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Updated: Sep 30, 2025

Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint
Published on: July 22, 2021
Constructing a competing endogenous RNA network for osteoarthritis
Shu-Liang Hua1, Jun-Qing Liang1, Guo-Fang Hu1
1Department of Bone and Joint Surgery, the People's Hospital of Baise, Baise, China.
Background:
Osteoarthritis (OA) is one of the most common diseases in elderly people; however, the correlation between molecular alterations and the occurrence and progression of OA are still not well understood. We conducted this study to investigate the molecular changes in OA via the competing endogenous ribonucleic acid (ceRNA) network.
Methods:
We downloaded the messenger RNA (mRNA) data set, GSE48556, the microRNA (miRNA) data set, GSE105027, and the long non-coding (lncRNA) data set, GSE126963 from the Gene Expression Omnibus (GEO) database, and examined the differentially expressed genes (DEGs) in these data sets. Further, we constructed a ceRNA network of the differentially expressed miRNAs, mRNAs, and lncRNAs. To determine the biological functions of the ceRNA network, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Finally, we conducted an immune cell infiltration analysisusing single-sample gene set enrichment analysis to examine the abundance of immune cells in healthy and OA patients, and compared the infiltration of 28 immune cells between the healthy and OA samples. We also analyzed the relationship between the abundance of immune cells and mRNA expression levels in the ceRNA network.
Results:
Ultimately hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs were identified in the ceRNA network. The functional enrichment analyses showed that these lncRNAs, miRNAs, and mRNAs are involved in various significant biological process, such as the regulation of leukocyte migration, Mitogen-Activated Protein (MAP) kinase tyrosine/serine/threonine phosphatase activity, the interleukin-17 signaling pathway, the tumor necrosis factor signaling pathway, and osteoclast differentiation, and can also have a strong effect on immune cell infiltration.
Conclusions:
The dual-specificity phosphatase 1-specific ceRNA network can be used as a diagnostic tool to assess the progression of OA patients.
Insights
This study reveals a dual-specificity phosphatase 1-specific competing endogenous RNA network in osteoarthritis (OA). This network, involving specific long non-coding RNAs and microRNAs, may serve as a diagnostic tool for OA progression.
Area of Science:
- Molecular biology
- Genomics
- Immunology
Background:
- Osteoarthritis (OA) is a prevalent degenerative joint disease in the elderly.
- The molecular underpinnings of OA occurrence and progression remain incompletely understood.
- Investigating molecular alterations through competing endogenous RNA (ceRNA) networks offers a novel approach to OA research.
Purpose of the Study:
- To identify key molecular players in OA pathogenesis.
- To construct and analyze a ceRNA network in OA.
- To explore the relationship between molecular changes and immune cell infiltration in OA.
Main Methods:
- Downloaded mRNA, miRNA, and lncRNA datasets (GSE48556, GSE105027, GSE126963) from the Gene Expression Omnibus (GEO) database.
- Identified differentially expressed genes (DEGs) and constructed a ceRNA network.
- Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses.
- Conducted immune cell infiltration analysis using single-sample gene set enrichment analysis (ssGSEA).
Main Results:
- A ceRNA network was constructed, identifying hsa-mir-425-3p, dual specificity phosphatase 1, and 24 lncRNAs.
- Functional enrichment revealed involvement in leukocyte migration, MAPK signaling, TNF signaling, and osteoclast differentiation.
- Significant correlations were found between ceRNA components and immune cell infiltration in OA.
Conclusions:
- The identified ceRNA network, particularly involving dual-specificity phosphatase 1, plays a crucial role in OA.
- This network holds potential as a diagnostic biomarker for assessing OA patient progression.
- Understanding these molecular interactions may lead to new therapeutic strategies for OA.
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