Elevated levels of arachidonic acid metabolites in follicular fluid of PCOS patients

in Reproduction
Authors:
Shengxian LiDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

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Jia QiCenter for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China

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Yongzhen TaoCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, China

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Qinling ZhuCenter for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China

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Rong HuangDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

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Yu LiaoDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

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Jiang YueDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

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Wei LiuDepartment of Endocrinology and Metabolism, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

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Hanting ZhaoCenter for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China

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Huiyong YinCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, China
School of Life Science and Technology, ShanghaiTech University, Shanghai, China
Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing, China

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Yun SunCenter for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China

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Correspondence should be addressed to H Yin or Y Sun; Email: hyyin@sibs.ac.cn or syun163@163.com

*(S Li, J Qi and Y Tao contributed equally to this work)

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Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in reproductive-age women usually accompanied by lipid metabolic disorders. However, it remains unknown whether arachidonic acid (AA) and its metabolites in follicular fluid (FF) were altered in PCOS patients. This study was intended to measure the levels of AA and its metabolites in the FF of non-obese PCOS patients that underwent in vitro fertilization (IVF) and to explore the possible causes of the alterations. Thirty-nine non-obese women with PCOS and 30 non-obese women without PCOS were enrolled. AA and its metabolites were measured by liquid chromatography-mass spectrometry. The levels of AA metabolites generated via cyclooxygenase-2 (COX-2) pathway and cytochrome P450 epoxygenase pathway but not lipoxygenase (LOX) pathway were significantly higher in the FF of PCOS patients. The metabolites generated via COX-2 pathway were significantly correlated with levels of testosterone and fasting insulin in serum. The in vitro study further demonstrated that insulin but not testosterone could promote the IL-1β and hCG-induced COX-2 expression and prostaglandin E2 (PGE2) secretion in primary human granulosa cells. In conclusion, there was an elevation in AA metabolites in FF of PCOS patients. Insulin played a pivotal role in the increased AA metabolites generated via COX-2, which could be interpreted as another novel molecular pathophysiological mechanism of PCOS.

Abstract

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in reproductive-age women usually accompanied by lipid metabolic disorders. However, it remains unknown whether arachidonic acid (AA) and its metabolites in follicular fluid (FF) were altered in PCOS patients. This study was intended to measure the levels of AA and its metabolites in the FF of non-obese PCOS patients that underwent in vitro fertilization (IVF) and to explore the possible causes of the alterations. Thirty-nine non-obese women with PCOS and 30 non-obese women without PCOS were enrolled. AA and its metabolites were measured by liquid chromatography-mass spectrometry. The levels of AA metabolites generated via cyclooxygenase-2 (COX-2) pathway and cytochrome P450 epoxygenase pathway but not lipoxygenase (LOX) pathway were significantly higher in the FF of PCOS patients. The metabolites generated via COX-2 pathway were significantly correlated with levels of testosterone and fasting insulin in serum. The in vitro study further demonstrated that insulin but not testosterone could promote the IL-1β and hCG-induced COX-2 expression and prostaglandin E2 (PGE2) secretion in primary human granulosa cells. In conclusion, there was an elevation in AA metabolites in FF of PCOS patients. Insulin played a pivotal role in the increased AA metabolites generated via COX-2, which could be interpreted as another novel molecular pathophysiological mechanism of PCOS.

Introduction

Polycystic ovary syndrome (PCOS) is a complex gynecological and endocrinological disorder affecting 5–10% of reproductive-age women (Azziz et al. 2004, Li et al. 2013, Zhuang et al. 2014). The clinical manifestations of PCOS patients include oligomenorrhea or chronic anovulation, hyperandrogenism, and polycystic ovarian morphology. Besides reproductive disorders, PCOS is often accompanied by several metabolic abnormalities, such as obesity, glucose intolerance, insulin resistance, and dyslipidemia.

Arachidonic acid (AA) is metabolized by cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 epoxygenase (P450epo) pathways that produce other key metabolites. For example, the COX pathway produces several prostaglandins (PGs) that affect oocyte maturation, ovulation, implantation, delivery, and other reproductive processes (Tokugawa et al. 1998, Marions & Danielsson 1999, Schaiff et al. 2000), whereas three LOX enzymes (5-, 12-, 15-LOXs) metabolize AA to 5-, 12-, and 15-hydroxyeicosatetraenoic acids (5-, 12-, 15-HETEs), respectively.

Follicular fluid (FF) is produced by a complex process that involves the diffusion of serum proteins through the blood–follicle barrier, as well as the secretion of granulosa cells and theca cells (Gerard et al. 2002, Schweigert et al. 2006, Kolialexi et al. 2008, Rodgers & Irving-Rodgers 2010). FF provides a microenvironment for follicle development and oocyte maturation, and alterations in the composition of FF may affect oocyte development and maturation, fertilization, cleavage, and early embryo formation (Kim et al. 2006, Revelli et al. 2009, Von Wald et al. 2010). Recent studies have addressed the role of FF in the pathogenesis of PCOS (Sorensen et al. 2016, Zhu et al. 2016). Furthermore, a detailed analysis of the FF revealed that the concentrations of fatty acids and amino acids were closely related to embryo development (Matoba et al. 2014). Other studies have identified an association between AA metabolites in the FF and oocyte developmental competence (Khajeh et al. 2017); however, the levels of AA and its metabolites in follicular fluid in PCOS patients remain unclear.

Taken collectively, there is a direct correlation between the microenvironment provided by the FF and embryo development. Epidemiological studies have shown that approximately 40% of women with PCOS are infertile (Teede et al. 2010) and undertake treatment of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI). Compared with women without PCOS, a higher number of oocytes are retrieved in women with PCOS receiving controlled ovarian stimulation. However, PCOS patients usually exhibit a relatively lower oocyte utilization rate and high-quality embryo rate (RHQE) (Homburg et al. 1993, Heijnen et al. 2006), and an increased risk of adverse outcomes (Boomsma et al. 2006). Currently, there is no study that measures the levels of AA and its metabolic profile in the FF of patients with PCOS.

In the present study, we measured and compared AA and its metabolites in FF of PCOS and non-PCOS patients. Our primary aim in this study was to clarify whether there is an imbalanced state of AA and its metabolites in the follicular fluid of PCOS. A secondary aim of this study was to elucidate the possible etiology of the imbalanced AA metabolism in PCOS patients.

Materials and methods

Participants

Thirty-nine non-obese (BMI, <25 kg/m2) patients with PCOS were enrolled according to the revised Rotterdam consensus guidelines (Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group 2004). According to three key clinical features of PCOS, namely oligo-/anovulation(OA), hyperandrogenism (HA) and polycystic ovary morphology (PCOM), the involved patients can be divided into four subtypes (HA + OA, n = 5; HA + PCOM + OA, n = 14; PCOM + OA, n = 14; HA + PCOM, n = 6) (Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group 2004). Thirty non-obese patients without PCOS were enrolled as non-PCOS patients; these patients took IVF because of tubal factors (unilateral or bilateral tubal obstruction, adhesion, unilateral or bilateral salpingectomy, or tubal ligation). All patients were 20–35 years old with a history of infertility for over 1 year. The following patients were excluded from the study: (1) women who underwent unilateral oophorectomy; (2) women with a history of a uterine abnormality (malformed uterus, adenomyosis, submucous myoma, or intrauterine adhesion); (3) women or their partners with a diagnosis of an abnormal chromosome karyotype; and (4) women with a history of recurrent spontaneous abortions.

