多囊卵巢综合征女性血清生物标志物的全球代谢组学分析
Global metabolomic profiling of serum biomarkers in women with polycystic ovary syndrome.
摘要(中文译文)
多囊卵巢综合征（PCOS）是一种以代谢紊乱为特征的复杂内分泌疾病。识别血清生物标志物有助于加深对其病理生理机制的理解。本研究采用非靶向代谢组学方法探讨PCOS中的代谢改变。收集了71例PCOS女性和54例健康对照者的血清样本。采用液相色谱-质谱联用技术进行非靶向代谢组学分析，以鉴定差异丰度代谢物。通过通路分析确定关键代谢紊乱，并评估所鉴定代谢物与临床参数之间的相关性。代谢组学分析在PCOS组与对照组之间鉴定出24种上调代谢物和17种下调代谢物。这些代谢物主要包括甘油磷脂、脂肪酸、鞘脂、肽类、神经酰胺和类固醇。通路分析表明，这些代谢物富集于胆汁酸生物合成、甘油脂代谢、色氨酸代谢、柠檬酸循环和脂肪酸代谢等通路。支链氨基酸和芳香族氨基酸水平升高提示其与胰岛素抵抗可能存在关联。胆汁酸代谢紊乱提示肠道微生物群与宿主之间相互作用的改变。此外，与氧化应激和线粒体功能相关的代谢物提示代谢功能障碍。相关性分析揭示了改变了的代谢物与胰岛素抵抗、雄激素水平等临床标志物之间的关联。本研究揭示了PCOS中明显的血清代谢改变，强调了其与胰岛素抵抗和炎症的关联。这些发现凸显了代谢组学在识别用于早期诊断的新型生物标志物以及开发靶向治疗策略方面的潜力。
Abstract
Polycystic ovary syndrome (PCOS) is a complex endocrine disorder characterized by metabolic dysregulation. Identifying serum biomarkers can enhance our understanding of its pathophysiology. This study employs an untargeted metabolomic approach to investigate metabolic alterations in PCOS. Serum samples were collected from 71 women with PCOS and 54 healthy controls. Untargeted Metabolomic profiling was performed using liquid chromatography-mass spectrometry to identify metabolites with differential abundance. Pathway analysis was conducted to identify key metabolic disruptions, and correlations between identified metabolites and clinical parameters were assessed. The metabolomics analysis identified 24 upregulated and 17 downregulated metabolites in PCOS compared with controls. These metabolites mainly include glycerophospholipids, fatty acids, sphingolipids, peptides, ceramides, and steroids. Pathway analysis indicated that these metabolites were enriched in pathways including bile acid biosynthesis, glycerolipid metabolism, tryptophan metabolism, the citric acid cycle, and fatty acid metabolism. Increased levels of branched-chain and aromatic amino acids suggested potential links to insulin resistance. Disruptions in bile acid metabolism suggested altered interactions between the gut microbiome and the host. Additionally, metabolites related to oxidative stress and mitochondrial function indicated metabolic dysfunction. Correlation analyses revealed associations between altered metabolites and clinical markers such as insulin resistance and androgen levels. This study reveals distinct serum metabolic alterations in PCOS, emphasizing their association with insulin resistance and inflammation. These findings highlight the potential of metabolomics to identify novel biomarkers for early diagnosis and to develop targeted therapeutic strategies.
如何引用
AMA
Jalpa Patel, Hiral Chaudhary, Sonal Panchal, Rushikesh Joshi. Global metabolomic profiling of serum biomarkers in women with polycystic ovary syndrome.. Scientific reports. 2026; doi:10.1038/s41598-026-60249-8.
APA
Jalpa Patel, Hiral Chaudhary, Sonal Panchal, Rushikesh Joshi (2026). Global metabolomic profiling of serum biomarkers in women with polycystic ovary syndrome.. Scientific reports. https://doi.org/10.1038/s41598-026-60249-8
GB/T 7714
Jalpa Patel, Hiral Chaudhary, Sonal Panchal, Rushikesh Joshi. Global metabolomic profiling of serum biomarkers in women with polycystic ovary syndrome.[J]. Scientific reports, 2026 doi:10.1038/s41598-026-60249-8.
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