Ignite Creation Date:
2025-12-25 @ 1:12 AM
Ignite Modification Date:
2026-02-25 @ 9:40 PM
Study NCT ID:
NCT02992093
Status:
UNKNOWN
Last Update Posted:
2016-12-15
First Post:
2016-12-01
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
A Metabolomic Study of Polycystic Ovary Syndrome With Insulin Resistance and Its Relationship With TCM Syndrome Types
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D011085', 'term': 'Polycystic Ovary Syndrome'}], 'ancestors': [{'id': 'D010048', 'term': 'Ovarian Cysts'}, {'id': 'D003560', 'term': 'Cysts'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D010049', 'term': 'Ovarian Diseases'}, {'id': 'D000291', 'term': 'Adnexal Diseases'}, {'id': 'D005831', 'term': 'Genital Diseases, Female'}, {'id': 'D052776', 'term': 'Female Urogenital Diseases'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D006058', 'term': 'Gonadal Disorders'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 300}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2016-12'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2016-12', 'completionDateStruct': {'date': '2020-08', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2016-12-14', 'studyFirstSubmitDate': '2016-12-01', 'studyFirstSubmitQcDate': '2016-12-11', 'lastUpdatePostDateStruct': {'date': '2016-12-15', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2016-12-14', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2020-05', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'metabolites', 'timeFrame': 'six months', 'description': 'Collect serum from all the subjects , through the sample pretreatment method,the metabolic features are first scanned by using Liquid Chromatography-Mass Spectrometry coupled w ith Mass Spectrometry,extracted ion-pairs were fetched to type RRLC and QTRAP(MS/MS) for multiple reaction monitoring（MRM） detection,Peak detection and alignment from the raw date use Analyst Quantitation software ,use SIMCA-P11.0 to conduct principle component analysis(PCA) and partial least squares-discriminant analysis(PLS-DA) model,use SPSS18.0 software package for statistical analysis'}], 'secondaryOutcomes': [{'measure': 'BMI', 'timeFrame': 'day 1', 'description': 'weight（kg）/ the square of height(m2)'}, {'measure': 'WHR', 'timeFrame': 'day 1'}, {'measure': 'FSH', 'timeFrame': 'day 2 to 5 in menstrual period', 'description': 'use the ELISA method to detect the levels of serum FSH'}, {'measure': 'LH', 'timeFrame': 'day 2 to 5 in menstrual period', 'description': 'use the ELISA method to detect the levels of serum LH'}, {'measure': 'PRL', 'timeFrame': 'day 2 to 5 in menstrual period', 'description': 'use the ELISA method to detect the levels of serum PRL'}, {'measure': 'T', 'timeFrame': 'day 2 to 5 in menstrual period', 'description': 'use the ELISA method to detect the levels of serum T'}, {'measure': 'E2', 'timeFrame': 'day 2 to 5 in menstrual period', 'description': 'use the ELISA method to detect the levels of serum E2'}, {'measure': 'TG', 'timeFrame': 'day 1', 'description': 'use the enzymatic method to detect the levels of serum TG'}, {'measure': 'CHOL', 'timeFrame': 'day 1', 'description': 'use the enzymatic method to detect the levels of serum CHOL'}, {'measure': 'LDL-C', 'timeFrame': 'day 1', 'description': 'use turbidity method to detect the levels of serum LDL-C'}, {'measure': 'HDL-C', 'timeFrame': 'day 1', 'description': 'use turbidity method to detect the levels of serum HDL-C'}, {'measure': 'FBG', 'timeFrame': 'day 1', 'description': 'use glucose oxidase method to detect the levels of serum FBG'}, {'measure': 'OGTT', 'timeFrame': 'day 1', 'description': 'The levels of blood glucose about 1, 2, 3 hours after glucose loading'}, {'measure': 'FINS', 'timeFrame': 'day 1', 'description': 'use radioimmunoassay to detect the levels of serum FINS'}, {'measure': 'insulin release test', 'timeFrame': 'day 1', 'description': 'The levels of Insulin about 1, 2, 3 hours after glucose loading'}, {'measure': 'HOMA index', 'timeFrame': 'day 1'}]}, 'oversightModule': {'oversightHasDmc': True}, 'conditionsModule': {'keywords': ['Polycystic ovary syndrome', 'Metabonomics', 'Traditional Chinese medicine syndromes'], 'conditions': ['PCOS']}, 'referencesModule': {'references': [{'pmid': '27026772', 'type': 'RESULT', 'citation': 'Suvarna Y, Maity N, Kalra P, Shivamurthy MC. Comparison of efficacy of metformin and oral contraceptive combination of ethinyl estradiol and drospirenone in polycystic ovary syndrome. J Turk Ger Gynecol Assoc. 