What is the risk of metabolic syndrome in adolescents with normal BMI who have polycystic ovary syndrome?

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1 Accepted Manuscript What is the risk of metabolic syndrome in adolescents with normal BMI who have polycystic ovary syndrome? Derya Burkankulu, Hikmet Hassa, Yunus Aydin, Didem Arslantaş, F. Deniz Sayıner, Nebahat Ozerdogan PII: S (14) DOI: /j.jpag Reference: PEDADO 1765 To appear in: Journal of Pediatric and Adolescent Gynecology Received Date: 6 August 2014 Accepted Date: 24 August 2014 Please cite this article as: Burkankulu D, Hassa H, Aydin Y, Arslantaş D, Sayıner FD, Ozerdogan N, What is the risk of metabolic syndrome in adolescents with normal BMI who have polycystic ovary syndrome?, Journal of Pediatric and Adolescent Gynecology (2014), doi: /j.jpag This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

2 What is the risk of metabolic syndrome in adolescents with normal BMI who have polycystic ovary syndrome? 1 Key words: adolescent; body mass index; metabolic syndrome; polycystic ovary syndrome Derya Burkankulu 1, Hikmet Hassa 2, Yunus Aydin 3 Didem Arslantaş 4, F. Deniz Sayıner 5, Nebahat Ozerdogan 5 1 Medical Doctor, Eskisehir Osmangazi University, Department of Obstetrics and Gynecology, Eskisehir, Turkey 2 Professor Doctor, Eskisehir Osmangazi University, Department of Obstetrics and Gynecology, Reproductive Medicine Unit, Eskisehir, Turkey 3 Assistant Professor Doctor, Eskisehir Osmangazi University, Department of Obstetrics and Gynecology, Reproductive Medicine Unit, Eskisehir, Turkey 4 Associate Professor Doctor, Eskisehir Osmangazi University, Department of Public Health, Eskisehir, Turkey 5 Associate Professor Doctor, Eskişehir Osmangazi University, Nursing College, Eskisehir, Turkey Corresponding Author: Yunus Aydin, Assistant Professor, Eskisehir Osmangazi University School of Medicine, Department of Obstetrics and Gynecology, Eskisehir, 26480, Turkey address: aydin.yunus@yahoo.com Phone number:

3 Abstract 2 Objective: The purpose of this study is to evaluate the effect of PCOS on the prevalence of MBS in adolescent girls with normal BMI Material-Method: Our study group consisted of 63 pubertal girls with a BMI less than 25 kg/m 2 who were referred to our center with signs of hirsutism or oligomenorrhea. The diagnosis of PCOS was based on the recent ESHRE/ASRM proposal and required that all three of the Rotterdam criteria for diagnosing PCOS in adolescents be met. The control group consisted of 159 pubertal girls matched for age and BMI. Glucose, insulin, testosterone, and sex hormone binding globulin (SHBG), free testosterone and all lipid parameters measured. For to diagnose the cases with MBS, modified Cook criteria s were used and cases who had at least 3 of 5 criteria s were diagnosed as MBS. Results: Girls with PCOS had higher blood pressure parameters (systolic/diastolic) (P<0.01), fasting insulin (p=0.007), LDL (p=0.017), triglyceride (p=0.045), total (p<0.001) and free testosterone (p=0.001) levels compared to control group. There were more cases who had at least one Cook s criteria in girls with PCOS compared to the control group but the difference was not significant. However, there were more cases who had MBS in girls with PCOS compared to the control group (P=0.02). Conclusion: MBS prevalence is higher in normal BMI adolescent girls with PCOS compared to age and BMI matched control group. So as clinicians, we must search for the MBS criteria s in girls with PCOS even if they have a normal BMI. Key words: adolescent; body mass index; metabolic syndrome; polycystic ovary syndrome

