- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03843736
The Role of Dysbiosis of Gut Microbiota in the Pathogenesis of PCOS.
The Role of Dysbiosis of Gut Microbiota in the Pathogenesis of Polycystic Ovary Syndrome.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
- Data quality assurance: ① all inspections and measurements will be performed by either the hospital or the sequencing company personnel according to standard operating procedures (SOPs), except for saliva and stool samples, which will be self-collected by patients. For sample collection, we will provide text descriptions of the SOPs as well as video instruction. Designated staff will be assigned for support and can be contacted if participants have any queries concerning sample collection; ② a case report form (CRF) will be prepared according to the current SOPs, and detailed instructions will be provided to ensure consistency in data collection. At the same time, each CRF will be properly stored at least 5 years for verification and backtracking; ③ all experimental data will be logged into the database to ensure information accuracy based on the existing data; ④ we will keep the contact information of each participant, remind them of precautions during participation, and conduct regular follow-ups.
- Sample size determination: The number of participants is based on comparable sample sizes in the literature. In this trial, there will be 50 healthy individuals (control group) and 150 PCOS (polycystic ovary syndrome) patients. The 150 PCOS patients will be randomly assigned to three intervention groups. This sample size accounts for a plausible insufficiency of data caused by patient dropouts and withdrawals before the study is completed. The participation cycle is of approximately four months, followed by a 2-year follow-up.
Metagenomic sequencing technology Metagenomic sequencing is the main technique used in this study. Metagenomics, also known as economics, was first proposed by Handelman and studies the molecular composition of microbial populations, their interactions, and gene functions.
In medicine, metagenomics compares the structural and functional changes of human microbial communities under normal and disease states. It can analyze the diversity and the functional differences of microbial communities from healthy individuals and from patients with diseases, thus determine how diseases relate to changes in the microbial communities and in their respective metabolic networks. Therefore, metagenomics provides theoretical evidence for disease prevention, detection, and treatment. At present, the internationally renowned Human Microbiome Project (HMP, http://www.hmpdacc.org/) and the Metagenomics of the Human Intestinal Tract (MetaHIT) are typical applications of metagenomics in medicine.
[Metagenomic species, genes, and functional annotation]
① Data quality control: the sequenced raw data will contain a certain amount of low-quality data, so quality control must be performed. Only high-quality data can correctly reflect the actual occurrence of microorganisms in the sample.
② Metagenome assembly: based on Clean Data, individual samples will be assembled separately at first, then reads that do not participate in the assembling above will be combined and mixed for assembly. This will increase the sequencing depth of low-abundance species in each sample and provide more sequencing information for each species.
③ Gene prediction: MetaGeneMark will be used for gene prediction based on single samples and mixed-assembled scaftigs. The redundancy of all predicted genes will be reduced to obtain a Uniq gene set. Then, the Clean Data of each sample will be compared to the gene set and the abundance of the gene set will be determined for each sample.
④ Species annotation: Clean Data will be used for quality control. It will be compared with an annotated according to reference genome databases of bacteria, archaea, viruses, and fungi from NCBI. A species abundance table will be obtained for each sample at different classification levels.
⑤ Functional annotation: functional annotation and abundance statistics will be based on the Uniq gene set and the KEGG database.
Study Type
Enrollment (Anticipated)
Phase
- Phase 3
Contacts and Locations
Study Contact
- Name: Rong Chen, Ph. D.
- Phone Number: (86-10)-69155012
- Email: chenrongpumch@163.com
Study Contact Backup
- Name: Xu Zhang, Master
- Email: zhangxu_5050@163.com
Study Locations
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Beijing, China
- Recruiting
- Peking Union Medical College Hospital
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Contact:
- Xu Zhang, Master
- Email: zhangxu_5050@163.com
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Contact:
- Rong Chen, Ph. D
- Phone Number: (86-10)-69155012
- Email: chenrongpumch@163.com
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
Conforms to the 2003 Rotterdam classic PCOS diagnostic criteria.
- sparse ovulation or anovulation;
- clinical manifestations of high androgen and/or hyperandrogenism;
ovarian polycystic changes: ultrasound suggests one or both sides of the ovary with a diameter of 2-9 mm follicles ≥ 12, and / or ovarian volume ≥ 10 ml;
2 out of 3 items, and exclude other high androgen causes, such as congenital adrenal hyperplasia, Cushing's syndrome, and androgen-secreting tumors;
- Age: 18-45 years old.
Exclusion Criteria:
- pregnancy;
- menopause;
- adrenal abnormalities;
- thyroid dysfunction;
- taking antibiotics for the past 3 months;
- is taking oral contraceptive treatment;
- basic diseases of the gastrointestinal tract (ulcerative colitis, Crohn's disease, inflammatory bowel disease, etc.);
- history of smoking;
- BMI<18kg/m2.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
No Intervention: Health control group
Participants are healthy women and there are no interventions.
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Experimental: Lifestyle interventions group
Participants are PCOS patients and only will be given lifestyle interventions.
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Patients have to take a probiotic powder (product name: Tangwen Tai, lactobacillus plantarum LP45 + Lactobacillus acidophilus La28 + Bifidobacterium lactobacillus BAL531) twice a day for three months.
Other Names:
The patient needs to take drospirenone ethinyl estradiol tablets (trade name: Yousi Yue) 1 tablet daily for 3 months.
Other Names:
|
Experimental: Probiotic Agent group
Participants are PCOS patients and will be given lifestyle interventions + Probiotic Agent interventions.
