The Prevalence of Polycystic Ovary Syndrome, Its Phenotypes and Cardio-Metabolic Features in a Community Sample of Iranian Population: Tehran Lipid and Glucose Study.

Can cluster analysis be used to differentiate between normo-ovulatory women with normal ovaries and normo-ovulatory women with polycystic ovarian morphology (PCOM) in a non-subjective manner? Cluster analysis can be used to accurately and non-subjectively differentiate between normo-ovulatory women with normal ovaries and normo-ovulatory women with PCOM. Currently, PCOM is diagnosed using a fixed threshold level, i.e. 12 or more follicles per ovary, and is one of the diagnostic criteria of polycystic ovary syndrome (PCOS). However, PCOM is also encountered in normo-ovulatory women, suggesting that it could just represent a normal variant. On the other hand, recent studies have shown subtle endocrine abnormalities in women with isolated PCOM that resemble those found in women with PCOS. Because of the strong correlation between anti-Müllerian hormone (AMH) and follicle number, a high serum AMH level has been proposed as a surrogate marker for PCOM and could, therefore, be integrated in the diagnostic classifications for PCOS. This was a retrospective observational cohort study. Original cohorts had been recruited for previous studies between 1998 and 2010. Two hundred ninety-seven regularly cycling women and 700 women with PCOS were eligible for inclusion. Cluster analysis was performed in 297 regularly cycling women. After exclusion of 'PCOM' clusters, each 'non-PCOM' cluster (young, n = 118 and old, n = 100) was included in the construction of a receiver operating characteristics curve to test the diagnostic performance of follicle number per ovary (FNPO) and serum AMH in discriminating similarly aged full-blown PCOS patients (n = 411 and 237, respectively) from normal regularly cycling non-PCOM women. The optimal number of clusters was four; age was the most important classifying variable, followed by the FNPO and serum AMH. Two distinct clusters of normo-ovulatory women with PCOM were isolated and differed solely by age, i.e. 'young' and 'old'. Both 'PCOM' clusters had their similarly aged counterpart of 'non-PCOM' clusters. Likewise, two clusters comprised women younger than 30 years, with (n = 28, 'PCOM regularly cycling women') or without (n = 118, 'normal regularly cycling women') features of PCOM (increased FNPO and/or serum AMH). The two other clusters in older women could be labelled 'normal regularly cycling women' or 'PCOM regularly cycling women' (n = 100 and 51, respectively). The prevalence of PCOM was significantly greater in old than in young regularly cycling women controls. In the young population, after exclusion of the 'PCOM regularly cycling women', the diagnostic performance of AMH, expressed by area under the curve (AUC) (AUC = 0.903; CI (0.876-0.930)) to differentiate PCOS women from normal regularly cycling women was similar to that using the FNPO (AUC = 0.915, CI (0.891-0.940)) (P = 0.25), confirming results from earlier studies. In the old population, the diagnostic performance of AMH was greater than that of FNPO (AUCs = 0.948 (0.927-0.970) vs 0.874 (0.836-0.912), respectively, P = 0.00035). Cut-off levels of AMH and antral follicle count distinguishing regularly cycling non-PCOM women from PCOS women were higher in young women than in older women. Data of normal women were obtained from earlier studies, aiming to measure normal endocrine values. Apparently, the strong effect of age in cluster analysis revealed a dichotomy in the age distribution among the cohort of regularly cycling women included. This was involuntary since in none of the original studies, eligibility was limited by age and there was considerable overlap in age ranges of the cohorts. Transvaginal ultrasound was performed using a 6.5-8 mHz probe and our data confirm that this threshold level for FNPO is still valid if using such probe frequencies, although the use of devices with a maximum frequency lower than 8 mHz has become obsolete. Obviously, newer ultrasound scanner using higher transducer frequency will facilitate the detection of more follicles. Our data support the use of AMH as a surrogate for ultrasound to define PCOM, which is one of the three items of the Rotterdam classification. They also show that age should be taken into account to define the optimal threshold. The fact that the prevalence of PCOM was increased in the older regularly cycling women, may be due to 'attenuated' PCOS, a phenomenon that has been described in ageing women with PCOS. These women might have had anovulatory cycles in the past and have become ovulatory with increasing age, and were, therefore, eligible for this study. However, since most women included at older age have had spontaneous pregnancies in the past, PCOM at older age may be associated with a subclinical form of PCOS, which may also be present in young regularly cycling women. No funding was received for this study. J.S.E.L. has received grants and support from Ferring, MSD, Organon, Merck-Serono, Schering Plough and Serono during recruitment and analysis of data for this study. S.L.F., A.D. and D.D. do not have any conflict of interest.

