Changes in the Gut- and Vaginal Microbiome Composition in Association With PCOS Clinical Phenotypes.
Conditions: Polycystic Ovary Syndrome
Sponsor: Erasmus Medical Center

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GuVa-PCOS 
Research Protocol Version 3.0, d.d. 23-09-2022 
GuVa PCOS study 
 Changes in the gut- and vaginal microbiome 
composition in association with PCOS clinical 
phenotypes. (Version 3.0, d.d.23-9-2022)

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Research Protocol Version 3.0, d.d. 23-09-2022 
 
 
PROTOCOL TITLE ‘Changes in the gut- and vaginal microbiome composition in association 
with PCOS clinical phenotypes.’ 
 
Protocol ID 
NA 
Short title 
GuVa- PCOS study     
EudraCT number  
NA 
Version 
3.0 
Date 
23-09-2022 
Principal investigator(s) (in 
Dutch: hoofdonderzoeker/ 
uitvoerder) 
 
Dr. S. Schoenmakers, MD PhD 
Department of Obstetrics and Gynecology 
Erasmus University Medical Center Rotterdam 
Email: s.schoenmakers@erasmusmc.nl  
Sponsor (in Dutch: 
verrichter/opdrachtgever) 
Erasmus University Medical Center Rotterdam 
Subsidising party 
NA 
Independent expert (s) 
Dr. R. Kraaij, PhD 
Senior scientist  
Genetic Laboratory of Internal Medicine / 
Population Genomics 
Erasmus University Medical Center Rotterdam 
Email: r.kraaij@erasmusmc.nl 
 
Prof. Dr. W.W. de Herder  
Department of Internal Medicine – Endocrinology  
Erasmus University Medical Center Rotterdam, 
E-mail: w.w.deherder@erasmusmc.nl 
 
Laboratory sites  
Laboratory of Erasmus University Medical Center 
Rotterdam  
 
 
 

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TABLE OF CONTENTS 
 
1. 
INTRODUCTION AND RATIONALE .............................................................................11 
2. 
OBJECTIVES ................................................................................................................15 
3. 
STUDY DESIGN ...........................................................................................................16 
4. 
STUDY POPULATION ..................................................................................................16 
4.1 
Population (base) ...................................................................................................16 
4.2 
Inclusion criteria .....................................................................................................16 
4.3 
Exclusion criteria ....................................................................................................17 
4.4 
Sample size calculation ..........................................................................................17 
5. 
TREATMENT OF SUBJECTS .......................................................................................19 
5.1 
Investigational product/treatment ............................................................................19 
5.2 
Use of co-intervention (if applicable) ......................................................................19 
5.3 
Escape medication (if applicable) ...........................................................................19 
6 
INVESTIGATIONAL PRODUCT ....................................................................................20 
6.1 
Name and description of investigational  product(s) ...............................................20 
6.2 
Summary of findings from non-clinical studies ........................................................20 
6.3 
Summary of findings from clinical studies ...............................................................20 
6.4 
Summary of known and potential risks and benefits ...............................................20 
6.5 
Description and justification of route of administration and dosage .........................20 
6.6 
Dosages, dosage modifications and method of administration ...............................20 
6.7 
Preparation and labelling of Investigational Medicinal Product ...............................20 
6.8 
Drug accountability .................................................................................................20 
7 
NON-INVESTIGATIONAL PRODUCT> .........................................................................21 
7.1 
Name and description of non-investigational product(s) .........................................21 
7.2 
Summary of findings from non-clinical studies ........................................................21 
7.3 
Summary of findings from clinical studies ...............................................................21 
7.4 
Summary of known and potential risks and benefits ...............................................21 
7.5 
Description and justification of route of administration and dosage .........................21 
7.6 
Dosages, dosage modifications and method of administration ...............................21 
7.7 
Preparation and labelling of Non Investigational Medicinal Product ........................21 
7.8 
Drug accountability .................................................................................................21 
8 
METHODS ....................................................................................................................22 
8.1 
Study parameters/endpoints ...................................................................................22 
8.1.1 
Main study parameter/endpoint .......................................................................22 
8.1.2 
Secondary study parameters/endpoints ..........................................................22 
8.1.3 
Other study parameters (if applicable) .............................................................22 
8.2 
Randomisation, blinding and treatment allocation ..................................................23 
8.3 
Study procedures ...................................................................................................23 
8.4 
Withdrawal of individual subjects ............................................................................25 
8.4.1 
Specific criteria for withdrawal (if applicable) ...................................................25 
8.5 
Replacement of individual subjects after withdrawal ...............................................25 
8.6 
Follow-up of subjects withdrawn from treatment .....................................................25 

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8.7 
Premature termination of the study .........................................................................25 
9 
SAFETY REPORTING ..................................................................................................26 
9.1 
Temporary halt for reasons of subject safety ..........................................................26 
9.2 
AEs, SAEs and SUSARs ........................................................................................26 
9.2.1 
Adverse events (AEs) ......................................................................................26 
9.2.2 
- Serious adverse events (SAEs).....................................................................26 
9.2.3 
Suspected unexpected serious adverse reactions (SUSARs) .........................27 
9.3 
Annual safety report ...............................................................................................27 
9.4 
Follow-up of adverse events ...................................................................................27 
9.5 
Data Safety Monitoring Board (DSMB) / Safety Committee ....................................27 
10 
STATISTICAL ANALYSIS ..........................................................................................28 
10.1 
Primary study parameter(s) ....................................................................................28 
10.2 
Secondary study parameter(s) ...............................................................................29 
10.3 
Other study parameters ..........................................................................................29 
10.4 
Interim analysis (if applicable) ................................................................................29 
11.ETHICAL CONSIDERATIONS 
11.1 
Regulation statement .............................................................................................30 
11.2 
Recruitment and consent........................................................................................30 
11.3 
Objection by minors or incapacitated subjects (if applicable) ..................................30 
11.4 
Benefits and risks assessment, group relatedness .................................................30 
11.5 
Compensation for injury .........................................................................................31 
11.6 
Incentives (if applicable) .........................................................................................31 
12. ADMINISTRATIVE ASPECTS, MONITORING ,AND PUBLICATION .............................32 
12.1 
Handling and storage of data and documents ........................................................32 
12.2 
Monitoring and Quality Assurance ..........................................................................33 
12.3 
Dossier Amendments .............................................................................................33 
12.4 
Annual progress report ...........................................................................................33 
12.5 
Temporary halt and (prematurely) end of study report ............................................34 
12.6 
Public disclosure and publication policy ..................................................................34 
13. STRUCTURED RISK ANALYSIS ...................................................................................35 
13.1 
Potential issues of concern .....................................................................................35 
13.2 
Synthesis ...............................................................................................................35 
14 
REFERENCES ..........................................................................................................36 
15. Supplementary I .............................................................................................................38 

