DAISy-PCOS Phenome Study - Dissecting Androgen Excess and Metabolic Dysfunction in Polycystic Ovary Syndrome

NCT03911297 | Recruiting DMC

• 2 other identifiers: 19HH5264WT209492/Z/17/Z
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

Polycystic ovary syndrome (PCOS) affects 10% of all women and usually presents with irregular menstrual periods and difficulties conceiving. However, PCOS is also a lifelong metabolic disorder and affected women have an increased risk of type 2 diabetes, high blood pressure, and heart disease. Increased blood levels of male hormones, also termed androgens, are found in most PCOS patients. Androgen excess appears to impair the ability of the body to respond to the sugar-regulating hormone insulin (=insulin resistance). The investigator has found that fat tissue of PCOS patients overproduces androgens and that this can result in a build-up of toxic fat, which increases insulin resistance and could cause liver damage. In a large cohort of women registered in a GP database, the study team have found that androgen excess increases the risk of fatty liver disease. The aim is to identify those women with PCOS who are at the highest risk of developing metabolic disease, which would allow for early detection and potentially prevention of type 2 diabetes, high blood pressure, fatty liver and cardiovascular disease. The investigator will assess clinical presentation, androgen production and metabolic function in women with PCOS to use similarities and differences in these parameters for the identification of subsets (=clusters) of women who are at the highest risk of metabolic disease. The investigator will do this by using a standardised set of questions to scope PCOS-related signs and symptoms and the patient's medical history and measure body composition and blood pressure. This standardised recording of a patient's clinical presentation (=clinical phenotype) is called Phenome analysis. The investigator will collect blood and urine samples for the systematic measurement of steroid hormones including a very detailed androgen profile (=steroid metabolome analysis) and of thousands of substances produced by human metabolism (=global metabolome analysis). Phenome and metabolome data will then undergo integrated computational analysis for the detection of clusters predictive of metabolic risk.

Conditions

Polycystic Ovary Syndrome

Keywords

polycystic ovary syndrome; androgens; steroids; metabolic risk; prediction; stratified medicine

Outcome Measures

Primary Outcomes (1)

• Metabolic risk

  Metabolic-risk prediction model would be made from a machine learning algorithm where the study team would be able to enter phenome and metabolome data of patient with a new diagnosis of PCOS. With this model, the study team would be able to stratify the women with PCOS into their risk of metabolic disease hence personalise the management of the condition

  5 years

Secondary Outcomes (2)

• Dissect the severity and pattern of androgen excess in development of metabolic disease

  5 years

• Eligibility for other PCOS-related studies

  3 years

Interventions

Women with polycystic ovary syndrome OTHER

Prospective cohort study in women with polycystic ovary syndrome to identify the risk of developing metabolic disease

Eligibility Criteria

• Age: 18 Years - 70 Years
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Women with a new diagnosis of Polycystic ovary syndrome aged 18-70 who are treatment naive

You may qualify if:

• Women with a suspected diagnosis of polycystic ovary syndrome
• Age range 18-70 years
• Ability to provide informed consent

You may not qualify if:

• Pregnancy or breastfeeding at the time of planned recruitment
• History of significant renal (eGFR\<30) or hepatic impairment (AST or ALT \>two-fold above ULN; pre-existing bilirubinaemia \>1.2 ULN)
• Any other significant disease or disorder that, in the opinion of the Investigator, may either put the participant at risk because of participation in the study, or may influence the result of the study, or the participant's ability to participate in the study.
• Participants who have participated in another research study involving an investigational medicinal product in the 12 weeks preceding the planned recruitment
• Glucocorticoid use via any route within the last six months
• Current intake of drugs known to impact upon steroid or metabolic function or intake of such drugs during the six months preceding the planned recruitment
• Use of oral or transdermal hormonal contraception in the three months preceding the planned recruitment
• Use of contraceptive implants in the twelve months preceding the planned recruitment

Sponsors & Collaborators

• Imperial College London: lead
• University Hospital Birmingham NHS Foundation Trust: collaborator
• Birmingham Women's and Children's NHS Foundation Trust: collaborator
• University Hospital of Wales: collaborator
• University Hospitals Coventry and Warwickshire NHS Trust: collaborator
• Royal Infirmary of Edinburgh: collaborator
• Royal College of Surgeons, Ireland: collaborator
• Imperial College Healthcare NHS Trust: collaborator
• Hull University Teaching Hospitals NHS Trust: collaborator
• King's College Hospital NHS Trust: collaborator

Study Sites (1)

Wellcome Trust Clinical Research Facility

Birmingham, West Midlands, B15 2TT, United Kingdom

RECRUITING

Biospecimen

Retention: SAMPLES WITH DNA

DNA will be stored in a Human tissue act approved site and ethics for a potential future analysis

MeSH Terms

Conditions

Polycystic Ovary Syndrome

Condition Hierarchy (Ancestors)

Ovarian Cysts; Cysts; Neoplasms; Ovarian Diseases; Adnexal Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases; Gonadal Disorders; Endocrine System Diseases

Study Officials

• Wiebke Arlt

  University of Birmingham

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Eka Melson

CONTACT

+447852146611; e.melson@bham.ac.uk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 8, 2019
• First Posted: April 11, 2019
• Study Start: August 14, 2019
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 1, 2027
• Last Updated: December 5, 2024

Record last verified: 2024-12

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)