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长链非编码RNA在多囊卵巢综合征中的研究进展
引用本文:何俊见,马晓欣.长链非编码RNA在多囊卵巢综合征中的研究进展[J].国际生殖健康/计划生育杂志,2018,37(4):303-306.
作者姓名:何俊见  马晓欣
作者单位:110004 沈阳,中国医科大学附属盛京医院妇产科
基金项目:国家自然科学基金资助项目(81472438,81272874);辽宁特聘教授;盛京自由研究者基金(201601)
摘    要:多囊卵巢综合征(PCOS)是一种常见的妇科内分泌疾病,但其发病机制尚不清楚。长链非编码RNA(lncRNA)是一类长度超过200个核苷酸的非编码RNA。一些针对PCOS患者的测序研究发现,PCOS患者的外周血白细胞、卵丘细胞和颗粒细胞中的lncRNA表达异于正常女性,如CTBP1-AS、甾体激素受体RNA激活物(SRA)、肿瘤低表达lncRNA(lncRNA-LET)和生长停滞敏感基因5(GAS5)等。进一步研究发现,这些差异表达的lncRNA可能通过参与类固醇的产生、增强类固醇受体的活性、肥胖和胰岛素抵抗(IR)等代谢过程,影响颗粒细胞的增殖、迁移和凋亡以及卵母细胞的发育,与PCOS发生、发展相关。现综述近年来lncRNA在PCOS中的研究进展,以期为PCOS的研究与治疗提供新思路。

关 键 词:多囊卵巢综合征  RNA  长链非编码RNA  微阵列分析  综述  
收稿时间:2018-05-28

Long Noncoding RNAs in Polycystic Ovary Syndrome
HE Jun-jian,MA Xiao-xin.Long Noncoding RNAs in Polycystic Ovary Syndrome[J].Journla of International Reproductive Health/Family Planning,2018,37(4):303-306.
Authors:HE Jun-jian  MA Xiao-xin
Affiliation:Department of Obstetrics and Gynecology,Shengjing Hospital of China Medical University,Shenyang 110004,China
Abstract:Polycystic ovary syndrome (PCOS) is a common gynecological endocrine disease, but its pathogenesis is still not very clear. Long noncoding RNAs (lncRNAs) are a class of non-coding RNAs with more than 200 nucleotides in length. Some sequencing studies found the differential expression of lncRNAs in the peripheral blood leukocytes, cumulus and granulosa cells of PCOS patients, such as CTBP1-AS, steroid receptor RNA activator (SRA), lncRNA-low expression in tumor (lncRNA-LET) and growth arrest specific 5 (GAS5), etc. Further studies found that these differentially expressed lncRNAs may be involved in steroid production, steroid receptor activity, obesity and insulin resistance (IR), the proliferation, migration and apoptosis of granulosa cells, and the development of oocytes. All of these pathophysiological mechanisms are related to PCOS pathogenesis and developemnt. Here we review the research progress of lncRNAs in PCOS, in order to provide new ideas for the study and treatment of PCOS.
Keywords:Polycystic ovary syndrome  RNA  long noncoding RNA  Microarray analysis  Review  
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