4 Introduction 3 Polycystic ovarian syndrome (PCOS) affects 5-10% of reproductive-aged women. Oligomenorrhea/amenorrhea with hirsutism is often included in the diagnosis, but the incidence varies with the application of different diagnostic criteria 1. In nearly all cases of PCOS, clinical characteristics of the syndrome start to develop from puberty, but some of the normal pubertal clinical symptoms (acne or menstrual irregularity) overlap with the findings of PCOS. Therefore, if we assume the abnormal pubertal signs (hirsutism, polycystic ovarian appearance on ultrasonography [USG], non-physiological menstrual delays) as normal variations in puberty, the diagnosis of PCOS is often delayed. Moreover, as clinicians, we must not overestimate normal pubertal findings (physiological menstrual irregularity, multifollicular appearance on USG, increased tendency for acne development) as the components of PCOS 2. According to the Rotterdam criteria 3, the incidence of PCOS during puberty is approximately 18-21% 4. However, with the application of standard criteria for the diagnosis of PCOS during the pubertal period, false positive rates are high due to increased overlapping of normal pubertal findings with the findings of PCOS 5. Therefore, as stated in Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group, we must determine the presence of all three Rotterdam criteria to diagnose PCOS in adolescents 1, 5. Today, it is abundantly obvious that PCOS is primarily a metabolic dysfunctional state, in addition to increased hair growth and irregular menstruation 6. Therefore, cardiovascular problems, obesity and insulin resistance are among the factors determining long-term life expectancy and quality of life 1. Metabolic dysfunction can start as early as puberty; thus, correctly diagnosing adolescent girls with PCOS is very important. In a retrospectively designed study, Roe et al. reported that, in adolescent PCOS girls using by the Androgen Excess-PCOS Society (AE-PCOS) criteria 7, the rate of metabolic syndrome (MBS) (10.8 %) was higher than that in a matched control group (1.7%) (P < 0.04) 6. In contrast, Rossi et al.

5 reported that, in obese adolescent PCOS girls diagnosed using the 1990 National Institutes of Health (NIH) criteria 8, the presence of PCOS did not add any additional risk for the development of MBS. Therefore, studies in girls with a normal body mass index (BMI) and 4 with more certain criteria for PCOS might be more informative for describing the relationship between PCOS and MBS 9. In this study, our aim was to investigate the association of metabolic risk factors and metabolic syndrome with PCOS in adolescent girls with normal BMI and PCOS (diagnosed by the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group criteria), compared with a matched control group. To our knowledge, this is the first study investigating the metabolic risk factors in this kind of specialized group. Materials and Methods This cross-sectional case-control study was conducted in the Reproductive Medicine Unit of Eskisehir Osmangazi University between October 2012 and November The reported investigations were performed in accordance with the principles of the Declaration of Helsinki (as revised in Tokyo, 2004). The study protocol was approved by the Ethics Committee of our university, and informed consent was obtained from all of the participants. We enrolled 63 pubertal girls with a BMI less than 25 kg/m 2 who were referred to our center with signs of hirsutism or oligomenorrhea. The diagnosis of PCOS was based on the recent ESHRE/ASRM proposal, requiring that all three of the Rotterdam criteria for diagnosing PCOS in adolescents be met 1. As recommended by ESHRE/ASRM, the diagnostic criteria included the presence of: 1) hyperandrogenemia, defined as elevated blood androgens plus clinical evidence of hyperandrogenemia; 2) oligomenorrhea present for 2 years (<10 menses per year or at >35-day intervals) or primary amenorrhea at the age of 16 years old; and 3) an abdominal ultrasound demonstrating an ovarian volume greater than 10 cm 3. The control group consisted of 159 pubertal girls matched for age and BMI, all of whom had no history or

