Gynecological Endocrinology
ISSN: 0951-3590 (Print) 1473-0766 (Online) Journal homepage: http://www.tandfonline.com/loi/igye20
Observation of phenotypic variation among Indian women with polycystic ovary syndrome (PCOS) from Delhi and Srinagar Mohd Ashraf Ganie, Raman Kumar Marwaha, Atul Dhingra, Sobia Nisar, Kaliavani Mani, Shariq Masoodi, Semanti Chakraborty & Aafia Rashid To cite this article: Mohd Ashraf Ganie, Raman Kumar Marwaha, Atul Dhingra, Sobia Nisar, Kaliavani Mani, Shariq Masoodi, Semanti Chakraborty & Aafia Rashid (2016): Observation of phenotypic variation among Indian women with polycystic ovary syndrome (PCOS) from Delhi and Srinagar, Gynecological Endocrinology, DOI: 10.3109/09513590.2016.1141879 To link to this article: http://dx.doi.org/10.3109/09513590.2016.1141879
Published online: 15 Feb 2016.
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http://informahealthcare.com/gye ISSN: 0951-3590 (print), 1473-0766 (electronic) Gynecol Endocrinol, Early Online: 1–5 ! 2016 Taylor & Francis. DOI: 10.3109/09513590.2016.1141879
ORIGINAL ARTICLE
Observation of phenotypic variation among Indian women with polycystic ovary syndrome (PCOS) from Delhi and Srinagar Mohd Ashraf Ganie1, Raman Kumar Marwaha1, Atul Dhingra1, Sobia Nisar2, Kaliavani Mani3, Shariq Masoodi4, Semanti Chakraborty1, and Aafia Rashid4
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1
Department of Endocrinology and Metabolism, 2Department of Geriatric Medicine, 3Department of Biostatistics, Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India, and 4Department of Endocrinology, Sheri-Kashmir Institute of Medical Sciences, Srinagar, J&K, India Abstract
Keywords
Polycystic ovary syndrome (PCOS) is a heterogeneous disorder that demonstrates ethnic and regional differences. To assess the phenotypic variability among Indian PCOS women, we evaluated clinical, biochemical and hormonal parameters of these women being followed in two tertiary care institutions located in Delhi and Srinagar. A total of 299 (210 PCOS diagnosed by Rotterdam 2003 criteria and 89 healthy) women underwent estimation of T4, TSH, LH, FSH, total testosterone, prolactin, cortisol, 17OHP, and lipid profile, in addition to post OGTT, C-peptide, insulin, and glucose measurements. Among women with PCOS, mean age, age of menarche, height, systolic, diastolic blood pressure, and serum LH were comparable. PCOS women from Delhi had significantly higher BMI (26.99 ± 5.38 versus 24.77 ± 4.32 kg/m2; P ¼ 0.01), glucose intolerance (36 versus 10%), insulin resistance as measured by HOMA-IR (4.20 ± 3.39 versus 3.01 ± 2.6; P ¼ 0.006) and QUICKI (0.140 ± 0.013 versus 0.147 ± 0.015; P ¼ 0.03) while PCOS from Srinagar had higher FG score (12.12 ± 3.91 versus 10.32 ± 2.22; P ¼ 0.01) and serum total testosterone levels (0.65 ± 0.69 versus 0.86 ± 0.41 ng/ml; P ¼ 0.01. Two clear phenotypes, i.e. obese hyperinsulinaemic dysglycemic women from Delhi and lean hyperandrogenic women from Srinagar are emerging. This is the first report on North Indian women with PCOS showing phenotypic differences in clinical, biochemical and hormonal parameters despite being in the same region.
Diabetes, hirsutism, insulin resistance, polycystic ovary syndrome
Introduction Polycystic ovary syndrome (PCOS) being one of the most common conditions affecting women in the reproductive age group, is associated with multiple reproductive and metabolic complications [1–2]. PCOS initially described by Stein and Leventhal [3] as a gynecological disorder, has now assumed importance due to the fact that it is associated with a constellation of metabolic derangements and cardiovascular risks including obesity, type 2 diabetes mellitus (DM), dyslipidemia, hypertension, metabolic syndrome and insulin resistance[4–7]. Several studies have reported prevalence of PCOS to be between 2.2% to as high as 26% with 40% of them having insulin resistance [2,4,8– 12]. Using Rotterdam criteria among reproductive age group women, prevalence figures vary in some Asian countries ranging from 2% to 5.6% in China [8,13] to 6.3% in Sri Lanka [14] and 22.5% in India [15]. Furthermore, three Indian studies have reported a higher prevalence of PCOS among urban participants as compared to rural subjects [16–18]. Similarly, Australian retrospective birth cohort study of 728 women reported a
Address for correspondence: Mohd Ashraf Ganie, Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India. Tel: +91-11-26593645/3968, +91-9419041546 (M). Fax: +91-11-26589162. E-mail: [email protected]
History Received 3 May 2015 Revised 8 January 2016 Accepted 11 January 2016 Published online 11 February 2016
prevalence of 12% as per Rotterdam criteria [19]. These variations in prevalence of PCOS have been explained by different ethnic origin of these populations. Heterogeneity has also been observed in clinical and biochemical features. In a study from USA, Goodrazi et al. [20] found a higher degree of insulin resistance among Mexican women with PCOS as compared to white women. Lo et al. [21] studied cardiovascular risk profile in white, African American, Asian and Hispanic PCOS patients, they found that whites (85%), Blacks (95.9%) and Hispanics(92.2%) were more likely and Asians (77.1%) less likely to be obese (BMI 25 kg/m2); Asians(11.9%) and Hispanics (11.9%) were more likely to have diabetes; and Blacks(40.9%) were more likely and Hispanics (26.6%] less likely to have hypertension. Wijeratne et al. [22] from Sri Lanka reported a higher degree of insulin resistance and increased prevalence of metabolic syndrome in 469 PCOS subjects. Similarly Sundararaman et al. [23] also observed a greater insulin resistance and intima–media thickness in South Indian women with PCOS. Norman et al. [24] studied Indian women and white women with PCOS and reported greater insulin responses in South Asian Indian women (PCOS and controls) had than matched white women. Due to the clinical and biochemical heterogeneity of PCOS, several studies have focused on hormonal, genetic and environmental factors involved in the development of this syndrome. Previously, De Ugarte et al [25] had reported that ethnicity has an independent and additive effect on insulin
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secretion in Carribean Hispanic PCOS women. Welt et al. [26] also reported differences in reproductive manifestations in Icelandic PCOS women and Boston Caucasian PCOS women. Polymorphisms in the genes that are involved in insulin secretion and action, ovarian and adrenal steroidogenesis and energy regulation may be responsible for these ethnic variations. India is a large country with significant regional, cultural and ethnic diversity. Data on clinical, biochemical and hormonal parameters in women with PCOS of different ethnic origin from India is scarce. To address this variability of PCOS phenotype across populations, we studied clinical and metabolic parameters of women with PCOS from Delhi and Srinagar located in North India.