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LIST OF ABBREVIATIONS AND RELEVANT DEFINITIONS  
 
ABR 
General Assessment and Registration form (ABR form), the application 
form that is required for submission to the accredited Ethics Committee; in 
Dutch: Algemeen Beoordelings- en Registratieformulier (ABR-formulier) 
AE 
Adverse Event 
CA 
Competent Authority 
CCMO 
Central Committee on Research Involving Human Subjects; in Dutch: 
Centrale Commissie Mensgebonden Onderzoek 
CV 
Curriculum Vitae 
DSMB 
Data Safety Monitoring Board 
EU 
European Union 
GCP 
Good Clinical Practice 
GDPR 
 
HA 
General Data Protection Regulation; in Dutch: Algemene Verordening 
Gegevensbescherming (AVG) 
Hyperandrogenism  
IC 
Informed Consent 
METC  
 
OD 
PCOM 
Medical research ethics committee (MREC); in Dutch: medisch-ethische 
toetsingscommissie (METC) 
Ovarian Dysfunction  
Polycystic ovarian morphology ovarian dysfunction (OD) 
(S)AE 
(Serious) Adverse Event  
Sponsor The sponsor is the party that commissions the organisation or performance 
of the research, for example a pharmaceutical 
company, academic hospital, scientific organisation, or investigator. A 
party that provides funding for a study but does not commission it is not 
regarded as the sponsor, but referred to as a subsidising party. 
UAVG 
Dutch Act on Implementation of the General Data Protection Regulation; in 
Dutch: Uitvoeringswet AVG 
WMO 
Medical Research Involving Human Subjects Act; in Dutch: Wet Medisch-
wetenschappelijk Onderzoek met Mensen 
 
 

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SUMMARY 
Rationale:  
Polycystic ovary syndrome (PCOS) is an endocrine disorder that affects up to 10% of 
reproductive-aged women worldwide. According to the Rotterdam criteria the syndrome is 
diagnosed based on two of the following three criteria: ovarian dysfunction (OD), 
hyperandrogenism (HA) (clinical or biochemical), and/or polycystic ovarian morphology 
(PCOM) (1) and there are four different PCOS phenotypes based on the features (2).  
In PCOS women, not only is infertility a concern but the syndrome is also associated with 
obesity, insulin resistance, type 2 diabetes mellitus, metabolic syndrome, and cardiovascular 
risk factors (3). 
Various factors have been reported to contribute to the pathophysiology of PCOS, but due to 
the heterogeneity of the syndrome, the pathophysiology remains unclear. However, studies 
emerged on the crucial role of the gut microbiome in human health. Recent studies 
confirmed that the gut microbiome is altered in women with PCOS compared to healthy 
women (4-7), and some of these alterations have been linked to the clinical markers of 
PCOS (4, 5). Different PCOS phenotypes may show different gut microbiome features due to 
the heterogeneity of this syndrome, which makes it hard to detect the significant changes in 
the gut microbiome. Age, obesity, androgen status, and insulin resistance or glucose 
intolerance should all be taken into account while studying the gut microbiome of PCOS 
patients.  
Even though studies have proven that PCOS patients have an altered gut microbiome, the 
characteristics of microbiome diversity and the specific types of gut bacteria have remained 
inconsistent. Studies reported on specific alterations of alpha and beta diversity in PCOS 
patients. Although some studies have shown that decreased alpha diversity and altered beta 
diversity were associated with PCOS (4, 5, 8), many studies have reported that microbial 
diversity remained unchanged (9-11).  
  
Studies have investigated correlations between the clinical features of PCOS and the gut 
microbiome. Features of PCOS such as hyperandrogenism, hirsutism, insulin resistance, and 
obesity can all have an impact on the gut microbiome to some extent. The decrease in α-
diversity has been linked to total testosterone levels and hirsutism (9, 12) ,and changes in β-
diversity were also correlated with hyperandrogenism (5). Also, some even suggested that 
the hyperandrogenism seen in the PCOS rodent model may affect the gut microbiome 
independently of diet (13). The role of metabolic factors, such as obesity and insulin 
resistance, in the PCOS patient's gut microbiome,e remains unclear. Although another study 
showed that obesity itself is linked to a decrease in gut microbial diversity (12), most studies 
on the gut microbiome in PCOS have included BMI-matched controls to exclude the 

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influence of body weight. In another study, BMI was found to positively correlate with three 
bacterial species, while waist-to-hip ratio and fat mass were also found to significantly 
correlate with the levels of multiple species (9, 12). 
While the etiology of the microbiome-mediated disease is yet unknown, one possible 
pathway is microbial metabolism. Using metabolomics technology to identify metabolites that 
constitute chemical fingerprints of several metabolic pathways relevant for the pathogenesis 
of PCOS. While PCOS affects metabolites from various metabolic pathways, this primarily 
includes abnormalities in the metabolism of lipids, steroid hormones, carbohydrates, and 
amino acids. Identifying disrupted pathways enables PCOS-specific molecules that could be 
used as biomarkers and future metabolomic research targets.  
Fewer studies are available investigating the relationship between PCOS and the vaginal 
microbiome, due to challenges in translating the vaginal microbiome of rodent models to 
humans. However, more consistent results were observed for the vaginal microbiome of 
PCOS patients (14, 15). The reason could be that the vaginal microbiome has lesser 
biomass and biodiversity than the gut, which makes it easier to get affected by PCOS.  
 
As far as we are aware, they are no studies investigating the vaginal microbiota and its 
relation with sex hormone concentrations and PCOS phenotypical, diagnostic, and metabolic 
characteristics. This study aims to get a better understanding of the relationship between 
PCOS phenotypical, diagnostic, and metabolic characteristics (hirsutism, hyperandrogenism, 
ovarian dysfunction, polycystic ovary) and the gut- or vaginal microbiome in 
overweight/obese and lean patients.  Hopefully, this may lead to a better understanding of 
the role of this microbiota in the pathogenesis of PCOS and future perspectives on treatment 
options.   
The hypothesis is that PCOS patients have a less diverse microbiome in comparison with 
non-PCOS patients. Obese patients with PCOS will have a more severe dysbiosis of the gut 
microbiome than lean patients with PCOS.  
 