All procedures were performed at the Center for Reproductive Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University. Written informed consent was obtained, and approval of the ethics protocol was granted from the Ethics Committee of Renji Hospital (Ethical Authorization Number: 2015030308).

Controlled ovarian hyperstimulation and FF collection

All patients were enrolled in a standardized gonadotropin-releasing hormone (GnRH) antagonist protocol (Shi et al. 2014, Zhu et al. 2016). In brief, patients received recombinant follicle-stimulating hormone (rFSH, Gonal-f; Merck Serono) on day 3 of spontaneous menses or day 3 of the cycle induced by oral contraceptive pills. Patients received the GnRH antagonist Cetrorelix (Merck Serono) at a daily dose of 250 μg by s.c. injection when there was at least one follicle with a mean diameter of ≥12 mm until the desired stage of follicular development was reached. Patients received human chorionic gonadotropin (hCG, Lvzhu, Zhuhai, China) to initiate ovulation when there was at least one leading follicle with a diameter of ≥18 mm. Transvaginal ultrasound-guided oocyte retrieval was performed 36 h later. The FF from the first leading oocytes without contaminating blood was collected immediately from the dominant follicles. The FF was centrifuged at 200 g for 5 min at room temperature, and 2 mL of the supernatant was collected and stored at −80°C until further analysis.

Clinical analyses

Hormone measurements

The blood samples were collected before gonadotropin use. The basal serum hormonal profiles of luteinizing hormone (LH), follicle-stimulating hormone (FSH), testosterone, estradiol (E2), prolactin (PRL), and anti-Müllerian hormone (AMH) were determined using chemiluminescent assay kits (Beckman Access Health Company, Chaska, MN, USA). Serum fasting insulin and fasting plasma glucose were measured using a chemiluminescence assay kit (Beckman Access Health Co) and a standard glucose oxidase method (Roche), respectively. The homeostasis model of assessment for insulin resistance index (HOMA-IR) was calculated as fasting serum insulin (μIU/mL) × fasting plasma glucose (mmol/L) / 22.5).

AA metabolite measurements

Standards and deuterated standards of AA, including PGD2, PGE2, PGF, PGI2, thromboxane B2 (TXB2), 5-HETE, 12-HETE, 15-HETE, and epoxyeicosatrienoic acids (EETs), were purchased from Cayman Chemicals. The solvents for sample preparation and mass spectrometry (MS), such as methanol, chloroform, and water, were purchased from Burdick & Jackson (Muskegon, MI, USA). Other HPLC quality solvents, such as methanol, 2-propanol, hexane, and acetonitrile, were purchased from either Fisher Chemical (Phillipsburg, NJ, USA) or EM Science (Gibbstown, NJ, USA).

Lipids were extracted from FF as previously described with minor modifications (Han et al. 2004, 2005), and AA metabolites were analyzed by a metabolomic method (Deems et al. 2007, Buczynski et al. 2009, Yang et al. 2009, Huang et al. 2014, Lu et al. 2017). After adding the mixture of deuterated internal standards (0.5 ng/μL) to 500 µL of the FF, the pH of the solution was adjusted to 3.0 using 1 N HCl. Liquid–liquid extraction of the mixture was carried out twice using hexane:methyl t-butyl ether (50:50, v/v). The samples were separated on a Phenomenex Kinetix C18 column (particle size, 3 μm; length × internal diameter, 100 × 2.1 mm) using a Thermo Accela HPLC system at a flow rate of 0.4 mL/min using a gradient of mobile phase A (water:acetonitrile:formic acid 63:37:0.02, v/v/v) and mobile phase B (acetonitrile:isopropanol 50:50, v/v). MS analysis was carried out on a TSQ Vantage triple quadrupole mass spectrometer (San Jose, CA, USA). The mass spectrometer was operated in the negative-ion mode using multiple-reaction monitoring. Data acquisition and analysis were performed using Xcalibur software, version 2.0. The limit of detection and coefficient variations of our method are comparable to those reported in the literature (Huang et al. 2014, Wang et al. 2014). Specifically, the limit of sensitivity for most AA metabolites is in the pg/mL range. All the metabolites were detected with a precision of coefficient variation less than 20% and accuracy of relative error less than 25%.

Isolation and culture of primary granulosa cells

The granulosa cells (GCs) were isolated from the follicular fluid as described previously (Zhu et al. 2016). Briefly, follicular fluid from each patient was pooled and centrifuged. The purified pellet was obtained by density centrifugation with Ficoll-Paque (GE Healthcare) and then dispersed in 0.1% hyaluronidase (Sigma) at 37°C for 10 min. The cells were then cultured in Dulbecco’s modified Eagle medium/Ham’s F12 with 10% fetal bovine serum (Gibco), 100 U/mL penicillin (Invitrogen, Life Technologies) and 100 μg/mL streptomycin sulfate (Invitrogen, Life Technologies). The viable cells were seeded at 7 × 105 cells per well in a six-well culture plate. Three days after culture, the cells were seeded in phenol red and serum-free medium. The cells were incubated with insulin (100 nM), testosterone (100 nM), hCG (10 IU/L) and interleukin 1β (IL-1β, 1 ng/mL) for 24 h.

Reverse transcription and real-time quantitative PCR

Total RNA from cultured granulosa cells was extracted using a total RNA Kit (Foregene) according to manufacturer’s instructions and was reverse transcribed to cDNA using the PrimeScript® RT kit (TaKaRa) with appropriate controls. Quantitative real-time PCR was performed and analyzed with ABI Prism System (Applied Biosystems) using SYBR® Premix (TaKaRa) in triplicate. Relative mRNA expression was calculated by the comparative cycle threshold method (∆∆Ct) with ACTB as the housekeeping gene. The primer sequences used of targeting genes were as follows:

Western blot analysis

Total protein was extracted from cells using an ice-cold radio-immunoprecipitation assay lysis buffer (Cwbio) containing a phosphatase inhibitor (Active Motif) and a protease inhibitor cocktail (Roche). Protein (40 μg) from each sample was electrophoresed in a 10% SDS–PAGE gel and then transferred onto a nitrocellulose blot. After 1 h of blocking with 5% nonfat milk, the blot was incubated overnight at 4°C with antibodies against COX-2 (1:1000, 320 μg/L, Poteintech) and ACTB (1:1000, 430 μg/L, Poteintech). On the second day, the blot was washed and then incubated with the respective secondary antibody conjugated to horseradish peroxidase (Proteintech) for 1 h. Bands with peroxidase activity were detected by an enhanced chemiluminescent detection kit (Merck Millipore) and visualized with a G-Box chemiluminescence image capture system (Syngene).