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Subjects and methods The study was carried out at the Endocrinology and Metabolism clinics of two tertiary care centers (All India Institute of Medical Sciences, New Delhi and Sheri-Kashmir Institute of Medical Sciences, Srinagar) located in North India, between January 2008 and December 2010. Consequent women attending the abovementioned outpatient clinics with complaints of menstrual disturbances, hirsutism, acne vulgaris, androgenic alopecia, infertility, etc., were informed about the study. The women who qualified diagnosis of PCOS by Rotterdam 2003 criteria [27] and volunteered to be part of the study were asked to sign an informed consent to undergo OGTT, in addition to routine evaluation. The data was acquired using a common predesigned proforma at both the centers. A detailed interview was arranged with the patient to record details of various medical facts with particular emphasis on menstrual history including age of menarche, regularity, duration, and number of cycles per year. Menstrual disturbances were classified as oligo-/amenorrhea (8 cycles/year or menstrual interval 35 days or 48 cycles but highly irregular) and amenorrhea (absence of menses in last six or more months). Other history included temporal profile of weight gain, duration of infertility, family history of PCOS, family history of type 2 DM, drug intake, progression and distribution of hirsutism, severity and treatment response in acne vulgaris etc. Women with any systemic disorders or those with history of intake of drugs known to interfere with glucose or insulin metabolism in the preceding six weeks were excluded from the study. Anthropometric assessment included measurement of height (cm), body weight (kg), waist and hip circumference (cm) with calculation of BMI (kg/m2). Modified Ferriman-Gallwey (FG) score was used to assess the degree of hirsutism and a score of 8 (out of a total of 36 from nine body areas) was taken as significant [28]. Blood samples were collected after an overnight (8–10 h) fast with a stable diet for preceding 72 h, and preferably on 3rd to 7th day (early follicular phase) of spontaneous menstrual cycle in regularly menstruating women or any day in ammenorrhic women. Blood samples were aliqouted for plasma insulin, total T4, TSH, LH, FSH, prolactin (PRL), total testosterone, 17-OHP, cortisol (morning), plasma glucose, blood counts, electrolytes, lipids, liver, and kidney functions. After obtaining the fasting blood sample an oral glucose challenge was performed with 75 gm anhydrous glucose dissolved in 250–300 ml water (OGTT), and blood samples were collected at 60 and 120 min later for plasma glucose. Serum was separated at room temperature and aliqouted as per the requirements. All biochemical analysis was done on the same day whereas the aliquots for hormones were stored at 70 C until the assay. Transabdominal ultrasonography was done to demonstrate any suggestion of polycystic ovarian morphology, i.e. presence of 10 or more peripheral follicles each measuring 2–8 mm in size with echogenic ovarian stroma and increased ovarian volume [29].
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Table 1. Clinical, biochemical and hormonal variables in women with PCOS and normal control women. Variable Age (years) Menarche (years) Ferriman–Gallwey Score Height (cm) Weight (kg) BMI (kg/m2) Waist (cm) Hip circum (cm) SBP (mm Hg) DBP (mm Hg) LH (mIU/ml) FSH (mIU/ml) Total testosterone (ng/ml) Total cholesterol (mg/dl) Triglycerides (mg/dl) HDL cholesterol (mg/dl) LDL cholesterol (mg/dl) Plasma glucose – 0 h (mg/dl) Plasma glucose – 2 h (mg/dl) Plasma Insulin – 0 h (mIU/ml) Plasma Insulin – 2 h (mIU/ml) Serum C-peptide – 0 h (ng/ml) Serum C-peptide – 2 h (ng/ml)
Control
Cases
p Values
25.62 ± 6.29 12.30 ± 0.92 3.14 ± 2.46 156.78 ± 5.33 61.13 ± 11.92 24.81 ± 4.25 80.66 ± 9.90 87.37 ± 7.68 111.31 ± 11.90 73.26 ± 6.60 8.05 ± 2.93 5.61 ± 1.96 0.36 ± 0.13 157.79 ± 28.92 106.94 ± 42.14 49.47 ± 10.26 92.17 ± 26.91 87.87 ± 11.71 101.98 ± 20.01 8.29 ± 4.00 35.37 ± 25.61 1.27 ± 1.00 4.81 ± 4.19
22.46± 4.80 12.76 ± 1.34 11.26 ± 3.38 156.76 ± 5.12 63.50 ± 12.73 25.83 ± 4.96 81.07 ± 9.92 86.76 ± 8.51 114.19 ± 9.05 77.03 ± 7.41 8.73 ± 5.69 6.30 ± 2.10 0.76 ± 0.57 167.55 ± 32.55 128.90 ± 63.28 45.57 ± 7.78 108.42 ± 26.43 90.61 ± 15.70 121.69 ± 41.22 15.66 ± 12.39 69.08 ± 75.52 2.55 ± 1.68 6.16 ± 4.76
0.01 0.01 0.01 0.97 0.10 0.06 0.72 0.52 0.01 0.01 0.62 0.01 0.01 0.01 0.01 0.06 0.01 0.09 0.01 0.01 0.01 0.01 0.06
Assays Plasma glucose and other biochemical parameters were assayed on autoanalysers (Roche Hitachi 912, Minatoku, Tokyo, Japan) at SKIMS, Srinagar and AIIMS, New Delhi. All the hormonal assays except plasma insulin were carried out in the respective departmental laboratories by radioimmunoassay (T4, cortisol, DHEAS, 17-OHP, testosterone) and immunoradiometric assays (TSH, LH, PRL, FSH) using commercial kits, in duplicate and according to supplier protocol (Diagnostic Products Corporation, Los Angeles, CA for cortisol, 17-OHP FSH, LH, TSH PRL and testosterone; Immunotech, France for DHEAS; and Diasorin USA for T4). Plasma insulin was done by RIA (BARC, Mumbai, India) at AIIMS, New Delhi for all the samples from both the centers. Intra and interassay coefficients of variations were within the limits permitted by the manufacturers.