 
Objective:  
To analyse, characterise and determine the gut- and vaginal microbiome and its association 
with PCOS.   
Main objectives 
- 
To analyse whether there is an association between the gut microbiome and PCOS 
as such and its diagnostic and metabolic characteristics.   
Secondary objectives  

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- 
To analyse whether there is an association between the vaginal microbiome and 
PCOS as such and its diagnostic and metabolic characteristics.   
- 
To analyse whether there is a correlation between the composition of the gut- and 
vaginal microbiome in PCOS patients  
- 
To analyse the difference in gut- and vaginal microbiome composition between 
overweight/obese and lean (with/without PCOS).   
- 
To analyse potential metabolic profiles characterizing different phenotypes of PCOS  
 
Study design: A prospective observational case-control study, conducted at the Department 
of Obstetrics and Gynecology (Division of Reproductive Medicine) at the Erasmus University 
Medical Center Rotterdam 
 
Study population: Patients with PCOS diagnosed based on the Rotterdam criteria must be 
Caucasian women, aged 18 - 45 years old (premenopausal), either overweight or obese 
(BMI>25) or lean (BMI18-25). 
 
Main study parameters/endpoints: 
The main parameter of this study is the differences in community structure (presence or 
absence of bacteria, alpha, and beta diversity) of the gut microbiome between PCOS 
patients and controls.  
Secondary study parameters:  1. Differences in community structure (presence or absence of 
bacteria, alpha, and beta diversity) in the vaginal microbiome between PCOS patients and 
controls. 2. The differences and similarities between the vaginal- and gut microbiome 
composition in PCOS patients 3. The differences and similarities between the vaginal- and 
gut microbiome composition between overweight/obese and lean patients (with/without 
PCOS). 4. Metabolic profiles from different phenotypes of PCOS  
Nature and extent of the burden and risks associated with participation, benefit, and 
group relatedness:  
For all participants, the risks involve primarily the burden of participating in a study, which in 
the current study proposal means 1 additional hospital visit and assessments. Women from 
the study group have already undergone the regular physical examination (transvaginal 
ultrasound) and laboratory tests for the standard outpatient clinic for COLA (Cycle disorders, 
Oligomenorrhea and Amenorrhea) screening. Patients will be asked to collect a stool sample 
at home and bring or send this to the hospital. A vaginal sample will be obtained by a 
physician without using a speculum. The risks of participation are considered to be minor and 
there are no obvious risks associated with participation in the study. The assessment and 
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the pathophysiology of PCOS and might provide future intervention strategies eventually 
leading to new therapeutic options reducing the risk of metabolic risk factors. Therefore, this 
project will have an impact on research, individual clinical care as well as on future medical 
health care costs. 
 

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1. INTRODUCTION AND RATIONALE 
 
Polycystic ovary syndrome (PCOS) is an endocrine disorder that affects up to 10% of 
reproductive-aged women worldwide. According to the Rotterdam criteria the syndrome is 
diagnosed based on two of the following three criteria (2): ovarian dysfunction (OD), 
hyperandrogenism (HA) (clinical or biochemical), and/or polycystic ovarian morphology 
(PCOM) (1). PCOS phenotypes are currently classified as phenotype-A (HA+ OD+ PCOM), 
phenotype-B (HA+OD), and phenotype-C (HA+PCOM). Phenotype-A or full-blown phenotype 
is present in half of the patients who present in the clinic. See Supplementary Table 1.  
In PCOS women, not only is infertility a concern, but the syndrome is also associated with 
obesity, insulin resistance, type 2 diabetes mellitus, metabolic syndrome, and cardiovascular 
risk factors (3). Various factors have been reported to contribute to the pathophysiology of 
PCOS, such as lifestyle, metabolic status, and genetic and epigenetic variants. However, 
studies emerged on the crucial role of the gut microbiome in human health. Recent studies 
confirmed that the gut microbiome is altered in women with PCOS (4-6). The gut microbiome 
composition of PCOS patients is altered compared to healthy women and some of these 
alterations have been linked to the clinical markers of PCOS (4, 5). PCOS patients seem to 
have a leaky gut: the gut bacteria change the intestinal lining, resulting in the release of 
bacterial endotoxins into the bloodstream. This could activate pro-inflammatory cytokines, 
promoting insulin resistance, hyperandrogenism, and fat storage, all of which are linked to 
PCOS (16).  
Even though studies have proven that PCOS patients have an altered gut microbiome, the 
characteristics of microbiome diversity and the specific types of gut bacteria have remained 
inconsistent. Studies reported on specific alterations of alpha and beta diversity in PCOS 
patients. Alpha diversity refers to the number of different taxa within a specific community; it 
indicates the richness of the gut microbiome. Beta diversity is a measure of how comparable 
the gut microbiome is between healthy people and PCOS patients. Although some studies 
have shown that decreased alpha diversity and altered beta diversity were associated with 
PCOS (4, 5, 8), many studies have reported that microbial diversity remained unchanged (9-
11). Of note, a recent study with more than 300 subjects did not find microbial diversity in 
PCOS patients compared to healthy patients. Although, this was a population-based cohort 
study, and subjects were asked retrospectively whether they had oligomenorrhea, hirsutism 
or were diagnosed with PCOM. Several other reasons could have led to an unchanged 
microbial diversity and inconsistent outcomes, such as small sample size, and differences in 
sequencing techniques and analytical methods.  
Unlike gut microbial diversity, most human studies have found differences in taxa between 
healthy women and PCOS patients. The phyla Bacteroidetes, Firmicutes, and Tenericutes, 

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as well as the families Bacteroidaceae, Ruminococcaceae, Lachnospiraceae, 
Prevotellaceae, and Streptococcaceae, are mostly represented. In many studies, significant 
changes in Bacteroides abundance were discovered (6, 7, 10, 17, 18). In addition, a 
metagenomic analysis revealed the existence of specific species of Bacteroides spp. in 
PCOS patients. The most typical aspect of the gut microbiome in patients with PCOS, 
according to Qi et al., is an increase in the abundance of Bacteroides vulgatus (6). More 
notably, administration of B. vulgatus mimics PCOS characteristics in mice (6). Additionally, 
Bacteroides fragilis was shown to be more abundant in another metagenomic study, and its 
abundance was positively linked with luteinizing hormone (LH) and antimullerian hormone 
levels (AMH) (17). According to these studies, Bacteroides spp plays an important role in 
PCOS patients. More research is needed to compare the pathogenic role of several species 
of Bacteroides spp.  
 