Is intrinsic dysregulation of granulosa cells (GC) and consequent increases in the per-follicle production of anti-Müllerian hormone (AMH), correlated with the phenotypic presentation of women with polycystic ovaries? Involvement of intrinsic GC dysregulation in oligo-anovulation associated with polycystic ovary syndrome (PCOS) is likely because among women with PCOS, those with oligo-amenorrhea have higher per-follicle AMH production than those who ovulate normally, irrespective of their androgen and/or metabolic status. Women with PCOS have higher serum AMH level than non-PCOS women due to an increased follicle number and excessive AMH production per follicle, the latter reflecting a putative GC dysfunction that may vary between PCOS phenotypes. This is a retrospective analysis of data collected from 1021 women undergoing infertility evaluation from March 2011 to October 2013. The study included women with polycystic ovarian morphology (PCOM) who met the Rotterdam criteria for PCOS (n = 272), women with PCOM only (n = 168) and controls (n = 581). We used serum AMH to antral follicle count (AFC) ratio (AMH/AFC) as a marker of per-follicle AMH production and checked whether this ratio was associated with the PCOS phenotype and to the menstrual, androgen and metabolic status in women with PCOS, women with PCOM only and in controls. AMH/AFC was significantly higher in oligo-amenorrheic women with PCOS than in eumenorrheic women with PCOS or PCOM (P < 0.001) but also in the latter group compared with controls (P < 0.001) regardless of androgen status. Stepwise discriminant analysis yielded a significant score for the menstrual status with a discriminant power of 26.5% (P < 0.001). This score included AFC, AMH/AFC, waist circumference and LH with partial R(2) of 0.172, 0.042, 0.024 and 0.023, respectively. The AMH to AFC ratio as a surrogate marker for average AMH may be subject to error because follicles below the sensitivity limit of the ultrasonography used may also contribute to serum AMH concentration and secondly, AFC can be subjective. The higher AMH/AFC in women with PCOM only than in controls suggests that isolated PCOM may represent a PCOS-like phenotype in which an inherent dysfunction of GC exists but is too mild to affect the ovulatory process. No funding was obtained for this study. There are no conflicts of interest to be declared. Non-applicable.

To evaluate the incidence of metabolic syndrome in Turkish adolescents with different phenotypes of polycystic ovary syndrome (PCOS). This cross-sectional study was performed on the Youth Center clinic of a tertiary referral hospital in Turkey. Adolescents with PCOS (n = 144) were classified into four phenotype groups according to the presence of oligo/anovulation (O), hyperandrogenism (H), and polycystic ovarian morphology (P) as follows: Phenotype A (O + H + P), Phenotype B (H + O), Phenotype C (H + P), Phenotype D (O + P). The adolescents gave early follicular phase blood samples for endocrine and metabolic tests. The incidence and the presence of parameters of metabolic syndrome were assessed among the four groups. In total, 54.9% of the adolescents with PCOS were overweight and 25.7% had metabolic syndrome. The incidence of metabolic syndrome in Phenotypes A-D were as follows: 39.5%, 20.5%, 26.5%, and 15.2%, respectively. Although body mass index was higher in the Phenotype A group, insulin resistance was similar in all of the phenotype groups. The most common dyslipidemia was low HDL-C levels and this was present in more than half of the adolescents with PCOS. Both body mass index and total testosterone levels were significantly higher in adolescents with metabolic syndrome in comparison to those without metabolic syndrome. Although low HDL-C levels and insulin resistance are common PCOS findings in adolescents, the metabolic profile seems to be worse in Phenotype A than the other phenotypes. Therefore, screening programs should evaluate patients based on the known risk factors and phenotypes for adolescents with PCOS.

