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. 2019 Mar 1;9:3204. doi: 10.1038/s41598-019-38944-6

Alterations of Sphingolipid Metabolism in Different Types of Polycystic Ovary Syndrome

Juan Li 1,2, Li-Min Xie 3, Jin-Long Song 4, Lee-Fong Yau 3, Jia-Ning Mi 3, Chun-Ren Zhang 1,2, Wan-Ting Wu 1,2, Mao-Hua Lai 1,2, Zhi-Hong Jiang 3,1, Jing-Rong Wang 3,✉, Hong-Xia Ma 1,2,✉
PMCID: PMC6397209  PMID: 30824725

Abstract

The roles of sphingolipids in polycystic ovary syndrome (PCOS) are still unknown. This study aimed to investigate the sphingolipid characteristics for different types of PCOS using liquid chromatography-mass spectrometry (LC-MS). A total of 107 women with PCOS and 37 healthy women as normal controls were studied. PCOS patients were further classified into non-obesity with insulin resistance (IR) (NOIR), obesity with IR (OIR), and non-obesity and non-IR (NIR) subgroups. A total of 87 serum sphingolipids, including 9 sphingosines, 3 sphinganines, 1 sphingosine-1-phosphate (S1P), 19 ceramides (Cers), 1 ceramide-1-phosphate, 44 sphingomyelins (SMs), 4 hexosylceramides, and 6 lactosylceramides (LacCers) were analyzed using an improved sphingolipidomic approach based on LC-MS. Notable elevations in the levels of S1P, Cer, and SM were observed in PCOS patients when compared with healthy women, and SM species with long saturated acyl chains showed potential as novel biomarkers of PCOS. In addition, the level of LacCer was only elevated in NIR, and there was almost no change in NOIR and OIR. This study is the first to report the comprehensive sphingolipidomic profiling of different subgroups of PCOS with or without IR or obesity and suggests that serum sphingolipids might be useful as diagnostic biomarkers for different types of PCOS.

Introduction

Polycystic ovary syndrome (PCOS) is one of the most common endocrine and metabolic disorders in women of reproductive age, and it accounts for 50–70% of anovulatory infertility cases and affects about 5.6% of 19–45-year-old women in China1,2. The clinical manifestations are diverse and include oligomenorrhea/amenorrhea, hirsutism, acne, obesity, polycystic ovaries, and infertility2,3. PCOS is associated with insulin resistance (IR)/hyperinsulinemia, impaired glucose tolerance, and dyslipidemia4–7, and long-term complications include metabolic syndrome, endometrial and breast cancer, and other gynecological tumors8.

The etiology of PCOS remains unclear9. Pathophysiological changes include hypothalamus-pituitary-ovarian axis dysfunction, hyperandrogenism, hyperinsulinemia, insulin resistance (IR), endocrine dysfunction, adrenal dysfunction, etc.10–12. IR is central to the pathogenesis of PCOS, while glucose and lipid disorders are considered to be the general pathology13. Compensatory IR is present in about 40% of women with PCOS14 and mainly affects classical target tissues of insulin action – such as skeletal muscle, adipose, and liver – and induces systemic glucose and lipid metabolism disorders. IR is a physiological condition in which the target organs become resistant to the effects of insulin. That is, the normal response to a given amount of insulin is reduced, thus weakening insulin’s ability to regulate glucose uptake and glucose utilization15.

Several serum/plasma metabolomic studies of PCOS have been carried out using advanced analytical methods, such as liquid or gas chromatography/time-of-flight mass spectrometry (LC or GC/TOF-MS) or nuclear magnetic resonance16–19, and these studies have shown that changes in amino acid metabolism, the tricarboxylic acid cycle, and gut microflora, as well as mild perturbations in lipid and glucose metabolism, are correlated with PCOS20. A lipidomic analysis of serum/plasma samples from PCOS patients was also recently performed, and disturbances in fatty acid, glycerolipid, and glycerophospholipid metabolism were shown to be related to the pathogenesis of IR in PCOS21. In addition, the levels of very long-chain monounsaturated fatty acids were found to be reduced in PCOS patients compared with healthy subjects22. However, there has been a lack of studies focusing on sphingolipid alterations in PCOS.

Sphingolipids are a complex family of compounds that are found in eukaryotes as well as some prokaryotes and viruses, and they comprise a small but vital fraction (2–20%) of the membrane lipids23. They are involved in a variety of biological processes in eukaryotic cells24,25, such as cell proliferation, differentiation, apoptosis, and migration; membrane trafficking; cell-cell interactions; and cell morphology, as well as both intracellular and extracellular signaling26,27. However, previous studies on sphingolipids have found that the changes in the levels of sphingolipids in the body directly affect the intensity of insulin signaling28. Ceramide (Cer), ganglioside monosialo 3 (GM3), and sphingosine-1-phosphate (S1P) have significant regulatory effects on insulin signaling, and studies have shown that Cer and GM3 play negative roles in insulin signaling and promote the development of IR29,30. Conversely, S1P can enhance insulin signaling and inhibit the development of IR31. Abnormal lipid metabolism is closely related to the development of IR, and oxidative damage caused by excessive lipid accumulation can induce IR32, while sphingolipids mediate the development of IR by regulating insulin signaling molecules33. The analysis of whole-serum sphingolipids has been shown to facilitate the understanding of potential mechanisms of some diseases occurrence and development34, but the characteristics of sphingolipids in PCOS are unknown.

In the present study, we explored the potential of sphingolipids as biomarkers for PCOS using an integrated sphingolipid analytical platform that combined the advantages of ultra-high performance liquid chromatography (UHPLC)-quadrupole time-of-flight mass spectrometry and UHPLC coupled with triple quadrupole mass spectrometry (UHPLC-QQQ-MS) to qualitatively and quantitatively analyze the sphingolipids in serum samples from healthy women and from different subgroups of PCOS patients.