PGE2 measurement

The culture medium of granulosa cells was collected. PGE2 was measured using PGE2 ELISA Kit (No. 514010, Cayman) following manufacturer’s instructions. The intra-assay variation at 500 pg/mL and 62.5 pg/mL were 3.9 and 6.6 respectively. The inter-assay variation at 500 pg/mL and 62.5 pg/mL were 6.4 and 15.5 respectively.

Statistical analyses

Data were presented as means ± s.d. The Kolmogorov–Smirnov test was used to determine whether the continuous variables fit a normal distribution. The unpaired t-test was used to assess the differences in normally distributed variables. The non-parametric Mann–Whitney test was used for non-normal distribution variables between PCOS and non-PCOS groups. The correlation between the variables was performed using the Pearson analysis. Multiple linear regression analysis was performed to investigate the correlations between the serum testosterone, fasting insulin and AA metabolites. The Statistical Package for Social Sciences (SPSS, version 18.0 for Windows) was used for data analysis.

Results

Clinical characteristics of patients with PCOS that underwent IVF

The basal testosterone (1.30 ± 0.83 vs 0.75 ± 0.45 nmol/L, P  < 0.05), basal LH (8.01 ± 4.94 vs 4.48 ± 1.44 IU/L, P  < 0.001) and fasting insulin levels (14.17 ± 13.85 vs 6.13 ± 1.83 mIU/L, P  < 0.05) in the serum were significantly higher (P < 0.05) in PCOS patients than in non-PCOS patients. Age (27.85 ± 3.86 vs 27.33 ± 3.49 years) and BMI (22.98 ± 3.30 vs 20.53 ± 2.65 years) were comparable in PCOS and non-PCOS patients, and there were no statistically significant differences in the FSH, E2, AMH and fasting glucose levels between groups. The fasting insulin, basal testosterone and basal LH levels in the FF were also significantly higher in PCOS patients than in non-PCOS patients (Supplementary Table 1, see section on supplementary materials given at the end of this article). In non-PCOS patients, the average number of retrieved oocytes is 13.29 ± 1.26, while in PCOS patients the average number of retrieved oocytes is 16.90 ± 1.15 (P < 0.05 vs non-PCOS).

Changes in the levels of AA and its metabolites in FF from PCOS patients that underwent IVF

Figure 1 shows representative liquid chromatography-mass spectrometry (LC-MS) of the FF from patients that underwent IVF. Complete LC-MS lipidomic datasets were obtained for the FF of patients with and without PCOS. The levels of free AA (F-C 20:4 n-6) and total AA (T-C 20:4 n-6) in follicular fluid from PCOS patients were comparable with non-PCOS group (Fig. 2). There was a significant elevation in the levels of AA metabolites generated via P450epo (8,9-DHET and 11,12-DHET) in PCOS group than in non-PCOS group (Fig. 2). The levels of AA metabolites generated via the COX pathway (PGI2, PGE2, PGD2, PGF and TXB2) were significantly higher (P < 0.05) in patients of PCOS group than in those of the non-PCOS group (Fig. 2). The levels of PGJ2 and 15-deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2), which were metabolized from PGD2, were also significantly higher (P < 0.05) in patients of the PCOS group than in those of the non-PCOS group (Fig. 2). There were no statistically significant differences in the levels of metabolites generated via the LOX pathways between groups.

Figure 1
Figure 1

Representative LC-MS chromatograms of follicular fluid (FF) specimens from patients that underwent IVF. Chromatograms of arachidonic acid metabolites in a standard mixture (A), FF from a PCOS patient (B), and an internal standard (C).

Citation: Reproduction 159, 2; 10.1530/REP-19-0136

Figure 2
Figure 2

Levels of AA and its metabolites generated in the FF from patients with PCOS and without PCOS (non-PCOS). COX, cyclooxygenase; PGD2, prostaglandin D2; PGJ2, prostaglandin J2; 15d-PGJ2, 15-deoxy-Δ12,14-prostaglandin J2; PGE2, prostaglandin E2; PGF, prostaglandin F2alpha; PGFM, prostaglandin F metabolite; PGI2, prostaglandin I2; and TXB2, thromboxane B2; LOX, lipoxidase; P450epo, cytochrome P450 epoxygenase; EETs, epoxyeicosatrienoic acids; HETEs, hydroxyeicosatetraenoic acids. Data are mean ± s.e.m. n = 30 for non-PCOS and n = 39 for PCOS. *P < 0.05, **P < 0.01 compared with group non-PCOS. The blue column represents non-PCOS and the red column represents PCOS.

Citation: Reproduction 159, 2; 10.1530/REP-19-0136

Correlation between the AA metabolites, testosterone and fasting insulin

In Pearson’s correlation tests, the levels of AA metabolites generated via P450epo (8,9-DHET, 11,12-DHET, and 14,15-DHET) in follicular fluid, the levels of AA metabolites generated via LOX (5-HETE and 15-HETE) in follicular fluid and the levels of AA metabolites generated via COX (PGJ2, PGE2, PGF, and TXB2) in follicular fluid were significantly correlated with serum basal testosterone levels. The levels of AA metabolites generated via COX (PGJ2, PGE2, PGF, and TXB2) were significantly correlated with serum fasting insulin levels.

Further multivariant linear regression analysis confirmed that only AA metabolites generated via COX (PGJ2, PGE2, and PGF) in follicular fluid were significantly associated with basal testosterone after adjusting for basal LH and BMI. As for the associations between AA metabolites and fasting insulin, significant correlations were also observed in AA metabolites generated via COX (PGJ2, PGE2, and PGF) adjusting for basal testosterone and BMI (Table 1).

Table 1

Correlation between AA metabolites, testosterone and fasting insulin.

Basal testosterone (nmol/L) Fasting insulin (μIU/L)
r* P* P r P* P
P450 metabolites
 5,6-EET −0.063 0.622 −0.118 0.366
 8,9-EET −0.038 0.764 −0.079 0.543
 11,12-EET −0.037 0.770 −0.113 0.385
 14,15-EET −0.103 0.419 −0.038 0.770
 5,6-DHET 0.195 0.122 −0.038 0.771
 8,9-DHET 0.283 0.024 0.313 −0.079 0.543
 11,12-DHET 0.321 0.010 0.675 −0.119 0.361
 14,15-DHET 0.252 0.045 0.550 −0.192 0.138
 20-HETE 0.227 0.072 0.132 0.310
LOX metabolites
 5-HETE 0.272 0.030 0.966 0.020 0.878
 12-HETE 0.094 0.459 −0.099 0.446
 15-HETE 0.266 0.033 0.299 0.248 0.054
 LTB4 −0.027 0.830 0.020 0.879
COX metabolites
 15-d-beta-12,14PGJ2 0.020 0.876 0.057 0.660
 PGJ2 0.400 0.001 0.032 0.431 0.001 0.013
 PGD2 0.206 0.102 0.386 0.002 0.520
 PGE2 0.328 0.008 0.027 0.455 0.000 0.004
 PGF2a 0.292 0.019 0.031 0.373 0.003 0.009
 8-iso-PGF2a −0.072 0.570 0.040 0.757
 PGFM 0.139 0.272 0.091 0.483
 PGI2 0.167 0.187 0.286 0.025 0.829
 TXB2 0.327 0.008 0.455 −0.083 0.527

*Pearson’s correlation tests. Multivariant linear regression model.

