Dataset Information

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

ABSTRACT:

Purpose

In 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.

Results

Multivariate 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.

Conclusions

Our study confirms that a lipidomic approach discriminates a specific phenotype from PCOS women without associated pathologies from healthy controls.

Methods

In 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.

SUBMITTER: Jove M

PROVIDER: S-EPMC5796992 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

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

Jové Mariona M Pradas Irene I Naudí Alba A Rovira-Llopis Susana S Bañuls Celia C Rocha Milagros M Portero-Otin Manuel M Hernández-Mijares Antonio A Victor Victor M VM Pamplona Reinald R

Oncotarget 20171217 4

<h4>Purpose</h4>In 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.<h4>Results</h4>Multivariate statistics revealed a specific lipidomic signature for PCOS patients without associated pathologies. This signature implies changes, mainly by ...[more]

PMID: 29435121

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Project description:BackgroundPolycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder associated with multiple metabolic conditions including obesity, insulin resistance, and dyslipidemia. PCOS is the most common cause of anovulatory infertility; however, the molecular diversity of the ovarian follicle microenvironment is not fully understood. This study aimed to investigate the follicular fluid (FF) lipidomic profiles in different phenotypes of PCOS and to explore novel lipid biomarkers.MethodsA total of 25 women with PCOS and 12 women without PCOS who underwent in vitro fertilization and embryo transfer were recruited, and their FF samples were collected for the lipidomic study. Liquid chromatography-tandem mass spectrometry was used to compare the differential abundance of FF lipids between patients with different PCOS phenotypes and controls. Subsequently, correlations between specific lipid concentrations in FF and high-quality embryo rate (HQER) were analyzed to further evaluate the potential interferences of lipid levels with oocyte quality in PCOS. Candidate biomarkers were then compared via receiver operating characteristic (ROC) curve analysis.ResultsIn total, 19 lipids were identified in ovarian FF. Of these, the concentrations of ceramide (Cer) and free fatty acids (FFA) in FF were significantly increased, whereas those of lysophosphatidylglycerol (LPG) were reduced in women with PCOS compared to controls, especially in obese and insulin-resistant groups. In addition, six subclasses of ceramide, FFA, and LPG were correlated with oocyte quality. Twenty-three lipid subclasses were identified as potential biomarkers of PCOS, and ROC analysis indicated the prognostic value of Cer,36:1;2, FFA C14:1, and LPG,18:0 on HQER in patients with PCOS.ConclusionsOur study showed the unique lipidomic profiles in FF from women with PCOS. Moreover, it provided metabolic signatures as well as candidate biomarkers that help to better understand the pathogenesis of PCOS.

Project description:ObjectivePolycystic 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).MethodsTwenty 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.ResultsThis multiethnic, obese sample was matched by age (PCOS, 37±6; MetS, 40±6years) and body mass index (BMI) (PCOS, 34.6±5.1; MetS, 33.7±5.2kg/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.ConclusionsPCOS 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.

Project description:ObjectivePolycystic ovary syndrome (PCOS) is a prevalent metabolic disorder with an increased risk for cardiovascular disease (CVD) that is enhanced by obesity. This study sought to determine whether a panel of cardiovascular risk proteins (CVRPs) would be dysregulated in overweight/obese PCOS patients, highlighting potential biomarkers for CVD in PCOS.MethodsIn this exploratory cross-sectional study, plasma levels of 54 CVRPs were analyzed in women with PCOS (n = 147) and controls (n = 97). CVRPs were measured using the SOMAscan proteomic platform (version 3.1), with significant proteins identified through linear models, regression analysis, and receiver operating characteristic (ROC) analysis. Analysis on BMI-matched subsets of the cohort were undertaken. Functional enrichment and protein-protein interaction analyses elucidated the pathways involved.ResultsEleven CVRPs were dysregulated in PCOS (whole set, without matching for body mass index (BMI) or insulin resistance (IR)): leptin, Interleukin-1 receptor antagonist protein (IL-1Ra), polymeric immunoglobulin receptor (PIGR), interleukin-18 receptor (IL-18Ra), C-C motif chemokine 3 (MIP-1a), and angiopoietin-1 (ANGPT1) were upregulated whilst advanced glycosylation end product-specific receptor, soluble (sRAGE), bone morphogenetic protein 6 (BMP6); growth/differentiation factor 2 (GDF2), superoxide dismutase [Mn] mitochondrial (MnSOD), and SLAM family member 5 (SLAF5) were downregulated versus the controls. In BMI-matched (overweight/obese, BMI ≥ 26 kg/m2) subset analysis, six CVRPs were common to the whole set: ANGPT1 and IL-1Ra were upregulated; and sRAGE, BMP6, GDF2, and Mn-SOD were downregulated. In addition, lymphotactin (XCL1) was upregulated and placenta growth factor (PIGF), alpha-L-iduronidase (IDUA), angiopoietin-1 receptor, and soluble (sTie-2) and macrophage metalloelastase (MMP12) were downregulated. A subset analysis of BMI-matched plus insulin resistance (IR)-matched women revealed only upregulation of tissue factor (TF) and renin in PCOS, potentially serving as biomarkers for cardiovascular risk in overweight/obese women with PCOS.ConclusionsA combination of upregulated obesity-related CVRPs (ANGPT1/IL/1Ra/XCL1) and downregulated cardioprotective proteins (sRAGE/BMP6/Mn-SOD/GDF2) in overweight/obese PCOS women may contribute to the increased risk for CVD. TF and renin upregulation observed in the BMI- and IR-matched limited sample PCOS subgroup indicates their potential risk of CVD.