Results

Baseline characteristics

A total of 107 PCOS patients and 37 healthy women were enrolled. Thirty-four (31.8%) of the 107 PCOS patients presented with a body mass index (BMI) < 25 kg/m2 and homeostatic model assessment of insulin resistance (HOMA-IR) ≥ 2.14 (the non-obesity with IR (NOIR) group), 41 patients (38.3%) had BMI ≥ 25 kg/m2 and HOMA-IR ≥ 2.14 kg/m2 (the obesity with IR (OIR) group), and 32 patients (29.9%) had BMI < 25 kg/m2 and HOMA-IR < 2.14 kg/m2 (the non-obesity and non-IR (NIR) group). The demographic, endocrine, and glycolipid metabolic features of controls and patients with different types of PCOS are described in Table 1. There were no significant differences in age for any of the groups. PCOS patients in the OIR group had a significantly greater BMI, waist-to-hip ratio (WHR), and HOMA-IR; higher levels of total cholesterol (CHOL), triglycerides (TG), and low-density lipoprotein (LDL); and lower levels of high-density lipoprotein (HDL) compared to controls. Except for BMI and HDL, these characteristics were also significantly increased in the NOIR group compared with the controls. However, PCOS in the NIR group only presented with obviously increased luteinizing hormone (LH) to follicle-stimulating hormone (FSH) ratio, LH level, and total testosterone (TT) level compared with controls. Overall, these changes in PCOS patients were clinically related to PCOS type and complemented the metabolomics analysis.

Table 1.

Baseline characteristics of the three polycystic ovary syndrome (PCOS) subgroups and control subjects.

Characteristic PCOS Controls
NOIR NIR OIR
Number 34 32 41 37
Age (years) 27.88 (26.30–29.46) 28.05 (26.96–29.14) 26.97 (25.56–28.38) 28.11 (26.33–29.89)
BMI (kg/m2) 21.03 (20.51–21.56) 20.06 (19.55–20.56) 28.05 (27.02–29.07)* 20.98 (20.15–21.81)
WHR 0.83 (0.81–0.85)* 0.80 (0.78–0.81) 0.88 (0.86–0.90)* 0.79 (0.78–0.80)
HOMA-IR 3.25 (3.01–3.48)* 1.19 (1.10–1.29) 4.85 (3.99–5.71)* 1.04 (0.95–1.14)
CHOL (mg/dl) 5.00 (4.74–5.25)* 4.38 (4.10–4.67) 5.28 (4.90–5.66)* 4.38 (4.17–4.58)
TG (mg/dl) 1.30 (1.10–1.49)* 0.74 (0.68–0.81) 2.08 (1.39–2.77)* 0.78 (0.68–0.88)
HDL (mg/dl) 1.33 (1.23–1.42) 1.51 (1.40–1.61) 1.19 (1.12–1.27)* 1.43 (1.34–1.51)
LDL (mg/dl) 3.18 (2.96–3.39)* 2.61 (2.45–2.77) 3.34 (3.08–3.60)* 2.59 (2.44–2.73)
LH (mIU/ml) 9.61 (7.78–11.44)* 9.83 (7.66–12.00)* 8.71 (7.42–10.00)* 4.63 (4.08–5.19)
LH/FSH 1.60 (1.32–1.89)* 1.41 (1.10–1.71)* 1.56 (1.34–1.78)* 0.67 (0.58–0.76)
TT (ng/ml) 0.64 (0.55–0.72)* 0.60 (0.53–0.67)* 0.64 (0.57–0.72)* 0.42 (0.37–0.47)
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Notes: Data are presented as the mean and (95% confidence interval). Differences in continuous variables among groups were analyzed by ANOVA or Kruskal–Wallis test. *p < 0.05.

Abbreviations: NOIR, non-obesity with insulin resistance; OIR, obesity with insulin resistance; NIR, non-obesity and non-insulin resistance; BMI, body mass index; WHR, waist-to-hip ratio; HOMA-IR, homeostasis model assessment of insulin resistance; CHOL, total cholesterol; TG, triglycerides; HDL, high-density lipoprotein; LDL, low-density lipoprotein; LH, luteinizing hormone; FSH, follicle-stimulating hormone; TT, total testosterone.

Identification of serum sphingolipids

The sphingolipids in human serum were comprehensively profiled using an established sphingolipidomic approach23. A total of 87 sphingolipids were identified and quantified in the serum samples, including 9 sphingosines, 3 sphinganines (Sas), S1P, 19 Cers, 1 ceramide-1-phosphate (Cer1P), 44 sphingomyelins (SMs), 4 hexosylceramides (HexCers), and 6 lactosylceramides (LacCers). The MS and MS/MS data of identified sphingolipids and the multiple reaction monitoring (MRM) transitions used to monitor each sphingolipid are listed in Table 2. The MRM chromatograms of all sphingolipids in human serum are shown in Fig. 1.

Table 2.

Identification and quantification of 87 sphingolipids in human serum using UHPLC-Q-TOF and UHPLC-QQQ MS.