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The patient needs to take drospirenone ethinyl estradiol tablets (trade name: Yousi Yue) 1 tablet daily for 3 months.
Other Names:
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Experimental: Oral contraceptive group
Participants are PCOS patients and will be given lifestyle intervention + Oral contraceptive interventions.
|
Patients have to take a probiotic powder (product name: Tangwen Tai, lactobacillus plantarum LP45 + Lactobacillus acidophilus La28 + Bifidobacterium lactobacillus BAL531) twice a day for three months.
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Diversity analysis of genes and species
Time Frame: Through study completion, an average of 12 weeks
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Based on the gene and species composition of each sample, the Chao1 and Shannon indexes, as well as the observed OTUs (operational taxonomic units), will be calculated in order to identify the differences in gene and species diversity for each group.
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Through study completion, an average of 12 weeks
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Analysis of differences in intestinal microbiota between PCOS patients and the control group
Time Frame: Through study completion, an average of 12 weeks
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The Spearman correlation coefficient between genes will be calculated, and genes with strong correlation will be grouped into one cluster, as a CAG.
The abundance of CAGs in each sample will be determined Furthermore, the significantly enriched species in the control and PCOS groups will be enumerated for network display.
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Through study completion, an average of 12 weeks
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Analysis of functional differences in the intestinal microbiota of PCOS patients in comparison to the control group
Time Frame: Through study completion, an average of 12 weeks
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The LEfSe discriminant analysis will be used to screen for significant differences between groups.
The dimensionality reduction will be implemented by LDA, and the impact of function difference will be evaluated to obtain the LDA score and identify significantly different functions between groups.
|
Through study completion, an average of 12 weeks
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Correlation analysis between biomarkers and clinical indicators
Time Frame: Through study completion, an average of 12 weeks
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For the obtained species, genes, or functions with significant difference, the correlation between them and clinical indicators will be calculated, and key biomarkers with significant and strong correlation will be identified.
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Through study completion, an average of 12 weeks
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Insulin resistance
Time Frame: Through study completion, an average of 12 weeks
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Use glucose tolerance and insulin test (75gOGTT+insulin) to assess whether the patient has insulin resistance, as well as the level of insulin resistance.
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Through study completion, an average of 12 weeks
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Androgen level
Time Frame: Through study completion, an average of 12 weeks
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Six-sex-hormone tests, one of the clinical examination items, will be performed to measure androgen levels in the subjects.
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Through study completion, an average of 12 weeks
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Collaborators and Investigators
Collaborators
Investigators
- Study Director: Rong Chen, Ph. D., Beijing Union Medical College Hospital
Publications and helpful links
General Publications
- Alvarez-Blasco F, Luque-Ramirez M, Escobar-Morreale HF. Diet composition and physical activity in overweight and obese premenopausal women with or without polycystic ovary syndrome. Gynecol Endocrinol. 2011 Dec;27(12):978-81. doi: 10.3109/09513590.2011.579658. Epub 2011 May 24.
- Tremellen K, Pearce K. Dysbiosis of Gut Microbiota (DOGMA)--a novel theory for the development of Polycystic Ovarian Syndrome. Med Hypotheses. 2012 Jul;79(1):104-12. doi: 10.1016/j.mehy.2012.04.016. Epub 2012 Apr 27.
- Liu R, Zhang C, Shi Y, Zhang F, Li L, Wang X, Ling Y, Fu H, Dong W, Shen J, Reeves A, Greenberg AS, Zhao L, Peng Y, Ding X. Dysbiosis of Gut Microbiota Associated with Clinical Parameters in Polycystic Ovary Syndrome. Front Microbiol. 2017 Feb 28;8:324. doi: 10.3389/fmicb.2017.00324. eCollection 2017.
- Guo Y, Qi Y, Yang X, Zhao L, Wen S, Liu Y, Tang L. Association between Polycystic Ovary Syndrome and Gut Microbiota. PLoS One. 2016 Apr 19;11(4):e0153196. doi: 10.1371/journal.pone.0153196. eCollection 2016.
- Torres PJ, Siakowska M, Banaszewska B, Pawelczyk L, Duleba AJ, Kelley ST, Thackray VG. Gut Microbial Diversity in Women With Polycystic Ovary Syndrome Correlates With Hyperandrogenism. J Clin Endocrinol Metab. 2018 Apr 1;103(4):1502-1511. doi: 10.1210/jc.2017-02153.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Pathologic Processes
- Neoplasms
- Endocrine System Diseases
- Disease
- Ovarian Cysts
- Cysts
- Ovarian Diseases
- Adnexal Diseases
- Gonadal Disorders
- Polycystic Ovary Syndrome
- Syndrome
- Dysbiosis
- Physiological Effects of Drugs
- Hormones
- Hormones, Hormone Substitutes, and Hormone Antagonists
- Estrogens
- Natriuretic Agents
- Diuretics
- Hormone Antagonists
- Contraceptive Agents, Hormonal
- Reproductive Control Agents
- Contraceptive Agents, Female
- Contraceptives, Oral, Hormonal
- Mineralocorticoid Receptor Antagonists
- Diuretics, Potassium Sparing
- Contraceptive Agents
- Ethinyl Estradiol
- Contraceptives, Oral
- Drospirenone
- Drospirenone and ethinyl estradiol combination
Other Study ID Numbers
- JS-1691
- 81871141 (Other Grant/Funding Number: National Natural Science Foundation of China)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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