The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis
Osteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predispos...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Genetics Research |
| Online Access: | http://dx.doi.org/10.1155/2023/5574636 |
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| _version_ | 1832548016702095360 |
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| author | Zhe Tan Rong Chen Hanyu Lin Hong Wang |
| author_facet | Zhe Tan Rong Chen Hanyu Lin Hong Wang |
| author_sort | Zhe Tan |
| collection | DOAJ |
| description | Osteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predisposition. As the pathogenesis of OA is unknown, there are almost no effective treatments available to prevent the onset or progression of the disease. In recent years, many researchers focused on bioinformatics analysis to explore new biomarkers for the diagnosis, treatment, and prognosis of human diseases. In this work, we obtain the traditional RNA sequencing data of OA patients from the GEO database. By performing the differentially expressed analysis, we successfully obtain the genes that are closely associated with the OA. In addition, the Venn diagram was applied to evaluate the genes that are involved in OA and immune-related genes. The protein-protein interaction analysis was further conducted to explore the hub genes. The single-cell RNA sequencing analysis was used to evaluate the expression distribution of the MMP, VEGFA, SPI1, and IRF8 in synovial tissues of patients with osteoarthritis. Finally, the GSVA enrichment analysis discovered the potential pathways involved in OA patients. Our analysis provides a new direction for the exploration of the process of OA patients. In addition, VEGFA may be considered a promising biomarker in OA. |
| format | Article |
| id | doaj-art-d3ffc37e14cc4e1482690a8057031aae |
| institution | Kabale University |
| issn | 1469-5073 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Genetics Research |
| spelling | doaj-art-d3ffc37e14cc4e1482690a8057031aae2025-02-03T06:42:41ZengWileyGenetics Research1469-50732023-01-01202310.1155/2023/5574636The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing AnalysisZhe Tan0Rong Chen1Hanyu Lin2Hong Wang3Orthopedics DepartmentOrthopedics DepartmentOrthopedics DepartmentOrthopedics DepartmentOsteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predisposition. As the pathogenesis of OA is unknown, there are almost no effective treatments available to prevent the onset or progression of the disease. In recent years, many researchers focused on bioinformatics analysis to explore new biomarkers for the diagnosis, treatment, and prognosis of human diseases. In this work, we obtain the traditional RNA sequencing data of OA patients from the GEO database. By performing the differentially expressed analysis, we successfully obtain the genes that are closely associated with the OA. In addition, the Venn diagram was applied to evaluate the genes that are involved in OA and immune-related genes. The protein-protein interaction analysis was further conducted to explore the hub genes. The single-cell RNA sequencing analysis was used to evaluate the expression distribution of the MMP, VEGFA, SPI1, and IRF8 in synovial tissues of patients with osteoarthritis. Finally, the GSVA enrichment analysis discovered the potential pathways involved in OA patients. Our analysis provides a new direction for the exploration of the process of OA patients. In addition, VEGFA may be considered a promising biomarker in OA.http://dx.doi.org/10.1155/2023/5574636 |
| spellingShingle | Zhe Tan Rong Chen Hanyu Lin Hong Wang The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis Genetics Research |
| title | The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis |
| title_full | The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis |
| title_fullStr | The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis |
| title_full_unstemmed | The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis |
| title_short | The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis |
| title_sort | identification of immune related biomarkers for osteoarthritis immunotherapy based on single cell rna sequencing analysis |
| url | http://dx.doi.org/10.1155/2023/5574636 |
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