Polycystic ovarian syndrome diagnostic marker

Abstract

The invention discloses a diagnostic marker for polycystic ovarian syndrome, and in particular, the diagnostic marker is 16 (17)-EpDPE. The diagnostic marker provided by the invention can be used for diagnosing the polycystic ovarian syndrome, and has high diagnostic efficiency and wide clinical application prospect.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine and relates to a diagnostic marker for polycystic ovary syndrome. Background Art

[0002] Polycystic ovary syndrome (PCOS) is the most common endocrine and metabolic disease in women of reproductive age. Clinically, it is mainly manifested as irregular menstruation, hirsutism, acne, obesity and reproductive disorders. The endocrine characteristics of PCOS patients often show hyperandrogenemia, insulin resistance, high luteinizing hormone, lipid metabolism disorders, etc. Due to long-term endocrine and metabolic abnormalities, PCOS patients have a significantly increased risk of developing diseases such as type 2 diabetes, cardiovascular diseases, and endometrial cancer. Therefore, clarifying the pathogenesis of endocrine and metabolic disorders in PCOS patients is particularly important for reducing the long-term prevalence. In addition, the incidence of anovulatory infertility in PCOS patients due to ovulation disorders is significantly higher than that in non-PCOS women, which makes in vitro fertilization and embryo transfer (IVF-ET) the main means of assisted reproduction for PCOS patients with fertility requirements. However, previous studies have shown that among patients undergoing assisted reproduction, PCOS patients often obtain more eggs, but the maturation rate of their eggs and the quality of embryos are often poor, resulting in unsatisfactory assisted reproduction outcomes, which has attracted more and more attention from researchers to the reasons for the decline in the utilization rate of oocytes in PCOS patients. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to screen and identify reliable biomarkers related to PCOS based on the follicular fluid metabolomics study of PCOS patients, and to provide a new and effective method for the research field of PCOS diagnosis.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] The present invention provides, in a first aspect, the use of a reagent for detecting the level of a metabolic marker in a sample of a subject in the preparation of a product for diagnosing polycystic ovary syndrome.

[0006] Further, the metabolic marker includes 16(17)-EpDPE.

[0007] As used herein, the terms "comprise", "include", "contain" can be used interchangeably and include not only closed definitions, but also semi-closed and open definitions. In other words, the terms include "consisting of" and "consisting essentially of".

[0008] As a preferred embodiment, the reagent includes a reagent for detecting the level of the metabolite marker in a sample by any one or more of nuclear magnetic resonance method, chromatography, spectroscopy, mass spectrometry, and chemical analysis method.

[0009] As a more preferred embodiment, the chromatography includes, but is not limited to: gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis (CE), high performance liquid chromatography (HPLC), ultra-high performance liquid chromatography (UHPLC).

[0010] As a more preferred embodiment, the spectroscopy includes, but is not limited to: ultraviolet-visible spectroscopy (UV-Vis), infrared spectroscopy (IR), near-infrared spectroscopy (NIR), nuclear magnetic resonance spectroscopy.

[0011] As a more preferred embodiment, the mass spectrometry includes, but is not limited to: electrospray ionization mass spectrometry (ESI), quadrupole mass spectrometer, ion trap mass spectrometer, matrix-assisted laser desorption / ionization time-of-flight mass spectrometer (MALDI-TOFMS), MALDI-TOF-TOF mass spectrometry, MALDI quadrupole-time-of-flight (Q-TOF) mass spectrometry, electrospray ionization (ESI)-TOF mass spectrometry, ESI-Q-TOF, ESI-TOF-TOF, ESI-ion trap mass spectrometry, ESI triple quadrupole mass spectrometry, ESI Fourier transform mass spectrometry (FTMS), MALDI-FTMS, MALDI-ion trap-TOF, and ESI-ion trap TOF. At its most basic level, mass spectrometry involves ionizing molecules and subsequently measuring the mass of the resulting ions. Since molecules are ionized in a known manner, the molecular weight of the molecule can be precisely determined from the mass of the ions.

[0012] As a more preferred embodiment, the chemical analysis method includes electrochemistry analysis method and radiochemistry analysis method.

[0013] As a preferred embodiment, the product is a kit.

[0014] In a specific embodiment of the present invention, the sample is preferably a follicular fluid sample from a subject, and the subject is preferably a human.

[0015] The second aspect of the present invention provides a product for diagnosing polycystic ovary syndrome, the product includes a reagent for detecting the level of a metabolite marker in a subject sample, and the metabolite marker includes 16(17)-EpDPE.

