<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02992093</url>
  </required_header>
  <id_info>
    <org_study_id>Dunjingjing</org_study_id>
    <nct_id>NCT02992093</nct_id>
  </id_info>
  <brief_title>A Metabolomic Study of Polycystic Ovary Syndrome With Insulin Resistance and Its Relationship With TCM Syndrome Types</brief_title>
  <official_title>Fujian Maternity and Child Health Hospital</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Fujian Maternity and Child Health Hospital</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Fujian Maternity and Child Health Hospital</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The type-2 diabetes mellitus（T2DM）, metabolic syndrome, cardiovascular disease complications&#xD;
      induced by polycystic ovary syndrome(PCOS) with insulin resistance(IR）, which become serious&#xD;
      threat to public health. In this observational study, obese patients with PCOS,nonobese&#xD;
      patients with PCOS, PCOS patients with impaired glucose tolerance（IGT）, PCOS patients with&#xD;
      type-2 diabetes mellitus（T2DM）, and healthy volunteers would enrolled into this study,&#xD;
      through the Liquid Chromatography-Mass Spectrometry coupled to Mass Spectrometry（&#xD;
      LC-MS/MS）and Rapid Resolution Liquid Chromatography（RRLC） and Quadrupole Linear&#xD;
      Trap（QTRAP）Mass Spectrometry coupled to Mass Spectrometry （MS/MS）analysis of serum samples&#xD;
      collected from PCOS patients and healthy volunteers to screen the biomarker of diagnosis for&#xD;
      PCOS with insulin resistance, to explore the correlation between traditional chinese medicine&#xD;
      （TCM） syndrome（phlegm, kidney yin deficiency, kidney yang deficiency, qi stagnation and blood&#xD;
      stasis，dampness-heat of liver channel）and metabolites of PCOS.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      1. The selection of research subjects: All the subjects collect from Fujian Maternity and&#xD;
           Child Health Hospital.&#xD;
&#xD;
        2. The participants will be divided into five groups：obese with PCOS，nonobese with&#xD;
           PCOS，PCOS with IGT，PCOS with T2DM，healthy volunteers.the syndrome type of PCOS will be&#xD;
           divided into five types: phlegm, kidney yin deficiency, kidney yang deficiency, liver qi&#xD;
           stagnation and blood stasis syndrome, dampness-heat of liver channel.&#xD;
&#xD;
        3. Ethical requirements and subjects' informed consent Before clinical trials begin, the&#xD;
           program needs to be approved by the ethics committee to approve and sign the&#xD;
           approval.The subjects need fully aware of the clinical trial and are given sufficient&#xD;
           time to consider whether they are willing to participate in the trial, and to sign the&#xD;
           informed consent form.&#xD;
&#xD;
        4. Indicator test (the cost of all health volunteers are paid by the research) (1)Physical&#xD;
           examination: blood pressure, height, body weight,waist circumference,hip&#xD;
           circumference，body mass index(BMI),waist-hip ratio（WHR）.&#xD;
&#xD;
      (2)Endocrine hormones: collect serum from all the subjects，use the enzyme linked&#xD;
      immunosorbent assay (ELISA) method to detect the level of serum follicle-stimulating&#xD;
      hormone（FSH）,luteinizing hormone（LH）,prolactin（PRL）,estradiol（E2）,testosterone（T）. Blood&#xD;
      lipid: glycerin three vinegar (TG), cholesterol (CHOL) detect by enzymatic method, low&#xD;
      density lipoprotein (LDL-C), high density lipoprotein (HDL-C) detect by the turbidity method.&#xD;
      Glucose tolerance and insulin release test after glucose loading: all subjects were fasting&#xD;
      for 8 to 10 h, check the fasting blood glucose(FBG)and fasting insulin （FINS）.The oral&#xD;
      glucose tolerance test（OGTT）and insulin release test were performed in the next morning.&#xD;
&#xD;
      5.Study on the characteristics of metabolism&#xD;
&#xD;
      （1）Through the sample pretreatment method, analyzes the optimization of the condition of mass&#xD;
      spectrometry, according to the requirements of the metabolism to establish the blood sample&#xD;
      LC-MS/MS metabolism analysis method.（2）Carry out the analysis of metabolism and data&#xD;
      collection.（3）Model building and data analysis（4）Use RRLC and QTRAP type MS/MS with positive&#xD;
      and negative ion detection mode with the combination of hyphenated techniques, combined with&#xD;
      the method of data statistics,to establish multiple reaction monitoring（MRM） detection, to&#xD;
      verify the precision and sensitivity of the method.&#xD;
&#xD;
      6.Statistical methods: All data use statistical product and service&#xD;
      solutions18.0（SPSS18.0）software package for statistical analysis. According to the character&#xD;
      of clinical trial data (measurement, classification and grade data), select the appropriate&#xD;
      statistical analysis method.receiver operating characteristic curve（ROC） analysis of the&#xD;