Statistical analysis Data analysis was performed using the STATA 13 (StataCorp LP, College Station, TX). Descriptive analysis was done for all clinical, biochemical and hormonal parameters and results were expressed as Mean ± SD. The differences between groups were assessed using two tailed unpaired Students’ t-test and Chi square for continuous and categorical variables respectively. For multiple comparisons between groups ANOVA was used. Pearson correlation was used to check the association between various clinical and biochemical parameters with the glucose values. Parameters were log transformed if the standard deviation was higher than mean. p values of50.05 was taken as the cut off level for significance.
Results A total of 210 subjects diagnosed as having PCOS by Rotterdam 2003 criteria and 89 healthy controls were evaluated. Table 1 shows clinical, biochemical and metabolic differences among women with PCOS and controls. To assess the regional differences among women with PCOS, all parameters were compared in the cases from Delhi and Srinagar. Among subjects with PCOS, the mean age, mean age of
PCOS phenotype
DOI: 10.3109/09513590.2016.1141879
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Table 2. Showing clinical, biochemical and hormonal variables in women with PCOS and normal control women from Srinagar and Delhi.
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Variable Mean age (years) Mean age of menarche (years) Height (cm) Weight (kg) BMI (kg/m2) Waist (cm) Hip (cm) FG Score SBP (mm of hg) DBP (mm of hg) LH (mIU/ml) FSH (mIU/ml) Testosterone (ng/ml) Total cholesterol (mg/dl) Triglycerides (mg/dl) BG 0 hr (mg/dl) BG 2 hr (mg/dl) Insulin 0 hr (uIU/ml) Insulin 2 h (uIU/ml) C peptide (0 h) C peptide (2 h) HOMA-IR QUICKI
Controls
Cases
Mean ± SD
Mean ± SD
Srinagar (n ¼ 45)
Delhi (n ¼ 44)
p Values
Srinagar (n ¼ 110)
Delhi (n ¼ 100)
p Values
22.02 ± 3.23 12.17 ± 0.911 155.77 ± 4.51 58.93 ± 12.03 24.20 ± 4.25 79.66 ± 9.66 85.93 ± 7.47 3.17 ± 2.46 115.06 ± 14.60 73.51 ± 8.05 7.88 ± 3.10 5.83 ± 1.82 0.40 ± 0.14 158.65 ± 29.72 119.44 ± 50.64 90.75 ± 14.84 90.75 ± 15.70 7.78 ± 4.11 20.57 ± 22.71 0.18 ± 0.20 0.20 ± 0.26 1.74 ± 0.91 0.157 ± 0.016
23.54 ± 3.65 12.47 ± 0.97 157.22 ± 5.03 61.61 ± 11.31 24.89 ± 4.22 81.29 ± 10.06 88.20 ± 7.60 3.12 ± 2.48 108.36 ± 9.28 72.77 ± 5.70 8.15 ± 2.83 5.85 ± 2.19 0.33 ± 0.11 157.33 ± 28.69 100.25 ± 35.42 85.25 ± 7.72 105.22 ± 18.10 8.62 ± 3.93 44.76 ± 22.86 1.97 ± 0.60 7.74 ± 2.54 1.84 ± 0.87 0.156 ± 0.019
0.04 0.13 0.15 0.28 0.44 0.43 0.15 0.37 0.01 0.61 0.38 0.96 0.01 0.42 0.32 0.03 0.01 0.08 0.01 0.01 0.01 0.32 0.78
22.45 ± 4.19 12.82 ± 1.24 156.77 ± 5.17 60.92 ± 11.37 24.77 ± 4.32 80.86 ± 10.08 87.56 ± 7.76 12.12 ± 3.91 113.3 ± 8.30 76.30 ± 6.90 8.35 ± 3.88 6.72 ± 1.58 0.86 ± 0.41 164.12 ± 32.93 132.30 ± 67.30 88.7 ± 16.35 112.20 ± 43.18 13.42 ± 10.73 53.92 ± 80.06 2.19 ± 1.91 5.71 ± 5.26 3.01 ± 2.6 0.147 ± 0.015
22.49 ± 4.37 12.69 ± 1.45 156.76 ± 5.09 66.33 ± 13.57 26.99 ± 5.38 81.30 ± 9.78 85.89 ± 9.22 10.32 ± 2.22 115.17 ± 9.76 77.84 ± 7.90 9.14 ± 7.17 5.85 ± 2.48 0.65 ± 0.69 179.80 ± 28.39 115.92 ± 43.37 92.73 ± 14.74 132.13 ± 36.40 18.12 ± 14.07 85.75 ± 66.68 2.95 ± 1.30 6.66 ± 4.01 4.20 ± 3.39 0.140 ± 0.013
0.96 0.46 0.98 0.01 0.01 0.75 0.15 0.01 0.13 0.13 0.68 0.01 0.01 0.01 0.31 0.63 0.01 0.01 0.01 0.01 0.01 0.01 0.01
menarche, height, waist circumference and hip circumference were comparable (Table 2). Delhi PCOS subjects had significantly higher BMI (26.99 ± 5.38 kg/m2 versus 24.77 ± 4.32 kg/m2 P ¼ 0.001) but lower FG score (10.32 ± 2.22 versus 12.12 ± 3.91; P¼ 0.0012) and serum testosterone (0.65 ± 0.69 versus 0.86 ± 0.41; P ¼ 0.01) as compared to those from Srinagar. Mean serum LH levels were comparable in two groups but serum FSH (5.85 ± 2.48 versus 6.72 ± 1.58 mIU/ml; P ¼ 0.002) was lower in Delhi PCOS subjects as compared to Srinagar PCOS subjects. Among metabolic parameters, Delhi and Srinagar subjects had comparable total cholesterol, triglycerides and fasting plasma glucose but 2 h post OGTT plasma glucose (132.13 ± 36.40 versus 112.20 ± 43.18; P ¼ 0.01) was significantly higher in Delhi subjects. Similarly, serum insulin and Cpeptide levels were significantly higher in Delhi PCOS subjects. Glucose intolerance was seen in 36% (36/100) PCOS subjects from Delhi and 10% (11/110) subjects from Srinagar. Furthermore, insulin resistance as measured by HOMA-IR was higher (4.20 ± 3.39 versus 3.01 ± 2.6; P ¼ 0.01) and insulin sensitivity as measured by QUICKI (0.140 ± 0.013 versus 0.147 ± 0.015; P ¼ 0.01) was lower in PCOS subjects from Delhi when compared with those from Srinagar. Among control subjects, the clinical, biochemical and hormonal parameters were mostly comparable except serum total testosterone and insulin resistance as shown in the table. Serum total testosterone was significantly higher in Srinagar controls while 2 h post OGTT serum insulin levels, C-peptide and QUICKI indicative of higher insulin resistance in controls from Delhi.