Then the correlation between the levels of AA metabolites generated via P450epo, LOX, and COX in follicular fluid with serum basal testosterone and fasting insulin levels were also analyzed in PCOS group and non-PCOS group by Pearson’s correlation tests. The levels of TXB2 generated via COX in follicular fluid were significantly correlated with serum basal testosterone levels in non-PCOS group. The levels of PGJ2 generated via COX in follicular fluid were significantly correlated with serum basal testosterone levels in PCOS group. The levels of AA metabolites generated via P450epo (5,6-EET, 11,12-EET) in follicular fluid, and the levels of AA metabolites generated via COX (15d-PGJ2, PGE2, and PGF) in follicular fluid were significantly correlated with serum fasting insulin levels in non-PCOS group. The levels of AA metabolites generated via COX (PGJ2, PGD2, and PGE2) in follicular fluid were significantly correlated with serum fasting insulin levels in PCOS group. Multivariant linear regression analysis showed that AA metabolites generated via COX (15d-PGJ2, PGE2 and PGF) and via P450epo (5,6-EET) in non-PCOS group, and only AA metabolites generated via COX (PGJ2, PGD2, and PGE2) in PCOS group were significantly associated with basal fasting insulin after adjusting for basal LH and BMI (Table 2).

Table 2

Correlation between AA metabolites, testosterone and fasting insulin in non-PCOS and PCOS patients separately.

Basal testosterone (nmol/L) Fasting insulin (μIU/L)
r* P* P*‡ r P P†‡ r* P* P*‡ r P P†‡
P450 metabolites
 5,6-EET −0.047 0.821 −0.115 0.492 0.419 0.033 0.031 −0.244 0.158
 8,9-EET −0.244 0.231 −0.120 0.472 0.019 0.928 −0.213 0.220
 11,12-EET 0.248 0.222 −0.139 0.404 0.439 0.025 0.094 −0.206 0.235
 14,15-EET −0.203 0.320 −0.157 0.345 0.181 0.377 −0.113 0.516
 5,6-DHET −0.127 0.536 0.245 0.139 0.331 0.099 −0.200 0.249
 8,9-DHET −0.083 0.686 0.260 0.116 0.043 0.834 −0.265 0.124
 11,12-DHET −0.047 0.820 0.297 0.070 0.065 0.751 −0.269 0.118
 14,15-DHET 0.100 0.627 0.275 0.095 −0.074 0.719 −0.288 0.094
 20-HETE 0.298 0.140 0.124 0.460 0.059 0.776 0.058 0.742
LOX metabolites
 5-HETE 0.104 0.613 0.237 0.152 0.080 0.698 −0.114 0.516
 12-HETE −0.022 0.914 0.105 0.531 0.144 0.484 −0.162 0.352
 15-HETE 0.102 0.620 0.239 0.148 0.168 0.413 0.203 0.242
 LTB4 −0.192 0.349 −0.083 0.621 0.354 0.076 −0.085 0.629
COX metabolites
 15-d-beta-12,14PGJ2 0.329 0.101 −0.094 0.576 0.539 0.004 0.011 −0.041 0.815
 PGJ2 0.154 0.453 0.322 0.049 0.068 0.154 0.451 0.356 0.036 0.025
 PGD2 0.279 0.167 0.092 0.583 0.343 0.086 0.344 0.043 0.006
 PGE2 0.143 0.485 0.261 0.114 0.548 0.004 0.010 0.391 0.020 0.003
 PGF2a 0.136 0.508 0.215 0.194 0.471 0.015 0.044 0.293 0.088
 8-iso-PGF2a 0.091 0.659 −0.165 0.322 0.195 0.339 0.022 0.899
 PGFM 0.123 0.548 0.105 0.529 0.271 0.181 0.035 0.843
 PGI2 0.329 0.101 0.015 0.927 0.222 0.275 0.250 0.148
 TXB2 0.433 0.027 0.051 0.212 0.200 0.299 0.138 −0.247 0.153

*Pearson’s correlation test model in non-PCOS patients. Pearson’s correlation test model in PCOS patients. *Multivariant linear regression model in non-PCOS patients. Multivariant linear regression model in PCOS patients.

Effects of testosterone and insulin on hCG- and IL-1β-induced COX-2 expression

The primary granulosa cells were obtained from non-PCOS patients. Treatment of human primary granulosa cells with IL-1β and hCG for 24 h upregulated COX-2 expression significantly (Fig. 3A and B) and the coexistence of IL-1β and hCG could further increase the expression of COX-2. Insulin alone could not induce the expression of COX-2 but could further upregulate the induction role of IL-1β and hCG (Fig. 3A). Testosterone alone could not induce the expression of COX-2, and it had no effect on the induction role of IL-1β and hCG either (Fig. 3B). The concentrations of COX-2 protein were further measured by Western blot, and the change of the protein level was same as the mRNA expression measured by real-time PCR (Fig. 3C and D).

Figure 3
Figure 3

The induction role of insulin, testosterone, interleukin-1β and hCG on COX-2 expression and PGE2 production. The mRNA level of COX-2 with treatment of insulin, interleukin-1β and hCG (A). The mRNA level of COX-2 with treatment of testosterone, interleukin-1β and hCG (B). The protein level of COX-2 with treatment of testosterone, interleukin-1β and hCG (C). The PGE2 concentration of culture medium of granulosa cells treated with testosterone, interleukin-1β and hCG (D). The medicine concentrations are as followed: insulin (100 nM), testosterone (100 nM), hCG (10 IU/L) and interleukin 1β (1 ng/mL). Data are represented as mean ± s.e.m. n = 4 for each experiment. Values with a different letter above are statistically significantly different (P < 0.05). CTRL, control; INS, insulin; T, testosterone; IL1B, interleukin-1β.

Citation: Reproduction 159, 2; 10.1530/REP-19-0136

Effects of testosterone and insulin on hCG and IL-1β-induced PGE2 secretion

The same treatment of human primary granulosa cells with testosterone and insulin with or without IL-1β and hCG for 24 h described as before. Insulin and testosterone alone could not increase the concentration of PGE2 in the culture medium, while IL-1β and hCG alone could (P < 0.05). IL-1β combined with hCG could further increase the secretion of PGE2 by the granulosa cells cultured in vitro. Only insulin, not testosterone, could further increase the stimulation role of IL-1β combined with hCG (Fig. 3E and F).