Q-TOF MS QQQ MS
Subclass Name RT (min) Molecular Formula Measured m/z Calculated m/z Error (ppm) MS/MS Fragments (m/z) MRM transition Fragmentor (V) CE (V)
So So (d17:1) [I.S.-1] 6.34 C17H35NO2 286.2748 286.2741 2.45 268.2649 286.4 → 268.2 80 5
So (m18:2) 8.59 C18H35NO 282.2791 282.2791 0.00 264.2691 282.3 → 264.3 80 5
So (m18:3) 7.79 C18H33NO 280.2639 280.2635 1.43 262.2542 280.3 → 262.3 80 5
So (d16:1) 4.85 C16H33NO2 272.2583 272.2584 −0.37 254.2833 272.3 → 254.3 80 5
So (d18:1) 6.71 C18H37NO2 300.2899 300.2897 0.67 282.2797 300.3 → 282.3 80 5
So (d18:2) 6.78 C18H35NO2 298.2743 298.2741 0.67 280.2630 298.3 → 280.3 80 5
So (d18:3) 6.34 C18H33NO2 296.2586 296.2584 0.68 278.2473 296.3 → 278.2 80 5
So (t18:1) 7.32 C18H37NO3 316.2841 316.2846 −1.58 298.2733 316.3 → 298.3 80 5
So (d22:3) 7.91 C22H41NO2 352.3205 352.3210 −1.42 334.3101 352.3 → 334.3 80 5
So (d22:3) isomer 7.62 C22H41NO2 352.3219 352.3210 2.55 334.3100 352.3 → 334.3 80 5
Sa Sa (d17:0) [I.S.-2] 6.57 C17H37NO2 288.2901 288.2897 1.39 270.2795, 60.0453 288.4 → 270.2 110 20
Sa (d16:0) 5.03 C16H35NO2 274.2743 274.2741 0.73 256.2653 274.3 → 256.3 110 20
Sa (d18:0) 6.34 C18H39NO2 302.3056 302.3054 0.66 284.2950 302.3 → 284.3 110 20
Sa (d20:0) 6.79 C20H43NO2 330.3376 330.3367 2.72 312.3268 330.3 → 312.3 110 20
S1P S1P (d17:1) [I.S.-3] 6.49 C17H36NO5P 366.2406 366.2404 0.55 250.2508 366.3 → 250.3 105 10
S1P (d18:1) 6.90 C18H38NO5P 380.2578 380.2560 4.73 264.2690 380.3 → 264.3 105 10
Sa1P (d17:0) [I.S.-4] 6.71 C17H38NO5P 368.2571 368.2560 2.99 270.2788 368.4 → 270.3 120 5
Cer Cer (d18:1/12:0) [I.S.-5] 10.92 C30H59NO3 482.4582 482.4568 2.90 464.4463, 282.2790, 264.2691 482.6 → 264.3 130 25
Cer (d18:0/16:0) 13.75 C34H69NO3 540.5349 540.5350 −0.19 266.2837 540.5 → 266.3 130 25
Cer (d18:0/18:0) 14.30 C36H73NO3 568.5674 568.5663 1.93 266.2831 568.6 → 266.3 130 25
Cer (d18:0/22:0) 17.00 C40H81NO3 624.6278 624.6289 −1.76 606.6, 284.2938, 266.2833 624.6 → 266.3 130 25
Cer (d18:0/23:0) 18.20 C41H83NO3 638.6446 638.6446 0.00 620.6307, 284.2939, 266.2846 638.6 → 266.3 130 25
Cer (d18:0/24:0) 19.14 C42H85NO3 652.6597 652.6602 −0.77 634.6402, 284.2925, 266.2838 652.7 → 266.3 130 25
Cer (d18:1/16:0) 13.06 C34H67NO3 538.5194 538.5194 0.00 520.5010, 282.2796, 264.2691 538.5 → 264.3 130 25
Cer (d18:1/18:0) 14.20 C36H71NO3 566.5503 566.5507 −0.71 548.5406, 264.2690 566.6 → 264.3 130 25
Cer (d18:1/18:1) 13.06 C36H69NO3 564.5340 564.5350 −1.77 264.2685 564.5 → 264.3 130 25
Cer (d18:1/20:1) 14.34 C38H73NO3 592.5670 592.5663 1.18 264.2688 592.6 → 264.3 130 25
Cer (d18:1/22:0) 17.01 C40H79NO3 622.6133 622.6133 0.00 604.6019, 264.2691 622.6 → 264.3 130 25
Cer (d18:1/23:0) 17.72 C41H81NO3 636.6285 636.6289 −0.63 618.6185, 264.2689 636.6 → 264.3 130 25
Cer (d18:1/24:0) 18.51 C42H83NO3 650.6448 650.6446 0.31 632.6343, 282.2783, 264.2691 650.6 → 264.3 130 25
Cer (d18:1/24:1) 17.02 C42H81NO3 648.6280 648.6289 −1.39 630.6188, 264.2688 648.6 → 264.3 130 25
Cer (d18:1/25:0) 19.05 C43H85NO3 664.6596 664.6602 −0.90 646.6434, 282.2795, 264.2695 664.7 → 264.3 130 25
Cer (d18:1/25:0) isomer 19.41 C43H85NO3 664.6598 664.6602 −0.60 646.6434, 282.2795, 264.2695 664.7 → 264.3 130 25
Cer (d18:1/26:0) 20.45 C44H87NO3 678.6741 678.6759 −2.65 660.6650, 264.2695 678.7 → 264.3 130 25
Cer (d18:2/16:0) 12.41 C34H65NO3 536.5044 536.5037 1.30 262.2549 536.5 → 262.3 130 25
Cer (d18:2/22:0) 16.08 C40H77NO3 620.5980 620.5976 0.64 602.5875, 262.2546 620.6 → 262.2 130 25
Cer (d18:2/23:0) 16.77 C41H79NO3 634.6115 634.6133 −2.84 262.2542 634.6 → 262.3 130 25
Cer1P (d18:1/12:0) [I.S.-6] 9.95 C30H60NO6P 562.4242 562.4231 1.96 264.2615 562.5 → 264.3 135 25
Cer1P (d18:1/18:0) 12.78 C36H72NO6P 646.5167 646.5170 −0.46 264.2611 646.5 → 264.3 135 25
SM SM (d18:1/12:0) [I.S.-7] 10.30 C35H71N2O6P 647.5124 647.5123 0.15 264.2704, 184.0741 647.5 → 184.1 170 20
SM (d18:0/18:0) 13.65 C41H85N2O6P 733.6217 733.6218 −0.14 184.0741 733.6 → 184.1 170 20
SM (d18:1/14:0) 11.08 C37H75N2O6P 675.5420 675.5436 −2.37 657.5282, 264.2670, 184.0758 675.5 → 184.1 170 20
SM (d18:1/16:0) 12.03 C39H79N2O6P 703.5735 703.5749 −1.99 685.5649, 264.2703, 184.0734 703.6 → 184.1 170 20
SM (d18:1/17:1) 11.75 C40H79N2O6P 715.5747 715.5749 −0.28 264.2670, 184.0759 715.6 → 184.1 170 20
SM (d18:1/18:0) 13.10 C41H83N2O6P 731.6056 731.6062 −0.82 713.5884, 264.2702, 184.0762 731.6 → 184.1 170 20
SM (d18:1/18:2) 11.60 C41H79N2O6P 727.5737 727.5749 −1.65 264.2671, 184.0749 727.6 → 184.1 170 20
SM (d18:1/20:0) 14.37 C43H87N2O6P 759.6356 759.6375 −2.50 741.6249, 264.2674, 184.0757 759.6 → 184.1 170 20
SM (d18:1/22:0) 15.60 C45H91N2O6P 787.6680 787.6688 −1.02 769.6525, 264.2690, 184.0761 787.7 → 184.1 170 20
SM (d18:1/23:0) 16.36 C46H93N2O6P 801.6833 801.6844 −1.37 264.2675, 184.0744 801.7 → 184.1 170 20
