Assessment of Metabolic Changes in Response to Glcuose Intake in Women With Polyendocrine Metabolic Ovarian Syndrome (PMOS)
METFLEX
METabolic FLEXibility in PMOS
1 other identifier
interventional
40
1 country
1
Brief Summary
Polyendocrine metabolic ovarian syndrome (PMOS), previously known as polycystic ovary syndrome (PCOS), is a common endocrine and metabolic condition affecting women of reproductive age. It is associated with hormonal imbalances, irregular menstrual cycles, elevated androgen levels, and metabolic disturbances such as insulin resistance. These metabolic changes can increase the risk of type 2 diabetes and cardiovascular disease. Insulin resistance means that the body's cells respond less effectively to insulin, a hormone that regulates blood glucose. This leads to compensatory increases in insulin levels, which can further disrupt hormonal balance and contribute to the clinical features of PMOS. This study aims to investigate how the bodies of women with PMOS respond dynamically to glucose intake compared with women without PMOS. A standard clinical test, the oral glucose tolerance test (oGTT), will be used. Participants consume a glucose solution, and blood samples are collected before and two hours afterward. This procedure is routinely used in clinical practice. Women with PMOS will be compared with age- and body mass index (BMI)-matched control participants without PMOS. Blood and urine samples will be analyzed using advanced multi-omics technologies to measure proteins, metabolites, extracellular vesicles, and immune-related signals. The main objective is to understand how metabolic, hormonal, and immune pathways respond over time to a glucose challenge and whether these responses differ in PMOS. Special attention is given to inter-organ communication and systemic metabolic regulation. The study includes two visits. The first visit involves health assessments, questionnaires, and body composition measurements. The second visit includes the glucose tolerance test and blood sampling. In total, approximately 100 mL of blood will be collected across both visits. Participation is voluntary, and participants may withdraw at any time without affecting their medical care. The procedures involve minimal risk and consist of standard clinical methods. The results of this study may improve understanding of PMOS and contribute to better diagnostic and therapeutic strategies in the future.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for not_applicable
Started Aug 2026
Typical duration for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
June 17, 2026
CompletedFirst Posted
Study publicly available on registry
July 7, 2026
CompletedStudy Start
First participant enrolled
August 1, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 30, 2029
ExpectedStudy Completion
Last participant's last visit for all outcomes
July 30, 2029
July 7, 2026
July 1, 2026
3 years
June 17, 2026
July 3, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Change in Normalized Relative Plasma Metabolite Abundance From Baseline to 2 Hours Post-Glucose Ingestion
Assessment of dynamic changes in circulating metabolites in response to a standardized oral glucose tolerance test (oGTT). Metabolomic profiling includes targeted and untargeted analyses of plasma metabolites involved in glucose metabolism, lipid metabolism, amino acid turnover, and energy homeostasis. Longitudinal changes between fasting state and post-glucose challenge will be compared between PMOS participants and age- and BMI-matched controls. The metabolomic response is used as a central readout of systemic metabolic flexibility.
Baseline (fasting, Visit 2) and 2 hours post-glucose ingestion (Visit 2).
Change in Normalized Relative Plasma Protein Abundance From Baseline to 2 Hours Post-Glucose Ingestion
Quantification of dynamic changes in circulating plasma proteins in response to oGTT using nanoparticle-enhanced high-resolution proteomics. The analysis focuses on proteins involved in insulin signaling, inflammatory pathways, lipid metabolism, endocrine regulation, and inter-organ communication. Temporal protein abundance changes between fasting and post-glucose states will be assessed to characterize systemic proteomic adaptations and differences in metabolic flexibility between PMOS and controls.
Baseline (fasting, Visit 2) and 2 hours post-glucose ingestion (Visit 2).
Secondary Outcomes (11)
Change in oGTT-Derived Glucose and Insulin Response Indices From Baseline to 2 Hours Post-Glucose Ingestion
Baseline and 2 hours post-glucose ingestion (Visit 2).
Change in Concentration of Plasma Extracellular Vesicles From Baseline to 2 Hours Post-Glucose Ingestion
Baseline and 2 hours post-glucose ingestion (Visit 2).
Change in Median Diameter of Plasma Extracellular Vesicles From Baseline to 2 Hours Post-Glucose Ingestion
Baseline and 2 hours post-glucose ingestion (Visit 2).
Change in Normalized Relative Abundance of Extracellular Vesicle-Associated Proteins From Baseline to 2 Hours Post-Glucose Ingestion
Baseline and 2 hours post-glucose ingestion (Visit 2).
Change in Normalized Relative Abundance of Extracellular Vesicle-Associated Metabolites From Baseline to 2 Hours Post-Glucose Ingestion
aseline and 2 hours post-glucose ingestion (Visit 2).