Studies have investigated on correlations between the clinical features of PCOS and the gut 
microbiome. Features of  PCOS such as hyperandrogenism, hirsutism, insulin resistance and 
obesity can all have an impact on the gut microbiome to some extent. The decrease in α-
diversity has been linked to total testosterone levels and hirsutism (9, 12) ,and changes in β-
diversity was also correlated with hyperandrogenism (5). Also, some even suggested that the 
hyperandrogenism seen in the PCOS rodent model may affect the gut microbiome 
independently of diet (13). The role of metabolic factors, such as obesity and insulin 
resistance, in the PCOS patient's gut microbiome remains unclear. Although another study 
showed that obesity itself is linked to a decrease in gut microbial diversity (12), most studies 
on the gut microbiome in PCOS have included BMI-matched controls to exclude the 
influence of body weight. In another study, BMI showed positive correlations with three 
bacterial species and waist-to-hip, ratio and fat mass was also correlated with several 
species levels (9, 12).  
 
While the etiology of microbiome-mediated disease is yet unknown, one possible pathway is 
microbial metabolism. Using metabolomics technology in order to identify metabolites that 
constitute chemical fingerprints of several metabolic pathways relevant for the pathogenesis 
of PCOS. Hyperandrogenism appears to be the major pathological component in the etiology 
of PCOS, according to a rodent study. In this work, eliminating the gut microbiota of DHEA-
treated rats did not prevent PCOS phenotypes, however transplanting microbiota from 
androgen-treated rats into pseudo germ-free animals caused hepatic glucolipid metabolic 
disruptions and reproductive hormone imbalance (19).   
 

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Human studies have shown that levels of metabolites from different biochemical pathways 
are altered in women with PCOS, but abnormalities in hormone and lipid metabolism were 
mainly involved in the onset of PCOS (20). Also, metabolites connected to amino acids as 
well as energy metabolism such as citric acid cycle appear to be the most common. 
Glycerophospholipid metabolism was shown to be down-regulated in PCOS, while glucose 
metabolism was found to be up-regulated. Zhao et al. found that in PCOS, all of the 
measured fatty acids are up-regulated when compared to control patients (21).  According to 
Zou et al., certain carbohydrates and fatty acid metabolites are up-regulated in PCOS 
compared to controls (22). Identifying disrupted pathways enables of PCOS-specific 
molecules that could be used as biomarkers and future metabolomic research targets. 
Finding relevant biochemical indicators may help in early diagnosis and future targeted 
pharmacological therapies. 
 
Fewer studies are available investigating the relationship between PCOS and the vaginal 
microbiome, due to challenges in translating the vaginal microbiome of rodent models to 
humans. However, a recent study found lower abundances of Lactobacillus spp. and 
elevated levels of Gardnerella, Prevotella, and Mycoplasma (15). In addition, the authors 
found highly comparative microbiome composition in vaginal and cervical canal samples in 
the same patient. In correspondence to another case-control study, they found that women 
with PCOS have higher alpha diversity, lower abundances of Lactobacillus crispatus, and 
higher abundances of Mycoplasma and Prevotella (14), after adjusting for BMI. These 
studies suggested a more consistent conclusion in the vaginal microbiome of PCOS patients. 
The reason could be that the vaginal microbiome has lesser biomass and biodiversity than 
the gut, which makes it easier to get affected by PCOS.  
 
As far as we are aware, they are no studies investigating the vaginal microbiota and its 
relation with sex hormone concentrations and PCOS phenotypical, diagnostic and metabolic 
characteristics. This study aims to get a better understanding of the relationship between 
PCOS phenotypical, diagnostic and metabolic characteristics (hirsutism, hyperandrogenism, 
ovarian dysfunction, polycystic ovary) and the gut- or vaginal microbiome in 
overweight/obese and lean patients. Hopefully, this may lead to a better understanding of the 
role of these microbiota in the pathogenesis of PCOS and future perspectives on treatment 
options.   
The hypothesis is that PCOS patients have a less diverse microbiome in comparison with 
non-PCOS patients. Obese patients with PCOS will have a more severe dysbiosis of the gut 
microbiome than lean patients with or without PCOS.  
 

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2. OBJECTIVES 
 
To analyse, characterise and determine the gut- and vaginal microbiome and its association 
with PCOS clinical phenotypes.  
Main objectives 
- 
To analyse whether there is an association between the gut microbiome and PCOS 
as such and its diagnostic and metabolic characteristics.   
Secondary objectives  
- 
To analyse whether there is an association between the vaginal microbiome and 
PCOS as such and its diagnostic and metabolic characteristics.   
- 
To analyse whether there is a correlation between gut- and vaginal microbiome in 
PCOS patients and controls  
- 
To analyse the difference in gut- and vaginal microbiome composition between obese 
and lean (with/without PCOS).   
- 
To analyse potential metabolic profiles characterizing different phenotypes of PCOS  
 
 
 
 

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3. STUDY DESIGN 
 
This is a prospective observational case-control study, conducted at the department of 
Obstetrics and Gynecology (Division of Reproductive Medicine) at the Erasmus University 
Medical Center Rotterdam. In this study changes of the gut- and vaginal microbiome will be 
analysed in correlation with PCOS phenotypes. 
 
Patients: 
women diagnosed by the division of Reproductive Medicine with PCOS  
 
 
in West- or Central Europe* 
Sample size:  
n=50 PCOS overweight/obese and n=50 PCOS lean patients  
Moments of inclusion: after PCOS diagnosis/ COLA screening (Cycle disorders, 
Oligomenorrhea and Amenorrhea screening) 
Controls:  
n=50 overweight/obese and n=50 lean non-PCOS healthy women  
Test sample:  
vaginal swab, stool sample and blood sample 
Study period:      1-11-2022 – 1-12-2024 
 
* The diet is strongly associated with the gut microbiome. The reason to only include women 
from Western and Central Europe, is because these women have a different diet compared 
to women from Asian, Mediterranean and African countries (recently reviewed in:(23)) . We 
want to include women who have a Western diet. In addition, the vaginal microbiome is 
structurally different across ethnicities (24). To avoid getting too small groups in sub-
analyses based on ethnicity or diet, we chose to include patients from Western and Central 
Europe. 
 