Birth weight below the 10th percentile as a risk factor for the development of polycystic ovary syndrome a reproductive age: a cohort study

Polycystic ovary syndrome (PCOS) has emerged as a significant international public health concern in East Asia and around the world. It is characterized by clinical manifestations such as oligo/anovulation, hyperandrogenism, and polycystic ovarian morphology, etc. The pathogenesis of PCOS is complex, involving the interaction of genetic and environmental factors. The prevalence of PCOS in China has reached 7.8% with variation across different regions, occupations, and age groups. Notably, the prevalence of PCOS among Chinese women has been increasing from 2010 to 2020. Similar upward trends in prevalence rates of PCOS have also been observed in other countries. The rise in prevalence is primarily driven by type III PCOS (O+P), while type IV PCOS (H+O+P) has remained relatively stable. PCOS is associated with significant metabolic consequences, including increased risk of impaired glucose tolerance and type 2 diabetes mellitus, atherogenic dyslipidemia, systemic inflammation due to increased secretion of pro-inflammatory factors by adipose tissue, non-alcoholic fatty liver disease, hypertension, and potential coagulation disorders. PCOS affects quality of life and can worsen anxiety and depression either due to its symptoms or due to the diagnosis of a chronic disease. Genetic studies have identified susceptibility loci for PCOS, shedding light on its genetic underpinnings. Treatment aims in PCOS include optimising healthy weight, improving underlying hormonal disturbances, prevention of future reproductive and metabolic complications, and improving quality of life. Effective intervention strategies for PCOS include pharmacological treatments, lifestyle modifications, and surgical treatments.

Introduction: Determinants of polycystic ovary syndrome

Application of the newly introduced Rotterdam criteria for polycystic ovary syndrome (PCOS) generates four phenotypic subgroups, defined by the presence/absence of three diagnostic elements: polycystic ovarian (PCO) morphology (P); hyperandrogenism (H); and oligo-amenorrhoea (O). Whilst PCOS is associated with adverse metabolic features, the strength of the association within individual subgroups is not established. We characterized the metabolic and endocrine profiles of PCOS women who are oligomenorrhoeic but normoandrogenaemic, and compared these to other PCOS women and controls. Retrospective dataset analyses. A total of 309 Europid PCOS women, all with PCO morphology, of whom 191 were also hyperandrogenaemic and oligomenorrhoeic (PHO), 76 hyperandrogenaemic with normal menses (PH) and 42 oligomenorrhoeic but normoandrogenaemic (PO); plus 76 Europid control women without PCOS. Metabolic parameters: fasting insulin, lipids, homeostasis model assessment (HOMA) measures of insulin sensitivity; endocrine variables: LH, FSH; prevalence of metabolic syndrome. Insulin sensitivity: PO women were indistinguishable from controls, and markedly less insulin-resistant than PHO women (vs. controls, P = 0.38 after adjustment for BMI and age; vs. PHO, P = 0.003). Metabolic syndrome: the prevalence in PO women (7.1%) was similar to that in controls (3.9%), and lower than in PHO women (29.3%, P < 0.0001). LH levels: PO women were intermediate between controls (vs. controls, P = 0.008) and PHO women (vs. PHO, P = 0.06). Normoandrogenaemic, oligomenorrhoeic women with PCOS are metabolically similar to control women with significantly fewer metabolic features than PCOS women who are also hyperandrogenaemic. However, higher than normal LH and lower sex hormone-binding globulin (SHBG) concentrations in the PO women support the view that they form part of the spectrum of PCOS.

