Literature DB >> 25860656

Serum metabolomics study of polycystic ovary syndrome based on UPLC-QTOF-MS coupled with a pattern recognition approach.

Fang Dong1, Dan Deng, Heng Chen, Wei Cheng, Qifu Li, Rong Luo, Shijia Ding.   

Abstract

Metabolomics has become an important tool in distinguishing changes in metabolic pathways and the diagnosis of human disease. Polycystic ovary syndrome (PCOS) is a relatively complicated, heterogeneous endocrine disorder. The etiology and pathogenesis of PCOS remain uncertain. In this study, based on the platform of ultra performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) and the method of pattern recognition, a comprehensive metabolomics approach has been applied to explore the changes in metabolic profiling between PCOS patients (n = 20) and controls (n = 15) as well as insulin-resistance (IR) PCOS patients (n = 11) and non-IR PCOS subjects (n = 9) in serum. In total, 36 metabolites were found significantly different between PCOS and controls, and 9 metabolites were discovered significantly different between IR and non-IR PCOS patients. Significant increases in the levels of saturated and unsaturated fatty acids (myristic acid, linoleic acid, 9-/13-HODE, etc.), fatty amides (palmitic amide, oleamide), dehydroepiandrosterone sulfate, L-glutamic acid, azelaic acid, L-glyceric acid, pyroglutamic acid, and decreases in the levels of lysophosphatidylethanolamine, lysophosphatidylcholine, uridine, and L-carnitine were found in PCOS patients compared with controls. In IR PCOS patients, linoleic acid, myristic acid, palmitoleic acid, and vaccenic acid also increased significantly compared with non-IR PCOS patients. All these changed metabolites showed abnormalities of steroid hormone biosynthesis, amino acids and nucleosides metabolism, glutathione metabolism, and lipids and carbohydrates metabolism in PCOS patients. The subgroup IR PCOS patients exhibited greater metabolic deviations than non-IR PCOS patients. These findings may help yield promising insights into the pathogenesis and advance the diagnosis and prevention of PCOS. Graphical Abstract Serum metabolomics signature of polycystic ovary syndrome.

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Year:  2015        PMID: 25860656     DOI: 10.1007/s00216-015-8670-x

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  15 in total

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

Authors:  Alice Y Chang; Antigoni Z Lalia; Gregory D Jenkins; Tumpa Dutta; Rickey E Carter; Ravinder J Singh; K Sreekumaran Nair
Journal:  Metabolism       Date:  2017-03-08       Impact factor: 8.694

Review 2.  Multiomics Analysis-Based Biomarkers in Diagnosis of Polycystic Ovary Syndrome.

Authors:  Shikha Rani; Piyush Chandna
Journal:  Reprod Sci       Date:  2022-01-27       Impact factor: 3.060

Review 3.  Follicular Fluid: A Powerful Tool for the Understanding and Diagnosis of Polycystic Ovary Syndrome.

Authors:  Ana Teresa Brinca; Ana Cristina Ramalhinho; Ângela Sousa; António Hélio Oliani; Luiza Breitenfeld; Luís A Passarinha; Eugenia Gallardo
Journal:  Biomedicines       Date:  2022-05-27

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

Authors:  Mariona Jové; Irene Pradas; Alba Naudí; Susana Rovira-Llopis; Celia Bañuls; Milagros Rocha; Manuel Portero-Otin; Antonio Hernández-Mijares; Victor M Victor; Reinald Pamplona
Journal:  Oncotarget       Date:  2017-12-17

5.  Metabolic profiling of polycystic ovary syndrome reveals interactions with abdominal obesity.

Authors:  A Couto Alves; B Valcarcel; V-P Mäkinen; L Morin-Papunen; S Sebert; A J Kangas; P Soininen; S Das; M De Iorio; L Coin; M Ala-Korpela; M-R Järvelin; S Franks
Journal:  Int J Obes (Lond)       Date:  2017-05-26       Impact factor: 5.095

6.  Effect of the environment microbiota on the flavour of light-flavour Baijiu during spontaneous fermentation.

Authors:  Xiao-Na Pang; Bei-Zhong Han; Xiao-Ning Huang; Xin Zhang; Lin-Feng Hou; Ming Cao; Li-Juan Gao; Guang-Hui Hu; Jing-Yu Chen
Journal:  Sci Rep       Date:  2018-02-21       Impact factor: 4.379

7.  UPLC/Q‑TOF‑MS based plasma metabolomics and clinical characteristics of polycystic ovarian syndrome.

Authors:  Xuemei Fan; Jianfa Jiang; Zhiqiang Huang; Jumei Gong; Yiming Wang; Wei Xue; Yan Deng; Yanfang Wang; Tingping Zheng; Aijun Sun; Guoan Luo
Journal:  Mol Med Rep       Date:  2018-11-12       Impact factor: 2.952

8.  Identification of potential metabolic biomarkers of polycystic ovary syndrome in follicular fluid by SWATH mass spectrometry.

Authors:  Zhengao Sun; Hsun-Ming Chang; Aijuan Wang; Jingyan Song; Xingxing Zhang; Jiayin Guo; Peter C K Leung; Fang Lian
Journal:  Reprod Biol Endocrinol       Date:  2019-06-11       Impact factor: 5.211

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

Authors:  Yan Zhang; Lingyan Liu; Tai-Lang Yin; Jing Yang; Cheng-Liang Xiong
Journal:  Oncotarget       Date:  2017-07-06

Review 10.  Metabolomics-A Promising Approach to Pituitary Adenomas.

Authors:  Oana Pînzariu; Bogdan Georgescu; Carmen E Georgescu
Journal:  Front Endocrinol (Lausanne)       Date:  2019-01-17       Impact factor: 5.555

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