2016 Jan 12;17(1):6-9. doi: 10.5152/jtgga.2016.16129. eCollection 2016.'}, {'pmid': '27007571', 'type': 'RESULT', 'citation': 'Victor VM, Rovira-Llopis S, Banuls C, Diaz-Morales N, Martinez de Maranon A, Rios-Navarro C, Alvarez A, Gomez M, Rocha M, Hernandez-Mijares A. Insulin Resistance in PCOS Patients Enhances Oxidative Stress and Leukocyte Adhesion: Role of Myeloperoxidase. PLoS One. 2016 Mar 23;11(3):e0151960. doi: 10.1371/journal.pone.0151960. eCollection 2016.'}, {'pmid': '22096112', 'type': 'RESULT', 'citation': 'Sathyapalan T, Atkin SL. Recent advances in cardiovascular aspects of polycystic ovary syndrome. Eur J Endocrinol. 2012 Apr;166(4):575-83. doi: 10.1530/EJE-11-0755. Epub 2011 Nov 17.'}, {'pmid': '25064406', 'type': 'RESULT', 'citation': 'Chen L, Xu WM, Zhang D. Association of abdominal obesity, insulin resistance, and oxidative stress in adipose tissue in women with polycystic ovary syndrome. Fertil Steril. 2014 Oct;102(4):1167-1174.e4. doi: 10.1016/j.fertnstert.2014.06.027. Epub 2014 Jul 23.'}, {'pmid': '21470992', 'type': 'RESULT', 'citation': 'Wehr E, Gruber HJ, Giuliani A, Moller R, Pieber TR, Obermayer-Pietsch B. The lipid accumulation product is associated with impaired glucose tolerance in PCOS women. J Clin Endocrinol Metab. 2011 Jun;96(6):E986-90. doi: 10.1210/jc.2011-0031. Epub 2011 Apr 6.'}, {'pmid': '23198915', 'type': 'RESULT', 'citation': 'Zhao Y, Fu L, Li R, Wang LN, Yang Y, Liu NN, Zhang CM, Wang Y, Liu P, Tu BB, Zhang X, Qiao J. Metabolic profiles characterizing different phenotypes of polycystic ovary syndrome: plasma metabolomics analysis. BMC Med. 2012 Nov 30;10:153. doi: 10.1186/1741-7015-10-153.'}, {'pmid': '12695777', 'type': 'RESULT', 'citation': 'Collins FS, Green ED, Guttmacher AE, Guyer MS; US National Human Genome Research Institute. A vision for the future of genomics research. Nature. 2003 Apr 24;422(6934):835-47. doi: 10.1038/nature01626. Epub 2003 Apr 14. No abstract available.'}, {'pmid': '18950759', 'type': 'RESULT', 'citation': 'Azziz R, Carmina E, Dewailly D, Diamanti-Kandarakis E, Escobar-Morreale HF, Futterweit W, Janssen OE, Legro RS, Norman RJ, Taylor AE, Witchel SF; Task Force on the Phenotype of the Polycystic Ovary Syndrome of The Androgen Excess and PCOS Society. The Androgen Excess and PCOS Society criteria for the polycystic ovary syndrome: the complete task force report. Fertil Steril. 2009 Feb;91(2):456-88. doi: 10.1016/j.fertnstert.2008.06.035. Epub 2008 Oct 23.'}, {'pmid': '22428626', 'type': 'RESULT', 'citation': 'Sun L, Hu W, Liu Q, Hao Q, Sun B, Zhang Q, Mao S, Qiao J, Yan X. Metabonomics reveals plasma metabolic changes and inflammatory marker in polycystic ovary syndrome patients. J Proteome Res. 2012 May 4;11(5):2937-46. doi: 10.1021/pr3000317. Epub 2012 Apr 13.'}, {'pmid': '22809877', 'type': 'RESULT', 'citation': 'Atiomo W, Daykin CA. Metabolomic biomarkers in women with polycystic ovary syndrome: a pilot study. Mol Hum Reprod. 2012 Nov;18(11):546-53. doi: 10.1093/molehr/gas029. Epub 2012 Jul 18.'}, {'pmid': '22427353', 'type': 'RESULT', 'citation': 'Escobar-Morreale HF, Samino S, Insenser M, Vinaixa M, Luque-Ramirez M, Lasuncion MA, Correig X. Metabolic heterogeneity in polycystic ovary syndrome is determined by obesity: plasma metabolomic approach using GC-MS. Clin Chem. 2012 Jun;58(6):999-1009. doi: 10.1373/clinchem.2011.176396. Epub 2012 Mar 16.'}, {'pmid': '24428203', 'type': 'RESULT', 'citation': 'Zhao X, Xu F, Qi B, Hao S, Li Y, Li Y, Zou L, Lu C, Xu G, Hou L. Serum metabolomics study of polycystic ovary syndrome based on liquid chromatography-mass spectrometry. J Proteome Res. 2014 Feb 7;13(2):1101-11. doi: 10.1021/pr401130w. Epub 2014 Jan 24.'}, {'pmid': '21247558', 'type': 'RESULT', 'citation': 'Wild RA, Rizzo M, Clifton S, Carmina E. Lipid levels in polycystic ovary syndrome: systematic review and meta-analysis. Fertil Steril. 2011 Mar 1;95(3):1073-9.e1-11. doi: 10.1016/j.fertnstert.2010.12.027. Epub 2011 Jan 17.'