[0016] As a preferred embodiment, the reagent includes a reagent for detecting the content of the metabolite marker in a sample by any one or more of nuclear magnetic resonance method, chromatography, spectroscopy, mass spectrometry, and chemical analysis method.

[0017] Further, the product is a kit.

[0018] Further, the kit further includes reagents for processing the sample.

[0019] The most reliable results are likely to be obtained when processing samples in a laboratory setting. For example, a sample can be obtained from a subject in a doctor's office and then sent to a hospital or commercial medical laboratory for further testing. However, in many cases, it may be desirable to provide immediate results in the clinician's office. In some cases, the need for a portable, pre-packaged, disposable test that can be used by the subject without assistance or guidance, etc. may be more important than high accuracy. In many cases, especially when there is physician follow-up, performing a preliminary test, even one with reduced sensitivity and / or specificity, may be sufficient. Thus, an assay provided in kit form may involve detecting and measuring a relatively small number of metabolites to reduce the complexity and cost of the assay.

[0020] Any form of sample assay capable of detecting sample metabolites as described herein can be used. Generally, the assay will quantify the metabolite in the sample to a certain extent, such as whether their concentration or amount is above or below a predetermined threshold. Such kits can take the form of test strips, dipsticks, cartridges, cassettes, chip- or bead-based arrays, multi-well plates, or a series of containers, etc. One or more reagents are provided to detect the presence and / or concentration and / or amount of the selected sample metabolite. The subject's sample can be directly dispensed into the assay or indirectly dispensed into the assay from a stored or previously obtained sample. The presence or absence of a metabolite above or below a predetermined threshold can be shown, for example, by color development, fluorescence, electrochemiluminescence, or other output (such as in an enzyme immunoassay (EIA), such as an enzyme-linked immunosorbent assay (ELISA)).

[0021] In one embodiment, the kit may comprise a solid substrate such as a chip, a slide, an array, etc., having reagents capable of detecting and / or quantifying one or more sample metabolites at predetermined positions immobilized on the substrate. As an illustrative example, a chip may be provided with reagents immobilized at discrete predetermined positions for detecting and quantifying the presence and / or concentration and / or amount of biomarkers in a sample. As described above, elevated levels of the biomarker are found in samples from subjects with PCOS. The chip may be configured such that a detectable output (e.g., a color change) is provided only when the concentration of one or more of these metabolites exceeds a threshold, which is selected to distinguish the concentration and / or amount of the biomarker indicative of a control subject from the concentration and / or amount of the biomarker indicative of a patient with or predisposed to the disease. Thus, the presence of a detectable output (such as a color change) immediately indicates that the sample contains a significantly elevated level of the biomarker, indicating that the subject has or is predisposed to PCOS.

[0022] In addition, the present invention also provides a polycystic ovary syndrome diagnosis device based on metabolomics data, and the polycystic ovary syndrome diagnosis device includes:

[0023] A data acquisition module that obtains the expression level of each metabolic biomarker corresponding to the subject to be diagnosed;

[0024] A data analysis module for determining whether the expression level of each metabolic biomarker corresponding to the subject to be diagnosed exceeds a preset normal value range;

[0025] A polycystic ovary syndrome diagnosis module for outputting a conclusion as to whether the subject to be diagnosed is a patient with polycystic ovary syndrome based on the determination result.

[0026] The term "area under the curve" or "AUC" refers to the area under the receiver operating characteristic (ROC) curve, both of which are well known in the art. AUC measurements are useful for comparing the accuracy of classifiers across the entire data range. A classifier with a higher AUC has a greater ability to correctly classify unknowns between two target groups (e.g., cancer tissue samples from patients with polycystic ovary syndrome and adjacent non-cancerous tissue samples from patients with polycystic ovary syndrome). The ROC curve is useful for depicting the performance of a particular feature (e.g., any biomarker described herein and / or any entry of additional biomedical information) when differentiating between two populations (e.g., individual patients with polycystic ovary syndrome and normal individuals). Typically, feature data is selected in ascending order across the entire population (e.g., cases and controls) based on the value of a single feature. Then, for each value of that feature, the true positive and false positive rates of the data are calculated. The true positive rate is determined by counting the number of cases with a value higher than that of the feature and dividing by the total number of cases. The false positive rate is determined by counting the number of controls with a value higher than that of the feature and dividing by the total number of controls. Although this definition refers to the situation where the feature is increased in cases compared to controls, this definition also applies to the situation where the feature is lower in cases compared to controls (in which case, samples with a value lower than that of the feature will be counted). ROC curves can be generated for individual features and can also be generated for other individual outputs. For example, combinations of two or more features can be mathematically combined (e.g., added, subtracted, multiplied, etc.) to provide a single sum value, and this single sum value can be plotted on the ROC curve. Additionally, any combination of multiple features whose combinations are derived from individual output values can be plotted on the ROC curve. These combinations of features can include assays. The ROC curve is a plot of the true positive rate (sensitivity) of the assay against the false positive rate (1 - specificity) of the assay.

