Dong Fang, Deng Dan, Chen Heng, Cheng Wei, Li Qifu, Luo Rong, Ding Shijia
Medical Examination Centre, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Anal Bioanal Chem. 2015 Jun;407(16):4683-95. doi: 10.1007/s00216-015-8670-x. Epub 2015 Apr 10.
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.
代谢组学已成为区分代谢途径变化和诊断人类疾病的重要工具。多囊卵巢综合征（PCOS）是一种相对复杂的异质性内分泌疾病。PCOS的病因和发病机制仍不明确。在本研究中，基于超高效液相色谱串联四极杆飞行时间质谱（UPLC-QTOF-MS）平台和模式识别方法，采用综合代谢组学方法，探索PCOS患者（n = 20）与对照组（n = 15）以及胰岛素抵抗（IR）PCOS患者（n = 11）与非IR PCOS受试者（n = 9）血清中代谢谱的变化。总共发现36种代谢物在PCOS患者与对照组之间存在显著差异，9种代谢物在IR与非IR PCOS患者之间存在显著差异。与对照组相比，PCOS患者中饱和脂肪酸和不饱和脂肪酸（肉豆蔻酸、亚油酸、9-/13-羟基十八碳二烯酸等）、脂肪酰胺（棕榈酰胺、油酰胺）、硫酸脱氢表雄酮、L-谷氨酸、壬二酸、L-甘油酸、焦谷氨酸水平显著升高，而溶血磷脂酰乙醇胺、溶血磷脂酰胆碱、尿苷和L-肉碱水平降低。与非IR PCOS患者相比，IR PCOS患者中亚油酸、肉豆蔻酸棕榈油酸和vaccenic酸也显著增加。所有这些变化的代谢物均显示PCOS患者存在类固醇激素生物合成、氨基酸和核苷代谢、谷胱甘肽代谢以及脂质和碳水化合物代谢异常。IR PCOS患者亚组比非IR PCOS患者表现出更大的代谢偏差。这些发现可能有助于深入了解PCOS的发病机制，并推进其诊断和预防。图形摘要多囊卵巢综合征的血清代谢组学特征。