Discussion PCOS, the commonest heterogeneous disorder of young women is characterized by a multitude of reproductive and metabolic abnormalities [20]. Due to its heterogeneity, PCOS can present with different features in different ethnic populations [14]. These differences are not only limited to incidence in different populations but also in the metabolic and reproductive
manifestations [21]. Overall, the differences in the clinical presentations such as higher age in the attainment of menarche, oligomenorrhea, higher FG score, higher serum testosterone, glucose intolerance, insulin resistance and lipid abnormalities in subjects with PCOS when compared with controls, are consistent with earlier reports. The age of achieving menarche (12.76 ± 1.34) was significantly higher against that of control girls as well as that has been observed in (i.e. 12.35 ± 1.2 years) normal Indian girls (thesis submitted to AIIMS, New Delhi). PCOS subjects from Srinagar had higher FG score, serum total testosterone and higher serum FSH levels as compared to those from Delhi who had higher BMI, waist circumference, higher cholesterol, TG, fasting and 2 h plasma insulin, C-peptide and 2 h blood glucose. Intrinsic differences in 17 -hydroxysteroid dehydrogenase pathway could be responsible for higher testosterone levels in PCOS patients from Srinagar. Welt et al. [26] reported higher BMI, higher DHEAS and lower serum testosterone levels in Icelandic women with PCOS as compared to Caucasian PCOS women from Boston. They hypothesized that low testosterone in Icelandic subjects was due to an intrinsic difference in the 17 -hydroxysteroid dehydrogenase pathway in women from Iceland and Boston. However, in addition, the higher levels of total testosterone among women with PCOS from Srinagar could be attributable to difference in aromatization rates due to body fat. Interestingly, the higher FSH levels observed in Srinagar cohort is difficult to explain and possibly could reflect poorer ovarian reserve in PCOS subjects from Srinagar [30]. More severe metabolic derangements (higher HOMA-IR, lower QUICKI, insulin and c peptide levels insulin resistance, glucose levels, lipid levels) among Delhi PCOS women can be explained on the basis of higher BMI in these girls. These differences may be accounted partly by varying background prevalence of type 2 diabetes mellitus and obesity in general population of these regions (6.1% and 2.9% in Srinagar and 10.3% and 18.4% in Delhi) or genetic differences in the two populations [31–33]. For example, some studies from United Kingdom [34] and Slovene [35] have reported genetic polymorphisms in the
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insulin gene, insulin receptor gene and insulin receptor substrates as mechanism for these variations whereas studies from China, Spain and Czech Republic did not find any association between insulin gene polymorphism and PCOS [36–38]. In view of the fact that similar differences in serum testosterone and insulin resistance were also noted between the two control populations, may suggest genetic variation between the two regions. These baseline population differences may act as determinants of the phenotypic expression of PCOS from different regions. It has been hypothesized that in utero fetal programming may play a role in the development of PCOS phenotype in adult life and it is the interaction of environmental factors (obesity) with genetic factors that leads to development of complete PCOS phenotype [39]. Social and environmental conditions in two states may also contribute to these differences. Delhi has 80% Hindu population with majority as vegetarians whereas Kashmir has 95% Muslim population with majority nonvegetarians. The weaknesses of the present study are: (a) absence of data on detailed family history, (b) smaller number of controls (c), and non-availability of serum DHEAS, free testosterone, and SHBG levels that could possibly influence these differences in the two groups were not undertaken. We conclude that this is the first report from India showing regional differences in clinical, biochemical and hormonal parameters within the same region. Large well-designed, multicentre studies are required to be undertaken to understand the mechanism underlying these differences.
Declaration of interest The authors report no conflict of interest. The authors alone are responsible for the content and writing of the paper.
