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Updated: Jan 10, 2026

Tissue Collection and RNA Extraction from the Human Osteoarthritic Knee Joint
Published on: July 22, 2021
Identification of osteoarthritis-related genes and potential drugs based on single cell RNA-seq data
Ning Wang1, Kun Liu1, Jia-Li Li1
1Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China.
Abstract:
Osteoarthritis (OA) is a global problem that seriously affects human health. At present, there is still a lack of effective drugs to treat OA. Therefore, we need to find more drugs with preventive and therapeutic effects on OA. In this study, we obtained single-cell RNA sequencing (scRNA-seq) and bulk-RNA seq datasets from Gene Expression Omnibus (GEO). By using high-dimensional weighted correlation network analysis (hdWGCNA), random forest method and protein-protein interaction (PPI) network analyses, five key genes (CXCL8, CCL20, MMP3, BIRC3 and ICAM1) related to OA were identified and the RT-qPCR experiments verified the differential expression of CXCL8, CCL20 and BIRC3 between Triclocarban (TCC) treated zebrafishes and controls. The SAVERUNNER algorithm predicted 42 candidate drugs. Mendelian randomization (MR) of the candidate drugs showed that the increased expression of TUBB1 led to a reduced risk of OA (β = -0.08, P-value = 4.56E-04), while Cabazitaxel (a microtubule dynamics inhibitor commonly used in the treatment of advanced prostate cancer) inhibits the expression of TUBB1, thus increases the risk of OA. Pitavastatin (a statin lipid-lowering drug that can reduce blood lipid levels and the risk of cardiovascular diseases) target genes expression (for HMGCR [Formula: see text]= 0.13, P-value = 2.67E-06, for ITGAL [Formula: see text]= 0.08, P-value = 6.57E-08) leads to an increased risk of OA, while Pitavastatin inhibits the expression of target genes, thus reduces risk of OA. The zebrafish experiments showed that Pitavastatin can increase the joint space of TCC treated OA zebrafish, while Cabazitaxel can decrease the joint space of TCC treated OA zebrafish. The RT-qPCR results of zebrafish verified that Pitavastatin inhibited the expression of HMGCR, while Cabazitaxel inhibited the expression of TUBB1. Our study suggested that Pitavastatin has therapeutic effects on OA, while Cabazitaxel increases the risk of OA.
Insights
This study identifies Pitavastatin as a potential treatment for osteoarthritis (OA) by analyzing gene expression data and zebrafish models. Conversely, Cabazitaxel was found to increase OA risk, highlighting distinct therapeutic potentials.
Area of Science:
- Genomics and Bioinformatics
- Pharmacology
- Translational Medicine
Background:
- Osteoarthritis (OA) poses a significant global health challenge with limited effective treatments.
- There is an unmet need for novel therapeutic agents for OA prevention and treatment.
Purpose of the Study:
- To identify key genes associated with OA using multi-omics data.
- To screen for potential drug candidates for OA treatment.
- To evaluate the therapeutic effects of candidate drugs in preclinical models.
Main Methods:
- Single-cell and bulk RNA sequencing (scRNA-seq, bulk-RNA seq) data analysis.
- High-dimensional weighted correlation network analysis (hdWGCNA), random forest, and protein-protein interaction (PPI) network analyses.
- Mendelian randomization (MR), drug prediction algorithms (SAVERUNNER), and zebrafish OA models.
Main Results:
- Five key OA-associated genes (CXCL8, CCL20, MMP3, BIRC3, ICAM1) were identified.
- Mendelian randomization indicated that increased TUBB1 expression reduces OA risk, and Cabazitaxel, by inhibiting TUBB1, increases OA risk.
- Zebrafish experiments demonstrated Pitavastatin's therapeutic effect in OA by increasing joint space, while Cabazitaxel worsened OA.
- RT-qPCR confirmed Pitavastatin inhibited HMGCR and Cabazitaxel inhibited TUBB1 expression in zebrafish.
Conclusions:
- Pitavastatin exhibits therapeutic potential for osteoarthritis.
- Cabazitaxel may increase osteoarthritis risk.
- This study provides a multi-omics and experimental validation approach for identifying OA therapeutics.
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