SM (d18:1/23:1) 15.18 C46H91N2O6P 799.6673 799.6688 −1.88 264.2680, 184.0764 799.7 → 184.1 170 20
SM (d18:1/24:0) 16.90 C47H95N2O6P 815.6989 815.7001 −1.47 264.2612, 184.0729 815.7 → 184.1 170 20
SM (d18:1/24:1) 16.10 C47H93N2O6P 813.6825 813.6844 −2.34 795.6724, 264.2606, 184.0759 813.7 → 184.1 170 20
SM (d18:1/26:1) 17.02 C49H97N2O6P 841.7166 841.7157 1.07 264.2602, 184.0761 841.7 → 184.1 170 20
SM (d18:2/16:0) 11.31 C39H77N2O6P 701.5585 701.5592 −1.00 683.5426, 262.2520, 184.0763 701.6 → 184.1 170 20
SM (d18:2/16:1) 10.79 C39H75N2O6P 699.5423 699.5436 −1.86 262.2523, 184.0765 699.5 → 184.1 170 20
SM (d18:2/18:0) 12.31 C41H81N2O6P 729.5893 729.5905 −1.64 711.5798, 262.2545, 184.0761 729.6 → 184.1 170 20
SM (d16:1/24:1) 14.50 C45H89N2O6P 785.6548 785.6531 2.16 236.2379, 184.0744 785.7 → 184.1 170 20
SM (d18:2/22:0) 14.70 C45H89N2O6P 785.6545 785.6531 1.78 262.2533, 184.0742 785.7 → 184.1 170 20
SM (d18:2/22:1) 13.60 C45H87N2O6P 783.6383 783.6375 1.02 262.2536, 184.0743 783.6 → 184.1 170 20
SM (d18:2/23:0) 15.41 C46H91N2O6P 799.6710 799.6688 2.75 262.2535, 184.0745 799.7 → 184.1 170 20
SM (d18:2/24:0) 15.77 C47H93N2O6P 813.6855 813.6844 1.35 262.2527, 184.0743 813.7 → 184.1 170 20
SM (d18:2/24:1) 14.80 C47H91N2O6P 811.6701 811.6688 1.60 262.2535, 184.0743 811.7 → 184.1 170 20
SM (d18:2/25:0) 16.21 C48H95N2O6P 827.6995 827.7001 −0.72 262.2548, 184.0741 827.7 → 184.1 170 20
SM (d18:2/25:0) isomer-1 16.42 C48H95N2O6P 827.6989 827.7001 −1.45 262.2548, 184.0741 827.7 → 184.1 170 20
SM (d18:2/25:0) isomer-2 16.72 C48H95N2O6P 827.7022 827.7001 2.54 262.2548, 184.0741 827.7 → 184.1 170 20
SM (d32:0) 11.43 C37H77N2O6P 677.5580 677.5592 −1.77 184.0740 677.6 → 184.1 170 20
SM (d33:0) 11.90 C38H79N2O6P 691.5761 691.5749 1.74 184.0739 691.6 → 184.1 170 20
SM (d33:1) 11.51 C38H77N2O6P 689.5606 689.5592 2.03 184.0744 689.6 → 184.1 170 20
SM (d34:0) 12.43 C39H81N2O6P 705.5924 705.5905 2.69 184.0745 705.6 → 184.1 170 20
SM (d35:0) 13.20 C40H83N2O6P 719.6050 719.6062 −1.67 184.0744 719.6 → 184.1 170 20
SM (d35:1) 12.54 C40H81N2O6P 717.5914 717.5905 1.25 184.0741 717.6 → 184.1 170 20
SM (d35:1) isomer 12.37 C40H81N2O6P 717.5918 717.5905 1.81 184.0754 717.6 → 184.1 170 20
SM (d37:1) 13.76 C42H85N2O6P 745.6223 745.6218 0.67 184.0740 745.6 → 184.1 170 20
SM (d37:2) 12.85 C42H83N2O6P 743.6081 743.6062 2.56 184.0733 743.6 → 184.1 170 20
SM (d38:0) 14.90 C43H89N2O6P 761.6530 761.6531 −0.13 184.0746 761.7 → 184.1 170 20
SM (d38:2) 13.46 C43H85N2O6P 757.6231 757.6218 1.72 184.0745 757.6 → 184.1 170 20
SM (d39:2) 14.09 C44H87N2O6P 771.6387 771.6375 1.56 184.0734 771.6 → 184.1 170 20
SM (d40:0) 16.10 C45H93N2O6P 789.6847 789.6844 0.38 184.0742 789.7 → 184.1 170 20
SM (d41:0) 16.85 C46H95N2O6P 803.7001 803.7001 0.00 184.0739 803.7 → 184.1 170 20
SM (d41:3) 14.31 C46H89N2O6P 797.6529 797.6531 −0.25 184.0737 797.7 → 184.1 170 20
SM (d42:4) 14.00 C47H89N2O6P 809.6553 809.6531 2.72 184.0744 809.7 → 184.1 170 20
SM (d43:1) 17.62 C48H97N2O6P 829.7169 829.7157 1.45 184.0747 829.7 → 184.1 170 20
SM (d43:1) isomer 17.35 C48H97N2O6P 829.7165 829.7157 0.96 184.0728 829.7 → 184.1 170 20
SM (t44:4) 14.82 C49H93N2O7P 853.6787 853.6793 −0.70 184.0730 853.7 → 184.1 170 20
HexCer GalCer (d18:1/12:0) [I.S.-8] 10.34 C36H69NO8 644.5107 644.5096 1.71 264.2684 644.5 → 264.3 130 30
HexCer (d18:1/20:0) 14.30 C44H85NO8 756.6327 756.6348 −2.78 264.2685 756.6 → 264.3 130 30
HexCer (d18:1/22:0) 15.60 C46H89NO8 784.6659 784.6661 −0.25 264.2689 784.7 → 264.3 130 30
HexCer (d18:1/23:0) 16.30 C47H91NO8 798.6805 798.6817 −1.50 264.2676 798.7 → 264.3 130 30
HexCer (d18:1/24:0) 16.90 C48H93NO8 812.6973 812.6974 −0.12 264.2685 812.7 → 264.3 130 30
LacCer (d18:1/12:0) [I.S.-9] 10.13 C42H79NO13 806.5640 806.5624 1.98 788.5498, 482.4589, 264.2683 806.7 → 264.3 145 40
LacCer (d18:1/16:0) 10.96 C46H87NO13 862.6259 862.6250 1.04 844.6139, 538.5174, 264.2687 862.6 → 264.3 145 40
LacCer (d18:1/18:0) 11.33 C48H91NO13 890.6549 890.6563 −1.57 264.2696 890.7 → 264.3 145 40
LacCer (d18:1/20:0) 16.95 C50H95NO13 918.6860 918.6876 −1.74 264.2688 918.7 → 264.3 145 40
LacCer (d18:1/22:0) 15.00 C52H99NO13 946.7192 946.7189 0.32 264.2679 946.7 → 264.3 145 40
LacCer (d18:1/24:0) 16.30 C54H103NO13 974.7512 974.7502 1.03 264.2672 974.8 → 264.3 145 40
LacCer (d18:1/24:1) 15.10 C54H101NO13 972.7323 972.7346 −2.36 264.2650 972.7 → 264.3 145 40
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Notes: Abbreviations: MRM, multiple reaction monitoring; RT, retention time; CE, collision energy; So, sphingosine; Sa, sphinganine; S1P, sphingosine-1-phosphate; Cer, ceramide; Cer1P, ceramide-1-phosphate; SM, sphingomyelin; GalCer, galactosylceramide; HexCer, hexosylceramide; LacCer, lactosylceramide. I.S. -1–9 represent the nine internal standards added for MS analysis.

