PCOS
Conditions
Keywords
Polycystic ovary syndrome, Metabonomics, Traditional Chinese medicine syndromes
Brief summary
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.
Detailed description
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.
Interventions
OTHERall the indicators
BMI、WHR、FSH、LH、PRL、T、E2、TG、CHOL、LDL-C、HDL-C、FBG、OGTT、FINS、insulin release test、HOMA index、identification of metabolites
Sponsors
Fujian Maternity and Child Health Hospital
Study design
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to 40 Years
Healthy volunteers
Yes
Inclusion criteria
1. 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. 2. 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. 3. voluntary subjects
Exclusion criteria
1. 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； 2. exclusion of organic disease or other endocrine diseases； 3. with liver and kidney, cerebral blood vessels, cardiovascular and hematopoietic disorders, such as primary disease, mental patients； 4. patients who had been treated with steroids in nearly three months , such as the birth control pill, and corticosteroids.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| metabolites | six months | 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 |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| WHR | day 1 | — |
| FSH | day 2 to 5 in menstrual period | use the ELISA method to detect the levels of serum FSH |
| LH | day 2 to 5 in menstrual period | use the ELISA method to detect the levels of serum LH |
| PRL | day 2 to 5 in menstrual period | use the ELISA method to detect the levels of serum PRL |
| T | day 2 to 5 in menstrual period | use the ELISA method to detect the levels of serum T |
| E2 | day 2 to 5 in menstrual period | use the ELISA method to detect the levels of serum E2 |
| TG | day 1 | use the enzymatic method to detect the levels of serum TG |
| BMI | day 1 | weight（kg）/ the square of height(m2) |
| LDL-C | day 1 | use turbidity method to detect the levels of serum LDL-C |
| HDL-C | day 1 | use turbidity method to detect the levels of serum HDL-C |
| FBG | day 1 | use glucose oxidase method to detect the levels of serum FBG |
| OGTT | day 1 | The levels of blood glucose about 1, 2, 3 hours after glucose loading |
| FINS | day 1 | use radioimmunoassay to detect the levels of serum FINS |
| insulin release test | day 1 | The levels of Insulin about 1, 2, 3 hours after glucose loading |
| HOMA index | day 1 | — |
| CHOL | day 1 | use the enzymatic method to detect the levels of serum CHOL |
Countries
China
Contacts
Primary ContactJinbang Xu
Backup ContactJingjing Dun
Outcome results
None listed