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Observation of phenotypic variation among Indian women with polycystic ovary syndrome (PCOS) from Delhi and Srinagar Mohd Ashraf Ganie, Raman Kumar Marwaha, Atul Dhingra, Sobia Nisar, Kaliavani Mani, Shariq Masoodi, Semanti Chakraborty & Aafia Rashid To cite this article: Mohd Ashraf Ganie, Raman Kumar Marwaha, Atul Dhingra, Sobia Nisar, Kaliavani Mani, Shariq Masoodi, Semanti Chakraborty & Aafia Rashid (2016): Observation of phenotypic variation among Indian women with polycystic ovary syndrome (PCOS) from Delhi and Srinagar, Gynecological Endocrinology, DOI: 10.3109/09513590.2016.1141879 To link to this article: http://dx.doi.org/10.3109/09513590.2016.1141879
Published online: 15 Feb 2016.
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http://informahealthcare.com/gye ISSN: 0951-3590 (print), 1473-0766 (electronic) Gynecol Endocrinol, Early Online: 1–5 ! 2016 Taylor & Francis. DOI: 10.3109/09513590.2016.1141879
ORIGINAL ARTICLE
Observation of phenotypic variation among Indian women with polycystic ovary syndrome (PCOS) from Delhi and Srinagar Mohd Ashraf Ganie1, Raman Kumar Marwaha1, Atul Dhingra1, Sobia Nisar2, Kaliavani Mani3, Shariq Masoodi4, Semanti Chakraborty1, and Aafia Rashid4
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1
Department of Endocrinology and Metabolism, 2Department of Geriatric Medicine, 3Department of Biostatistics, Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India, and 4Department of Endocrinology, Sheri-Kashmir Institute of Medical Sciences, Srinagar, J&K, India Abstract
Keywords
Polycystic ovary syndrome (PCOS) is a heterogeneous disorder that demonstrates ethnic and regional differences. To assess the phenotypic variability among Indian PCOS women, we evaluated clinical, biochemical and hormonal parameters of these women being followed in two tertiary care institutions located in Delhi and Srinagar. A total of 299 (210 PCOS diagnosed by Rotterdam 2003 criteria and 89 healthy) women underwent estimation of T4, TSH, LH, FSH, total testosterone, prolactin, cortisol, 17OHP, and lipid profile, in addition to post OGTT, C-peptide, insulin, and glucose measurements. Among women with PCOS, mean age, age of menarche, height, systolic, diastolic blood pressure, and serum LH were comparable. PCOS women from Delhi had significantly higher BMI (26.99 ± 5.38 versus 24.77 ± 4.32 kg/m2; P ¼ 0.01), glucose intolerance (36 versus 10%), insulin resistance as measured by HOMA-IR (4.20 ± 3.39 versus 3.01 ± 2.6; P ¼ 0.006) and QUICKI (0.140 ± 0.013 versus 0.147 ± 0.015; P ¼ 0.03) while PCOS from Srinagar had higher FG score (12.12 ± 3.91 versus 10.32 ± 2.22; P ¼ 0.01) and serum total testosterone levels (0.65 ± 0.69 versus 0.86 ± 0.41 ng/ml; P ¼ 0.01. Two clear phenotypes, i.e. obese hyperinsulinaemic dysglycemic women from Delhi and lean hyperandrogenic women from Srinagar are emerging. This is the first report on North Indian women with PCOS showing phenotypic differences in clinical, biochemical and hormonal parameters despite being in the same region.
Diabetes, hirsutism, insulin resistance, polycystic ovary syndrome
Introduction Polycystic ovary syndrome (PCOS) being one of the most common conditions affecting women in the reproductive age group, is associated with multiple reproductive and metabolic complications [1–2]. PCOS initially described by Stein and Leventhal [3] as a gynecological disorder, has now assumed importance due to the fact that it is associated with a constellation of metabolic derangements and cardiovascular risks including obesity, type 2 diabetes mellitus (DM), dyslipidemia, hypertension, metabolic syndrome and insulin resistance[4–7]. Several studies have reported prevalence of PCOS to be between 2.2% to as high as 26% with 40% of them having insulin resistance [2,4,8– 12]. Using Rotterdam criteria among reproductive age group women, prevalence figures vary in some Asian countries ranging from 2% to 5.6% in China [8,13] to 6.3% in Sri Lanka [14] and 22.5% in India [15]. Furthermore, three Indian studies have reported a higher prevalence of PCOS among urban participants as compared to rural subjects [16–18]. Similarly, Australian retrospective birth cohort study of 728 women reported a
Address for correspondence: Mohd Ashraf Ganie, Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi, India. Tel: +91-11-26593645/3968, +91-9419041546 (M). Fax: +91-11-26589162. E-mail: [email protected]
History Received 3 May 2015 Revised 8 January 2016 Accepted 11 January 2016 Published online 11 February 2016
prevalence of 12% as per Rotterdam criteria [19]. These variations in prevalence of PCOS have been explained by different ethnic origin of these populations. Heterogeneity has also been observed in clinical and biochemical features. In a study from USA, Goodrazi et al. [20] found a higher degree of insulin resistance among Mexican women with PCOS as compared to white women. Lo et al. [21] studied cardiovascular risk profile in white, African American, Asian and Hispanic PCOS patients, they found that whites (85%), Blacks (95.9%) and Hispanics(92.2%) were more likely and Asians (77.1%) less likely to be obese (BMI 25 kg/m2); Asians(11.9%) and Hispanics (11.9%) were more likely to have diabetes; and Blacks(40.9%) were more likely and Hispanics (26.6%] less likely to have hypertension. Wijeratne et al. [22] from Sri Lanka reported a higher degree of insulin resistance and increased prevalence of metabolic syndrome in 469 PCOS subjects. Similarly Sundararaman et al. [23] also observed a greater insulin resistance and intima–media thickness in South Indian women with PCOS. Norman et al. [24] studied Indian women and white women with PCOS and reported greater insulin responses in South Asian Indian women (PCOS and controls) had than matched white women. Due to the clinical and biochemical heterogeneity of PCOS, several studies have focused on hormonal, genetic and environmental factors involved in the development of this syndrome. Previously, De Ugarte et al [25] had reported that ethnicity has an independent and additive effect on insulin
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secretion in Carribean Hispanic PCOS women. Welt et al. [26] also reported differences in reproductive manifestations in Icelandic PCOS women and Boston Caucasian PCOS women. Polymorphisms in the genes that are involved in insulin secretion and action, ovarian and adrenal steroidogenesis and energy regulation may be responsible for these ethnic variations. India is a large country with significant regional, cultural and ethnic diversity. Data on clinical, biochemical and hormonal parameters in women with PCOS of different ethnic origin from India is scarce. To address this variability of PCOS phenotype across populations, we studied clinical and metabolic parameters of women with PCOS from Delhi and Srinagar located in North India.