Objectives: The aim of the present study was to evaluate the impact of polycystic ovarian morphology in the hormonal and metabolic features of the classical phenotypes of PCOS. Design: The study included 1275 Caucasian women with PCOS with a mean age of 24.25 ± 5.79 years and a mean BMI of 26.80 ± 7.03 kg/m2. Diagnosis of PCOS was based on the 2003 Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus criteria. Two phenotypes, matched for age and BMI were compared: Phenotype I (n=620) which included PCOS women with biochemical hyperandrogenemia and/or clinical hyperandrogenemia, chronic anovulation and polycystic ovarian morphology on ultrasound (PCO). Phenotype II (n=400) which included PCOS women with biochemical hyperandrogenemia and/or clinical hyperandrogenemia and chronic anovulation, without PCO. These phenotypes were further subdivided in normal weight and obese PCOS women. Results: PCOS women of Phenotype I had higher LH/FSH ratio (p<0.001), higher Testosterone (p<0.01), Δ4 Androstenedione (p<0.001) and 17-OH progesterone levels (p<0.001), and higher Free Androgen Index (FAI) values (p<0.01) compared to Phenotype II. With the exception of fasting glucose levels, all other indices of insulin resistance (fasting insulin, fasting glucose/insulin ratio, QUICKI and HOMA2IR) document an association between Phenotype I and greater insulin resistance in overweight/obese PCOS women. Conclusions: In conclusion, in classical phenotypes of polycystic ovary syndrome (PCOS), polycystic ovarian morphology is associated with more severe hyperandrogenemia and deranged LH/FSH ratio. In overweight/obese PCOS subjects, PCO is positively correlated with insulin resistance.

This hospital-based observational study aims to estimate differences in metabolic abnormalities between different polycystic ovary syndrome (PCOS) phenotypes and their distribution characteristics. The prevalence of metabolic abnormalities among different PCOS phenotypes, including diabetes mellitus (DM), metabolic syndrome (MS), pre-diabetes mellitus (pre-DM), insulin resistance (IR) and dyslipidemia were compared. A total of 2436 women who were ≥18 years old and who were hospitalized in Sun Yat-Sen University affiliated hospital from 1998 to 2015 in GuangZhou, China, were included in this study. PCOS phenotypes were recorded according to the 2003 Rotterdam criteria, including the polycystic ovary morphology (PCO), hyperandrogenism (HA) and ovulation dysfunction (OD) phenotype (PCO+HA+OD); the ovulation phenotype (PCO+HA); the non-PCO phenotype (HA+OD); and the non-HA phenotype (PCO+OD). Notably, 56% of the patients had the classic phenotype (PCO+HA+OD). Importantly, there was no significant difference in the prevalence of metabolic abnormalities or the distribution characteristics of the metabolic abnormalities among these four PCOS phenotypes. Our study supports the notion that metabolic abnormalities and the distribution characteristics of metabolic abnormalities should not be used to distinguish among the various clinical PCOS phenotypes.