- +6 more secondary outcomes
Study Arms (2)
PMOS group
EXPERIMENTALWoman diagnosed with PMOS, BMI 18.5-39.9 kg/m2
Control group
EXPERIMENTALControl participants will be selected to match PMOS group participants with respect to age (±3 years) and BMI (≤ ±2 kg/m²).
Interventions
After an overnight fasting period (≥8 hours), participants ingest a 75 g oral glucose solution. Venous blood samples are collected at predefined time points (fasting and typically 2 hours post-ingestion) to measure plasma glucose and insulin levels. The test evaluates whole-body glucose tolerance and insulin response under controlled metabolic conditions and is routinely used in clinical and research settings.
Eligibility Criteria
You may qualify if:
- Age: 18-35 years
- Body weight (BMI): between BMI 18.5-39.9 kg/m2
- Ability to consent and to provide written informed consent
- CG: History of regular MCs (21 to 35 days) 3 months prior to study enrollment
- Oligo- or anovulation
- Clinical and/or biochemical signs of hyperandrogenism
- Polycystic ovaries on ultrasound (≥12 follicles per ovary measuring 2-9 mm in diameter and/or ovarian volume \>10 mL)
You may not qualify if:
- Use of systemic hormonal contraceptives within the last 3 months prior to study enrollment. Use of levonorgestrel-releasing intrauterine devices is permitted; all other hormonal contraceptive methods are excluded.
- CG: A clinically diagnosed or history of a menstrual disorder (e.g., polycystic ovarian syndrome (PCOS), premenstrual dysphoric disorder (PMDD) or amenorrhea)
- A clinically diagnosed mental disorder (e.g. major depression, anxiety disorder)
- history of epileptic seizure
- history of or current manic or psychotic episode
- existing/current eating disorders (bulimia nervosa, anorexia nervosa) within the past 5 years
- inability to communicate adequately in speech
- inability to follow instructions
- regular use of medication other than thyroxine
- alcohol consumption as equivalent doses of more than 12 g of pure alcohol per day
- vegan diet
- daily nicotine consumption
- currently or history of (regular) consumption of illegal drugs within the last year
- pregnancy or breastfeeding
- known diseases of the cardiovascular system
- +6 more criteria
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University of Zurichlead
- ETH Zurichcollaborator
- University Hospital, Bonncollaborator
Study Sites (1)
University Hospital Zurich
Zurich, Canton of Zurich, 8091, Switzerland
Related Publications (15)
Rotterdam ESHRE/ASRM-Sponsored PCOS consensus workshop group. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod. 2004 Jan;19(1):41-7. doi: 10.1093/humrep/deh098.
PMID: 14688154BACKGROUNDFerdosi S, Tangeysh B, Brown TR, Everley PA, Figa M, McLean M, Elgierari EM, Zhao X, Garcia VJ, Wang T, Chang MEK, Riedesel K, Chu J, Mahoney M, Xia H, O'Brien ES, Stolarczyk C, Harris D, Platt TL, Ma P, Goldberg M, Langer R, Flory MR, Benz R, Tao W, Cuevas JC, Batzoglou S, Blume JE, Siddiqui A, Hornburg D, Farokhzad OC. Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions. Proc Natl Acad Sci U S A. 2022 Mar 15;119(11):e2106053119. doi: 10.1073/pnas.2106053119. Epub 2022 Mar 11.
PMID: 35275789BACKGROUNDMansournia MA, Jewell NP, Greenland S. Case-control matching: effects, misconceptions, and recommendations. Eur J Epidemiol. 2018 Jan;33(1):5-14. doi: 10.1007/s10654-017-0325-0. Epub 2017 Nov 3.
PMID: 29101596BACKGROUNDTkach M, Thery C. Communication by Extracellular Vesicles: Where We Are and Where We Need to Go. Cell. 2016 Mar 10;164(6):1226-1232. doi: 10.1016/j.cell.2016.01.043.
PMID: 26967288BACKGROUNDChen R, Mias GI, Li-Pook-Than J, Jiang L, Lam HY, Chen R, Miriami E, Karczewski KJ, Hariharan M, Dewey FE, Cheng Y, Clark MJ, Im H, Habegger L, Balasubramanian S, O'Huallachain M, Dudley JT, Hillenmeyer S, Haraksingh R, Sharon D, Euskirchen G, Lacroute P, Bettinger K, Boyle AP, Kasowski M, Grubert F, Seki S, Garcia M, Whirl-Carrillo M, Gallardo M, Blasco MA, Greenberg PL, Snyder P, Klein TE, Altman RB, Butte AJ, Ashley EA, Gerstein M, Nadeau KC, Tang H, Snyder M. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell. 2012 Mar 16;148(6):1293-307. doi: 10.1016/j.cell.2012.02.009.
