Construction of Glycometabolism- and Hormone-Related lncRNA-Mediated Feedforward Loop Networks Reveals Global Patterns of lncRNAs and Drug Repurposing in Gestational Diabetes - Fu, Xuelian; Cong, Huifang; Zhao, Shuyu; Li, Yan; Liu, Tianyi; Sun, Yuhong; Lv, Nan (Frontiers in Endocrinology, 2020)
Gestational diabetes mellitus (GDM) is the initiated occurrence during pregnancy with abnormal glucose tolerance. Long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and genes can form lncRNA-mediated feed-forward loops (lnc-FFLs), which are functional network motifs that regulate a wide range of biological processes and disease. However, lnc-FFL network motifs have not been systematically identified, and their roles in GDM are largely unknown. In present study, a global lnc-FFL network is constructed and analyzed. Glycometabolism- and hormone-related lnc-FFL networks are extracted. An integrated computational algorithm is designed to identify dysregulated glycometabolism- and hormone-related lnc-FFLs in GDM. The patterns of dysregulated lnc-FFLs in GDM are complex. There are strong associations between dysregulated glycometabolism- and hormone-related lnc-FFLs in GDM. Some core modules are extracted from dysregulated lnc-FFL network in GDM and show specific and essential functions. In addition, the dysregulated lnc-FFLs and ceRNAs could form more complex modules to play their roles in GDM. Specially, we discover that these dysregulated lnc-FFLs are enrichment in thyroid hormone signaling pathway. Some drug repurposing candidates such as hormonal drugs are identified based on lnc-FFLs in GDM. Collectively, the study highlighted the effect of dysregulated glycometabolism- and hormone-related lnc-FFLs in GDM, which revealed their possibility as novel biomarkers and treatment targets in GDM.