precluding conclusions regarding BFD in lean PCOS cases), and those of some previous investigators who studied mainly lean subjects (13).
A limitation of our study was that, although the 22 pairs of PCOS cases and controls were pair matched for BMI and fat mass, it was not possible to match them also for age. Therefore, it is not possible to exclude a residual effect of age on the paired-sample analyses. However, a confounding effect of age is unlikely in our study, given that we found no relationship between age and fat depot measurements within our cohort. Furthermore, the comparisons between the PCOS cases and controls were adjusted for both fat mass and age. It is important to emphasize that the 22 pairs of PCOS cases and controls represents a distillation of much larger sample sizes due to the need to limit important confounders and normalize the groups with respect to BMI/fat mass. A further limitation was that we could not exclude subtle differences in BFD between groups, which our study would have been underpowered to detect. However, the numbers of subjects in our study are comparable with most previous studies of BFD in PCOS (12, 13, 14, 15). Furthermore, we have demonstrated that our MRI data are very reproducible, confirming their validity.
Fat distribution in the main deposition sites (i.e. eutopic fat, including visceral fat) was shown to be comparable between the matched-pairs of PCOS cases and controls in our study. Despite the similarity in fat distribution, there were significant differences in HOMA2 IR measures of insulin sensitivity between these two groups. A possible explanation for this is that women with PCOS have abnormal ectopic fat deposition (e.g. in liver and muscle) (27, 28). Any differences in ectopic fat deposition between PCOS cases and controls, including differences in intrahepatic fat content, would not have been detected by our approach. Comparison of ectopic fat deposition between PCOS cases and controls would therefore be a fruitful area for further study.
To summarize, we provide the strongest evidence yet presented that obese and overweight women with PCOS and BMI/fat mass-matched control women are indistinguishable with respect to fat distribution and that excessive insulin resistance in PCOS appears to be independent of visceral adiposity.
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Acknowledgments |
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Footnotes |
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First Published Online December 18, 2007.
Abbreviations: AI, Android index; BFD, body fat distribution; BMI, body mass index; FAI, free androgen index; HOMA2 IR, homeostasis model assessment of insulin resistance; InsI, insulinogenic index; MRI, magnetic resonance imaging; PCO, polycystic ovarian; PCOS, polycystic ovary syndrome.
Received September 20, 2007.
Accepted December 6, 2007.
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References |
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