4. STUDY POPULATION 
 
4.1 Population (base)  
Patients who have had COLA screening at the outpatient clinic of Reproductive Medicine.  
Study group: overweight/obese women (BMI>25) and lean women BMI (18-25) with PCOS  
Control group: overweight/obese women and lean women without PCOS. 
4.2 Inclusion criteria 
In order to be eligible to participate in this study, a subject must meet all of the following 
criteria: 
- 
Age 18-45years (premenopausal)  
- 
Caucasian  
- 
Willing to provide vaginal swab and stool sample  
- 
Willing to provide informed consent  
- 
Sufficient command of the Dutch language 
- 
Diagnosed with PCOS at Erasmus MC using the Rotterdam criteria 2003 (2) (see 
also H.15 Supplementary 1)  

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4.3 Exclusion criteria 
A potential subject who meets any of the following criteria will be excluded from 
participation in this study: 
- 
BMI <18 
- 
Smoking  
- 
Diabetes Mellitus or use of insulin sensitizer  
- 
Chronic and acute infection diseases 
- 
Endometriosis (American Fertility Score (AFS) III/IV) 
- 
Elevated prolactin levels, thyroid disease, Cushing disease or gastro-intestinal 
disease 
- 
The use of hormonal contraceptives, other steroid hormones in last 3 months 
- 
Use of antibiotics, probiotics or laxatives in the last 3 months 
 
Control group:  
o After a COLA screening, subjects who have not been diagnosed with PCOS and have a 
regular menstrual cycle without hyperandrogenism or PCOM will have their dossiers 
individually evaluated to see whether they can participate in the control group.  
o COLA screening volunteers who have already agreed to be approached for 
any future studies, will receive the PIF and be asked to participate in this study. 
These candidates are healthy and have a regular menstrual cycle.  
o Online advertisement will be published to recruit volunteers.  
- 
Inclusion criteria control group: 
o Age 18-45years (premenopausal)  
o Caucasian 
o Willing to provide vaginal and stool sample 
o Willing to provide informed consent  
o Regular menstrual cycle (25-35days)  
o Sufficient command of the Dutch language 
o No history of diagnosed PCOS and do not meet any of the Rotterdam criteria.  
- 
Exclusion criteria: see above.  
 
4.4 Sample size calculation  
Sample size is estimated on the basis of sample availability and literature. An 
important study is by Torres et al. (5), where they included 48 controls and 73 
women with PCOS. In figures 1a and 1b they show that with these numbers they 
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Faith PD. The Faith PD is a measure of diversity based on the phylum of the 
bacteria. There are several studies that show no difference with a small sample 
size (n=10-30), but the study by Lindheim et al.(4) shows that with 24 PCOS 
women and 19 controls a decreased diversity was found with also significantly 
decreased abundances of Tenericutes and Bacteroidetes. Due to the novelty of 
this field of study, the pilot data set is not publicly accessible. In order to analyze 
the differences in microbiome composition between gut and vaginal microbiome, 
between study and control group, 100 patients will be included (n=50 with a BMI > 
30 kg/m2 and n=50 with BMI 19-25 kg/m2) in study group. Also, 100 healthy women 
will be included in the control group.  

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TREATMENT OF SUBJECTS 
 
5.1 Investigational product/treatment 
 
 
Not applicable 
5.2 Use of co-intervention (if applicable) 
 
 
Not applicable 
5.3 Escape medication (if applicable) 
 
Not applicable 

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6 INVESTIGATIONAL PRODUCT  
 
6.1 Name and description of investigational  product(s) 
 
 
Not applicable 
6.2 Summary of findings from non-clinical studies 
 
 
Not applicable 
6.3 Summary of findings from clinical studies 
 
 
Not applicable 
6.4 Summary of known and potential risks and benefits 
 
 
Not applicable 
6.5 Description and justification of route of administration and dosage 
 
 
Not applicable 
6.6 Dosages, dosage modifications and method of administration 
 
 
Not applicable 
6.7 Preparation and labelling of Investigational Medicinal Product 
 
 
Not applicable 
6.8 Drug accountability 
 
 
Not applicable 

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7 NON-INVESTIGATIONAL PRODUCT> 
  
7.1 Name and description of non-investigational product(s) 
 
 
Not applicable 
7.2 Summary of findings from non-clinical studies 
 
 
Not applicable 
7.3 Summary of findings from clinical studies 
 
 
Not applicable 
7.4 Summary of known and potential risks and benefits 
 
 
Not applicable 
7.5 Description and justification of route of administration and dosage 
 
 
Not applicable 
7.6 Dosages, dosage modifications and method of administration 
 
 
Not applicable 
7.7 Preparation and labelling of Non Investigational Medicinal Product 
 
 
Not applicable 
7.8 Drug accountability 
 
 
Not applicable 

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8 METHODS 
 
8.1 Study parameters/endpoints 
8.1.1 Main study parameter/endpoint 
- 
Differences in community structure of the gut microbiome between PCOS patients 
and controls as such and its diagnostic and metabolic characteristics.   
8.1.2 Secondary study parameters/endpoints  
- 
Differences in community structure in the vaginal microbiome between PCOS patients 
and controls as such and its diagnostic and metabolic characteristics.   
- 
Differences and similarities in community structure of the vaginal- and gut microbiome 
in PCOS patients  
- 
Differences and similarities between the vaginal- and gut microbiome composition 
between overweight/obese and lean patients (with/without PCOS)  
- 
Metabolic profiles from different phenotypes of PCOS  
8.1.3 Other study parameters (if applicable) 
       
Not applicable 
 
The analyses for differences in community structure in the gut and vaginal microbiome are 
explained here:  
A common strategy is to group reads at some level of similarity into representative 
sequences of hypothetical species called Operational Taxonomic Units (OTUs), where all 
reads within, 97% similarity are clustered together and represented by a single OTU 
sequence. This is done because bacterial taxonomy is incomplete and there are sequencing 
errors in the Next Generation Sequencing (NGS) reads.  
 
Alpha diversity refers to the number of different taxa within a specific community; it indicates 
the richness of the gut microbiome. Beta diversity is a measure of how comparable the gut 
microbiome is between healthy people and PCOS patients. Shannon diversity index is a way 
to measure the diversity of species in a community. The higher the value of H, the higher the 
diversity in a particular community. Another measure of alpha diversity could be the species 
richness, which is the count of the number of species or OTUs present in that sample.  
 