[0027] Advantages and beneficial effects of the present invention over the prior art:

[0028] (1) Based on metabolomics analysis, the present invention has screened out the polycystic ovary syndrome metabolic biomarker 16(17)-EpDPE that can be used for the diagnosis of polycystic ovary syndrome. The present invention has for the first time discovered that the above-mentioned metabolic biomarker can be used for the effective diagnosis of polycystic ovary syndrome;

[0029] (2) Validation was respectively carried out in retrospective studies and prospective studies including the real samples collected by the present invention and found that when the above-mentioned metabolic biomarker provided by the present invention is used alone for the diagnosis of polycystic ovary syndrome, the AUC is above 0.7 in both cases, having high accuracy, sensitivity and specificity, and having broad clinical application value. Brief Description of the Drawings

[0030] Figure 1Show the statistical charts of Oxylipins with differences between the PCOS group and the control group in the retrospective study, *: P < 0.05; #: Adj-P < 0.05;

[0031] Figure 2 Show the OPLS-DA score plots of the PCOS group and the control group in the retrospective study. Among them, Figure A is the OPLS-DA score plot of Oxylipins in follicular fluid of PCOS patients and the control group, and Figure B is the permutation test plot of the OPLS-DA model;

[0032] Figure 3 Show the ROC curve plots of four up-regulated differential metabolites in the retrospective study;

[0033] Figure 4 Show the Oxylipins with differences between the PCOS group and the control group in the prospective study, AA: arachidonic acid; LA: linoleic acid; DGLA: dihomo-γ-linolenic acid; α-LA: α-linolenic acid; *: P < 0.05; #: Adj-P < 0.05;

[0034] Figure 5 Show the OPLS-DA score plots of the PCOS group and the control group in the prospective study. Figure A is the OPLS-DA score plot of Oxylipins metabolites in follicular fluid of PCOS patients and the control group. Figure B is the permutation test plot of the OPLS-DA model;

[0035] Figure 6 Show the ROC curve plots of differential metabolites in the prospective study. Among them, Figure A is the ROC curve plot of 5 up-regulated differential metabolites, and Figure B is the ROC curve plot of 6 down-regulated differential metabolites. Detailed implementation manners

[0036] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention. For the experimental methods without specific conditions noted in the embodiments, they are usually carried out under conventional conditions, such as the conditions described in Sambrook et al., Molecular Cloning: A Laboratory Manual (New York: Cold Spring Harbor Laboratory Press, 1989), or the conditions recommended by the manufacturer.

[0037] Example 1 Retrospective study

[0038] 1 Objects and Methods

[0039] 1.1 Research objects and inclusion criteria

[0040] 1.1.1 Research objects

[0041] In this study, 29 PCOS patients who underwent assisted reproductive treatment for the first time at the Reproductive Center of Tianjin Medical University General Hospital from September 2022 to December 2022 and 33 patients in the control group (non-PCOS) were included in the retrospective study group. Another 40 PCOS patients and 20 patients in the control group were recruited in the prospective study from January 2023 to December 2023. This study was approved by the Ethics Committee of Tianjin Medical University General Hospital (IRB2021-YX-223-01), and all patients signed informed consent forms before the study.

[0042] 1.1.2 Inclusion criteria

[0043] The included PCOS patients were diagnosed according to the Rotterdam criteria and needed to meet two of the following three conditions: (1) anovulation or oligoovulation; (2) hyperandrogenemia or clinical manifestations of hyperandrogenism; (3) polycystic ovary changes (≥12 follicles with a diameter of 2-9 mm in one ovary and / or ovarian volume by ultrasound >10 mL); among them, hyperandrogenemia was diagnosed according to the detection criteria of our hospital (>56.94 ng / dL), and other diseases causing hyperandrogenemia needed to be excluded. The control group recruited women of childbearing age who did not meet the Rotterdam PCOS diagnostic criteria. The above inclusion criteria were applied to both the retrospective study and the prospective study.

[0044] 1.1.3 Exclusion criteria

[0045] The exclusion criteria for both the retrospective study and the prospective study included: (1) severe intrauterine adhesions and uterine malformations; (2) endometriosis; (3) diminished ovarian reserve; (4) severe oligoasthenospermia in men; (5) repeated implantation failure; (6) patients with severe systemic diseases; (7) immune diseases; (8) Cushing's syndrome, hyperprolactinemia, and other endocrine tumor diseases.

