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Identification of key genes and small molecule drugs in osteoarthritis by integrated bioinformatics analysis
Zhendong Liu1, Hongbo Wang2, Xingbo Cheng1
1Department of Surgery of Spine and Spinal Cord, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450003, Henan Province, China.
Background:
Osteoarthritis (OA) is a common joint degenerative disease that can affect multiple joints. Genetic events may play an important regulatory role in the early stages of the disease, but the specific mechanisms have not yet been fully elucidated. The main purpose of this study was to screen for disease-causing hub genes and effective small molecule drugs to reveal the pathogenesis of OA and to develop novel drugs for treatment.
Methods:
Two gene expression profile datasets, GSE55235 and GSE55457, were integrated and further analyzed. The consistently differentially expressed genes (DEGs) were identified, and functional annotation and pathway analysis of these genes were performed with GO and KEGG. A protein-protein interaction network (PPI) of the DEGs was generated using STRING, and potential small molecule drug screening was performed on the connectivity map (CMap).
Results:
A total of 158 consistently differentially expressed genes were identified from the two profile datasets. The functions of these DEGs are mainly related to the TNF signaling pathway, osteoclast differentiation, MAPK signaling pathway and so on. The PPI network contains 127 nodes and 1802 edges, and the ten hub genes were interleukin 6 (IL6), vascular endothelial growth factor A (VEGFA)and so on. 7 small molecule drugs were identified as potential interactors with these hubs.
Conclusions:
This study explains the disorder of expression in the pathological process of OA at transcriptome, which will help to understand the pathogenesis of OA.
Insights
This study identifies key genes and potential drugs for osteoarthritis (OA) by analyzing gene expression data. Findings offer insights into OA pathogenesis and potential new treatments.
Area of Science:
- Genomics
- Molecular Biology
- Pharmacology
Background:
- Osteoarthritis (OA) is a prevalent degenerative joint disease with incompletely understood genetic mechanisms.
- Genetic factors are implicated in early OA development, necessitating further research into specific pathways.
- Understanding the molecular basis of OA is crucial for developing effective therapeutic strategies.
Purpose of the Study:
- To identify disease-causing hub genes in osteoarthritis.
- To screen for effective small molecule drugs for OA treatment.
- To elucidate the pathogenesis of osteoarthritis through transcriptomic analysis.
Main Methods:
- Integrated and analyzed two gene expression datasets (GSE55235, GSE55457).
- Identified consistently differentially expressed genes (DEGs) and performed functional/pathway analysis (GO, KEGG).
- Constructed a protein-protein interaction (PPI) network and screened for potential drugs using the Connectivity Map (CMap).
Main Results:
- Identified 158 consistently differentially expressed genes.
- Key pathways include TNF signaling, osteoclast differentiation, and MAPK signaling.
- Discovered ten hub genes, including IL6 and VEGFA, and identified 7 potential small molecule drugs.
Conclusions:
- Transcriptomic analysis reveals gene expression dysregulation in OA pathology.
- This study enhances the understanding of osteoarthritis pathogenesis.
- Identified hub genes and potential drugs may pave the way for novel OA therapies.
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