6 evidence of oligomenorrhea, hirsutism or acne. The exclusion criteria for both groups were: 1) previously diagnosed cardiovascular disease; 2) the presence of an endocrine disorder, such as thyroid dysfunction or hyperprolactinemia; 3) the presence of congenital adrenal hyperplasia, 5 androgen-secreting neoplasms or severe insulin resistance; 4) a history of any type of drug use, including contraceptive, anti-diabetic, antihypertensive, anti-androgenic or weightreduction agents; 5) a history of smoking or alcohol use; 6) and BMI greater than 25 kg/m 2. Clinical variables, such as weight, height and blood pressure (BP) were assessed in all of the subjects using standard protocols during outpatient hospital visits. BMI was calculated as weight divided by the square of height (kg/m 2 ). All of the biochemical and hormonal measurements were obtained during the basal portion of the follicular phase (day 2-5 of menstruation) and were processed in the biochemistry laboratory of the university hospital. Plasma was processed from blood samples by adding 1 mg/ml Na2-EDTA. The blood samples were centrifuged at 3000 g for 15 minutes at 4 C. Immediately after centrifugation, the plasma samples were frozen and stored at -80 C for a period of no more than 4 weeks. Assays for glucose, insulin, testosterone, and sex hormone binding globulin (SHBG) were performed using an automated analyzer (Abbott Architect; Abbott Laboratories, Abbott Park, IL, USA). Free testosterone levels were measured with a commercially available ELISA kit (Diasource, Belgium). All of the lipid parameters (total cholesterol, triglycerides [TG], highdensity lipoprotein cholesterol [HDL cholesterol], and low-density lipoprotein cholesterol [LDL cholesterol]) were measured using an enzymatic colorimetric test. The estimate of insulin resistance, as used for the homeostasis model assessment (HOMA) score, was calculated as fasting insulin x fasting glucose/22.5. For all of the hormonal assays, the intra- and inter-assay coefficients of variation (CVs) were <5%.

7 To diagnose cases of MBS, the modified Cook criteria 10 were used, and patients were diagnosed with MBS who had at least 3 of the 5 criteria: (1) waist circumference > 90th percentile; 2) fasting glucose level 100 mg/dl; 3) triglyceride level 110 mg/dl; 4) HDL 6 level 40 mg/dl; and 5) blood pressure measurement 90th percentile. All of the statistical analyses were performed with SPSS software, version 20.0 (Statistical Package for Social Science, IBM, SPSS Inc.). Descriptive analysis was used to calculate the means and standard deviations of the variables. Significant differences between mean values were estimated by Pearson's correlation analysis, the Mann-Whitney U test and the Kruskal- Wallis test. The χ² test was used to evaluate the groups according to the MBS criteria. The point of statistical significance was noted when probability was P<0.05. Results Table I demonstrates the anthropometric, biochemical, and hormonal data for pubertal girls with PCOS and for the control group. As stated previously, the control group consisted of 159 pubertal girls matched for age and BMI. Blood pressure parameters (systolic/diastolic) were significantly higher in girls with PCOS ( mm Hg vs mm Hg; p<0,001 for systolic BP/74.12 mm Hg vs mm Hg; P<0,007 for diastolic BP). No significant differences in the plasma levels of fasting glucose, total cholesterol, HDL or SHBG were found in girls with PCOS, compared to the control group (table II). Conversely, girls with PCOS had higher fasting insulin (P=0.007), LDL (P=0.017), triglyceride (P=0.045), and total (P<0.001) and free testosterone (P=0.001) levels, compared to the control group (table II). More cases with at least one (P=0.05) and two (P=0.81) of Cook s criteria were found among girls with PCOS compared to the control group (table III). Additionally the prevalence of MBS was 7.9% in girls with PCOS compared with 0.6% in those without PCOS (P=0.02).

8 Discussion 7 According to our results, it seems that the presence of PCOS increases the risk of MBS in pubertal girls, even if they have a normal BMI. In general, MBS consists of metabolic and cardiovascular risk factors 11. It is a syndrome mostly predisposing to atherosclerotic cardiovascular diseases and type II diabetes. The primary pathophysiological mechanism is unclear for this syndrome, but it mostly accompanies chronic low-stage inflammatory conditions, and it mostly affects the length and quality of life 12, 13. Increases in visceral adiposity and central obesity are believed to be the triggering points 14, 15. Furthermore, chronic low-stage inflammatory conditions resulting in endothelial dysfunction and metabolic dysfunction are also common components of PCOS, and today it is clear that PCOS is a systemic disorder that occurs beyond the ovaries 1. Although the prevalence of MBS differs with the nationality and geographic location of populations, the presence of PCOS increases the risk of MBS in reproductive-aged women. The effects of PCOS on the prevalence of MBS in the adolescent population seem contradictory 2. The subject is ambiguous for two reasons; (1) Until now, most of the studies used the same criteria in adolescents and reproductive-aged women to diagnose PCOS, such as the NIH 8, Rotterdam 3 or AE-PCOS 7 criteria. However, as stated in ESHRE/ASRM 1 we must use different criteria to diagnose PCOS in the adolescent population. Particularly with the Rotterdam criteria, over-diagnosis of PCOS during the pubertal period is unavoidable. (2) Diagnostic criteria for metabolic syndrome have been varied over the years, and to diagnose MBS in an adolescent population, we must use different diagnostic criteria from those used in adults 10, 16. In one of the studies of MBS in an adolescent population, in which the AE-PCOS criteria were applied to diagnose PCOS, Roe et al. found an increased rate of MBS in girls with