      potential metabolites selected from the targeting metabolic biomarker.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date>December 2016</start_date>
  <completion_date type="Anticipated">August 2020</completion_date>
  <primary_completion_date type="Anticipated">May 2020</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>metabolites</measure>
    <time_frame>six months</time_frame>
    <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</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>BMI</measure>
    <time_frame>day 1</time_frame>
    <description>weight（kg）/ the square of height(m2)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>WHR</measure>
    <time_frame>day 1</time_frame>
  </secondary_outcome>
  <secondary_outcome>
    <measure>FSH</measure>
    <time_frame>day 2 to 5 in menstrual period</time_frame>
    <description>use the ELISA method to detect the levels of serum FSH</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>LH</measure>
    <time_frame>day 2 to 5 in menstrual period</time_frame>
    <description>use the ELISA method to detect the levels of serum LH</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>PRL</measure>
    <time_frame>day 2 to 5 in menstrual period</time_frame>
    <description>use the ELISA method to detect the levels of serum PRL</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>T</measure>
    <time_frame>day 2 to 5 in menstrual period</time_frame>
    <description>use the ELISA method to detect the levels of serum T</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>E2</measure>
    <time_frame>day 2 to 5 in menstrual period</time_frame>
    <description>use the ELISA method to detect the levels of serum E2</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>TG</measure>
    <time_frame>day 1</time_frame>
    <description>use the enzymatic method to detect the levels of serum TG</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>CHOL</measure>
    <time_frame>day 1</time_frame>
    <description>use the enzymatic method to detect the levels of serum CHOL</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>LDL-C</measure>
    <time_frame>day 1</time_frame>
    <description>use turbidity method to detect the levels of serum LDL-C</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>HDL-C</measure>
    <time_frame>day 1</time_frame>
    <description>use turbidity method to detect the levels of serum HDL-C</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>FBG</measure>
    <time_frame>day 1</time_frame>
    <description>use glucose oxidase method to detect the levels of serum FBG</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>OGTT</measure>
    <time_frame>day 1</time_frame>
    <description>The levels of blood glucose about 1, 2, 3 hours after glucose loading</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>FINS</measure>
    <time_frame>day 1</time_frame>
    <description>use radioimmunoassay to detect the levels of serum FINS</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>insulin release test</measure>
    <time_frame>day 1</time_frame>
    <description>The levels of Insulin about 1, 2, 3 hours after glucose loading</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>HOMA index</measure>
    <time_frame>day 1</time_frame>
  </secondary_outcome>
  <number_of_groups>5</number_of_groups>
  <enrollment type="Anticipated">300</enrollment>
  <condition>PCOS</condition>
  <arm_group>
    <arm_group_label>obese with PCOS</arm_group_label>
    <description>all the indicators</description>
  </arm_group>
  <arm_group>
    <arm_group_label>nonobese with PCOS</arm_group_label>
    <description>all the indicators</description>
  </arm_group>
  <arm_group>
    <arm_group_label>PCOS with IGT</arm_group_label>
    <description>all the indicators</description>
  </arm_group>
  <arm_group>
    <arm_group_label>PCOS with T2DM</arm_group_label>
    <description>all the indicators</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Healthy volunteers</arm_group_label>
    <description>all the indicators</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>all the indicators</intervention_name>
    <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</description>
    <arm_group_label>Healthy volunteers</arm_group_label>
    <arm_group_label>PCOS with IGT</arm_group_label>
    <arm_group_label>PCOS with T2DM</arm_group_label>
    <arm_group_label>nonobese with PCOS</arm_group_label>
    <arm_group_label>obese with PCOS</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        The selection of research subjects: PCOS non obese patients, PCOS obese patients,PCOS with&#xD;
        IGT patients,PCOS with T2DM patients,and body mass index matched healthy volunteers collect&#xD;
        from Fujian Maternity and Child Health Hosptial&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. The diagnosis of polycystic ovary syndrome (PCOS) according to the Rotterdam consensus&#xD;