[0046] 1.2 Controlled ovarian stimulation protocol

[0047] All patients in this study adopted individualized controlled ovarian stimulation protocols, including the long follicular phase protocol, short protocol, and antagonist protocol. When a follicle diameter was ≥18 mm or the diameters of 3 or more follicles were ≥17 mm, human chorionic gonadotropin (hCG) and / or gonadotropin-releasing hormone agonist (GnRH-α) were given for triggering. Oocyte retrieval was performed under transvaginal ultrasound guidance 36 - 38 h later. In vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) was used for fertilization according to the cause of infertility in patients. The fertilization status was evaluated 18 - 24 h after fertilization. The embryo grading was evaluated according to the Istanbul Consensus 66 - 72 h after fertilization. The blastocyst grading was performed according to the Gardner scoring criteria 5 - 7 days after fertilization. At the time of transplantation, the embryo with the highest score was preferentially transplanted.

[0048] 1.3 Follicular fluid collection

[0049] After aspirating the 1st - 2nd follicles with diameters of 17 - 20 mm using an oocyte retrieval needle, the oocytes were separated, and the remaining follicular fluid that was not significantly contaminated with blood was collected into a 50-ml sterile centrifuge tube. It was centrifuged at 2000 rpm for 10 min at room temperature, the supernatant was separated, transferred to a 2-ml sterile cryotube, and stored in liquid nitrogen at -196°C for subsequent LC-MS detection.

[0050] The follicular fluid used for the retrospective study was obtained by retrieving the follicular fluid samples frozen in liquid nitrogen at -196°C, and the collection method was the same as above.

[0051] 1.4 Liquid chromatography - mass spectrometry (LC-MS)

[0052] 1.4.1 Main experimental instruments and reagents

[0053] Experimental Instruments & Reagents Manufacturer Mass Spectrometer SCIEX QTRAP6500+ from SCIEX, USA Chromatograph ExionLC from SCIEX, USA Chromatographic Column Waters, USA Low Temperature Centrifuge Thermo, USA Methanol Thermo, USA Water Thermo, USA Formic Acid Thermo, USA Acetonitrile Thermo, USA Ammonium Bicarbonate Thermo, USA

[0054] 1.4.2 Extraction of metabolites

[0055] After the sample was slowly thawed at 4°C, 100 μL of follicular fluid was taken into an EP tube, 700 μL of 50 mM PBS was added, and the supernatant was obtained by centrifugation for later use. 700 μL of 10% methanol was added to the precipitate, and the supernatant was obtained by centrifugation for later use. Then 700 μL of methanol was added to the precipitate, and the supernatant was obtained by centrifugation for later use. A PEP desalting column was used, activated with 700 μL of methanol, centrifuged, and the filtrate was discarded. 700 μL of pure water was added for equilibration. Centrifuged, and the filtrate was discarded. The first 3 obtained supernatants were loaded in sequence, centrifuged, and the filtrate was discarded after each supernatant was loaded twice. 700 μL of 10% methanol was added to wash the sample precipitate, loaded onto the PEP desalting column, centrifuged, and the filtrate was discarded. 700 μL of methanol was added to elute the metabolites, and the filtrate was the sample collection solution. The collection solution was placed on a nitrogen blower to be freeze-dried. Then the sample was dissolved in a reconstitution solvent (water / acetonitrile / acetic acid (volume ratio 60:40:0.02)), vortexed and mixed evenly, centrifuged at 15000 rpm at 4°C for 10 min, the supernatant was collected, and injected into LC-MS for analysis. Equal volumes of samples were taken from each experimental sample and mixed evenly as quality control (QC) samples.

[0056] 1.4.3 Instrument Parameters and Mass Spectrometry Conditions

[0057] Determination was carried out using an Exion LC high-performance liquid chromatography system (SCIEX). The system was configured with a Waters C18 chromatographic column (10 cm × 2.1 mm). Mobile phases A and B were 0.1% formic acid and acetonitrile respectively. The column oven temperature was configured at 40°C. The flow rate was configured at 0.3 mL / min. The gradient elution was as follows: 0 - 0.5 min, 65% A, 35% B; 0.5 - 9.5 min, 65 - 5% A, 35 - 95% B; 9.5 - 10.5 min, 5% A, 95% B; 10.5 - 11 min, 5 - 65% A, 95 - 35% B; 11–14 min, 65% A, 35% B. The mass spectrometry conditions were as follows: Curtain Gas: 40; Collision Gas: Medium; IonSpray Voltage: -4500; Temperature: 500; Ion Source Gas 1: 55; Ion Source Gas2: 55.