UniFrac will be used to compare the (dis-)similarities among the microbial communities 
samples (beta-diversity). Unweighted UniFrac analyses is based on presence/absence of 
difference taxa and abundances and weighted UniFrac will take the abundances of different 
taxa into consideration.   

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8.2 Randomisation, blinding and treatment allocation 
       
 Not applicable 
 
 
8.3 Study procedures 
Patients are eligible for the study after they are diagnosed with PCOS at the regular COLA 
screening. The abbreviation COLA stands for: Cycle disorders, Oligomenorrhea and 
Amenorrhea. During the regular COLA screening visit, patients will undergo a physical 
examination, including a transvaginal ultrasound. Three to four weeks after the COLA 
screening patients will receive their COLA screening results. Patients who are diagnosed 
with PCOS and are eligible for the study will be informed about the details of the study. 
Patients will receive a patient information leaflet with the informed consent form, together 
with the contact information of the clinical coordinator in case they might have any remaining 
questions. 
 
The main investigator will contact them by phone 1 week after their appointment for their 
COLA screening result and ask if they are interested in participating in the study. If the 
patient agrees to participate,  the material for stool sample collection will be sent to her. 
Patients will be instructed to collect the stool sample after signing the informed consent 
(preferably on the day of the second appointment, but no more than 2 days before) On the 
day of the second appointment, the researcher will sign the informed consent and provide a 
copy to the patient. A vaginal swab will be obtained by the physician and the stool sample 
will be handed in by the patient.  
 Vaginal samples and blood samples will be collected in the non-menstrual period during the 
appointment. Patients will be asked to fill in an online Food Frequency Questionnaire (max 
45min).   
Also, PCOS patients in the COLA database who are eligible will be approached to participate 
in this study. They will be contacted by phone, and if they are interested in participation, a 
PIF will be sent to their home address.  
 
Participants in the control group will be informed by the main investigator. When they meet 
the inclusion criteria and they decide to participate in the study, the same COLA screening 
will be conducted, in combination with this study protocol.  
COLA screening volunteers who have already agreed to be approached for any future 
studies, will receive the PIF and be asked to participate in this study. These candidates are 
healthy and have a regular menstrual cycle.  

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Online advertisement will be published to recruit volunteers.  
 
After collection the vaginal swab and stool sample will be split in different portions to be 
analysed using the 16S rRNA gene sequencing. In both the stool and vaginal swab samples 
the following parameters will be measured: both the microbiome profile patterns (three 
different groups of microorganisms: (1) Firmicutes/ Actinobacteria/ Verrucomicrobia (2) 
Bacteroidetes and (3) Proteobacteria) by the NGS and another high throughput technique for 
the Lactobacillus, Staphylococcus, E coli and Bacillus RG4 composition as percentage of the 
total microbiome content. 
 
16S ribosomal RNA amplicon sequencing  
Both gut and vaginal microbiome will be analysed by using 16S ribosomal RNA 
sequencing (rRNA). For each sample the V4 hypervariable region of the 16S rRNA gene 
will be amplified by polymerase chain reaction (PCR) with primers. The steps in the PCR 
process are as follow and each step occurs at a different temperature. First denaturation 
at 94°C occurs and the two DNA strands get separated out. Then amplification at 
different temperatures occurs. Finally, the enzyme Polymerase is added which make the 
primers extend along the length of the DNA strand. 
 
 
Laboratory measurements includes: estradiol, total testosterone, androstenedione, 
dyhydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), 
dehydrotestosterone (DHT), serum cortisol, thyroid-stimulating hormone (TSH), prolactin, 
insulin, anti-Muellerian hormone (AMH), sex hormone-binding globulin (SHBG), serum 
luteinizing hormone (LH), follicle-stimulating hormone (FSH), 17-hydroxyprogesterone 
(17OH-P), plasma total cholesterol, high-density lipoprotein (HDL)- cholesterol, triglycerides 
and glucose. These laboratory measurements are already included in the COLA screening. 
Addition measurements that will be obtained include but will not limited to: LH, FSH, 
estradiol, progresteron, hsC-reactive protein (CRP), interleukin-22 (IL-22), IL6, tumor 
necrosis factor-a (TNF-a), serum endotoxin (=lipopolyssacharide, LPS), adiponectin, serum 
zonulin, sCD14: soluble CD14 (endotoxin co-receptor), bile acids in serum and in stool, stool 
calprotectin and stool zonulin.  
Vaginal samples will be taken using a cotton swab: eSwabTM (COPAN Italia S.p.A.) The 
swab will be inserted 5-6 cm beyond the vaginal orifice, and moved around along the vaginal 
wall for 10–15 s. The vaginal samples will be stored at -20°C and transported to a freezer at -
80°C twice per week. Stool samples will be collected using a stool collection tube and stored 
in a cold transport container. Until further processing, samples will be stored in a freezer at -

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20 °C immediately by the patient and at -80°C at the day the stool sample has arrived at 
Erasmus MC.  
 
8.4 Withdrawal of individual subjects 
Subjects can leave the study at any time for any reason if they wish to do so without any 
consequences. The investigator can decide to withdraw a subject from the study for urgent 
medical reasons. 
8.4.1 Specific criteria for withdrawal (if applicable) 
 
 
 
Not applicable 
 
8.5 Replacement of individual subjects after withdrawal 
Subjects who opt to withdraw will not be replaced. 
 
8.6 Follow-up of subjects withdrawn from treatment 
 
 
Not applicable 
 
8.7 Premature termination of the study 
A premature termination of the study is not expected. However, in case of a premature 
termination of the study no consequences for the study subjects are to be expected. 
 
 

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9 SAFETY REPORTING 
 
9.1 Temporary halt for reasons of subject safety 
In accordance to section 10, subsection 4, of the WMO, the sponsor will suspend the 
study if there is sufficient ground that continuation of the study will jeopardise subject 
health or safety. The sponsor will notify the accredited METC without undue delay of a 
temporary halt including the reason for such an action. The study will be suspended 
pending a further positive decision by the accredited METC. The investigator will take 
care that all subjects are kept informed.  
 