}, {'pmid': '22385297', 'type': 'RESULT', 'citation': 'Gaster M, Nehlin JO, Minet AD. Impaired TCA cycle flux in mitochondria in skeletal muscle from type 2 diabetic subjects: marker or maker of the diabetic phenotype? Arch Physiol Biochem. 2012 Jul;118(3):156-89. doi: 10.3109/13813455.2012.656653. Epub 2012 Mar 5.'}], 'seeAlsoLinks': [{'url': 'http://dx.doi.org/10.1016/j.cca.2015.06.008', 'label': 'Detection of urine metabolites in polycystic ovary syndrome by UPLC triple-TOF-MS'}, {'url': 'http://dx.doi.org/10.1016/j.steroids.2011.12.002', 'label': 'Metabonomic analysis and biomarker screening of serum for polycystic ovary syndrome patients with phlegm-dampness syndrome'}]}, 'descriptionModule': {'briefSummary': 'The type-2 diabetes mellitus（T2DM）, metabolic syndrome, cardiovascular disease complications induced by polycystic ovary syndrome(PCOS) with insulin resistance(IR）, which become serious threat to public health. In this observational study, obese patients with PCOS,nonobese patients with PCOS, PCOS patients with impaired glucose tolerance（IGT）, PCOS patients with type-2 diabetes mellitus（T2DM）, and healthy volunteers would enrolled into this study, through the Liquid Chromatography-Mass Spectrometry coupled to Mass Spectrometry（ LC-MS/MS）and Rapid Resolution Liquid Chromatography（RRLC） and Quadrupole Linear Trap（QTRAP）Mass Spectrometry coupled to Mass Spectrometry （MS/MS）analysis of serum samples collected from PCOS patients and healthy volunteers to screen the biomarker of diagnosis for PCOS with insulin resistance, to explore the correlation between traditional chinese medicine （TCM） syndrome（phlegm, kidney yin deficiency, kidney yang deficiency, qi stagnation and blood stasis，dampness-heat of liver channel）and metabolites of PCOS.', 'detailedDescription': "1. The selection of research subjects: All the subjects collect from Fujian Maternity and Child Health Hospital.\n2. The participants will be divided into five groups：obese with PCOS，nonobese with PCOS，PCOS with IGT，PCOS with T2DM，healthy volunteers.the syndrome type of PCOS will be divided into five types: phlegm, kidney yin deficiency, kidney yang deficiency, liver qi stagnation and blood stasis syndrome, dampness-heat of liver channel.\n3. Ethical requirements and subjects' informed consent Before clinical trials begin, the program needs to be approved by the ethics committee to approve and sign the approval.The subjects need fully aware of the clinical trial and are given sufficient time to consider whether they are willing to participate in the trial, and to sign the informed consent form.\n4. Indicator test (the cost of all health volunteers are paid by the research) (1)Physical examination: blood pressure, height, body weight,waist circumference,hip circumference，body mass index(BMI),waist-hip ratio（WHR）.\n\n(2)Endocrine hormones: collect serum from all the subjects，use the enzyme linked immunosorbent assay (ELISA) method to detect the level of serum follicle-stimulating hormone（FSH）,luteinizing hormone（LH）,prolactin（PRL）,estradiol（E2）,testosterone（T）. Blood lipid: glycerin three vinegar (TG), cholesterol (CHOL) detect by enzymatic method, low density lipoprotein (LDL-C), high density lipoprotein (HDL-C) detect by the turbidity method. Glucose tolerance and insulin release test after glucose loading: all subjects were fasting for 8 to 10 h, check the fasting blood glucose(FBG)and fasting insulin （FINS）.The oral glucose tolerance test（OGTT）and insulin release test were performed in the next morning.\n\n5.Study on the characteristics of metabolism\n\n（1）Through the sample pretreatment method, analyzes the optimization of the condition of mass spectrometry, according to the requirements of the metabolism to establish the blood sample LC-MS/MS metabolism analysis method.（2）Carry out the analysis of metabolism and data collection.（3）Model building and data analysis（4）Use RRLC and QTRAP type MS/MS with positive and negative ion detection mode with the combination of hyphenated techniques, combined with the method of data statistics,to establish multiple reaction monitoring（MRM） detection, to verify the precision and sensitivity of the method.