[0058] 1.4.4 Qualitative and Quantitative Analysis of Metabolites

[0059] The characteristic ions of each substance were screened out by a triple quadrupole, and the signal intensity (CPS) of the characteristic ions was obtained in the detector. The sample off-line mass spectrometry file was opened with SCIEX OS V1.4 software for chromatographic peak integration and correction work. The peak area (Area) of each chromatographic peak represented the relative quantitative value of the corresponding substance, and finally all chromatographic peak area integration data were exported.

[0060] 2. Statistical methods

[0061] 2.1 Basic inspection analysis

[0062] SPSS26.0 software was used for data processing and analysis. PASS15.0 software was used to calculate the sample size of the prospective study. Since most of the oxylipins data were not normally distributed, the oxylipins data were analyzed after lg10 logarithmic transformation. Kolmogorov-Smirnov was used to test the normality of the data. The measurement data that met the normal distribution were expressed as mean ± standard deviation. The data were expressed as , and the independent sample t test was used for comparison between the two groups, and analysis of variance (ANOVA) was used for comparison between multiple groups; the measurement data that did not conform to the normal distribution were expressed as the median (25th percentile, 75th percentile) [M (Q1, Q3)], and the Mann-Whitney U test was used for comparison between the two groups, and the Kruskal-Wallis test was used for comparison between multiple groups; the count data were expressed as the constituent ratio or rate (%), and the chi-square test or Fisher's exact probability method was used for comparison between the groups. Binary logistic regression was used; P < 0.05 indicated statistical significance.

[0063] 2.2 Metabolomics analysis

[0064] SIMCA 14.1 software was used to perform principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) modeling and metabolomics analysis. The OPLS-DA model used 200 permutations to evaluate repeatability and overfitting risk. R2X (the explanation rate of the X model), R2Y (the explanation rate of the distinction between groups) and Q2 (the predictive ability of the model) were used to evaluate the fitting quality of the OPLS-DA model. R2X>0.5 indicated good model quality, and the closer the values of R2Y and Q2 were to 1, the better the model effect. The variable importance inprojection (VIP) value of each metabolite was obtained in the OPLS-DA analysis. In multivariate analysis, a value greater than 1 was considered to have a significant contribution to the model explanation. In the univariate analysis, fold change analysis (FC analysis) and t-test were used to screen the metabolites with significant differences between the groups. The screening criteria were VIP value > 1.0, FC value > 1.2 or < 0.833, and P < 0.05. Metabolites that met the screening criteria were defined as significantly different metabolites. Metaboanalyst 5.0 software was used to draw the OPLS-DA model diagram and correlation analysis diagram.

[0065] 3. Results

[0066] 3.1 Patient basic information

[0067] In this study, 29 PCOS patients receiving IVF / ICSI treatment were included for the first time, and 33 patients in the control group, with a total of 62 oocyte retrieval cycles. The baseline characteristics of the patients are shown in Table 1. Among the basic observation indexes of the two groups, the BMI of PCOS patients was significantly higher than that of the control group (P = 0.016), and the number of antral follicles, LH, LH / FSH, T, and AMH were significantly higher than those of the control group (P < 0.001, P = 0.007, P = 0.001, P = 0.0495, P < 0.0001). After adjusting for age and BMI, the differences were still significant. The TG level was significantly higher than that of the control group (P = 0.028), but the difference was not significant after adjusting for age and BMI. There were no significant differences in female age, basal FSH, total serum cholesterol, HDL, and LDL between the two groups (P > 0.05). The dosage of gonadotropin (Gn) for ovulation induction in the PCOS group was lower than that in the control group (P = 0.024), and it was still significant after adjusting for age and BMI. The E2 on the hCG day in the PCOS group was significantly higher than that in the control group (P = 0.047), and it was still significant after adjusting for age and BMI. There were no significant differences in the number of days of Gn use, LH and P on the hCG day between the two groups (P > 0.05). The number of retrieved oocytes, mature oocytes, 2PN embryos, and high-quality embryos on D3 in the PCOS group were significantly higher than those in the control group (P = 0.032, P = 0.047, P = 0.031, P = 0.037), and they were still significant after adjusting for age and BMI. There were no significant differences in the oocyte retrieval rate, MII oocyte rate, 2PN rate, D3 high-quality embryo rate, blastocyst formation rate, and high-quality blastocyst rate between the two groups (P > 0.05).