9.2 AEs, SAEs and SUSARs 
9.2.1 Adverse events (AEs) 
The interventions performed in this pilot study are blood collection and a vaginal swab. 
Adverse events are defined as any undesirable experience occurring to a subject during the 
study. Events considered related to the experiment, reported spontaneously by the subject or 
observed by the investigator or his staff will be recorded. Regular laboratory screening is part 
of the standard care on the PICU, although unlikely, adverse reactions from blood collection 
can occur. Personnel collecting blood specimens know what can occur and how best to 
manage the reactions. This is an observational study, adverse drug events are not caused by 
study intervention. All adverse events due to blood collection, vaginal swab collection or 
faeces collection will be registered. 
9.2.2 - 
Serious adverse events (SAEs) 
A serious adverse event is any untoward medical occurrence or effect that  
- 
results in death; 
- 
is life threatening (at the time of the event); 
- 
requires hospitalisation or prolongation of existing inpatients’ 
hospitalisation; 
- 
results in persistent or significant disability or incapacity; 
- 
is a congenital anomaly or birth defect; or 
- 
any other important medical event that did not result in any of the outcomes 
listed above due to medical or surgical intervention but could have been based upon 
appropriate judgement by the investigator. 
An elective hospital admission will not be considered as a serious adverse event  
 

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In line with the CCMO guidelines, the SAEs will be reported to the MEC via yearly line 
listings together with the progress report.  
9.2.3 Suspected unexpected serious adverse reactions 
(SUSARs) 
 
 
 
 
Not applicable  
 
9.3 Annual safety report 
 
 
Not applicable 
9.4 Follow-up of adverse events 
All AEs will be followed until they have abated, or until a stable situation has been 
reached. Depending on the event, follow up may require additional tests or medical 
procedures as indicated, and/or referral to the general physician or a medical specialist. 
SAEs need to be reported till end of study within the Netherlands, as defined in the 
protocol  
9.5 Data Safety Monitoring Board (DSMB) / Safety Committee 
 
 
Not applicable 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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10 STATISTICAL ANALYSIS 
 
10.1 Primary study parameter(s) 
Statistical analyses  
The statistical analyses will be conducted using the statistical software R.  
 
Continuous variables will be expressed as mean and standard deviation for normally 
distributed variables, median and interquartile range for not normally distributed variables.  
 
To analyse the association between the gut microbiome and PCOS compared to controls, 
reads with some level of similarity will be grouped into operational taxonomic units 
(OTUs). Alpha and beta diversity analyses will be calculated to estimate the abundance 
and diversity of species within samples.  
Alpha diversity comparisons will be analysed with Shannon diversity index and richness 
as continuous variables. Higher Shannon diversity index is associated with a more 
diverse and rich vaginal microbiome. It measures the number of species and the 
differences between species abundances. A logistic regression model will be used to test 
the changes of alpha diversity in PCOS and non-PCOS women. Same analyses will be 
conducted for changes of alpha diversity in overweight/obese and lean women with or 
without PCOS. Linear regression analyses will be conducted to study the correlation 
between the diversity of the microbiome (Alpha and Beta diversity) and parameters such 
as hyperandrogenism, rated as serum total testosterone level or Free Androgen Index 
(FAI). Other PCOS-associated variables included in the univariable linear regression 
analyses are: hirsutism, acne, BMI, LH/FSH, testosterone, androstenedione. Significant 
variables from the univariable regression analyses will be tested in a multivariable linear 
regression model. To correct for multiple testing, Bonferroni’s correction will be 
conducted.   
 
UniFrac will be used to compare the (dis-)similarities among the microbial communities 
samples (beta-diversity). Unweighted UniFrac analyses is based on presence/absence of 
difference taxa and abundances and weighted UniFrac will take the abundances of different 
taxa into consideration.  The results from Unifrac analyses will be represented using Principal 
Coordinate Analysis (PCoA) plots. PCoA plots will represent the dissimilarity of microbiome 
samples. The PCoA will be based on the overall structure of the gut microbiome in all 
samples for PCOS and controls.    
 
 

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10.2 Secondary study parameter(s)  
To analyse the association between the vaginal microbiome and PCOS compared to 
controls, the bacterial taxa will be first classified to the genus level. The relative 
abundance will be quantified based on each taxa contribution to an individual sample. 
Operational taxonomic unit (OTU) abundance will be noted for all samples.   
Alpha and Beta diversity will be calculated. Associations between the vaginal microbiome 
(Alpha and Beta diversity) and PCOS-associated variables as BMI, hirsutism, acne, 
testosterone, androstenedione, LH/FSH, insulin, will be tested in a linear regression 
model. 
 
 
To investigate the association between the bacterial diversity and markers for gut 
permeability and inflammation in PCOS patients, a logistic regression model will be used.  
Leaky gut markers as calprotectin, zonulin, lipopolysaccharide and soluble CD15 and 
inflammation markers as CRP, IL-22, IL6 and TNF-a will be tested in the logistic 
regression model. Also the results of the Food Frequency Questionnaire (FFQ) will be 
analysed in the logistic regression model.  
 
Differences on clinical characteristics and metabolic biomarkers will be evaluated using t-
test or a one-way analysis of variance (ANOVA) for normally distributed variables or non-
parameter Wilcoxon test for non-normally distributed variables. Two-sided tests will be 
used, and p-values less than 0.05 will be considered statistically significant. 
 
As for the metabolomic analysis, the raw data will be pre-processed first. Log-
transformation and centering are techniques used to make the data normal distributed. To 
investigate differences between the PCOS and controls, univariate analysis will be 
performed to examine each metabolite feature separately. 
 
10.3 Other study parameters 
 
Not applicable 
 
10.4 Interim analysis (if applicable) 
 
 
Not applicable 

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11. ETHICAL CONSIDERATIONS 
 
11.1 Regulation statement 
The investigators will ensure that this study is conducted in agreement with the Declaration 
of Helsinki (version of October 2013, www.wma.net) and all relevant national guidelines and 
regulations, whichever provides the greatest protection for the patient. The study protocol will 
be submitted to the ethics committee. 
11.2 Recruitment and consent 
Women who are eligible for the study will be informed by the clinician about the the GuVa 
PCOS study and when the patient is interested in participation, the main investigator will 
contact the patient The main investigator will inform the patient. about the voluntary nature of 
their participation as well as by means of the information leaflet and informed consent form. 
Full comprehensive information will be given to all patients according to the regulations of the 
competent authorities that need to approve the clinical study.  
Participants in the control group will be recruited via online advertisement and via the 
outpatient clinic of Reproductive medicine.   
 