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Subjects and methods The study was carried out at the Endocrinology and Metabolism clinics of two tertiary care centers (All India Institute of Medical Sciences, New Delhi and Sheri-Kashmir Institute of Medical Sciences, Srinagar) located in North India, between January 2008 and December 2010. Consequent women attending the abovementioned outpatient clinics with complaints of menstrual disturbances, hirsutism, acne vulgaris, androgenic alopecia, infertility, etc., were informed about the study. The women who qualified diagnosis of PCOS by Rotterdam 2003 criteria [27] and volunteered to be part of the study were asked to sign an informed consent to undergo OGTT, in addition to routine evaluation. The data was acquired using a common predesigned proforma at both the centers. A detailed interview was arranged with the patient to record details of various medical facts with particular emphasis on menstrual history including age of menarche, regularity, duration, and number of cycles per year. Menstrual disturbances were classified as oligo-/amenorrhea (8 cycles/year or menstrual interval 35 days or 48 cycles but highly irregular) and amenorrhea (absence of menses in last six or more months). Other history included temporal profile of weight gain, duration of infertility, family history of PCOS, family history of type 2 DM, drug intake, progression and distribution of hirsutism, severity and treatment response in acne vulgaris etc. Women with any systemic disorders or those with history of intake of drugs known to interfere with glucose or insulin metabolism in the preceding six weeks were excluded from the study. Anthropometric assessment included measurement of height (cm), body weight (kg), waist and hip circumference (cm) with calculation of BMI (kg/m2). Modified Ferriman-Gallwey (FG) score was used to assess the degree of hirsutism and a score of 8 (out of a total of 36 from nine body areas) was taken as significant [28]. Blood samples were collected after an overnight (8–10 h) fast with a stable diet for preceding 72 h, and preferably on 3rd to 7th day (early follicular phase) of spontaneous menstrual cycle in regularly menstruating women or any day in ammenorrhic women. Blood samples were aliqouted for plasma insulin, total T4, TSH, LH, FSH, prolactin (PRL), total testosterone, 17-OHP, cortisol (morning), plasma glucose, blood counts, electrolytes, lipids, liver, and kidney functions. After obtaining the fasting blood sample an oral glucose challenge was performed with 75 gm anhydrous glucose dissolved in 250–300 ml water (OGTT), and blood samples were collected at 60 and 120 min later for plasma glucose. Serum was separated at room temperature and aliqouted as per the requirements. All biochemical analysis was done on the same day whereas the aliquots for hormones were stored at 70 C until the assay. Transabdominal ultrasonography was done to demonstrate any suggestion of polycystic ovarian morphology, i.e. presence of 10 or more peripheral follicles each measuring 2–8 mm in size with echogenic ovarian stroma and increased ovarian volume [29].
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Table 1. Clinical, biochemical and hormonal variables in women with PCOS and normal control women. Variable Age (years) Menarche (years) Ferriman–Gallwey Score Height (cm) Weight (kg) BMI (kg/m2) Waist (cm) Hip circum (cm) SBP (mm Hg) DBP (mm Hg) LH (mIU/ml) FSH (mIU/ml) Total testosterone (ng/ml) Total cholesterol (mg/dl) Triglycerides (mg/dl) HDL cholesterol (mg/dl) LDL cholesterol (mg/dl) Plasma glucose – 0 h (mg/dl) Plasma glucose – 2 h (mg/dl) Plasma Insulin – 0 h (mIU/ml) Plasma Insulin – 2 h (mIU/ml) Serum C-peptide – 0 h (ng/ml) Serum C-peptide – 2 h (ng/ml)
Control
Cases
p Values
25.62 ± 6.29 12.30 ± 0.92 3.14 ± 2.46 156.78 ± 5.33 61.13 ± 11.92 24.81 ± 4.25 80.66 ± 9.90 87.37 ± 7.68 111.31 ± 11.90 73.26 ± 6.60 8.05 ± 2.93 5.61 ± 1.96 0.36 ± 0.13 157.79 ± 28.92 106.94 ± 42.14 49.47 ± 10.26 92.17 ± 26.91 87.87 ± 11.71 101.98 ± 20.01 8.29 ± 4.00 35.37 ± 25.61 1.27 ± 1.00 4.81 ± 4.19
22.46± 4.80 12.76 ± 1.34 11.26 ± 3.38 156.76 ± 5.12 63.50 ± 12.73 25.83 ± 4.96 81.07 ± 9.92 86.76 ± 8.51 114.19 ± 9.05 77.03 ± 7.41 8.73 ± 5.69 6.30 ± 2.10 0.76 ± 0.57 167.55 ± 32.55 128.90 ± 63.28 45.57 ± 7.78 108.42 ± 26.43 90.61 ± 15.70 121.69 ± 41.22 15.66 ± 12.39 69.08 ± 75.52 2.55 ± 1.68 6.16 ± 4.76
0.01 0.01 0.01 0.97 0.10 0.06 0.72 0.52 0.01 0.01 0.62 0.01 0.01 0.01 0.01 0.06 0.01 0.09 0.01 0.01 0.01 0.01 0.06
Assays Plasma glucose and other biochemical parameters were assayed on autoanalysers (Roche Hitachi 912, Minatoku, Tokyo, Japan) at SKIMS, Srinagar and AIIMS, New Delhi. All the hormonal assays except plasma insulin were carried out in the respective departmental laboratories by radioimmunoassay (T4, cortisol, DHEAS, 17-OHP, testosterone) and immunoradiometric assays (TSH, LH, PRL, FSH) using commercial kits, in duplicate and according to supplier protocol (Diagnostic Products Corporation, Los Angeles, CA for cortisol, 17-OHP FSH, LH, TSH PRL and testosterone; Immunotech, France for DHEAS; and Diasorin USA for T4). Plasma insulin was done by RIA (BARC, Mumbai, India) at AIIMS, New Delhi for all the samples from both the centers. Intra and interassay coefficients of variations were within the limits permitted by the manufacturers.