To compare pregnancy and neonatal outcomes in women with hyperandrogenic polycystic ovarian syndrome (PCOS) phenotypes compared with nonhyperandrogenic PCOS phenotypes. We conducted a retrospective cohort study of participants in the PPCOS (Pregnancy in Polycystic Ovary Syndrome) I and II randomized controlled trials; all of the participants met the National Institutes of Health diagnostic criteria for PCOS and were then sorted into three of the four Rotterdam criteria categories based on medical interview, demographics, physical examination, and laboratory data. The two hyperandrogenic (A and B) Rotterdam categories were compared with the nonhyperandrogenic phenotype of PCOS (phenotype D). Our outcomes of interest were clinical pregnancy, pregnancy loss, live birth, obstetric complications (including preterm labor, preeclampsia, gestational diabetes, intrauterine growth restriction, and premature rupture of membranes), and neonatal outcomes (including jaundice, respiratory distress syndrome, neonatal hospitalization, and neonatal infection). Of the 1,376 participants included in the study, 1,249 (90.8%) had hyperandrogenic PCOS phenotypes compared with 127 (9.2%) nonhyperandrogenic PCOS (nonhyperandrogenic PCOS). Compared with participants with nonhyperandrogenic PCOS, those with hyperandrogenic PCOS had higher body mass index (BMI) (35.5±8.9 vs 31.9±9.3 kg/m 2 , P <.001), fasting insulin (21.6±27.7 vs 14.7±15.0 micro-international units/mL, P <.001), and homeostatic model assessment for insulin resistance score (5.01±9.1 vs 3.4±4.1, P =.0002). Age and race were similar between groups. Months attempting pregnancy were greater in participants with hyperandrogenic PCOS compared with nonhyperandrogenic PCOS (41.8±37.3 vs 33.9±32.0). The proportion of participants who achieved pregnancy (29.9% vs 40.2%, P =.02) and live birth rates (20.1% vs 33.1%, P =.001) were lower among those with hyperandrogenic PCOS compared with nonhyperandrogenic PCOS, although pregnancy loss rates did not differ significantly (23.9% vs 32.3%, P =.06). The hyperandrogenic PCOS group had lower odds of live birth compared with the nonhyperandrogenic PCOS group (odds ratio [OR] 0.51, CI, 0.34-0.76), even after adjusting for BMI (adjusted odds ratio [aOR] 0.59, CI, 0.40-0.89). The hyperandrogenic PCOS group also had lower odds of achieving pregnancy compared with the nonhyperandrogenic PCOS group (OR 0.63, CI, 0.44-0.92); however, this association was no longer significant after adjusting for BMI (aOR 0.74, CI, 0.50-1.10). The overall low prevalence of prenatal complications and neonatal outcomes precluded a meaningful comparison between the two groups. Participants with hyperandrogenic PCOS achieved lower rates of pregnancy and live birth compared with those with nonhyperandrogenic PCOS. Evaluating distinct PCOS phenotypes may allow for individualized guidance regarding the probability of pregnancy and live birth. ClinicalTrials.gov , NCT00068861 and NCT00718186.

Risk of metabolic complications in the new PCOS phenotypes based on the Rotterdam criteria

