Detection of urine metabolites in polycystic ovary syndrome by UPLC triple-TOF-MS

Wang, Wencui; Wang, Shenglin; Tan, S.G.; Wen, Meiqin; Qian, Yanzhi; Zeng, Xiaofang; Guo, Yanlei

doi:10.1016/j.cca.2015.06.008

Cited by 26 publications

(24 citation statements)

References 25 publications

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“…Previous metabolomic studies using plasma, serum, urine and follicular fluids suggested marked metabolic shifts associated with PCOS disease. In these studies, metabolomics techniques have been applied in PCOS patients suffering from obesity, insulin resistance, cardiovascular disease or treated with polytherapy in order to refine their molecular traits [ 44 , 45 , 47 , 49 – 55 ]. The results suggested some particular changes in lipid profile, and different levels of free fatty acids, phosphoglycerides, and sphingolipids are recurrent findings.…”

Section: Discussionmentioning

confidence: 99%

“…More recently, metabolomics has offered a new perspective to study PCOS [ 44 , 45 ], because it is closer to the actual phenotype than either both genomics/transcriptomics or proteomics. This approach allows to identify in plasma/serum and urine samples metabolites involved mostly in carbohydrate, lipid, and amino acid metabolism, as well as steroid hormone metabolism, as potential biomarkers for different PCOS phenotypes [ 46 – 49 ] or PCOS patients with other pathologies associated (e.g. overweight/obesity [ 48 , 50 ] or insulin resistance or type 2 diabetes [ 51 – 55 ]).…”

Section: Introductionmentioning

confidence: 99%

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Lipidomics reveals altered biosynthetic pathways of glycerophospholipids and cell signaling as biomarkers of the polycystic ovary syndrome

et al. 2017

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PurposeIn this work, a non-targeted approach was used to unravel changes in the plasma lipidome of PCOS patients. The aim is to offer new insights in PCOS patients strictly selected in order to avoid confounding factors such as dyslipemia, obesity, altered glucose/insulin metabolism, cardiovascular disease, or cancer.ResultsMultivariate statistics revealed a specific lipidomic signature for PCOS patients without associated pathologies. This signature implies changes, mainly by down-regulation, in glycerolipid, glycerophospholipid and sphingolipid metabolism suggesting an altered biosynthetic pathway of glycerophospholipids and cell signaling as second messengers in women with PCOS.ConclusionsOur study confirms that a lipidomic approach discriminates a specific phenotype from PCOS women without associated pathologies from healthy controls.MethodsIn a cross-sectional pilot study, data were obtained from 34 subjects, allocated to one of two groups: a) lean, healthy controls (n = 20), b) PCOS patients (n = 14) with diagnosis based on hyperandrogenaemia, oligo-anovulation and abnormal ovaries with small follicular cysts. A detailed biochemical characterization was made and lipidomic profiling was performed via an untargeted approach using LC-ESI-QTOF MS/MS.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lipidomics reveals altered biosynthetic pathways of glycerophospholipids and cell signaling as biomarkers of the polycystic ovary syndrome

et al. 2017

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“…Studies using NMR or/and GC-MS found carbohydrate, fat, and protein metabolism disturbance in PCOS plasma [ 9 – 12 ]. Additional abnormalities including saturated and unsaturated fatty acids, fatty acid amides, sulfated steroid, lysophosphatidylcholines, lysophosphatidyl ethanolamines, and carnitine were discovered by ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) [ 13 – 16 ]. Almost all these articles studied on human sera, except one [ 16 ] looked into urine metabolites.…”

Section: Introductionmentioning

confidence: 99%

Follicular metabolic changes and effects on oocyte quality in polycystic ovary syndrome patients

et al. 2017

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Polycystic ovary syndrome (PCOS) is a common complex and heterogeneous disorder, affecting up to 10% women at reproductive age. It causes three fourth of the ovulatory infertility and PCOS patients often give poor IVF quality. Although some metabolic profiles have been investigated in PCOS patient sera and urine, the follicular fluid, providing fruitful biochemical information about oocyte environment during development has been ignored. In this work, based on NMR metabolomics approach, metabolic profile of follicular fluid of PCOS patients has been explored and compared with healthy controls. Significant increases of glycoprotein, acetate, cholesterol, significant decreases of lactic acid, glutamine, pyruvate, and alanine, have been discovered in PCOS follicular fluids. Furthermore, the Pearson correlations analysis indicated significant relationship existed between ART results and NMR detected follicular metabolites. All these results indicated that PCOS may induce dyslipidemia, low-grade inflammation, and disorder of glycolysis, pyruvate and amino acid metabolism in follicular fluids.

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“…Therefore, any detected differences could have been due to obesity and obesity-related insulin resistance, rather than to PCOS. In addition, only 3 nontargeted metabolomics studies included a limited targeted quantitative approach (15, 17, 22) to further validate candidate pathways and correlations with PCOS characteristics.…”

Section: Introductionmentioning

confidence: 99%

Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome

et al. 2017

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Objective Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Methods Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. Results This multiethnic, obese sample was matched by age (PCOS, 37 ± 6; MetS, 40 ± 6 years) and body mass index (BMI) (PCOS, 34.6 ± 5.1; MetS, 33.7 ± 5.2 kg/m2). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P = .02), essential amino acids (P = .03), the essential amino acid lysine (P = .02), and the lysine metabolite α-aminoadipic acid (P = .02) in models adjusted for surrogate variables representing technical variation in metabolites. No significant differences between groups were observed in concentrations of free fatty acids or vitamin D metabolites. Evaluation of the relationship of metabolites with clinical characteristics showed 1) negative associations of essential and BCAA with insulin sensitivity and sex hormone–binding globulin and 2) positive associations with homeostasis model of insulin resistance and free testosterone; metabolites were not associated with BMI or percent body fat. Conclusions PCOS was associated with significant metabolic alterations not attributed exclusively to androgen-related pathways, obesity, or MetS. Concentrations of essential amino acids and BCAA are increased in PCOS, which might result from or contribute to their insulin resistance.

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Detection of urine metabolites in polycystic ovary syndrome by UPLC triple-TOF-MS

Cited by 26 publications

References 25 publications

Lipidomics reveals altered biosynthetic pathways of glycerophospholipids and cell signaling as biomarkers of the polycystic ovary syndrome

Lipidomics reveals altered biosynthetic pathways of glycerophospholipids and cell signaling as biomarkers of the polycystic ovary syndrome

Follicular metabolic changes and effects on oocyte quality in polycystic ovary syndrome patients

Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome

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