PMID: 22424236BACKGROUNDOzer OF, Ibrahimoglu AZ, Gul AZ, Demirel M, Ates S, Taha HS, Ibrahimoglu M, Selek S. Mass spectrometry-based untargeted metabolomics study of polycystic ovary syndrome. J Ovarian Res. 2025 Nov 12;18(1):255. doi: 10.1186/s13048-025-01842-9.
PMID: 41225634BACKGROUNDStener-Victorin E, Eriksson G, Mohan Shrestha M, Rodriguez Paris V, Lu H, Banks J, Samad M, Perian C, Jude B, Engman V, Boi R, Nilsson E, Ling C, Nystrom J, Wernstedt Asterholm I, Turner N, Lanner J, Benrick A. Proteomic analysis shows decreased type I fibers and ectopic fat accumulation in skeletal muscle from women with PCOS. Elife. 2024 Jan 5;12:RP87592. doi: 10.7554/eLife.87592.
PMID: 38180081BACKGROUNDRajska A, Buszewska-Forajta M, Rachon D, Markuszewski MJ. Metabolomic Insight into Polycystic Ovary Syndrome-An Overview. Int J Mol Sci. 2020 Jul 9;21(14):4853. doi: 10.3390/ijms21144853.
PMID: 32659951BACKGROUNDDunaif A, Segal KR, Futterweit W, Dobrjansky A. Profound peripheral insulin resistance, independent of obesity, in polycystic ovary syndrome. Diabetes. 1989 Sep;38(9):1165-74. doi: 10.2337/diab.38.9.1165.
PMID: 2670645BACKGROUNDPetersen MC, Shulman GI. Mechanisms of Insulin Action and Insulin Resistance. Physiol Rev. 2018 Oct 1;98(4):2133-2223. doi: 10.1152/physrev.00063.2017.
PMID: 30067154BACKGROUNDHenquin JC. Regulation of insulin secretion: a matter of phase control and amplitude modulation. Diabetologia. 2009 May;52(5):739-51. doi: 10.1007/s00125-009-1314-y. Epub 2009 Mar 14.
PMID: 19288076BACKGROUNDTeede HJ, Khomami MB, Morman R, Laven JSE, Joham AE, Costello MF, Patil M, Rees DA, Berry L, Cree MG, Zhao H, Norman RJ, Dokras A, Piltonen T; Global Name Change Consortium. Polyendocrine metabolic ovarian syndrome, the new name for polycystic ovary syndrome: a multistep global consensus process. Lancet. 2026 Jun 6;407(10545):2329-2339. doi: 10.1016/S0140-6736(26)00717-8. Epub 2026 May 12.
PMID: 42119588BACKGROUNDGast KB, Tjeerdema N, Stijnen T, Smit JW, Dekkers OM. Insulin resistance and risk of incident cardiovascular events in adults without diabetes: meta-analysis. PLoS One. 2012;7(12):e52036. doi: 10.1371/journal.pone.0052036. Epub 2012 Dec 28.
PMID: 23300589BACKGROUNDStener-Victorin E, Teede H, Norman RJ, Legro R, Goodarzi MO, Dokras A, Laven J, Hoeger K, Piltonen TT. Polycystic ovary syndrome. Nat Rev Dis Primers. 2024 Apr 18;10(1):27. doi: 10.1038/s41572-024-00511-3.
PMID: 38637590BACKGROUNDMarch WA, Moore VM, Willson KJ, Phillips DI, Norman RJ, Davies MJ. The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Hum Reprod. 2010 Feb;25(2):544-51. doi: 10.1093/humrep/dep399. Epub 2009 Nov 12.
PMID: 19910321BACKGROUND
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- NONE
- Purpose
- BASIC SCIENCE
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
June 17, 2026
First Posted
July 7, 2026
Study Start
August 1, 2026
Primary Completion (Estimated)
July 30, 2029
Study Completion (Estimated)
July 30, 2029
Last Updated
July 7, 2026
Record last verified: 2026-07
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP
- Time Frame
- 12 months after publication until 10 years after publication
- Access Criteria
- Upon reasonable request and approva
De-identified individual participant data (IPD) underlying the results reported in publications may be shared with qualified researchers for scientific research purposes. Shared data may include demographic, physiological, questionnaire, laboratory, and multi-omics datasets collected as part of the study. The study protocol, statistical analysis plan, informed consent form, and data dictionary may also be made available. Data will be available beginning 12 months after publication of the primary study results and for up to 10 years thereafter. Access will be granted upon reasonable request, following review and approval of a scientifically sound research proposal by the study investigators and sponsoring institution. Any data sharing will be subject to approval by the responsible ethics committee, where required, and compliance with applicable data protection regulations. Data sharing will further require execution of an appropriate data sharing or transfer agreement to ensure partici