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pmid:37555363

Integrated bioinformatics analysis of differentially expressed genes in the temporomandibular joint internal derangement.

Junda Yang

Clinical and experimental dental research · 2023 doi:10.1002/cre2.768

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Integrated bioinformatics analysis of differentially expressed genes in the temporomandibular joint internal derangement.
doi
10.1002/cre2.768
pmid
37555363
authors array · 1 item
[0]
Junda Yang
journal
Clinical and experimental dental research
year
2023
abstract
OBJECTIVES: This study aimed to identify significant mechanisms and potential treatments for temporomandibular joint internal derangement (TMJD) through integrated bioinformatics analysis. MATERIALS AND METHODS: Gene expression data sets (GSE66864) from the Gene Expression Omnibus (GEO) database were downloaded. Differentially expressed genes (DEGs) were identified both in the treatment groups and in controls by R packages. Network analysis of protein-protein interaction (PPI) and Human Protein Atlas was used to explore DEGs' potential function. DGIdb database was utilized to gain potential drug targets. RESULTS: In conclusion, 126 DEGs were selected for TMJD through bioinformatics analysis. Both GO and Kyoto Encyclopedia of Genes and Genomes analyses combined showed the pathways involved in TMJD. A PPI network was constructed to select the top 10 hub genes, of which five hub genes were chosen for further investigation. Moreover, the microenvironment of immune cells related to hub genes was evaluated by R packages. Macrophages play an important role in inflammation and oral-related tumors. The Human Protein Atlas analysis indicated that the five hub genes are highly related to head and neck cancer. Finally, eight potential drugs were selected for two genes using the DGIdb database. CONCLUSION: Our integrated bioinformatics analysis identified DEGs in TMJD and provided potential ideas for further research and treatment approaches. However, experimental validation of the hub genes and potential drug targets is still needed. The key mechanisms of the identified genes and their potential roles as biomarkers or drug targets in TMJD require further investigation.
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WGCNA was utilized to confirm the reliability of DEGs in the different samples.
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The analysis identified 104 upregulated and 22 downregulated genes and selected five upregulated hub genes: ITGA6, PTHLH, FPR1, ANXA8, and ATP6V0A2.
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sections[10] "Identification of DEGs" paragraph 2
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A total of 104 upregulated and 22 downregulated genes were shown in Figure 1b.
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sections[10] "Identification of DEGs" paragraph 2
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Five hub genes were selected including ITGA6, PTHLH, FPR1, ANXA8, and ATP6V0A2, which are highly upregulated in the DEGs.
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The analysis identified 104 upregulated and 22 downregulated genes and selected five upregulated hub genes: ITGA6, PTHLH, FPR1, ANXA8, and ATP6V0A2.
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Transcriptomic study on the impact of Temporomandibular joint Internal derangement in the Condylar Cartilage of Rabbits
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Complete file
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Differentially expressed genes (DEGs) were identified both in the treatment groups and in controls by R packages. Network analysis of protein-protein interaction (PPI) and Human Protein Atlas was used to explore DEGs' potential function. DGIdb database was utilized to gain potential drug targets.\nRESULTS: In conclusion, 126 DEGs were selected for TMJD through bioinformatics analysis. Both GO and Kyoto Encyclopedia of Genes and Genomes analyses combined showed the pathways involved in TMJD. A PPI network was constructed to select the top 10 hub genes, of which five hub genes were chosen for further investigation. Moreover, the microenvironment of immune cells related to hub genes was evaluated by R packages. Macrophages play an important role in inflammation and oral-related tumors. The Human Protein Atlas analysis indicated that the five hub genes are highly related to head and neck cancer. 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