[0068] Table 1 Baseline characteristics of patients in the two groups receiving IVF / ICSI treatment

[0069]

[0070]

[0071] FBG: Fasting blood glucose; *: P < 0.05; Adj-P: Adjusted for age and BMI

[0072] 3.2 Comparison of Oxylipins levels in follicular fluid between the two groups of patients

[0073] A total of 16 Oxylipins were detected by LC-MS. The levels of AA and its COX pathway product 11-HETE in the PCOS group were significantly higher than those in the control group (P = 0.002, P = 0.017), and remained significant after adjusting for BMI and age. The CYP450 pathway product 8,9-diHETrE of AA was significantly higher than that in the control group (P = 0.027), but not significant after adjusting for BMI and age. There were no significant differences in the CYP450 pathway products 14,15-diHETrE of AA and the LOX pathway products (14,15-LTC4, LTE4) (P > 0.05).

[0074] There were no significant differences in EPA and its COX pathway product PGF3α between the two groups (P > 0.05).

[0075] The CYP450 pathway product 16(17)-EpDPE of DHA in the PCOS group was significantly higher than that in the control group (P < 0.001), and remained significant after adjusting for BMI and age. There was no significant difference in the CYP450 pathway product 19(20)-EpDPE (P > 0.05).

[0076] There were no significant differences in the products of the LACYP450 pathway, the LOX pathway, and the DGLA LOX pathway (P > 0.05). The levels of Oxylipins in the follicular fluid of the two groups of patients are shown in Table 2, and the differential metabolites were plotted. Figure 1 .

[0077] Table 2 Oxylipins in follicular fluid

[0078]

[0079] *: P < 0.05; Adj-P: adjusted for age and BMI

[0080] 3.3 Screening of differential metabolites of Oxylipins in patients' follicular fluid

[0081] OPLS-DA comparison was performed on the metabolites of the two groups of patients. The OPLS-DA scores are Figure 2 shown. The samples of the control group were clustered on the left, and most of the samples of PCOS patients were located on the right, as Figure 2 shown in A. Figure 2B indicates that R2Y(cum) and Q2(cum) are 0.414 and 0.216 respectively, indicating that the OPLS-DA model is not overfitted and has analytical ability, and can be used for subsequent analysis. In this study, 4 metabolites were detected to meet the differential metabolite screening criteria (as described above) between PCOS patients and the control group. For the DHA CYP450 pathway 16(17)-EpDPE, AA, the AA COX pathway 11-HETE, and the AA CYP450 pathway 8,9-diHETrE, the FC values indicated that the four metabolites showed an upward trend in the follicular fluid of PCOS patients. The situation of differential metabolite screening is shown in Table 3.

[0082] Table 3 Differential metabolites in the follicular fluid of PCOS group and control group

[0083]

[0084] 3.4 Predictive value of differential metabolites of Oxylipins in the follicular fluid of patients for PCOS

[0085] The predictive value of the four metabolites for PCOS was analyzed by ROC curve, and the 95% confidence interval of AUC, specificity and sensitivity were obtained (Table 4) and the ROC curve graph was drawn ( Figure 3 ). It was found that follicular fluid 16(17)-EpDPE had good specificity and sensitivity for the prediction of PCOS (AUC = 0.801). While AA and 8,9-diHETrE had certain specificity and sensitivity for the prediction of PCOS, with AUC of 0.743 and 0.724 respectively, and the specificity and sensitivity of 11-HETE were general (AUC = 0.682).

[0086] Table 4 ROC curve report of PCOS group and control group

[0087]

[0088] AUC: Area Under Curve; 95%CI: 95% Confidence Interval; Sens: Sensitivity; Specific: Specificity; Sens+Spec: Sensitivity + Specificity

[0089] Example 2 Prospective study

[0090] 1. Basic information of patients

[0091] In this study, 40 PCOS patients who received IVF / ICSI treatment and 20 patients in the control group were included again, with a total of 60 oocyte retrieval cycles. The baseline characteristics of the patients are shown in Table 5. Among the basic observation indexes of the two groups, the levels of antral follicles, LH, LH / FSH, T, and AMH in PCOS patients were significantly higher than those in the control group (P < 0.001), and the differences were still significant after adjusting for age and BMI (P < 0.001, P = 0.003, P = 0.001, P = 0.001, P = 0.002). The fasting blood glucose and TC were significantly higher than those in the control group (P = 0.038, P = 0.031), but the differences were not significant after adjusting for age and BMI. There were no significant differences in female age, BMI, basal FSH, serum triglyceride, HDL, and LDL between the groups (P > 0.05). The E2 on the hCG day in the PCOS group was significantly higher than that in the control group (P = 0.006), and it was still significant after adjusting for age and BMI. There were no significant differences in the dosage of ovulation-stimulating Gn, the number of days of Gn use, LH, and P on the hCG day between the two groups (P > 0.05). The PCOS group had more retrieved oocytes (P = 0.042), more MII oocytes (P = 0.034), and more 2PNs (P = 0.032), and the differences were still significant after adjusting for age and BMI (P = 0.027, P = 0.026, P = 0.03). There were no significant differences in the oocyte retrieval rate, mature oocyte rate, 2PN rate, number (rate) of high-quality embryos on D3, blastocyst formation rate, and high-quality blastocyst rate between the two groups (P > 0.05).