Discussion

More than 40% of PCOS patients are infertile and require IVF/ICSI (Teede et al. 2010). Although the number of retrieved oocytes is higher in PCOS patients who undergo controlled ovarian stimulation, the oocyte utilization rate does not increase accordingly and IVF/ICSI outcomes are unsatisfactory (Boomsma et al. 2006, Heijnen et al. 2006). Emerging evidence suggests that FF provides a microenvironment for oocyte development and maturation, and the FF components might influence the oocyte development (Robker et al. 2009, Jungheim et al. 2011, Leroy et al. 2011). AA-derived metabolites, especially PGs, which play key roles in oocyte maturation, cumulus expansion and ovulation. To our knowledge, the profile of AA-derived metabolites in FF in PCOS patients has never been examined. Testosterone or insulin, or both was involved in regulating the concentration of AA-derived metabolites in human FF at the moment has not been reported either. This study provides an extensive profile of follicular AA metabolism in PCOS patients. We evaluated the AA metabolites via COX, P450epo, and LOX in FF and first demonstrated the elevation of AA metabolites via COX (PGI2, PGE2, PGD2, PGF, TXB2, PGJ2, and 15d-PGJ2) and P450epo (8,9-DHET and 11,12-DHET) in PCOS patients when compared with non-obese control.

We previously reported the diminished AA metabolites in the serum of PCOS patients (Li et al. 2017) and elevated COX-2 expression in ovaries of PCOS rats (Huang et al. 2018). Here we further clarified that AA metabolites via COX-2 were also increased in FF of PCOS patients, which was consistent with the rat model results. While the levels of AA and its downstream metabolites in serum reflect the AA metabolism in the whole body, the AA in the ovaries of PCOS rats and in the FF of PCOS patients has more profound effects on the local metabolism and biological consequence in the ovaries. These differences between serum and FF in PCOS patients further indicate the important role of local AA metabolism in PCOS patients. Furthermore, we also clarified the elevation of AA metabolites via P450epo in PCOS follicular fluid. Although the function of AA metabolites via P450epo has not been clarified, our finding provides a new insight in the pathophysiology and potential treatment of PCOS patients in the future.

PGs played important roles in many processes of reproduction. For example, PGE2 is an autocrine and paracrine mediator of oocyte maturation and cumulus expansion. PGE2 participates in cumulus-oocyte coupling and cumulus cell expansion (Calder et al. 2001), thus enhancing the release of luteinizing hormone-releasing hormone (LHRH) from the hypothalamus (Kim & Ramirez 1986). On the other hand, an increased PGE2 level in the FF may delay follicle development, and a very high PGE2 level may be detrimental to oocyte maturation (Marei et al. 2010, Wang et al. 2012). Along with PGE2, PGF is critical for ovulation because it increases collagenolysis and ovarian contractility. The increase in the PGF level in the ovary may serve to overcome the inability to ovulate in patients with PCOS. Besides PGE2 and PGF, we also found that PGJ2 was significantly elevated in PCOS patients, and it was closely correlated with serum insulin and testosterone. However, the role of PGJ2 in granulosa cells remains to be studied. PGJ2 is not stable in vivo, and it could be easily transformed to cyclopentenone PGs, including 9-deoxy-Δ9,12,13,14-dihydro PGD2 (Δ12-PGJ2) and 15d-PGJ2 (Narumiya & Fukushima 1985). 15d-PGJ2 is an endogenous ligand of peroxisome proliferator-activated receptor gamma (PPARγ) that regulates inflammation (Jiang et al. 1998, Valledor & Ricote 2004), granulosa cell proliferation (Chen et al. 2015), steroid hormone biosynthesis (Komar 2005), and fibrosis (Iwase et al. 2009). By using ‘one follicle – one retrieved oocyte – one resulting embryo’ approach, Ciepiela et al. found that elevated concentrations of AA- derived metabolites in FF at the time of oocyte retrieval significantly decreased the ability of oocytes to form pronuclei after ICSI in non-PCOS patients (Ciepiela et al. 2015). The specific function of PGs in IVF/ICSI still needs further exploration.

Both hyperandrogenism and hyperinsulinemia are two common characteristics in PCOS patients (Diamanti-Kandarakis & Dunaif 2012). Insulin resistance, characterized by compensatory hyperinsulinemia, is observed not only in peripheral tissues but also in ovarian granulosa cells in PCOS patients (Zhu et al. 2016). Previous studies have explored the role of insulin on COX-2 in other tissues but the results remain controversial. Some studies demonstrated that insulin could increase COX-2 expression, and might further augment the IL-1β-induced COX-2 expression and PGE2 production (Martins et al. 2010, Song et al. 2014). Meanwhile, there were also some studies that clarified the reduction role of insulin on COX-2 expression (Martins et al. 2008, Xu et al. 2018). These findings led us to speculate whether insulin and androgen were correlated with the increased AA metabolites.

Our study revealed that AA metabolites via COX-2 pathway (PGE2, PGF, and PGJ2) were significantly related with serum insulin and testosterone levels in the multivariate linear regression model, which indicates hyperinsulinemia and hyperandrogenism in PCOS might contribute to the enhanced AA metabolism through COX-2 pathway. Multivariant linear regression analysis showed that AA metabolites generated via COX (PGJ2, PGD2, and PGE2) in PCOS group were significantly associated with basal fasting insulin level, not testosterone, after adjusting for basal LH and BMI in the groups separately. To clarify whether testosterone or insulin regulates COX2 and PGE2 expression, we designed an in vitro experiment using primary isolated granulosa cell.

Considering the chronic inflammation state of PCOS patients and the application of hCG in supra-ovulation, the in vitro study mimics the collaboration role of the inflammatory PCOS state. We treated granulosa cells together with IL-1β, hCG, testosterone and insulin to figure out their induction role on COX-2. IL-1β and hCG are known to induce COX-2 expression and PGs production in many different cells and tissues. Our study revealed that both IL-1β and hCG could significantly induce the expression of COX-2 and the combined treatment of IL-1β and hCG could further increase the expression of COX-2. However, neither insulin nor testosterone had an induction role on the expression of COX-2 without the IL-1β and hCG treatment. Insulin, but not testosterone, could enhance the IL-1β- and hCG-induced COX-2 expression in granulosa cells. These in vitro findings demonstrated the hyperinsulinemia in PCOS might be a causing factor in the increased prostaglandins in follicular fluid. Although we previously reported that androgens downregulate the levels of COX metabolites in the serum of patients with PCOS, there are several important differences between the previous and present studies. Firstly, the levels of AA metabolites in serum are contributed from many different cells, such as hepatocytes, endotheliocytes, peripheral blood granulocytes, and mononuclear cells, whereas only ovarian cells contribute to the levels of these metabolites in the FF. The AA metabolites in follicular fluid specifically reflect local ovarian state. Second, the patients in this study underwent gonadotropin stimulation, which upregulated the levels of PGs. Hyperinsulinemia could exaggerate the induction role of inflammation and LH on COX-2 expression and stimulate the granulosa cells producing more PGs, PGE2 for example. Consistent with the correlation analysis, in vitro study provided evidence for the enhancement of insulin on the IL-1β and hCG-induced COX-2 expression. Therefore, we put forward the elevated AA metabolites in PCOS follicular fluid and its close correlation with hyperinsulinemia for the first time.

