AUTHOR=Dong Qianqian , Han Ziqi , Tian Limin 

TITLE=Identification of Serum Exosome-Derived circRNA-miRNA-TF-mRNA Regulatory Network in Postmenopausal Osteoporosis Using Bioinformatics Analysis and Validation in Peripheral Blood-Derived Mononuclear Cells

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.899503

DOI=10.3389/fendo.2022.899503

ISSN=1664-2392

ABSTRACT=Background: Osteoporosis is one of the most common systemic metabolic bone diseases, especially in postmenopausal women. As a crucial type of competitive endogenous RNA (ceRNA), circular RNA (circRNA) plays a significant role in the pathogenesis and progression of various human diseases. However, the potential role of circRNAs in postmenopausal osteoporosis (PMOP) remains largely unknown. The study aims to identify potential biomarkers and therapeutic targets of PMOP by constructing a circRNA-associated ceRNA network.
Methods: The PMOP-related datasets GSE161361, GSE64433, and GSE56116 were downloaded from the Gene Expression Omnibus (GEO) database and were used to obtain differentially expressed genes (DEGs). Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied to determine possible relevant functions of differentially expressed messenger RNAs (mRNAs). The TRRUST database was used to predict differential transcription factor (TF)-mRNA regulatory pairs. Afterwards, combined CircBank and miRTarBase with differentially expressed circRNAs and microRNAs (miRNAs), circRNA-miRNA as well as miRNA-TF regulatory relationships were identified. Finally, a circRNA-miRNA-TF-mRNA network was established.
Results: A total of 1201 DE mRNAs, 44 DE miRNAs and 1613 DE circRNAs associated with PMOP were obtained. GO function annotation showed DE mRNAs were mainly related to inflammatory responses. KEGG analysis revealed DE mRNAs were mainly enriched in osteoclast differentiation, rheumatoid arthritis, hematopoietic cell lineage, and cytokine-cytokine receptor interaction pathways. We first identified 26 transcription factors and their target mRNAs. Combining DE miRNAs, we next obtained miRNA-TF/mRNA pairs, which included 9 miRNAs and 12 TF/mRNAs. Combining DE circRNAs, we finally constructed the ceRNA network that contained 6 circRNAs, 4 miRNAs, 4 TFs, and 12 mRNAs.
Conclusions: A circRNA-associated ceRNA network containing TFs was established for PMOP, which may help further explore the molecular mechanisms and may serve as potential biomarkers or therapeutic targets for PMOP.