Statistical analysis Data analysis was performed using the STATA 13 (StataCorp LP, College Station, TX). Descriptive analysis was done for all clinical, biochemical and hormonal parameters and results were expressed as Mean ± SD. The differences between groups were assessed using two tailed unpaired Students’ t-test and Chi square for continuous and categorical variables respectively. For multiple comparisons between groups ANOVA was used. Pearson correlation was used to check the association between various clinical and biochemical parameters with the glucose values. Parameters were log transformed if the standard deviation was higher than mean. p values of50.05 was taken as the cut off level for significance.
Results A total of 210 subjects diagnosed as having PCOS by Rotterdam 2003 criteria and 89 healthy controls were evaluated. Table 1 shows clinical, biochemical and metabolic differences among women with PCOS and controls. To assess the regional differences among women with PCOS, all parameters were compared in the cases from Delhi and Srinagar. Among subjects with PCOS, the mean age, mean age of
PCOS phenotype
DOI: 10.3109/09513590.2016.1141879
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Table 2. Showing clinical, biochemical and hormonal variables in women with PCOS and normal control women from Srinagar and Delhi.
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Variable Mean age (years) Mean age of menarche (years) Height (cm) Weight (kg) BMI (kg/m2) Waist (cm) Hip (cm) FG Score SBP (mm of hg) DBP (mm of hg) LH (mIU/ml) FSH (mIU/ml) Testosterone (ng/ml) Total cholesterol (mg/dl) Triglycerides (mg/dl) BG 0 hr (mg/dl) BG 2 hr (mg/dl) Insulin 0 hr (uIU/ml) Insulin 2 h (uIU/ml) C peptide (0 h) C peptide (2 h) HOMA-IR QUICKI
Controls
Cases
Mean ± SD
Mean ± SD
Srinagar (n ¼ 45)
Delhi (n ¼ 44)
p Values
Srinagar (n ¼ 110)
Delhi (n ¼ 100)
p Values
22.02 ± 3.23 12.17 ± 0.911 155.77 ± 4.51 58.93 ± 12.03 24.20 ± 4.25 79.66 ± 9.66 85.93 ± 7.47 3.17 ± 2.46 115.06 ± 14.60 73.51 ± 8.05 7.88 ± 3.10 5.83 ± 1.82 0.40 ± 0.14 158.65 ± 29.72 119.44 ± 50.64 90.75 ± 14.84 90.75 ± 15.70 7.78 ± 4.11 20.57 ± 22.71 0.18 ± 0.20 0.20 ± 0.26 1.74 ± 0.91 0.157 ± 0.016
23.54 ± 3.65 12.47 ± 0.97 157.22 ± 5.03 61.61 ± 11.31 24.89 ± 4.22 81.29 ± 10.06 88.20 ± 7.60 3.12 ± 2.48 108.36 ± 9.28 72.77 ± 5.70 8.15 ± 2.83 5.85 ± 2.19 0.33 ± 0.11 157.33 ± 28.69 100.25 ± 35.42 85.25 ± 7.72 105.22 ± 18.10 8.62 ± 3.93 44.76 ± 22.86 1.97 ± 0.60 7.74 ± 2.54 1.84 ± 0.87 0.156 ± 0.019
0.04 0.13 0.15 0.28 0.44 0.43 0.15 0.37 0.01 0.61 0.38 0.96 0.01 0.42 0.32 0.03 0.01 0.08 0.01 0.01 0.01 0.32 0.78
22.45 ± 4.19 12.82 ± 1.24 156.77 ± 5.17 60.92 ± 11.37 24.77 ± 4.32 80.86 ± 10.08 87.56 ± 7.76 12.12 ± 3.91 113.3 ± 8.30 76.30 ± 6.90 8.35 ± 3.88 6.72 ± 1.58 0.86 ± 0.41 164.12 ± 32.93 132.30 ± 67.30 88.7 ± 16.35 112.20 ± 43.18 13.42 ± 10.73 53.92 ± 80.06 2.19 ± 1.91 5.71 ± 5.26 3.01 ± 2.6 0.147 ± 0.015
22.49 ± 4.37 12.69 ± 1.45 156.76 ± 5.09 66.33 ± 13.57 26.99 ± 5.38 81.30 ± 9.78 85.89 ± 9.22 10.32 ± 2.22 115.17 ± 9.76 77.84 ± 7.90 9.14 ± 7.17 5.85 ± 2.48 0.65 ± 0.69 179.80 ± 28.39 115.92 ± 43.37 92.73 ± 14.74 132.13 ± 36.40 18.12 ± 14.07 85.75 ± 66.68 2.95 ± 1.30 6.66 ± 4.01 4.20 ± 3.39 0.140 ± 0.013
0.96 0.46 0.98 0.01 0.01 0.75 0.15 0.01 0.13 0.13 0.68 0.01 0.01 0.01 0.31 0.63 0.01 0.01 0.01 0.01 0.01 0.01 0.01
menarche, height, waist circumference and hip circumference were comparable (Table 2). Delhi PCOS subjects had significantly higher BMI (26.99 ± 5.38 kg/m2 versus 24.77 ± 4.32 kg/m2 P ¼ 0.001) but lower FG score (10.32 ± 2.22 versus 12.12 ± 3.91; P¼ 0.0012) and serum testosterone (0.65 ± 0.69 versus 0.86 ± 0.41; P ¼ 0.01) as compared to those from Srinagar. Mean serum LH levels were comparable in two groups but serum FSH (5.85 ± 2.48 versus 6.72 ± 1.58 mIU/ml; P ¼ 0.002) was lower in Delhi PCOS subjects as compared to Srinagar PCOS subjects. Among metabolic parameters, Delhi and Srinagar subjects had comparable total cholesterol, triglycerides and fasting plasma glucose but 2 h post OGTT plasma glucose (132.13 ± 36.40 versus 112.20 ± 43.18; P ¼ 0.01) was significantly higher in Delhi subjects. Similarly, serum insulin and Cpeptide levels were significantly higher in Delhi PCOS subjects. Glucose intolerance was seen in 36% (36/100) PCOS subjects from Delhi and 10% (11/110) subjects from Srinagar. Furthermore, insulin resistance as measured by HOMA-IR was higher (4.20 ± 3.39 versus 3.01 ± 2.6; P ¼ 0.01) and insulin sensitivity as measured by QUICKI (0.140 ± 0.013 versus 0.147 ± 0.015; P ¼ 0.01) was lower in PCOS subjects from Delhi when compared with those from Srinagar. Among control subjects, the clinical, biochemical and hormonal parameters were mostly comparable except serum total testosterone and insulin resistance as shown in the table. Serum total testosterone was significantly higher in Srinagar controls while 2 h post OGTT serum insulin levels, C-peptide and QUICKI indicative of higher insulin resistance in controls from Delhi.