Informed consent: 
The study will be performed according to written informed consent procedures and this study 
protocol that are approved by local and/or national ethics committees. The informed consent 
procedures ensure personal data protection and confidentiality. Data will be coded, i.e. 
information will not be directly traceable to an individual person. 
Patients who signed the informed consent, agree on sharing unexpected findings with the 
specialist or general practitioner. Patients who do not want their physician and or general 
practitioner to be informed about the following, cannot participate in the study. 
 
11.3 Objection by minors or incapacitated subjects (if applicable) 
 
 
Not applicable  
11.4 Benefits and risks assessment, group relatedness 
Participants will not benefit directly from the study. The only study procedure for the subjects 
is the collection of stool samples by themselves and a vaginal sample by the physician. The 
participation will not influence any standard care provided. 
 

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11.5 Compensation for injury 
The sponsor/investigator has a liabity insurance which is in accordance with article 7 of the 
WMO. 
  
Dispensation from the statutory obligation to provide insurance has been obtained because 
participating in the study is without risks. 
11.6 Incentives (if applicable) 
 
 
Not applicable 

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12. ADMINISTRATIVE ASPECTS, MONITORING ,AND PUBLICATION 
12.1 Handling and storage of data and documents 
Each subject will be assigned a study number. Data on microbiome composition will be 
stored anonymously and coded on basis of that study number. Only the coordinating 
investigators, project leader, and the principal investigator(s) will have access to patient 
identifying data and their respective study numbers. This is according to the EU General 
Data Protection Regulation and the Dutch Act on Implementation of the General Data 
Protection Regulation. 
 
Storage of samples  
Vaginal and stool samples will be frozen at -80°C and stored up to a maximum of 25 
years. 
 
Storage of data  
Every patient will have to sign an informed consent form. All data will be stored and handled 
in the same way and according to the same rules and regulations as other patient-related 
data at the Erasmus MC. It will be stored as files on a separate research storage platform. 
Access will be limited to authorized study personnel. Should data transfer to other parties be 
necessary for testing or validation purposes, we will code the datasets and remove all 
personal data before the transfer. Data and information about the patient will be extracted 
from the clinical file. The signed consent forms must accompany the rectal and vaginal swab 
samples. 
 
Data extracted from the clinical file are: 
 
 
Age 
 
Body Mass Index (BMI) 
 
Ethnicity  
 
Hirsutism or not (and Modified Ferriman Gallwey score)  
 
PCOM (polycystic ovarian morphology) or not  
 
Amenorrhea or oligomenorrhea   
 
Smoking / non-smoking 
 
Alcohol consumption  
 
Previous treatments for fertility 
 
Gynaecological history 
 
General health status and diseases 
 
Operations before treatment 

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 
Menstrual cycle 
 
Previous use of antibiotics (estimated dates) 
 
Use of hormonal contraceptives 
 
Data will be stored in a databank file in the Erasmus MC using Castor. Data will be 
further analyzed using analyzing and statistical software (e.g. R). The originally informed 
consent will be archived. Data sets used for analysis will be stored along with data 
analysis output and syntax files to facilitate control measures. These sets of data and 
files will be stored together with the versions of scientific publications reporting the 
findings of the study for an unlimited time.  
 
12.2 Monitoring and Quality Assurance  
To guarantee high-quality research and reliability of data a minimal intensive form of 
monitoring will be performed in compliance with Good Clinical Practice (GCP) and other 
rules and regulations. Monitoring services will be provided by the qualified monitoring-unit 
of the OZBS (Onderzoeksbureau Sophia). This trial was classified as having ‘negligible 
risk’ according to the Dutch Federation of Universities (NFU) guidance ‘Quality Assurance 
of Human Subject Research’, requiring minimal monitoring. Using guidelines from the 
NFU, the monitor has established a specific monitoring plan. Based on this plan, the 
monitoring visit will take place a year after the first inclusion. To assure the quality of 
research data this monitor will have access to the data and source documents of the trial. 
For details, see the provided NFU risk classification form in Section K of the METC. 
 
12.3 Dossier Amendments  
Amendments are changes made to the research after a favourable opinion by the accredited 
METC has been given. All substantial amendments will be notified to the METC and the 
competent authority. 
Non-substantial amendments will not be notified to the accredited METC and the competent 
authority, but will be recorded and filed by the sponsor.  
 
12.4 Annual progress report 
The sponsor/investigator will submit a summary of the progress of the trial to the accredited 
METC once a year. Information will be provided on the date of inclusion of the first subject, 
numbers of subjects included and numbers of subjects that have completed the trial, serious 
adverse events/ serious adverse reactions, other problems, and amendments.  
 

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12.5 Temporary halt and (prematurely) end of study report 
The investigator/sponsor will notify the accredited METC of the end of the study within a 
period of 8 weeks. The end of the study is defined as the last patient’s last visit.  
The sponsor will notify the METC immediately of a temporary halt of the study, including the 
reason of such an action.  
In case the study is ended prematurely, the sponsor will notify the accredited METC within 15 
days, including the reasons for the premature termination. 
 Within one year after the end of the study, the investigator/sponsor will submit a final study 
report with the results of the study, including any publications/abstracts of the study, to the 
accredited METC.  
 
12.6 Public disclosure and publication policy 
This trial will be registered on public trial registry ClinicalTrials.gov. 
The results will be published in a scientific journal and be made available through a press 
release. The data will remain accessible upon request. The project will, if necessary, be 
communicated at the Erasmus MC at the outpatient clinic, University communication boards 
and the intranet. 
All data will be available for verification and re-use for at least 15 years. Full permission to 
access the data will be granted only to the project leader / coordinating investigator and the 
principal investigator. In case of an additional research question, this research can only be 
done with permission of all members of the research team and a signed statement ensuring 
confidentiality must be obtained. 

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13. STRUCTURED RISK ANALYSIS  
Not applicable 
13.1 Potential issues of concern 
 
Not applicable  
 
 
13.2 Synthesis 
Not applicable  
 
 

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NL80648.078.22  
 
GuVa-PCOS  
Version number: 2.0, 11-08-2022 
 
38 of 38 
 
15. Supplementary I 
PCOS diagnose using the Rotterdam criteria by a presence of at least two of the following 
criteria: 
o Oligomenorrorrhea or amenorrhea 
o Clinical or biochemical hyperandrogenism (modified Ferriman-Gallway score >5; 
testosterone level >2nmol/L, Free Androgen Index > 2.9) 
o Polycystic ovaries  
 
Table 1 
Phenotypes of PCOS according to the Rotterdam 2003 criteria 
 
X, Features included in phenotypes