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多囊卵巢综合征蛋白质组生物标志物分析的系统方法框架。

Framework for a systems approach to proteomic biomarker profiling in polycystic ovary syndrome.

机构信息

Division of Human Development, School of Clinical Sciences, University of Nottingham, D Floor, East Block, Queens Medical Centre Campus, Nottingham University Hospitals, Nottingham NG7 2UH, UK.

出版信息

Expert Rev Proteomics. 2009 Oct;6(5):469-99. doi: 10.1586/epr.09.68.

Abstract

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in females of reproductive age, and its prevalence ranges between 6 and 8%. Associated problems include infertility, menstrual disorders, hirsutism and obesity. In addition, individuals with PCOS may be at increased risk of diabetes, endometrial cancer and, possibly, cardiovascular disease and breast cancer in later life. Biomarkers identified from proteomic analyses may help to improve the clinical management of PCOS, provided that new proteomic data can be integrated with existing knowledge and/or pathways implicated in disease etiology. In this study, a database of identity, descriptions and functions/pathways has been developed from 148 published proteomic biomarkers in PCOS. From analysis of the database, a variety of pathways possibly implicated in PCOS were determined, including those related to fibrinolysis, thrombosis, the antioxidant pathway and the immune system. This database, if developed further, will provide a framework for a systems approach to profiling biomarkers in the future.

摘要

多囊卵巢综合征(PCOS)是育龄女性中最常见的内分泌疾病,其患病率在 6%至 8%之间。相关问题包括不孕、月经紊乱、多毛症和肥胖症。此外,患有 PCOS 的个体可能面临更高的糖尿病、子宫内膜癌风险,并且可能在以后的生活中面临心血管疾病和乳腺癌的风险。从蛋白质组学分析中确定的生物标志物可能有助于改善 PCOS 的临床管理,前提是新的蛋白质组学数据可以与现有知识和/或与疾病病因相关的途径整合。在这项研究中,从 148 个发表的 PCOS 蛋白质组学生物标志物中开发了一个包含身份、描述和功能/途径的数据库。通过对数据库的分析,确定了多种可能与 PCOS 相关的途径,包括与纤维蛋白溶解、血栓形成、抗氧化途径和免疫系统相关的途径。如果进一步开发这个数据库,它将为未来的生物标志物分析提供一个系统方法的框架。

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