Discussion PCOS, the commonest heterogeneous disorder of young women is characterized by a multitude of reproductive and metabolic abnormalities [20]. Due to its heterogeneity, PCOS can present with different features in different ethnic populations [14]. These differences are not only limited to incidence in different populations but also in the metabolic and reproductive
manifestations [21]. Overall, the differences in the clinical presentations such as higher age in the attainment of menarche, oligomenorrhea, higher FG score, higher serum testosterone, glucose intolerance, insulin resistance and lipid abnormalities in subjects with PCOS when compared with controls, are consistent with earlier reports. The age of achieving menarche (12.76 ± 1.34) was significantly higher against that of control girls as well as that has been observed in (i.e. 12.35 ± 1.2 years) normal Indian girls (thesis submitted to AIIMS, New Delhi). PCOS subjects from Srinagar had higher FG score, serum total testosterone and higher serum FSH levels as compared to those from Delhi who had higher BMI, waist circumference, higher cholesterol, TG, fasting and 2 h plasma insulin, C-peptide and 2 h blood glucose. Intrinsic differences in 17 -hydroxysteroid dehydrogenase pathway could be responsible for higher testosterone levels in PCOS patients from Srinagar. Welt et al. [26] reported higher BMI, higher DHEAS and lower serum testosterone levels in Icelandic women with PCOS as compared to Caucasian PCOS women from Boston. They hypothesized that low testosterone in Icelandic subjects was due to an intrinsic difference in the 17 -hydroxysteroid dehydrogenase pathway in women from Iceland and Boston. However, in addition, the higher levels of total testosterone among women with PCOS from Srinagar could be attributable to difference in aromatization rates due to body fat. Interestingly, the higher FSH levels observed in Srinagar cohort is difficult to explain and possibly could reflect poorer ovarian reserve in PCOS subjects from Srinagar [30]. More severe metabolic derangements (higher HOMA-IR, lower QUICKI, insulin and c peptide levels insulin resistance, glucose levels, lipid levels) among Delhi PCOS women can be explained on the basis of higher BMI in these girls. These differences may be accounted partly by varying background prevalence of type 2 diabetes mellitus and obesity in general population of these regions (6.1% and 2.9% in Srinagar and 10.3% and 18.4% in Delhi) or genetic differences in the two populations [31–33]. For example, some studies from United Kingdom [34] and Slovene [35] have reported genetic polymorphisms in the
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insulin gene, insulin receptor gene and insulin receptor substrates as mechanism for these variations whereas studies from China, Spain and Czech Republic did not find any association between insulin gene polymorphism and PCOS [36–38]. In view of the fact that similar differences in serum testosterone and insulin resistance were also noted between the two control populations, may suggest genetic variation between the two regions. These baseline population differences may act as determinants of the phenotypic expression of PCOS from different regions. It has been hypothesized that in utero fetal programming may play a role in the development of PCOS phenotype in adult life and it is the interaction of environmental factors (obesity) with genetic factors that leads to development of complete PCOS phenotype [39]. Social and environmental conditions in two states may also contribute to these differences. Delhi has 80% Hindu population with majority as vegetarians whereas Kashmir has 95% Muslim population with majority nonvegetarians. The weaknesses of the present study are: (a) absence of data on detailed family history, (b) smaller number of controls (c), and non-availability of serum DHEAS, free testosterone, and SHBG levels that could possibly influence these differences in the two groups were not undertaken. We conclude that this is the first report from India showing regional differences in clinical, biochemical and hormonal parameters within the same region. Large well-designed, multicentre studies are required to be undertaken to understand the mechanism underlying these differences.
Declaration of interest The authors report no conflict of interest. The authors alone are responsible for the content and writing of the paper.
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PCOS phenotype
5
37. Vankova M, Vrbikova J, Hill M, et al. Association of insulin gene VNTR polymorphism with polycystic ovary syndrome. Ann N Y Acad Sci 2002;967:558–65. 38. Calvo RM, Telleria D, Sancho J, et al. Insulin gene variable number of tandem repeats regulatory polymorphism is not associated with hyperandrogenism in Spanish women. Fertil Steril 2002;77:666–8. 39. Allahbadia GN, Merchant R. Polycystic ovary syndrome in the Indian Subcontinent. Semin Reprod Med 2008;26:22–34.