Figure 1.

Figure 1

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MRM chromatograms of 87 sphingolipids in human serum.

Differences in serum sphingolipidomes between PCOS patients and healthy women

As shown in Fig. 2a, the total sphingolipid content in PCOS patients showed a significant increase (15.9% increase) when compared with healthy women. Among the sphingolipids, three subclasses demonstrated remarkable elevations in PCOS patients, including S1P (10.8% increase), Cer (12.2% increase), and SM (16.3% increase). Sa was the only subclass showing a decrease in PCOS patients. Multivariate analysis was subsequently carried out to discriminate between PCOS patients and healthy women. As shown in Fig. 2b, the three-dimensional (3D) orthogonal partial least squares discriminant analysis (OPLS-DA) score plot demonstrated a clear separation between the PCOS group and the healthy group (R2X = 0.523, R2Y = 0.697, Q2 = 0.533). Sphingolipids with a variable importance plot (VIP) value > 1.5 were regarded as the important variables contributing to the 3D OPLS-DA model. As a result, 7 sphingolipids, including 6 SMs (SM (d40:0), SM (d38:0), SM (d18:1/22:0), SM (d18:1/24:0), SM (d41:0), and SM (d18:1/23:0)) and 1 Cer (Cer (d18:0/24:0)) were selected as potential biomarkers (Fig. 2c).

Figure 2.

Figure 2

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(a) The levels of total sphingolipids and of each subclass of sphingolipid in healthy women (n = 37) and PCOS patients (n = 107). Each column represents the mean ± SD (*p < 0.05, ***p < 0.001). So, sphingosine; Sa, sphinganine; S1P, sphingosine-1-phosphate; Cer, ceramide; Cer1P, ceramide-1-phosphate; SM, sphingomyelin; HexCer, hexosylceramide; LacCer, lactosylceramide. (b) The 3D OPLS-DA score plot for the healthy group (n = 37) and the PCOS group (n = 107) (R2X = 0.523, R2Y = 0.697, Q2 = 0.533). (c) The potential biomarkers (SM (d40:0), SM (d38:0), SM (d18:1/22:0), Cer (d18:0/24:0), SM (d18:1/24:0), SM (d41:0), and SM (d18:1/23:0)) for the classification between the healthy group and the PCOS group. Each column represents the mean ± SD (***p < 0.001).

Differences in serum sphingolipidomes between different subgroups of PCOS and healthy women

The PCOS group was classified into three subgroups (OIR, NOIR, NIR) as described above for further comparison with the healthy group. As shown in Fig. 3, the levels of total sphingolipids and of each sphingolipid subclass in all three subgroups of PCOS followed similar trends as the overall PCOS group. Notably, OIR showed the most obvious elevation (23.83%) in the total sphingolipid level when compared to the healthy group. All three subgroups of PCOS demonstrated significant increases in the level of SM (OIR > NOIR > NIR), while only NOIR and OIR showed significant increases in the level of Cer (OIR > NOIR), and only OIR showed significant increases in the level of S1P. The level of Sa was decreased in all three subgroups of PCOS, in which only OIR demonstrated a significant change. Unexpectedly, the level of LacCer was only elevated in NIR (28.72%), and there was almost no change in NOIR and OIR.