Project description:BackgroundWomen with polycystic ovary syndrome (PCOS) manifest a host of ovarian defects like impaired folliculogenesis, anovulation, and poor oocyte quality, which grossly affect their reproductive health. Addressing the putative epigenetic anomalies that tightly regulate these events is of foremost importance in this disorder. We therefore aimed to carry out DNA methylome profiling of cumulus granulosa cells and assess the methylation and transcript expression profiles of a few differentially methylated genes contributing to ovarian defects in PCOS. A total of 20 controls and 20 women with PCOS were selected from a larger cohort of women undergoing IVF, after carefully screening their sera and follicular fluids for hormonal and biochemical parameters. DNA extracted from cumulus granulosa cells of three women each, from control and PCOS groups was subjected to high-throughput, next generation bisulfite sequencing, using the Illumina HiSeq 2500® platform. Remaining samples were used for the validation of methylation status of some identified genes by pyrosequencing, and the transcript expression profiles of these genes were assessed by quantitative real-time PCR.ResultsIn all, 6486 CpG sites representing 3840 genes associated with Wnt signaling, G protein receptor, endothelin/integrin signaling, angiogenesis, chemokine/cytokine-mediated inflammation, etc., showed differential methylation in PCOS. Hypomethylation was noted in 2977 CpGs representing 2063 genes while 2509 CpGs within 1777 genes showed hypermethylation. Methylation differences were also noted in noncoding RNAs regulating several ovarian functions that are dysregulated in PCOS. Few differentially methylated genes such as aldo-keto reductase family 1 member C3, calcium-sensing receptor, resistin, mastermind-like domain 1, growth hormone-releasing hormone receptor and tumor necrosis factor, which predominantly contribute to hyperandrogenism, premature luteolysis, and oocyte development defects, were explored as novel epigenetic candidates in mediating ovarian dysfunction. Methylation profiles of these genes matched with our NGS findings, and their transcript expression patterns correlated with the gene hypo- or hypermethylation status.ConclusionOur findings suggest that the epigenetic dysregulation of genes involved in important processes associated with follicular development may contribute to ovarian defects observed in women with PCOS.

Project description:BackgroundIn this study, we aimed to identify novel biomarkers for polycystic ovary syndrome (PCOS) and analyze their potential roles in immune infiltration during PCOS pathogenesis.MethodsFive datasets, namely GSE137684, GSE80432, GSE114419, GSE138518, and GSE155489, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were selected from the train datasets. The least absolute shrinkage and selection operator logistic regression model and support vector machine-recursive feature elimination algorithm were combined to screen potential biomarkers. The test datasets validated the expression levels of these biomarkers, and the area under the curve (AUC) was calculated to analyze their diagnostic value. Quantitative real-time PCR was conducted to verify biomarkers' expression in clinical samples. CIBERSORT was used to assess differential immune infiltration, and the correlations of biomarkers with infiltrating immune cells were evaluated.ResultsHerein, 1265 DEGs were identified between PCOS and control groups. The gene sets related to immune response and adaptive immune response were differentially activated in PCOS. The two diagnostic biomarkers of PCOS identified by us were HD domain containing 3 (HDDC3) and syndecan 2 (SDC2; AUC, 0.918 and 0.816, respectively). The validation of hub biomarkers in clinical samples using RT-qPCR was consistent with bioinformatics results. Immune infiltration analysis indicated that decreased activated mast cells (P = 0.033) and increased eosinophils (P = 0.040) may be a part of the pathogenesis of PCOS. HDDC3 was positively correlated with T regulatory cells (P = 0.0064), activated mast cells (P = 0.014), and monocytes (P = 0.024) but negatively correlated with activated memory CD4 T cells (P = 0.016) in PCOS. In addition, SDC2 was positively correlated with activated mast cells (P = 0.0021), plasma cells (P = 0.0051), and M2 macrophages (P = 0.038) but negatively correlated with eosinophils (P = 0.01) and neutrophils (P = 0.031) in PCOS.ConclusionHDDC3 and SDC2 can serve as candidate biomarkers of PCOS and provide new insights into the molecular mechanisms of immune regulation in PCOS.

Dataset Information

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

Purpose

Results

Conclusions

Methods

Publications

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

Similar Datasets

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