Polycystic ovary morphology (PCOM) on ultrasonography is considered as a cardinal feature of polycystic ovarian syndrome (PCOS). Its relevance as a diagnostic criterion for PCOS was reaffirmed in the most recent International Evidence-Based Guideline for the Assessment and Management of PCOS. However, there remains a lack of clarity regarding the best practices and specific ultrasonographic markers to define PCOM. The aim of this systematic review and diagnostic meta-analysis was to assess the diagnostic accuracy of various ultrasonographic features of ovarian morphology in the diagnosis of PCOS. Relevant studies published from 1 January 1990 to 12 June 2023 were identified by a systematic search in PubMed, Web of Science, Scopus, CINAHL, and CENTRAL. Studies that generated diagnostic accuracy measures (e.g. proposed thresholds, sensitivity, specificity) for PCOS using the following ultrasonographic markers met criteria for inclusion: follicle number per ovary (FNPO) or per single cross-section (FNPS), ovarian volume (OV), and stromal features. Studies on pregnant or post-menopausal women were excluded. Risk of bias and applicability assessment for diagnostic test accuracy studies were determined using the QUADAS-2 and QUADAS-C tool for a single index test or between multiple index tests, respectively. Diagnostic meta-analysis was conducted using a bivariate model of pooled sensitivity and specificity, and visualized using forest plots and summary receiver-operating characteristic (SROC) curves. From a total of 2197 records initially identified, 31 studies were included. Data from five and two studies were excluded from the meta-analysis due to duplicate study populations or limited data for the index test, leaving 24 studies. Pooled results of 20 adult studies consisted of 3883 control participants and 3859 individuals with PCOS. FNPO was the most accurate diagnostic marker (sensitivity: 84%, CI: 81-87%; specificity: 91%, CI: 86-94%; AUC: 0.905) in adult women. OV and FNPS had similar pooled sensitivities (OV: 81%, CI: 76-86%; FNPS: 81%, CI: 70-89%) but inferior pooled specificities (OV: 81%, CI: 75-86%; FNPS: 83%, CI: 75-88%) and AUCs (OV: 0.856; FNPS: 0.870) compared to FNPO. Pooled results from four adolescent studies consisting of 210 control participants and 268 girls with PCOS suggested that OV may be a robust ultrasonographic marker for PCOS diagnosis albeit the current evidence remains limited. The majority of the studies had high risk of bias for the patient selection (e.g. lack of randomized/consecutive patient selection) and index test (e.g. lack of pre-proposed thresholds for comparison) domains across all ultrasonographic markers. As such, diagnostic meta-analysis was unable to determine the most accurate cutoff for ultrasonographic markers to diagnose PCOS. Subgroup analysis suggested that stratification based on previously proposed diagnostic thresholds, age, BMI, or technology did not account for the heterogeneity in diagnostic accuracy observed across the studies. Studies that diagnosed PCOS using the Rotterdam criteria had improved sensitivity for FNPO. Studies from North America had lower diagnostic accuracy when compared to Asian studies (FNPO: sensitivity) and European studies (OV: specificity, diagnostic odds ratio and positive likelihood ratio). Geographic differences in diagnostic accuracy may potentially be due to differences in age, BMI, and diagnostic criteria of the PCOS group across regions. This diagnostic meta-analysis supports the use of FNPO as the gold standard in the ultrasonographic diagnosis of PCOS in adult women. OV and FNPS provide alternatives if total antral follicle counts cannot be accurately obtained. Our findings support the potential for ultrasonographic evidence of PCOM in adolescents as more data becomes available. Subgroup analysis suggests the need to investigate any relative contributions of geographical differences on PCOS phenotypes. These findings may provide the basis for the development of strategies and best practices toward a standardized definition of PCOM and a more accurate ultrasonographic evaluation of PCOS.

Polycystic ovary syndrome (PCOS) coexisting mood disorders along with a combination of aesthetic manifestations may have a detrimental effect on women's sexual function. Hence, different phenotypes of PCOS have different clinical and biochemical signs and symptoms. The aim of this study was to compare women's sexual function (SF) in different phenotypes of PCOS. This cross-sectional study was conducted on 364 women who met the Rotterdam diagnostic criteria to compare different PCOS phenotypes (A = 95, B = 79, C = 95, and D = 95) and 100 non PCOS women in control group. All participants were invited to fill out the female sexual function index (FSFI). Significant differences were observed between the different phenotypes and control group in terms of the total score, sexual desire, arousal, lubrication, and satisfaction (P < 0.001); however, no significant differences were found between different phenotypes in terms of pain (P > 0.05) and orgasm (P > 0.05) but difference was significant between different phenotypes and control group. In addition, phenotype B had the lowest mean score of total FSFI (P < 0.05). The results indicated that women's SF is significantly different in different PCOS phenotypes. It is concluded that in order to solve the SF problems of women with PCOS, different treatment and care measures should be considered according to the relevant phenotype.