9 PCOS, compared to the control group 6. In contrast, the mean BMI of girls with PCOS (28.5 kg/m 2 ) was significantly higher than that of the control group (24.7 kg/m 2 ) (P<0.01). Consequently, the higher prevalence of MBS in adolescents with PCOS compared to the 8 control group might have depended on the higher BMI of the girls with PCOS. Accordingly, the study by Rossi et al. is very important because they examined the prevalence of MBS in obese adolescents with PCOS, and they found that obesity was a greater determining factor for MBS than the presence of PCOS 9. However, they used the NIH criteria to diagnose PCOS 8 and Cook criteria s 16 to diagnose MBS. The most important factors that distinguish our study were as follows. (1) To diagnose PCOS cases in adolescents, we used the latest criteria described by ESHRE/ASRM. Therefore, we believe that we distinguished real PCOS cases from normal girls who had one or two normal pubertal characteristics, such as acne, menstrual irregularity or multifollicular appearance of the ovaries on USG. (2) The effects of obesity on PCOS are obvious; thus, our study and control groups consisted of girls with normal BMI. We believe that with this approach, we eliminated the probable effects of increased BMI on MBS. (3) To diagnose MBS in adolescents, we used the latest criteria defined by NHANES 10. According to our study, using these refined selection criteria, it seems that the presence of PCOS increased the prevalence of MBS in an adolescent population with normal BMI. However, although the criteria for MBS in adolescents are abundantly clear, clinicians are not screening adolescents, regardless of whether the criteria for MBS are present 17. In conclusion, the prevalence of MBS was higher in adolescent girls with normal BMI and PCOS, compared to an age- and BMI-matched control group. Thus, as clinicians, we must determine the criteria for MBS in girls with PCOS, even if they have a normal BMI. In addition to the most important complaints of adolescent girls with PCOS, such as hirsutism,

10 acne and oligomenorrhea, we must consider the criteria for MBS, which can determine longterm quality of life. Acknowledgments 9 None

11 10 Declaration of Interests This study was funded by the Scientific Investigations Department of our University with the number of All authors have no conflict of interest.

12 11 References 1. Fauser BC, Tarlatzis BC, Rebar RW, et al. Consensus on women's health aspects of polycystic ovary syndrome (PCOS): the Amsterdam ESHRE/ASRM-Sponsored 3rd PCOS Consensus Workshop Group. Fertil Steril 2012; 97: Hardy TS, Norman RJ. Diagnosis of adolescent polycystic ovary syndrome. Steroids 2013; 78: Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group. Revised 2003 Consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome. Fertil Steril 2004; 81: Hickey M, Doherty DA, Atkinson H, et al. Clinical, ultrasound and biochemical features of polycystic ovary syndrome in adolescents: implications for diagnosis. Hum Reprod 2011; 26: Nicandri KF, Hoeger K. Diagnosis and treatment of polycystic ovarian syndrome in adolescents. Curr Opin Endocrinol Diabetes Obes 2012; 19: Roe AH, Prochaska E, Smith M, et al. Using the androgen excess-pcos society criteria to diagnose polycystic ovary syndrome and the risk of metabolic syndrome in adolescents. J Pediatr 2013; 162: Azziz R, Carmina E, Dewailly D, et al. Task Force on the Phenotype of the Polycystic Ovary Syndrome of The Androgen Excess and PCOS Society. The Androgen Excess and PCOS Society criteria for the polycystic ovary syndrome: the complete task force report. Fertil Steril 2009; 91:

