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Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Genet. | doi: 10.3389/fgene.2019.00772

Polycystic Ovary Syndrome: Novel and Hub lncRNAs in the Insulin Resistance-associated lncRNA-mRNA Network

  • 1Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, China
  • 2Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, China
  • 3Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, China
  • 4Center for Reproductive Medicine, Shandong Provincial Hospital, Shandong University, National Research Center for Assisted Reproductive Technology and Reproductive Genetics, The Key Laboratory for Reproductive Endocrinology (Shandong University), Ministry of Education, Shandong Provincial Clinical Medicine Research Center for reproductive health, Shandong Provincial Key Laboratory of Reproductive Medicine, No.157 Jingliu Road, Shandong University, China

Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA-mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of LncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared to that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA, and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.

Keywords: Insulin Resistance, Polycystic ovary syndrome (PCOS), type 2 diabetes, metabolic and reproductive disorder, Long non-coding RNAs (lncRNAs), insulin resistance-associated lncRNA-mRNA network, RNA protein interactions

Received: 06 May 2019; Accepted: 22 Jul 2019.

Edited by:

Naoyuki Kataoka, The University of Tokyo, Japan

Reviewed by:

Nobuyoshi Akimitsu, The University of Tokyo, Japan
Chi-Ming Wong, The University of Hong Kong, Hong Kong  

Copyright: © 2019 Huang, Zhao, Du, Chen, Geng, Chu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Yanzhi Du, Shanghai Jiao Tong University, Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai, China, duyz@sjtu.edu.cn