Figure 3.

Figure 3

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Box and whiskers plot showing the levels of total sphingolipids and of each subclass of sphingolipid in healthy women (n = 37), NIR PCOS patients (n = 32), NOIR PCOS patients (n = 34), and OIR PCOS patients (n = 41). *p < 0.05, **p < 0.01, ***p < 0.001. So, sphingosine; Sa, sphinganine; S1P, sphingosine-1-phosphate; Cer, ceramide; Cer1P, ceramide-1-phosphate; SM, sphingomyelin; HexCer, hexosylceramide; LacCer, lactosylceramide.

Differences in serum sphingolipidomes among different subgroups of PCOS patients

Multivariate statistical analysis was carried out to discriminate between NIR, NOIR, and OIR. Figure 4a shows the 3D OPLS-DA score plot of NOIR and NIR (R2X = 0.499, R2Y = 0.691, Q2 = 0.301), and 3 sphingolipids, including 2 LacCers (LacCer (d18:1/16:0) and LacCer (d18:1/24:1)) and 1 Cer (Cer (d18:1/24:1)), were identified as potential markers (Fig. 4b). Figure 4c shows the 3D OPLS-DA score plot of NOIR and OIR (R2X = 0.481, R2Y = 0.415, Q2 = 0.113), and 1 Cer (Cer (d18:1/25:0)) was identified as a potential marker (Fig. 4d). Figure 4e shows the 3D OPLS-DA score plot of NIR and OIR (R2X = 0.516, R2Y = 0.534, Q2 = 0.416), and 6 sphingolipids, including 3 Cers (Cer (d18:1/22:0), Cer (d18:0/24:0), and Cer (d18:1/24:1)), 2 SMs (SM (d40:0) and SM (d38:0)), and 1 LacCer (LacCer (d18:1/16:0)) were identified as potential markers (Fig. 4f).

Figure 4.

Figure 4

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(a) The 3D OPLS-DA score plot for NOIR patients (n = 34) and NIR patients (n = 32) (R2X = 0.499, R2Y = 0.691, Q2 = 0.301). (b) The potential markers (LacCer (d18:1/16:0), LacCer (d18:1/24:1), and Cer (d18:1/24:1)) for the classification between NOIR patients and NIR patients. Each column represents the mean ± SD. *p < 0.05, ***p < 0.001. (c) The 3D OPLS-DA score plot for NOIR patients (n = 34) and OIR patients (n = 41) (R2X = 0.481, R2Y = 0.415, Q2 = 0.113). (d) The potential marker (Cer (d18:1/25:0)) for the classification between NOIR patients and OIR patients. The columns represent the mean ± SD. *p < 0.05. (e) The 3D OPLS-DA score plot for NIR patients (n = 32) and OIR patients (n = 41) (R2X = 0.516, R2Y = 0.534, Q2 = 0.416). (f) The potential markers (Cer (d18:1/22:0), SM (d40:0), Cer (d18:0/24:0), Cer (d18:1/24:1), SM (d38:0), and LacCer (d18:1/16:0)) for the classification between NIR patients and OIR patients. Each column represents the mean ± SD. **p < 0.01, ***p < 0.001.

Discussion

In this study, the serum sphingolipids in healthy controls and PCOS patients were comprehensively investigated using the improved LC-MS–based sphingolipidomic approach23. As a result, 87 sphingolipids were identified and quantified in each sample. Notable elevations in the levels of S1P, Cer, and SM were observed in PCOS patients, and these made the largest contribution to the significant increase in the total sphingolipid content in PCOS patients. Our results are in accordance with a previous study that suggested that PCOS is associated with increased TG and SM and decreased phosphatidylethanolamines and lysophosphatidylcholines in patient plasma35. The multivariate analysis between PCOS patients and healthy women also suggested that SM was the most dominant subclass of sphingolipid involved in the pathogenesis of PCOS because 6 out of 7 potential markers were SMs. Notably, all potential markers, including the one Cer marker, have saturated acyl chains. A previous report showed that the increase in SM species with long saturated acyl chains (18:0, 20:0, 22:0, and 24:0) was closely correlated with the development of metabolic syndrome associated with lipid metabolism, obesity, and IR36. Therefore, we suggest that SM species with long saturated acyl chains might serve as novel biomarkers of PCOS, and further studies should be carried out to confirm this.

In addition to PCOS, other metabolic diseases such as obesity and IR have also been shown to be associated with lipid alterations37. Therefore, we further divided the PCOS patients into three subgroups (NIR, NOIR, OIR) according to their HOMA-IR and BMI values. NIR represented the group without IR or obesity, NOIR represented the group with IR only, and OIR represented the group with both IR and obesity. The levels of total sphingolipids and of each subclass in all three subgroups of PCOS followed similar trends as for all PCOS patients combined, while the subgroups of PCOS with IR or obesity exhibited greater changes than their corresponding subgroups without IR or obesity. As mentioned above, an increase in SM species with long saturated acyl chains was closely associated with lipid metabolism, obesity, and IR. Therefore, the presence of IR or both IR and obesity contributed to the increase in the level of SM in the order of OIR > NOIR > NIR. In addition, plasma Cer was reported to be elevated in obese subjects with type 2 diabetes mellitus, and increased levels of plasma Cer might also be a marker of IR38. However, in our study the occurrence of PCOS seems to have no direct relationship with Cer, and only NOIR and OIR showed significant increases in the level of Cer (OIR > NOIR). Furthermore, S1P was also reported to be elevated in the plasma of obese subjects and to correlate with IR39, and this is the likely explanation for why only OIR demonstrated a significant increase in the level of S1P in our study.

No previous report has discussed the relation between Sa and PCOS. However, because Sa is upstream of Cer in the metabolism pathway of sphingolipids, we speculate that the decrease we observed in Sa might be the result of the upregulation of Cer synthases leading to the accumulation of Cer and further downstream products. However, further studies are needed to confirm this hypothesis.