             criteria recommended by European Society of Human Reproduction and Embryology and&#xD;
             American Society for Reproductive Medicine in 2003（2 out of 3)：Oligo-and/or&#xD;
             anovulation；Clinical and/or biochemical signs of hyperandrogenism；Polycystic ovaries.&#xD;
&#xD;
          2. Diagnostic criteria for insulin resistance: use the HOMA model to evaluate insulin&#xD;
             resistance. The HOMA index of insulin resistance (HOMA-IR) = (fasting blood glucose&#xD;
             (mmol/L)× fasting insulin (mIU/L) /22.5.&#xD;
&#xD;
          3. voluntary subjects&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. the exclusion of other causes of Kaohsiung hormones, such as congenital adrenal&#xD;
             hyperplasia, Cushing syndrome, androgen secreting tumors, and other diseases caused by&#xD;
             ovulation disorders, such as hyperprolactinemia, premature ovarian failure, pituitary&#xD;
             or hypothalamus closed by etc；&#xD;
&#xD;
          2. exclusion of organic disease or other endocrine diseases；&#xD;
&#xD;
          3. with liver and kidney, cerebral blood vessels, cardiovascular and hematopoietic&#xD;
             disorders, such as primary disease, mental patients；&#xD;
&#xD;
          4. patients who had been treated with steroids in nearly three months , such as the birth&#xD;
             control pill, and corticosteroids.&#xD;
      </textblock>
    </criteria>
    <gender>Female</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>40 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Jinbang Xu</last_name>
    <role>Principal Investigator</role>
    <affiliation>Fujian Maternity and Child Health Hosptial</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Jinbang Xu</last_name>
    <phone>13559958096</phone>
    <email>13559958096@126.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Jingjing Dun</last_name>
    <phone>18520124299</phone>
    <email>409381572@qq.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Fujian Maternity and Child Health Hosptial</name>
      <address>
        <city>Fuzhou</city>
        <state>Fujian</state>
        <zip>350000</zip>
        <country>China</country>
      </address>
    </facility>
    <contact>
      <last_name>Jinbang Xu</last_name>
      <phone>13559958096</phone>
      <email>13559958096@126.com</email>
    </contact>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <link>
    <url>http://dx.doi.org/10.1016/j.cca.2015.06.008</url>
    <description>Detection of urine metabolites in polycystic ovary syndrome by UPLC triple-TOF-MS</description>
  </link>
  <link>
    <url>http://dx.doi.org/10.1016/j.steroids.2011.12.002</url>
    <description>Metabonomic analysis and biomarker screening of serum for polycystic ovary syndrome patients with phlegm-dampness syndrome</description>
  </link>
  <results_reference>
    <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.</citation>
    <PMID>27026772</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>27007571</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>22096112</PMID>
  </results_reference>
  <results_reference>
    <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. Erratum In: Fertil Steril. 2014 Nov;102(5):1499.</citation>
    <PMID>25064406</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>21470992</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>23198915</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>12695777</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>18950759</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>22428626</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>22809877</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>22427353</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>24428203</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>21247558</PMID>
  </results_reference>
  <results_reference>
    <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.</citation>
    <PMID>22385297</PMID>
  </results_reference>
  <verification_date>December 2016</verification_date>
  <study_first_submitted>December 1, 2016</study_first_submitted>
  <study_first_submitted_qc>December 11, 2016</study_first_submitted_qc>
  <study_first_posted type="Estimate">December 14, 2016</study_first_posted>
  <last_update_submitted>December 14, 2016</last_update_submitted>
  <last_update_submitted_qc>December 14, 2016</last_update_submitted_qc>
  <last_update_posted type="Estimate">December 15, 2016</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Polycystic ovary syndrome</keyword>
  <keyword>Metabonomics</keyword>
  <keyword>Traditional Chinese medicine syndromes</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Polycystic Ovary Syndrome</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02992093
org study id: Dunjingjing
nct id: NCT02992093
lead sponsor: 
has dmc: Yes
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.
1. The selection of research subjects: All the subjects collect from Fujian Maternity and
           Child Health Hospital.