\n\n6.Statistical methods: All data use statistical product and service solutions18.0（SPSS18.0）software package for statistical analysis. According to the character of clinical trial data (measurement, classification and grade data), select the appropriate statistical analysis method.receiver operating characteristic curve（ROC） analysis of the potential metabolites selected from the targeting metabolic biomarker."}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT'], 'maximumAge': '40 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'The selection of research subjects: PCOS non obese patients, PCOS obese patients,PCOS with IGT patients,PCOS with T2DM patients,and body mass index matched healthy volunteers collect from Fujian Maternity and Child Health Hosptial', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. The diagnosis of polycystic ovary syndrome (PCOS) according to the Rotterdam consensus criteria recommended by European Society of Human Reproduction and Embryology and American Society for Reproductive Medicine in 2003（2 out of 3)：Oligo-and/or anovulation；Clinical and/or biochemical signs of hyperandrogenism；Polycystic ovaries.\n2. Diagnostic criteria for insulin resistance: use the HOMA model to evaluate insulin resistance. The HOMA index of insulin resistance (HOMA-IR) = (fasting blood glucose (mmol/L)× fasting insulin (mIU/L) /22.5.\n3. voluntary subjects\n\nExclusion Criteria:\n\n1. the exclusion of other causes of Kaohsiung hormones, such as congenital adrenal hyperplasia, Cushing syndrome, androgen secreting tumors, and other diseases caused by ovulation disorders, such as hyperprolactinemia, premature ovarian failure, pituitary or hypothalamus closed by etc；\n2. exclusion of organic disease or other endocrine diseases；\n3. with liver and kidney, cerebral blood vessels, cardiovascular and hematopoietic disorders, such as primary disease, mental patients；\n4. patients who had been treated with steroids in nearly three months , such as the birth control pill, and corticosteroids.'}, 'identificationModule': {'nctId': 'NCT02992093', 'briefTitle': 'A Metabolomic Study of Polycystic Ovary Syndrome With Insulin Resistance and Its Relationship With TCM Syndrome Types', 'organization': {'class': 'OTHER', 'fullName': 'Fujian Maternity and Child Health Hospital'}, 'officialTitle': 'Fujian Maternity and Child Health Hospital', 'orgStudyIdInfo': {'id': 'Dunjingjing'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'obese with PCOS', 'description': 'all the indicators', 'interventionNames': ['Other: all the indicators']}, {'label': 'nonobese with PCOS', 'description': 'all the indicators', 'interventionNames': ['Other: all the indicators']}, {'label': 'PCOS with IGT', 'description': 'all the indicators', 'interventionNames': ['Other: all the indicators']}, {'label': 'PCOS with T2DM', 'description': 'all the indicators', 'interventionNames': ['Other: all the indicators']}, {'label': 'Healthy volunteers', 'description': 'all the indicators', 'interventionNames': ['Other: all the indicators']}], 'interventions': [{'name': 'all the indicators', 'type': 'OTHER', 'description': 'BMI、WHR、FSH、LH、PRL、T、E2、TG、CHOL、LDL-C、HDL-C、FBG、OGTT、FINS、insulin release test、HOMA index、identification of metabolites', 'armGroupLabels': ['Healthy volunteers', 'PCOS with IGT', 'PCOS with T2DM', 'nonobese with PCOS', 'obese with PCOS']}]}, 'contactsLocationsModule': {'locations': [{'zip': '350000', 'city': 'Fuzhou', 'state': 'Fujian', 'country': 'China', 'contacts': [{'name': 'Jinbang Xu', 'role': 'CONTACT', 'email': '13559958096@126.com', 'phone': '13559958096'}], 'facility': 'Fujian Maternity and Child Health Hosptial', 'geoPoint': {'lat': 26.06139, 'lon': 119.30611}}], 'centralContacts': [{'name': 'Jinbang Xu', 'role': 'CONTACT', 'email': '13559958096@126.com', 'phone': '13559958096'}, {'name': 'Jingjing Dun', 'role': 'CONTACT', 'email': '409381572@qq.com', 'phone': '18520124299'}], 'overallOfficials': [{'name': 'Jinbang Xu', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Fujian Maternity and Child Health Hosptial'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Fujian Maternity and Child Health Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}