Limitation

There are some limitations in this study. (1) Since the FF in this study are collected from more than one follicle, which may have been sub-par to the one follicle-one retrieved oocyte-one resulting embryo design. (2) Previously, we reported that there was no significant difference in serum AA concentration between lean control group and lean PCOS group (Li et al. 2017). In this study, there was no change in the concentration of AA in follicular fluid, but its metabolism was higher in non-obese PCOS group than BMI-matched control group, suggesting a high transfer of AA from circulation or increased hydrolysis of local phospholipids in the ovary. But lack of serum AA and its metabolites is a real shortage of this study. (3) We have not directly detected the activity of COX in primary isolated granulosa cells from PCOS patients and control. (4) Relatively small sample sizes, large data variations, may weaken statistical efficiency. (5) The in vitro experiment could not exactly mimic the in vivo effects of testosterone. Firstly, testosterone may exert its physiological effects through different signaling pathways (androgen receptor or membrane receptors) depending on the target tissue and microenvironments in the body (Goldman et al. 2017). Meanwhile, testosterone could metabolite to estrogen and have complicated functions in vivo. In vitro cell experiments could not fully mimic the in vivo condition and exert the actual action of testosterone in the body. Second, the metabolites or hormones in the follicular fluid reflect the changes in testosterone after it acts on various cells in ovarian tissue (e.g. theca cell, granulosa cell, etc.), while in vitro experiments only reflect the secretion changes of primary isolated granulosa cells after the stimulation of testosterone.

In conclusion, we demonstrated that under gonadotropin stimulation, the levels of AA metabolites generated via the COX-2 were elevated in the FF of patients with PCOS and for the first time reported the elevation of AA metabolites via P450epo in PCOS patients. We also suggest the possible role of hyperinsulinemia on AA metabolism via COX-2 pathway in PCOS patients. Further studies are needed to define the potential mechanism and to further characterize the relationship between PGs and follicle development in patients that undergo IVF. These results provide new insights on how to improve embryo health and IVF outcomes.

Supplementary materials

This is linked to the online version of the paper at https://doi.org/10.1530/REP-19-0136.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This study was supported by the National Key R&D Program of China (No. 2017YFC1001403 to Y S), National Natural Science Foundation of China under Grant (No. 81571499 to Y S, No. 81471029 to S L, No. 81671518 to W L), Clinical skills improvement project of major disorders hospital development center of Shanghai (No. 16CR1022A to Y S) and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (Grant 20161413 to Y S).

Author contribution statement

Y S and H Y designed the study. Q Z, R H, Y L, J Y and W L collected patients’ specimens and related information. S L, J Q, Y T and H Z contributed to conducting the experiments and analyzing the data. S L, J Q and H Y drafted and revised the paper. All authors reviewed the results and approved the final version of the manuscript.

References

  • Azziz R, Woods KS, Reyna R, Key TJ, Knochenhauer ES & Yildiz BO 2004 The prevalence and features of the polycystic ovary syndrome in an unselected population. Journal of Clinical Endocrinology and Metabolism 27452749. (https://doi.org/10.1210/jc.2003-032046)

    • Search Google Scholar
    • Export Citation
  • Boomsma CM, Eijkemans MJ, Hughes EG, Visser GH, Fauser BC & Macklon NS 2006 A meta-analysis of pregnancy outcomes in women with polycystic ovary syndrome. Human Reproduction Update 673683. (https://doi.org/10.1093/humupd/dml036)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Buczynski MW, Dumlao DS & Dennis EA 2009 Thematic Review Series: proteomics. An integrated omics analysis of eicosanoid biology. Journal of Lipid Research 10151038. (https://doi.org/10.1194/jlr.R900004-JLR200)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Calder MD, Caveney AN, Westhusin ME & Watson AJ 2001 Cyclooxygenase-2 and prostaglandin E(2)(PGE(2)) receptor messenger RNAs are affected by bovine oocyte maturation time and cumulus-oocyte complex quality, and PGE(2) induces moderate expansion of the bovine cumulus in vitro. Biology of Reproduction 135140. (https://doi.org/10.1095/biolreprod65.1.135)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Chen MJ, Chou CH, Chen SU, Yang WS, Yang YS & Ho HN 2015 The effect of androgens on ovarian follicle maturation: dihydrotestosterone suppress FSH-stimulated granulosa cell proliferation by upregulating PPARgamma-dependent PTEN expression. Scientific Reports 18319. (https://doi.org/10.1038/srep18319)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Ciepiela P, Baczkowski T, Drozd A, Kazienko A, Stachowska E & Kurzawa R 2015 Arachidonic and linoleic acid derivatives impact oocyte ICSI fertilization – a prospective analysis of follicular fluid and a matched oocyte in a ‘one follicle–one retrieved oocyte–one resulting embryo’ investigational setting. PLoS ONE e0119087. (https://doi.org/10.1371/journal.pone.0119087)

    • Search Google Scholar
    • Export Citation
  • Deems R, Buczynski MW, Bowers-Gentry R, Harkewicz R & Dennis EA 2007 Detection and quantitation of eicosanoids via high performance liquid chromatography-electrospray ionization-mass spectrometry. Methods in Enzymology 5982. (https://doi.org/10.1016/S0076-6879(07)32003-X)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Diamanti-Kandarakis E & Dunaif A 2012 Insulin resistance and the polycystic ovary syndrome revisited: an update on mechanisms and implications. Endocrine Reviews 9811030. (https://doi.org/10.1210/er.2011-1034)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Gerard N, Loiseau S, Duchamp G & Seguin F 2002 Analysis of the variations of follicular fluid composition during follicular growth and maturation in the mare using proton nuclear magnetic resonance (1H NMR). Reproduction 241248. (https://doi.org/10.1530/rep.0.1240241)

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Goldman AL, Bhasin S, Wu FCW, Krishna M, Matsumoto AM & Jasuja R 2017 A reappraisal of testosterone’s binding in circulation: physiological and clinical implications. Endocrine Reviews 302324. (https://doi.org/10.1210/er.2017-00025)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Han X, Yang J, Cheng H, Ye H & Gross RW 2004 Toward fingerprinting cellular lipidomes directly from biological samples by two-dimensional electrospray ionization mass spectrometry. Analytical Biochemistry 317331. (https://doi.org/10.1016/j.ab.2004.04.004)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Han X, Yang K, Cheng H, Fikes KN & Gross RW 2005 Shotgun lipidomics of phosphoethanolamine-containing lipids in biological samples after one-step in situ derivatization. Journal of Lipid Research 15481560. (https://doi.org/10.1194/jlr.D500007-JLR200)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Heijnen EM, Eijkemans MJ, Hughes EG, Laven JS, Macklon NS & Fauser BC 2006 A meta-analysis of outcomes of conventional IVF in women with polycystic ovary syndrome. Human Reproduction Update 1321. (https://doi.org/10.1093/humupd/dmi036)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Homburg R, Berkowitz D, Levy T, Feldberg D, Ashkenazi J & Ben-Rafael Z 1993 In vitro fertilization and embryo transfer for the treatment of infertility associated with polycystic ovary syndrome. Fertility and Sterility 858863. (https://doi.org/10.1016/s0015-0282(16)56287-6)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Huang Y, Zhu M, Li Z, Sa R, Chu Q, Zhang Q, Zhang H, Tang W, Zhang M & Yin H 2014 Mass spectrometry-based metabolomic profiling identifies alterations in salivary redox status and fatty acid metabolism in response to inflammation and oxidative stress in periodontal disease. Free Radical Biology and Medicine 223232. (https://doi.org/10.1016/j.freeradbiomed.2014.02.024)