Polycystic ovary syndrome (PCOS) is a complex and prevalent endocrine condition among reproductive-age women associated with adverse metabolic consequences. Metabolic syndrome (MetS) is a cluster of risk factors conferring an increased risk for type 2 diabetes (DM2) and cardiovascular disease (CVD). Research has been limited, in part, due to marked heterogeneity in criteria employed to determine MetS, retrospective data collection, and the use of older or less accurate criteria to diagnose PCOS and polycystic ovarian morphology (PCOM). We aimed to 1) examine the prevalence of MetS and evaluate DM2 and CVD risk factors in reproductive-age Canadian women with PCOS; and, 2) assess the relevance of MetS to clinical and biochemical features of PCOS using a prospective comprehensive approach and a rigorously-defined PCOS population. Baseline observations were evaluated in 237 women with PCOS (Androgen Excess and PCOS [AE-PCOS] Society 2006 criteria for PCOS and AE-PCOS Society 2014 recommendations to determine PCOM) and 42 healthy controls (18-36 years). Clinical and biochemical measures of MetS (International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute 2009), DM2 (Diabetes Canada Clinical Practice Guidelines 2018), and CVD risk factors (AE-PCOS Society statement 2010) were assessed. The prevalence of MetS was 29.5% in women with PCOS; that is, approximately 6-fold higher than age-matched controls (P<0.001). Women with PCOS presented with higher glucose abnormality, acanthosis nigricans, total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, and lower sex-hormone binding globulin (SHBG) concentrations when compared with controls after accounting for differences in the body mass index (BMI; P<0.01). Women with both PCOS and MetS exhibited exacerbated insulin and glucose responses to a 75-gram glucose tolerance test, increased TC/HDL-C ratio, TC, and SHBG concentrations, as well as increased hirsutism and acanthosis nigricans when compared to women with PCOS without MetS after adjusting for BMI (P≤0.05). Canadian reproductive-age women with PCOS whose PCOM were characterized according to the AE-PCOS Society 2014 recommendations have a high prevalence of MetS and exhibit adverse cardiometabolic and DM2 risk profiles. MetS is associated with increased hyperandrogenism and hypercholesterolemia in women with PCOS attributed to inherent insulin resistance, hyperinsulinemia, and synergistic effects of concomitant obesity. Screening and regular monitoring for CVD and DM2 risk factors are reinforced for women with PCOS across the reproductive lifespan.

Introduction: PCOS is commonest endocrine syndrome characterized by combination of reproductive, metabolic and psychological features. Its global prevalence is estimated between 5 and 21%. In India it varies in urban region (9- 22%) and rural region (2-8%). The prevalence according to Rotterdam’s criteria is 11.33%. In Kashmir the prevalence of PCOS is 28.9% by NIH criteria and 34.3% by AE- PCOS criteria. The prevalence of PCOS is high among Kashmiri women and is probably the highest in a published series globally. polycystic ovarian syndrome (PCOS) was originally described in 1935 by Stein and Leventhal as a syndrome manifested by amenorrhoea, hirsutism, and obesity associated with enlarged polycystic ovaries. This heterogenous disorder is characterised by excessive androgen production by the ovaries mainly. PCOS is a multifactorial and polygenic condition. Diagnosis is based upon the presence of any two of the following three criteria. (ASRM/ ESHRE). 1.Oligo- anovulation2.Hyperandrogenism (clinically or biochemically)3.Polycystic ovaries on ultrasound.Aim of the study: To find the cause of PCOS based on Mizaj (temperament)Materials and Method: The Study was carried out in the regional research of Unani medicine Naseem bagh campus, University of Kashmir from December 2018 to August 2019 after approval of BOS and IEC. The total number of patients screened for PCOS were 89 and 77 were enrolled in the study after obtaining written informed consent. The data of 77 patients were document in the case record form meant for the study. They were divided into two groups test group n=33 and control group n=33. The dropout number of patients was 11. The cause of the syndrome is keenly observed for the period 2 months.Observation and Result: The cause that is mentioned in our classical literature is same that reveals in this study. For statistical analysis data was compiled and exported to data editor of SPSS version 20.0 and graph pad prism software.Financial support: The financial support was provided by Central Council of Unani Medicine, (CCRUM), New Delhi, I am highly thankful to them.