13 8. Zawadski JK and Dunaif A. Diagnostic criteria for polycystic ovary syndrome; towards a rational approach. In: Dunaif A, Givens JR and Haseltine F (eds), Polycystic Ovary Syndrome. Blackwell Scienti Boston, pp. 1992; Rossi B, Sukalich S, Droz J, et al. Prevalence of metabolic syndrome and related characteristics in obese adolescents with and without polycystic ovary syndrome. J Clin Endocrinol Metab 2008; 93: Johnson WD, Kroon JJ, Greenway FL, et al. Prevalence of risk factors for metabolic syndrome in adolescents: National Health and Nutrition Examination Survey (NHANES), Arch Pediatr Adolesc Med 2009; 163: Grundy SM, Cleeman JI, Daniels SR, et al. American Heart Association; National Heart, Lung, and Blood Institute. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112: Hanley AJ, Festa A, D Agostino RB Jr, et al. Metabolic and inflammation variable clusters and prediction of type 2 diabetes: factor analysis using directly measured insulin sensitivity. Diabetes. 2004; 53: Hu FB, Meigs JB, Li TY, et al. Inflammatory markers and risk of developing type 2 diabetes in women. Diabetes.2004; 53: National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002; 106: Jensen MD, Haymond MW, Rizza RA, et al. Influence of body fat distribution on free fatty acid metabolism in obesity. J Clin Invest 1989; 83:

14 16. Cook S, Weitzman M, Auinger P, et al. Prevalence of a metabolic syndrome phenotype in adolescents: findings from the third National Health and Nutrition Examination Survey, Arch Pediatr Adolesc Med 2003; 157: Broder-Fingert S, Shah B, Kessler M, et al. Evaluation of adolescents for polycystic ovary syndrome in an urban population. J Clin Res Ped Endocrinol 2009; 1:

15 14 Table I: Baseline demographic and clinical parameters of the cases with and without PCOS

16 15 Table II: Comparison of androgens, biochemical glycemic and lipid profile in cases with and without PCOS

17 16 Table III: Prevalence of metabolic risk factors and metabolic syndrome in adolescents with and without PCOS

18 Table I: Baseline demographic and clinical parameters of the cases with and without PCOS Cases with PCOS Cases without PCOS P value (n=63) (n=159 ) Age (years) 15.72± ±1.84 NS Weight (kg) 57.28± ±11.97 NS Height (cm) ± ±4.87 NS BMI (kg/m 2 ) 20.23( ) 21.03( ) NS Waist circumference 77.49± ±10.22 NS Systolic blood pressure ± ±13.93 <0.01 (mmhg) Diastolic blood pressure 74.12± ±11.29 <0.01 (mmhg) NS: non-significant, BMI: Body mass index.

19 Table II: Comparison of androgens, biochemical glycemic and lipid profile in cases with and without PCOS Cases with PCOS Cases without PCOS P value (n=63 ) (n=159 ) Fasting insulin (µiu/ml) 14,35 10,93 0,007 Fasting glucose (mg/dl) 84,44 85,91 NS HOMA IR 2,85 2,35 NS Total cholesterol 156,48 153,98 NS (mg/dl) HDL (mg/dl) 61,09 57,98 NS LDL (mg/dl) 92,88 86,14 0,017 Triglyceride (mg/dl) 91,22 78,91 0,045 Total testosterone 45,36 28,23 0,000 (ng/dl) Free testosterone 3,26 1,99 0,001 (pg/ml) SHBG (nmol/liter) 56,93 45,45 NS HOMA IR, homeostasis model assessment insulin resistance; HDL, high-density lipoprotein cholesterol; LDL, low-density lipoprotein cholesterol; apoa1, ApolipoproteinA-I; apob, Apolipoprotein B; SHBG, sex hormone binding globulin; FAI, free androgen index; NS: non-significant

20 Table III: Prevalence of metabolic risk factors and metabolic syndrome in adolescents with and without PCOS Cases with PCOS Cases without PCOS P value Cases with 1 metabolic risk factor, n (%) Cases with 2 metabolic risk factor, n (%) Cases with 3 metabolic risk factor (metabolic syndrome), n (%) NS: non-significant (n=63) (n=159) 31 (50.1) 34 (21.3) (11.1) 10 (6.2) NS 5 (7.9) 1 (0.6) 0.02