    • Search Google Scholar
    • Export Citation
  • Huang R, Xue X, Li S, Wang Y, Sun Y, Liu W, Yin H & Tao T 2018 Alterations of polyunsaturated fatty acid metabolism in ovarian tissues of polycystic ovary syndrome rats. Journal of Cellular and Molecular Medicine 33883396. (https://doi.org/10.1111/jcmm.13614)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Iwase A, Goto M, Harata T, Takigawa S, Nakahara T, Suzuki K, Manabe S & Kikkawa F 2009 Insulin attenuates the insulin-like growth factor-I (IGF-I)-Akt pathway, not IGF-I-extracellularly regulated kinase pathway, in luteinized granulosa cells with an increase in PTEN. Journal of Clinical Endocrinology and Metabolism 21842191. (https://doi.org/10.1210/jc.2008-1948)

    • Search Google Scholar
    • Export Citation
  • Jiang C, Ting AT & Seed B 1998 PPAR-gamma agonists inhibit production of monocyte inflammatory cytokines. Nature 8286. (https://doi.org/10.1038/34184)

  • Jungheim ES, Macones GA, Odem RR, Patterson BW, Lanzendorf SE, Ratts VS & Moley KH 2011 Associations between free fatty acids, cumulus oocyte complex morphology and ovarian function during in vitro fertilization. Fertility and Sterility 19701974. (https://doi.org/10.1016/j.fertnstert.2011.01.154)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Khajeh M, Rahbarghazi R, Nouri M & Darabi M 2017 Potential role of polyunsaturated fatty acids, with particular regard to the signaling pathways of arachidonic acid and its derivatives in the process of maturation of the oocytes: contemporary review. Biomedicine and Pharmacotherapy 458467. (https://doi.org/10.1016/j.biopha.2017.07.140)

    • Search Google Scholar
    • Export Citation
  • Kim K & Ramirez VD 1986 Effects of prostaglandin E2, forskolin and cholera toxin on cAMP production and in vitro LH-RH release from the rat hypothalamus. Brain Research 258265. (https://doi.org/10.1016/0006-8993(86)90162-9)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Kim YS, Kim MS, Lee SH, Choi BC, Lim JM, Cha KY & Baek KH 2006 Proteomic analysis of recurrent spontaneous abortion: identification of an inadequately expressed set of proteins in human follicular fluid. Proteomics 34453454. (https://doi.org/10.1002/pmic.200500775)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Kolialexi A, Mavrou A, Spyrou G & Tsangaris GT 2008 Mass spectrometry-based proteomics in reproductive medicine. Mass Spectrometry Reviews 624634. (https://doi.org/10.1002/mas.20181)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Komar CM 2005 Peroxisome proliferator-activated receptors (PPARs) and ovarian function – implications for regulating steroidogenesis, differentiation, and tissue remodeling. Reproductive Biology and Endocrinology 41. (https://doi.org/10.1186/1477-7827-3-41)

    • Search Google Scholar
    • Export Citation
  • Leroy JL, Rizos D, Sturmey R, Bossaert P, Gutierrez-Adan A, Van Hoeck V, Valckx S & Bols PE 2011 Intrafollicular conditions as a major link between maternal metabolism and oocyte quality: a focus on dairy cow fertility. Reproduction, Fertility, and Development 112. (https://doi.org/10.1071/RD11901)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Li R, Zhang Q, Yang D, Li S, Lu S, Wu X, Wei Z, Song X, Wang X & Fu S et al.2013 Prevalence of polycystic ovary syndrome in women in China: a large community-based study. Human Reproduction 25622569. (https://doi.org/10.1093/humrep/det262)

    • Search Google Scholar
    • Export Citation
  • Li S, Chu Q, Ma J, Sun Y, Tao T, Huang R, Liao Y, Yue J, Zheng J & Wang L et al.2017 Discovery of novel lipid profiles in PCOS: do insulin and androgen oppositely regulate bioactive lipid production? Journal of Clinical Endocrinology and Metabolism 810821. (https://doi.org/10.1210/jc.2016-2692)

    • Search Google Scholar
    • Export Citation
  • Lu J, Chen B, Chen T, Guo S, Xue X, Chen Q, Zhao M, Xia L, Zhu Z & Zheng L et al.2017 Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases. Redox Biology 899907. (https://doi.org/10.1016/j.redox.2017.04.032)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Marei WF, Wathes DC & Fouladi-Nashta AA 2010 Impact of linoleic acid on bovine oocyte maturation and embryo development. Reproduction 979988. (https://doi.org/10.1530/REP-09-0503)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Marions L & Danielsson KG 1999 Expression of cyclo-oxygenase in human endometrium during the implantation period. Molecular Human Reproduction 961965. (https://doi.org/10.1093/molehr/5.10.961)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Martins JO, Ferracini M, Ravanelli N, Landgraf RG & Jancar S 2008 Insulin suppresses LPS-induced iNOS and COX-2 expression and NF-kappaB activation in alveolar macrophages. Cellular Physiology and Biochemistry 279286. (https://doi.org/10.1159/000149806)

    • Search Google Scholar
    • Export Citation
  • Martins JO, Wittlin BM, Anger DB, Martins DO, Sannomiya P & Jancar S 2010 Early phase of allergic airway inflammation in diabetic rats: role of insulin on the signaling pathways and mediators. Cellular Physiology and Biochemistry 739748. (https://doi.org/10.1159/000322341)

    • Search Google Scholar
    • Export Citation
  • Matoba S, Bender K, Fahey AG, Mamo S, Brennan L, Lonergan P & Fair T 2014 Predictive value of bovine follicular components as markers of oocyte developmental potential. Reproduction, Fertility, and Development 337345. (https://doi.org/10.1071/RD13007)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Narumiya S & Fukushima M 1985 delta 12-prostaglandin J2, an ultimate metabolite of prostaglandin D2 exerting cell growth inhibition. Biochemical and Biophysical Research Communications 739745. (https://doi.org/10.1016/s0006-291x(85)80005-x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Revelli A, Delle Piane L, Casano S, Molinari E, Massobrio M & Rinaudo P 2009 Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics. Reproductive Biology and Endocrinology 40. (https://doi.org/10.1186/1477-7827-7-40)

    • Search Google Scholar
    • Export Citation
  • Robker RL, Akison LK, Bennett BD, Thrupp PN, Chura LR, Russell DL, Lane M & Norman RJ 2009 Obese women exhibit differences in ovarian metabolites, hormones, and gene expression compared with moderate-weight women. Journal of Clinical Endocrinology and Metabolism 15331540. (https://doi.org/10.1210/jc.2008-2648)

    • Search Google Scholar
    • Export Citation
  • Rodgers RJ & Irving-Rodgers HF 2010 Formation of the ovarian follicular antrum and follicular fluid. Biology of Reproduction 10211029. (https://doi.org/10.1095/biolreprod.109.082941)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group 2004 Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome. Fertility and Sterility 1925. (https://doi.org/10.1016/j.fertnstert.2003.10.004)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Schaiff WT, Carlson MG, Smith SD, Levy R, Nelson DM & Sadovsky Y 2000 Peroxisome proliferator-activated receptor-gamma modulates differentiation of human trophoblast in a ligand-specific manner. Journal of Clinical Endocrinology and Metabolism 38743881. (https://doi.org/10.1210/jcem.85.10.6885)