[0092] Table 5 Baseline characteristics of two groups of patients receiving IVF / ICSI treatment

[0093]

[0094]

[0095] *: P < 0.05; Adj-P: adjusted for age and BMI

[0096] 2. Comparison of Oxylipins levels in follicular fluid between the two groups of patients

[0097] A total of 59 Oxylipins were detected by LC-MS. The AA in the PCOS group was significantly higher than that in the control group (P = 0.002), and there was no significant difference after adjusting for age and BMI. The product of the AACYP450 pathway, 20-HETE, was significantly lower than that in the control group (P = 0.034), and the level of 14,15-diHETrE was significantly higher than that in the control group (P = 0.002). There was still a significant difference after adjusting for age and BMI; the product of the COX pathway, 11-HETE, was significantly higher than that in the control group (P = 0.033), and there was no significant difference after adjusting for age and BMI; the products of the LOX pathway, 6R-LXA4 and 5-oxoETE, were significantly higher than that in the control group (P = 0.018, P = 0.022), and there was still a significant difference after adjusting for age and BMI. There were no statistical differences in the AACYP450 pathway (11,12-diHETrE, 8,9-diHETrE, 16-HETE, 18-HETE) (P > 0.05); there were no statistical differences in the products of the COX pathway, 12-HHTrE, dhk PGF2α, and PGF2α (P > 0.05); there were no statistical differences in the LOX pathway (15-oxoETE, 12-oxoETE, LTE4, 15R-LXA4, HXB3, 5-HETE, 14,15-LTE4, Adrenic acid, 5,15-diHETE, 8,15-diHETE, HXA3, 14,15-LTC4) and the non-enzymatic pathway 9-HETE (P > 0.05).

[0098] In the PCOS group, 18-HEPE of the EPACYP450 pathway was significantly lower than that in the control group (P = 0.001), and there was still a significant difference after adjusting for age and BMI; 15-oxoEDE of the non-enzymatic pathway was significantly higher than that in the control group (P = 0.003), and there was still a significant difference after adjusting for age and BMI; there were no statistical differences in EPA, 5,6-diHETE of the EPACYP450 pathway, the metabolites of the COX pathway, and 11-HEPE of the non-enzymatic pathway (P > 0.05).

[0099] The DHA in the PCOS group was significantly lower than that in the control group (P = 0.007), and the 16(17)-EpDPE in the DHA CYP450 pathway was significantly higher than that in the control group (P = 0.001). The differences were still significant after adjusting for age and BMI. The LOX pathway (4-HDoHE, 16-HDoHE, 10-HDoHE) was significantly lower than that in the control group (P = 0.001, P < 0.001, P = 0.02). Among them, the differences in 4-HDoHE and 16-HDoHE were still significant after adjusting for age and BMI, while the difference in 10-HDoHE was not significant after adjusting for age and BMI. There were no significant differences in 19(20)-EpDPE in the DHA CYP450 pathway, the LOX pathway (17-HDoHE, 20-HDoHE, 14-HDoHE, 11-HDoHE), and the non-enzymatic pathway (7-HDoHE, 8-HDoHE) (P > 0.05).

[0100] The LACYP450 pathway (12,13-EpOME, 9,10-EpOME) in the PCOS group was significantly lower than that in the control group (P = 0.001, P = 0.006). The differences were still significant after adjusting for age and BMI. The LOX pathway (9-HODE, 13-HODE, 9-oxoEDE) was significantly lower than that in the control group (P = 0.003, P = 0.001, P = 0.001). The differences were still significant after adjusting for age and BMI. There were no significant differences in the LA CYP450 pathway (9,10-diHOME, 12,13-diHOME) and 13-oxoEDE in the LOX pathway (P > 0.05).

[0101] The DGLA LOX pathway (15-HETrE, 8-HETrE) was significantly lower than that in the control group (P < 0.001, P = 0.018). The differences were still significant after adjusting for age and BMI. The 13-HOTrE in the α-LA LOX pathway was significantly lower than that in the control group (P = 0.015). The differences were still significant after adjusting for age and BMI.

