Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome
Objective: Osteoarthritis (OA) and Myelodysplastic syndrome (MDS) are diseases caused by the same immune disorder with unclear etiology and many similarities in clinical manifestations; however, the specific mechanisms between osteoarthritis and myelodysplastic syndrome are unclear.Methods: The expr...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1040438/full |
| _version_ | 1811157826743042048 |
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| author | Peicheng Xin Ming Li Jing Dong Hongbo Zhu Jie Li |
| author_facet | Peicheng Xin Ming Li Jing Dong Hongbo Zhu Jie Li |
| author_sort | Peicheng Xin |
| collection | DOAJ |
| description | Objective: Osteoarthritis (OA) and Myelodysplastic syndrome (MDS) are diseases caused by the same immune disorder with unclear etiology and many similarities in clinical manifestations; however, the specific mechanisms between osteoarthritis and myelodysplastic syndrome are unclear.Methods: The expression profile microarrays of osteoarthritis and myelodysplastic syndrome were searched in the GEO database, the intersection of their differential genes was taken, Venn diagrams were constructed to find common pathogenic genes, bioinformatics analysis signaling pathway analysis was performed on the obtained genes, and protein-protein interaction networks were constructed to find hub genes in order to establish diagnostic models for each disease and explore the immune infiltration of hub genes.Results: 52 co-pathogenic genes were screened for association with immune regulation, immune response, and inflammation. The mean area under the receiver operating characteristic (ROC) for all 10 genes used for co-causal diagnosis ranged from 0.71–0.81. Immune cell infiltration analysis in the myelodysplastic syndrome subgroup showed that the relative numbers of Macrophages M1, B cells memory, and T cells CD4 memory resting in the myelodysplastic syndrome group were significantly different from the normal group, however, in the osteoarthritis subgroup the relative numbers of Mast cells resting in the osteoarthritis subgroup was significantly different from the normal group.Conclusion: There are common pathogenic genes in osteoarthritis and myelodysplastic syndrome, which in turn mediate differential alterations in related signaling pathways and immune cells, affecting the high prevalence of osteoarthritis and myelodysplastic syndrome and the two disease phenomena. |
| first_indexed | 2024-04-10T05:12:52Z |
| format | Article |
| id | doaj.art-9f25f226af9546c79eb83c5d677789ef |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-10T05:12:52Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-9f25f226af9546c79eb83c5d677789ef2023-03-09T06:03:44ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-03-011310.3389/fgene.2022.10404381040438Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndromePeicheng Xin0Ming Li1Jing Dong2Hongbo Zhu3Jie Li4Department of Orthopedics, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, ChinaDepartment of Orthopedics, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, ChinaDepartment of Hematology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, ChinaDepartment of Hematology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, ChinaDepartment of Hematology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, ChinaObjective: Osteoarthritis (OA) and Myelodysplastic syndrome (MDS) are diseases caused by the same immune disorder with unclear etiology and many similarities in clinical manifestations; however, the specific mechanisms between osteoarthritis and myelodysplastic syndrome are unclear.Methods: The expression profile microarrays of osteoarthritis and myelodysplastic syndrome were searched in the GEO database, the intersection of their differential genes was taken, Venn diagrams were constructed to find common pathogenic genes, bioinformatics analysis signaling pathway analysis was performed on the obtained genes, and protein-protein interaction networks were constructed to find hub genes in order to establish diagnostic models for each disease and explore the immune infiltration of hub genes.Results: 52 co-pathogenic genes were screened for association with immune regulation, immune response, and inflammation. The mean area under the receiver operating characteristic (ROC) for all 10 genes used for co-causal diagnosis ranged from 0.71–0.81. Immune cell infiltration analysis in the myelodysplastic syndrome subgroup showed that the relative numbers of Macrophages M1, B cells memory, and T cells CD4 memory resting in the myelodysplastic syndrome group were significantly different from the normal group, however, in the osteoarthritis subgroup the relative numbers of Mast cells resting in the osteoarthritis subgroup was significantly different from the normal group.Conclusion: There are common pathogenic genes in osteoarthritis and myelodysplastic syndrome, which in turn mediate differential alterations in related signaling pathways and immune cells, affecting the high prevalence of osteoarthritis and myelodysplastic syndrome and the two disease phenomena.https://www.frontiersin.org/articles/10.3389/fgene.2022.1040438/fullmyelodysplastic syndromeosteoarthritisbioinformaticshub genesignaling pathway |
| spellingShingle | Peicheng Xin Ming Li Jing Dong Hongbo Zhu Jie Li Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome Frontiers in Genetics myelodysplastic syndrome osteoarthritis bioinformatics hub gene signaling pathway |
| title | Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome |
| title_full | Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome |
| title_fullStr | Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome |
| title_full_unstemmed | Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome |
| title_short | Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome |
| title_sort | bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome |
| topic | myelodysplastic syndrome osteoarthritis bioinformatics hub gene signaling pathway |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1040438/full |
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