    • Search Google Scholar
    • Export Citation
  • Schweigert FJ, Gericke B, Wolfram W, Kaisers U & Dudenhausen JW 2006 Peptide and protein profiles in serum and follicular fluid of women undergoing IVF. Human Reproduction 29602968. (https://doi.org/10.1093/humrep/del257)

    • Search Google Scholar
    • Export Citation
  • Shi Y, Wei D, Liang X, Sun Y, Liu J, Cao Y, Zhang B, Legro RS, Zhang H & Chen ZJ 2014 Live birth after fresh embryo transfer vs elective embryo cryopreservation/frozen embryo transfer in women with polycystic ovary syndrome undergoing IVF (FreFro-PCOS): study protocol for a multicenter, prospective, randomized controlled clinical trial. Trials 154. (https://doi.org/10.1186/1745-6215-15-154)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Song NY, Na HK, Baek JH & Surh YJ 2014 Docosahexaenoic acid inhibits insulin-induced activation of sterol regulatory-element binding protein 1 and cyclooxygenase-2 expression through upregulation of SIRT1 in human colon epithelial cells. Biochemical Pharmacology 142148. (https://doi.org/10.1016/j.bcp.2014.08.030)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Sorensen AE, Wissing ML, Englund AL & Dalgaard LT 2016 MicroRNA species in follicular fluid associating with polycystic ovary syndrome and related intermediary phenotypes. Journal of Clinical Endocrinology and Metabolism 15791589. (https://doi.org/10.1210/jc.2015-3588)

    • Search Google Scholar
    • Export Citation
  • Teede H, Deeks A & Moran L 2010 Polycystic ovary syndrome: a complex condition with psychological, reproductive and metabolic manifestations that impacts on health across the lifespan. BMC Medicine 41. (https://doi.org/10.1186/1741-7015-8-41)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Tokugawa Y, Kunishige I, Kubota Y, Shimoya K, Nobunaga T, Kimura T, Saji F, Murata Y, Eguchi N & Oda H et al.1998 Lipocalin-type prostaglandin D synthase in human male reproductive organs and seminal plasma. Biology of Reproduction 600607. (https://doi.org/10.1095/biolreprod58.2.600)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Valledor AF & Ricote M 2004 Nuclear receptor signaling in macrophages. Biochemical Pharmacology 201212. (https://doi.org/10.1016/j.bcp.2003.10.016)

  • Von Wald T, Monisova Y, Hacker MR, Yoo SW, Penzias AS, Reindollar RR & Usheva A 2010 Age-related variations in follicular apolipoproteins may influence human oocyte maturation and fertility potential. Fertility and Sterility 23542361. (https://doi.org/10.1016/j.fertnstert.2008.12.129)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Wang J, Shen XX, Huang XH & Zhao ZM 2012 Follicular fluid levels of prostaglandin E2 and the effect of prostaglandin E2 on steroidogenesis in granulosa-lutein cells in women with moderate and severe endometriosis undergoing in vitro fertilization and embryo transfer. Chinese Medical Journal 39853990.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Wang Y, Armando AM, Quehenberger O, Yan C & Dennis EA 2014 Comprehensive ultra-performance liquid chromatographic separation and mass spectrometric analysis of eicosanoid metabolites in human samples. Journal of Chromatography A 6069. (https://doi.org/10.1016/j.chroma.2014.07.006)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Xu J, Cao L, Suo Y, Xu X, Sun H, Xu S, Zhu X, Yu H & Cao W 2018 Chitosan-microcapsulated insulin alleviates mesenteric microcirculation dysfunction via modulating COX-2 and VCAM-1 expression in rats with diabetes mellitus. International Journal of Nanomedicine 68296837. (https://doi.org/10.2147/IJN.S174030)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Yang J, Schmelzer K, Georgi K & Hammock BD 2009 Quantitative profiling method for oxylipin metabolome by liquid chromatography electrospray ionization tandem mass spectrometry. Analytical Chemistry 80858093. (https://doi.org/10.1021/ac901282n)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • Zhu Q, Zuo R, He Y, Wang Y, Chen ZJ, Sun Y & Sun K 2016 Local regeneration of cortisol by 11beta-HSD1 contributes to insulin resistance of the granulosa cells in PCOS. Journal of Clinical Endocrinology and Metabolism 21682177. (https://doi.org/10.1210/jc.2015-3899)

    • Search Google Scholar
    • Export Citation
  • Zhuang J, Liu Y, Xu L, Liu X, Zhou L, Tang L, Kang D, Guo W, He M & Yang F et al.2014 Prevalence of the polycystic ovary syndrome in female residents of Chengdu, China. Gynecologic and Obstetric Investigation 217223. (https://doi.org/10.1159/000358485)

    • PubMed
    • Search Google Scholar
    • Export Citation

 

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    Figure 1

    Representative LC-MS chromatograms of follicular fluid (FF) specimens from patients that underwent IVF. Chromatograms of arachidonic acid metabolites in a standard mixture (A), FF from a PCOS patient (B), and an internal standard (C).

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    Figure 2

    Levels of AA and its metabolites generated in the FF from patients with PCOS and without PCOS (non-PCOS). COX, cyclooxygenase; PGD2, prostaglandin D2; PGJ2, prostaglandin J2; 15d-PGJ2, 15-deoxy-Δ12,14-prostaglandin J2; PGE2, prostaglandin E2; PGF, prostaglandin F2alpha; PGFM, prostaglandin F metabolite; PGI2, prostaglandin I2; and TXB2, thromboxane B2; LOX, lipoxidase; P450epo, cytochrome P450 epoxygenase; EETs, epoxyeicosatrienoic acids; HETEs, hydroxyeicosatetraenoic acids. Data are mean ± s.e.m. n = 30 for non-PCOS and n = 39 for PCOS. *P < 0.05, **P < 0.01 compared with group non-PCOS. The blue column represents non-PCOS and the red column represents PCOS.

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    Figure 3

    The induction role of insulin, testosterone, interleukin-1β and hCG on COX-2 expression and PGE2 production. The mRNA level of COX-2 with treatment of insulin, interleukin-1β and hCG (A). The mRNA level of COX-2 with treatment of testosterone, interleukin-1β and hCG (B). The protein level of COX-2 with treatment of testosterone, interleukin-1β and hCG (C). The PGE2 concentration of culture medium of granulosa cells treated with testosterone, interleukin-1β and hCG (D). The medicine concentrations are as followed: insulin (100 nM), testosterone (100 nM), hCG (10 IU/L) and interleukin 1β (1 ng/mL). Data are represented as mean ± s.e.m. n = 4 for each experiment. Values with a different letter above are statistically significantly different (P < 0.05). CTRL, control; INS, insulin; T, testosterone; IL1B, interleukin-1β.