Identification of a Potential MiRNA-mRNA Regulatory Network for Osteoporosis by Using Bioinformatics Methods: A Retrospective Study Based on the Gene Expression Omnibus Database

Shi Lin; Jianjun Wu; Baixing Chen; Shaoshuo Li; Hongxing Huang

doi:10.3389/fendo.2022.844218

Identification of a Potential MiRNA-mRNA Regulatory Network for Osteoporosis by Using Bioinformatics Methods: A Retrospective Study Based on the Gene Expression Omnibus Database

Front Endocrinol (Lausanne). 2022 May 10:13:844218. doi: 10.3389/fendo.2022.844218. eCollection 2022.

Authors

Shi Lin¹, Jianjun Wu¹, Baixing Chen², Shaoshuo Li³, Hongxing Huang⁴

Affiliations

¹ The Third Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangdong, China.
² Department of Development and Regeneration, KU Leuven, University of Leuven, Leuven, Belgium.
³ Laboratory of New Techniques of Restoration and Reconstruction of Orthopedics and Traumatology, Nanjing University of Chinese Medicine, Jiangsu, China.
⁴ Department of Orthopaedics, The Third Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong, China.

Abstract

Introduction: As a systemic skeletal dysfunction, osteoporosis (OP) is characterized by low bone mass, impairment of bone microstructure, and a high global morbidity rate. There is increasing evidence that microRNAs (miRNAs) are associated with the pathogenesis of OP. Weighted gene co-expression network analysis (WGCNA) is a systematic method for identifying clinically relevant genes involved in disease pathogenesis. However, the study of the miRNA-messenger RNA (mRNA) regulatory network in combination with WGCNA in OP is still lacking.

Methods: The GSE93883 and GSE7158 microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DE-miRNAs) and differentially expressed genes (DEGs) were analyzed with the limma package. OP-related miRNAs from the most clinically relevant module were identified by the WGCNA method. The overlap of DE-miRNAs and OP-related miRNAs was identified as OP-related DE-miRNAs. Both upstream transcription factors and downstream targets of OP-related DE-miRNAs were predicted by FunRich. An intersection of predicted target genes and DEGs was confirmed as downstream target genes of OP-related DE-miRNAs. With the use of clusterProfiler in R, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed on target genes. Finally, both the protein-protein interaction (PPI) network and miRNA-mRNA network were constructed and analyzed.

Results: A total of 79 OP-related DE-miRNAs were obtained, most of which were predicted to be regulated by specificity protein 1 (SP1). Subsequently, 197 downstream target genes were screened out. The target genes were enriched in multiple pathways, including signaling pathways closely related to the onset of OP, such as Ras, PI3K-Akt, and ErbB signaling pathways. Through the construction of the OP-related miRNA-mRNA regulatory network, a hub network that may play a prominent role in the formation of OP was documented.

Conclusion: By using WGCNA, we constructed a potential OP-related miRNA-mRNA regulatory network, offering a novel perspective on miRNA regulatory mechanisms in OP.

Keywords: WGCNA; bioinformatics analysis; miRNAs; miRNA–mRNA regulatory network; osteoporosis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology / methods
Gene Expression
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
MicroRNAs* / genetics
MicroRNAs* / metabolism
Osteoporosis* / genetics
Phosphatidylinositol 3-Kinases / metabolism
RNA, Messenger / genetics
RNA, Messenger / metabolism
Retrospective Studies

Substances

MicroRNAs
RNA, Messenger