Effect of lncRNA MALAT1 on the Granulosa Cell Proliferation and Pregnancy Outcome in Patients With PCOS

Author:

Tu Mixue,Wu Yiqing,Wang Feixia,Huang Yun,Qian Yuli,Li Jingyi,Lv Pingping,Ying Yanyun,Liu Juan,Liu Yifeng,Zhang Runju,Zhao Wei,Zhang Dan

Abstract

Follicle arrest is one of the main characteristics of polycystic ovary syndrome (PCOS), the most common endocrinological disorder in reproductive-aged women. Increasing evidence proves that high anti-Mullerian hormone (AMH) levels may play an important role in follicular development. Long noncoding RNA (lncRNA) with a length of more than 200 nt is widely involved in the directional differentiation, growth, and development of cells, whereas whether lncRNA is involved in AMH’s role in follicular development is unknown. In this study, we analyzed lncRNA expression in ovarian granulosa cells (GCs) collected from women with and without PCOS via high-throughput sequencing. The results showed that a total of 79 noncoding transcripts were differently expressed in GCs of PCOS patients, including upregulated lncRNA MALAT1. The upregulation of MALAT1 was further confirmed by RT-qPCR in GCs from a larger cohort of PCOS patients. Furthermore, knockdown MALAT1 can promote the proliferation of KGN cell in vitro. These data suggested a role for MALAT1 in the development of PCOS. Meanwhile, MALAT1 and phosphorylated SMAD 1/5 (Ser463/465) protein were upregulated in KGN cells after exogenous AMH stimulation, which identified AMH perhaps as a regulator for the expression of MALAT1. We also found that MALAT1 can predict clinical pregnancy outcome to a certain extent by ROC curve analysis (area: 0.771, p = 0.007, 95% CI: 0.617–0.925, sensitivity: 57.1%, specificity: 91.7%). Thus, our findings revealed a role of lncRNA MALAT1 in inhibiting granulosa cell proliferation and may be correlated with pregnancy outcome in PCOS.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Frontiers Media SA

Subject

Endocrinology, Diabetes and Metabolism

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