It is interesting that the level of LacCer was only elevated in NIR, while there was almost no change in NOIR and OIR. This implies that the level of LacCer was significantly increased in PCOS patients who did not suffer from IR and obesity. However, previous studies indicated that there is a negative correlation between gangliosides (complex glycosphingolipids) and insulin responsiveness40, and it was observed that inhibition of glucosylceramide synthase activity reversed IR in several rodent models of obesity41. Therefore, in theory the level of LacCer would be expected to be increased in PCOS patients with IR. However, up to now there have been no studies to investigate the direct interaction of LacCer on insulin responsiveness and the relationship between glucosylceramide synthase activity and IR in humans. Thus the results of the subgroup analysis further suggest that PCOS patients have unique sphingolipid biomarkers that are not caused only by obesity and IR.

In the multivariate statistical analysis of sphingolipid alterations among the three subgroups of PCOS, it was found that the discrimination between the three subgroups of PCOS was unsatisfactory, especially between NOIR and OIR. Only a single sphingolipid showed a significant difference between NOIR and OIR, and this might be explained by the close relationship between IR and obesity, which often cause similar alterations in sphingolipid metabolism. The differentiation between NIR and OIR was comparatively better. These results suggested that alterations in sphingolipid metabolism might play a role in the pathogenesis of PCOS and that sphingolipids might be useful as diagnostic biomarkers for different types of PCOS.

This study represents the first report of a comprehensive sphingolipidomic profiling of PCOS and different subgroups of PCOS with or without IR and/or obesity. The results shed light on the diagnosis and pathogenesis of PCOS. A limitation of the study is that we only detected some of the sphingolipid characteristics for different types of PCOS patients, and the mechanism of alterations of sphingolipid metabolism in PCOS needs further investigation in both human subjects and animal models.

Materials and Methods

Study Participants

PCOS patients aged 18 to 40 years were recruited between January 2014 and May 2015 from the Department of Traditional Chinese Medicine of the First Affiliated Hospital of Guangzhou Medical University. The first woman was recruited on January 2, 2014, and the last one was on May 28, 2015. Age-matched healthy female subjects were selected from community volunteers. PCOS was diagnosed as having two of the following three Rotterdam criteria42: (1) oligomenorrhea/amenorrhea; (2) more than 12 follicles ≤9 mm in diameter or ovarian volume >10 ml on pelvic scanning; and (3) clinical or biochemical hyperandrogenism. Oligomenorrhea is defined as an intermenstrual interval >35 days or <8 menstrual bleedings in the past year. Amenorrhea is defined as an intermenstrual interval >90 days. Biochemical hyperandrogenism is defined as a TT level ≥ 0.6 ng/ml43, and clinical hyperandrogenism is defined as a Ferriman–Gallwey score ≥ 544. Women were excluded if they had other endocrine disorders such as hyperprolactinemia, type I or type II diabetes mellitus, non-classic congenital adrenal hyperplasia, suspected Cushing’s syndrome, androgen-secreting tumors, thyroid diseases, or drug-induced androgen excess. Women who had received any hormonal treatments, Chinese herbal prescriptions, or acupuncture treatments in the past 3 months were also excluded from the study. All controls had regular menstrual cycles and normal hormone levels.

Eligible PCOS patients were further categorized as obese if they had a BMI ≥ 25 (kg/m2) according to the World Health organization (WHO) criteria for Asians45 and were categorized as insulin resistant if they had a HOMA-IR (calculated as [fasting glucose] × [fasting insulin]/22.5)) ≥ 2.1446.

This study was approved by the ethics committee of the First Affiliated Hospital of Guangzhou Medical University (No. 2013–39 and 2016–64). Informed written consent was obtained from all subjects before inclusion.

Body conditions and detection of substances related to endocrine, glucose, and lipid metabolism

The height, weight, waist circumference, hip circumference, and hirsutism scores of all women were recorded, and blood samples were collected in the first 2–5 days of their menstrual cycle at 08.00–10.00 in the morning after fasting for 12 hours. The serum samples were batched and analyzed in the laboratory in the First Affiliated Hospital of Guangzhou Medical University, and serum FSH, LH, estradiol (E2), TT, prolactin, TG, CHOL, LDL, HDL, fasting plasma glucose, and fasting insulin were measured. The intra-assay and inter-assay coefficients of variation were less than 5%. HOMA-IR was calculated to assess changes in insulin sensitivity40. FSH, LH, and TT levels were measured with a Beckman-Coulter Unicel DXi800 automatic chemiluminescence analyzer (Beckman Coulter, Brea, USA), and TG, CHOL, LDL, and HDL levels were measured on a Beckman-Coulter AU5800 automatic biochemical analyzer. Fasting insulin was analyzed using the Modular E170® automatic electrochemiluminescent analyzer (Roche Diagnostics, Mannheim, Germany). Fasting plasma glucose was measured on a Beckman Coulter LX20 automatic biochemical analyzer. All assays were performed based on the instructions of manufacturers and with reagents and materials provide by the manufacturers.

Sample collection and processing

All of the blood samples were collected by staff in the First Affiliated Hospital of Guangzhou Medical University. The blood samples were 5 ml and were centrifuged for 15 minutes at 3,000 rpm within 30 minutes after the blood samples were drawn. The separated serum was stored at −80 °C and was delivered to the State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, within 3 months of being collected.