        2. 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.

        3. 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.

        4. 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）.

      (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.

      5.Study on the characteristics of metabolism

      （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.

      6.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.
time perspective: Prospective
measure: metabolites
time frame: 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
measure: BMI
time frame: day 1
description: weight（kg）/ the square of height(m2)
measure: WHR
time frame: day 1
measure: FSH
time frame: day 2 to 5 in menstrual period
description: use the ELISA method to detect the levels of serum FSH
measure: LH
time frame: day 2 to 5 in menstrual period
description: use the ELISA method to detect the levels of serum LH
measure: PRL
time frame: day 2 to 5 in menstrual period
description: use the ELISA method to detect the levels of serum PRL
measure: T
time frame: day 2 to 5 in menstrual period
description: use the ELISA method to detect the levels of serum T
measure: E2
time frame: day 2 to 5 in menstrual period
description: use the ELISA method to detect the levels of serum E2
measure: TG
time frame: day 1
description: use the enzymatic method to detect the levels of serum TG
measure: CHOL
time frame: day 1
description: use the enzymatic method to detect the levels of serum CHOL
measure: LDL-C
time frame: day 1
description: use turbidity method to detect the levels of serum LDL-C
measure: HDL-C
time frame: day 1
description: use turbidity method to detect the levels of serum HDL-C
measure: FBG
time frame: day 1
description: use glucose oxidase method to detect the levels of serum FBG
measure: OGTT
time frame: day 1
description: The levels of blood glucose about 1, 2, 3 hours after glucose loading
measure: FINS
time frame: day 1
description: use radioimmunoassay to detect the levels of serum FINS
measure: insulin release test
time frame: day 1
description: The levels of Insulin about 1, 2, 3 hours after glucose loading
measure: HOMA index
time frame: day 1
arm group label: obese with PCOS
description: all the indicators
arm group label: nonobese with PCOS
description: all the indicators
arm group label: PCOS with IGT
description: all the indicators
arm group label: PCOS with T2DM
description: all the indicators
arm group label: Healthy volunteers
description: all the indicators
intervention type: Other
intervention name: all the indicators
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
arm group label: Healthy volunteers
arm group label: PCOS with IGT
arm group label: PCOS with T2DM
arm group label: nonobese with PCOS
arm group label: obese with PCOS
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: Female
minimum age: 18 Years
maximum age: 40 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Jinbang Xu
role: Principal Investigator
affiliation: Fujian Maternity and Child Health Hosptial
last name: Jinbang Xu
phone: 13559958096
email: 13559958096@126.com
last name: Jingjing Dun
phone: 18520124299
email: 409381572@qq.com
facility: 
contact: 
country: China
url: http://dx.doi.org/10.1016/j.cca.2015.06.008
description: 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
description: Metabonomic analysis and biomarker screening of serum for polycystic ovary syndrome patients with phlegm-dampness syndrome
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: 27026772
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: 27007571
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: 22096112
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. Erratum In: Fertil Steril. 2014 Nov;102(5):1499.
PMID: 25064406
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: 21470992
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: 23198915
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: 12695777
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: 18950759
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: 22428626
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: 22809877
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: 22427353
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: 24428203
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: 21247558
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.
PMID: 22385297
responsible party type: Sponsor
mesh term: Polycystic Ovary Syndrome
sharing ipd: No