[0102] The Oxylipins levels in the follicular fluid of the two groups of patients are shown in Table 6, and the metabolites with differences are shown in Figure 4 .

[0103] Table 6 Oxylipins in follicular fluid

[0104]

[0105]

[0106]

[0107] *: P < 0.05; Adj-P: adjusted for age and BMI

[0108] 3. Screening of differential metabolites of Oxylipins in patients' follicular fluid

[0109] OPLS-DA comparison was performed on the metabolites of the two groups of patients. The OPLS-DA scores were as Figure 5 shown, and the sample clustering was the same as that of the retrospective study, as Figure 5 shown in A. Figure 5 B indicated that R2Y(cum) and Q2(cum) were 0.611 and 0.474 respectively, indicating that the OPLS-DA model was not overfitted and had good analytical ability. In this study, 11 differential metabolites were detected between PCOS patients and the control group, AA, 14,15-diHETrE in the AACYP450 pathway, 6R-LXA4 in the AALOX pathway, DHA, (16-HDoHE, 4-HDoHE) in the DHALOX pathway, 16(17)-EpDPE in the DHA CYP450 pathway, 18-HEPE in the EPACYP450 pathway, 15-oxoEDE in the EPANE pathway, 9-oxoODE in the LALOX pathway, 15-HETrE in the DGLA LOX pathway. Combining the FC values indicated that 14,15-diHETrE, 6R-LXA4, AA, 16(17)-EpDPE, 15-oxoEDE showed an upward trend in the follicular fluid of PCOS patients, while 16-HDoHE, 4-HDoHE, 15-HETrE, 9-oxoODE, 18-HEPE, DHA showed a downward trend. The screening of differential metabolites is shown in Table 7.

[0110] Table 7 Differential metabolites in the follicular fluid of PCOS group and control group

[0111]

[0112] 4. Predictive value of differential metabolites of Oxylipins in patients' follicular fluid for PCOS

[0113] The ROC curve was used to analyze the predictive value of 11 metabolites for PCOS, and the 95% confidence interval of AUC, specificity and sensitivity were obtained (Table 8), and the ROC curve graphs of up-regulated metabolites ( Figure 6 A) and down-regulated metabolites ( Figure 6 B) were plotted respectively. The predictive value of 11 metabolites for PCOS was analyzed. It was found that 15-oxoEDE (AUC = 0.768), 16(17)-EpDPE (AUC = 0.768), 16-HDoHE (AUC = 0.783), 4-HDoHE (AUC = 0.769), 15-HETrE (AUC = 0.77), 9-oxoODE (AUC = 0.781), 18-HEPE (AUC = 0.738) in the follicular fluid had good specificity and sensitivity for the prediction of PCOS.

[0114] Table 8 ROC curve reports for the PCOS group and the control group

[0115]

[0116] AUC: Area Under the Curve; 95% CI: 95% Confidence Interval; Sens: Sensitivity; Specific: Specificity; Sens+Spec: Sensitivity + Specificity

[0117] Although the specific embodiments of the present invention have been described in detail, those skilled in the art will understand that various modifications and variations can be made to the details based on all the teachings that have been published, and such changes are within the scope of protection of the present invention. The entire scope of the present invention is given by the appended claims and any equivalents thereof.

Claims

1. Use of a reagent for detecting the level of a metabolic marker in a subject sample in the preparation of a product for diagnosing polycystic ovary syndrome, characterized in that, The metabolic marker comprises 16(17)-EpDPE.

2. The application according to claim 1, characterized in that, The metabolic marker is 16(17)-EpDPE.

3. The application according to claim 1, wherein The reagent includes a reagent for detecting the level of the metabolic marker in a sample by any one or more of nuclear magnetic resonance method, chromatography, spectrometry, mass spectrometry, and chemical analysis method.

4. The application according to claim 1, characterized in that, The sample is follicular fluid.

5. The application according to claim 1, characterized in that, The subject is a human.

6. The application according to claim 1, wherein The product includes a chip or a kit.

7. A product for diagnosing polycystic ovary syndrome, the product comprising a reagent for detecting the level of a metabolic marker in a sample from a subject, characterized in that, The metabolic marker comprises 16(17)-EpDPE.

8. The product according to claim 7, wherein The reagent includes a reagent for detecting the level of the metabolic marker in a sample by any one or more of nuclear magnetic resonance method, chromatography, spectrometry, mass spectrometry, and chemical analysis method.

9. The product according to claim 7, wherein, The product includes a chip or a kit.

10. The product according to claim 9, characterized in that, The chip has a reagent capable of detecting and / or quantifying the levels of one or more metabolites at a predetermined position fixed on a substrate.

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