Identifying potential functional lncRNAs in metabolic syndrome by constructing a lncRNA-miRNA-mRNA network

The metabolic syndrome (MS) is a cluster of interrelated risk factors including diabetes mellitus, abdominal obesity, high cholesterol, and hypertension, which can significantly increase mortality and disability. Accumulating evidence suggest that long non-coding RNAs (lncRNAs) are involved in the pathogenesis of human metabolic diseases. However, little is known about the regulatory role of lncRNAs in MS. In this work, we proposed a method for identifying potential MS-associated lncRNAs by constructing an lncRNA-miRNA-mRNA network (LMMN). Firstly, we constructed LMMN by integrating MS-associated genes, miRNA-mRNA interactions, miRNA-lncRNA interactions and mRNA/miRNA expression profiles in patients with MS. Then, we predicted potential MS-associated lncRNAs based on the topological properties of LMMN. As a result, we identified XIST as the most important lncRNA in LMMN. Furthermore, we focused on XIST/miR-214-3p and mir-181a-5p/PTEN axis and validated their expression in MS using real-time quantitative polymerase chain reaction (RT-qPCR). The RT-qPCR results showed that the expression of XIST and PTEN was significantly decreased (P