Sample preparation and sphingolipidomic assays

Extraction of sphingolipids

Serum sphingolipids were extracted using an established method23. Briefly, 20 μl of serum was transferred into a borosilicate glass tube, and 10 μl of internal standards (2.5 μM each) and 0.75 ml of extraction solvent [methanol (MeOH): chloroform, 2:1, v/v] were added. The contents were dispersed in an ultrasonicator at room temperature for 30 seconds, followed by incubation at 48 °C for 12 hours. After cooling, 75 μl of potassium hydroxide in MeOH (1 M) was added and incubated with shaking at 37 °C for 2 hours, after which 3 μl acetic acid was added to neutralize the extract. After centrifugation, the supernatant was stored in a 4 ml bottle, and the residue was re-extracted twice. Finally, the extract was dried by nitrogen and re-dissolved in 150 μl of MeOH for liquid chromatography-mass spectrometry (LC-MS) detection. The quality control (QC) sample was pooled with equal quantities of samples from the different groups for the sphingolipid analysis.

Detection of sphingolipids by LC-MS

Serum sphingolipids were detected with the improved LC-MS–based sphingolipidomic approach23. The chromatographic separation of sphingolipids was performed on an Agilent 1290 Infinity UHPLC system (Santa Clara, CA, USA) with an Agilent Eclipse Plus C18 column (100 mm × 2.1 mm, 1.8 μm) at 40 °C. The mobile phase consisted of (A) MeOH/H2O/formic acid (HCOOH) (60:40:0.2, v/v/v) and (B) MeOH/isopropyl alcohol/HCOOH (60:40:0.2, v/v/v), both containing 10 mM NH4OAc. Qualitative analysis of sphingolipids was performed on an Agilent ultra high definition (UHD) 6550 quadrupole time-of-flight (Q-TOF) MS (Santa Clara, CA, USA). The MS source parameters were as follows: drying gas (nitrogen) temperature 200 °C, drying gas flow 11 L/min, sheath gas (nitrogen) temperature 300 °C, sheath gas flow 12 L/min, capillary voltage 4000 V, nozzle voltage 200 V, nebulizer pressure 40 psi, skimmer voltage 65 V, octopole RF peak 500 V, and fragmentor voltage 175 V. The targeted MS/MS collision energy was set at 20–60 eV. MS spectra and MS-MS spectra were acquired in positive mode with the mass range of m/z 110–1700 and m/z 40–1700, respectively. A reference solution was nebulized for continuous calibration using the reference mass of m/z 922.0098. Quantitative analysis of sphingolipids was carried out on an Agilent 6460 triple quadrupole (QQQ) MS. The MS source parameters were as follows: drying gas (nitrogen) temperature 325 °C, drying gas flow 11 L/min, capillary voltage 4000 V, and nebulizer pressure 30 psi. The optimized parameters for each individual sphingolipid, such as characteristic transition (precursor ion → product ion), fragmentor voltage, and collision energy are shown in Table 2.

Data analysis

An in-house sphingolipid database has been established in our laboratory based on the Agilent MassHunter Personal Compound Database and Library software and information from the LIPID MAPS Lipidomics Gateway. Using this customized sphingolipid database and the “find-by-formula” option in the MassHunter Qualitative Analysis Software (version B.06.00), potential sphingolipids were identified based on a comparison of accurate mass, abundance of the isotopes, and isotope spacing with the calculated theoretical masses and abundances. The structures of potential identified sphingolipids were further determined according to the characterized fragments obtained from high-resolution MS/MS data.

The raw data for quantitative analysis were processed with Agilent MassHunter Quantitative Analysis B.06.00 software. The resulting data were first transferred into a Microsoft Excel-type spreadsheet and then imported into the SIMCA-P+ 14.0 software (Umetrics, Umea, Sweden) for multivariate statistical analysis. Principal component analysis (PCA) was used to visualize general clustering among the different groups. 3D OPLS-DA was carried out to identify differences in sphingolipid expression between the different groups based on their VIP values. Variables that were significantly changed among different samples were selected as potential biomarkers based on VIP > 1.5 and then validated using t-test analysis.

Analysis of variance (ANOVA) or Kruskal–Wallis tests were performed to examine the differences in the clinical characteristics among the different groups using the SPSS version 21.0 software (SPSS Inc., Chicago, IL, USA). Values are shown as the mean and 95% confidence interval, and a value of p < 0.05 was considered statistically significant.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (Reference: 2013039 and 2016064) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Conclusion

In conclusion, remarkable elevations in the levels of S1P, Cer, and SM were observed in PCOS patients compared to healthy women. Notably, SM (d40:0), SM (d38:0), SM (d18:1/22:0), SM (d18:1/24:0), SM (d41:0) and Cer (d18:0/24:0) showed the most significant alterations, which showed that SM species with long saturated acyl chains were the best candidates to serve as novel biomarkers of PCOS. Our results are in accordance with previous studies suggesting that PCOS is associated with increased SM and that SM species with long saturated acyl chains are closely correlated with the development of metabolic syndrome, obesity, and IR. In all three subgroups of PCOS (NIR, NOIR, OIR), the alteration of sphingolipid levels followed a similar trend as the overall PCOS group except for LacCer, which was only elevated in NIR. Our results suggest that serum sphingolipids might be useful as diagnostic biomarkers for different subgroups of PCOS.

Acknowledgements

We thank Professor Ernest Hung Yu Ng for language correction and critical review of the manuscript. This study was funded by the Natural Science Foundation of Guangdong Province, China (grant number 2015A030310508), the Program for Doctor Startup of Guangzhou Medical University (grant number 2014C29), and the Macao Science and Technology Development Fund (grant number 023/2016/AFJ to WJR).

Author Contributions

J.L., L.X. and J.S. contributed equally to this work. H.M. and J.W. conceived and designed the study. J.L., L.X., J.S. and J.W. drafted and critically revised the manuscript for important intellectual content. J.W., L.X. and J.M. finished the sample preparation and sphingolipidomic assays. C.Z. and W.W. collected and handled the samples. H.M., J.L. and J.W. sought funding and ethics approval. Z.J. and L.Y. provided the technical platform and support. All of the authors contributed to the writing of the manuscript and approved the final manuscript.

Competing Interests

The authors declare no competing interests.

Footnotes

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Jing-Rong Wang, Email: jrwang@must.edu.mo.

Hong-Xia Ma, Email: doctorhongxia@126.com.

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