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Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis
BACKGROUND: A chronic progressive degenerative joint disease, such as osteoarthritis (OA) is positively related to age. The medical economy is facing a major burden, because of the high disability rate seen in patients with OA. Therefore, to prevent and treat OA, exploring the diagnostic biomarkers...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8801091/ https://www.ncbi.nlm.nih.gov/pubmed/35093162 http://dx.doi.org/10.1186/s41065-022-00226-z |
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author | Han, Yaguang Wu, Jun Gong, Zhenyu Zhou, Yiqin Li, Haobo Chen, Yi Qian, Qirong |
author_facet | Han, Yaguang Wu, Jun Gong, Zhenyu Zhou, Yiqin Li, Haobo Chen, Yi Qian, Qirong |
author_sort | Han, Yaguang |
collection | PubMed |
description | BACKGROUND: A chronic progressive degenerative joint disease, such as osteoarthritis (OA) is positively related to age. The medical economy is facing a major burden, because of the high disability rate seen in patients with OA. Therefore, to prevent and treat OA, exploring the diagnostic biomarkers of OA will be of great significance. METHODS: Differentially expressed genes (DEGs) were obtained from the Gene Expression Omnibus database using the RobustRankAggreg R package, and a protein–protein interaction network was constructed. The module was obtained from Cytoscape, and the four algorithms of degree, MNC, closeness, and MCC in CytoHubba were used to identify the hub genes. A diagnostic model was constructed using Support Vector Machines (SVM), and the ability of the model to predict was evaluated by other cohorts. RESULTS: From normal and OA samples, 136 DEGs were identified, out of which 45 were downregulated in the normal group and 91 were upregulated in the OA group. These genes were associated with the extracellular matrix-receptor interactions, the PI3K-Akt signaling pathway, and the protein digestion and absorption pathway, as per a functional enrichment analysis. Finally, we identified the 7 hub genes (COL6A3, COL1A2, COL1A1, MMP2, COL3A1, POST, and FN1). These genes have important roles and are widely involved in the immune response, apoptosis, inflammation, and bone development. These 7 genes were used to construct a diagnostic model by SVM, and it performed well in different cohorts. Additionally, we verified the methylation expression of these hub genes. CONCLUSIONS: The 7-genes signature can be used for the diagnosis of OA and can provide new ideas in the clinical decision-making for patients with OA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41065-022-00226-z. |
format | Online Article Text |
id | pubmed-8801091 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88010912022-02-02 Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis Han, Yaguang Wu, Jun Gong, Zhenyu Zhou, Yiqin Li, Haobo Chen, Yi Qian, Qirong Hereditas Research BACKGROUND: A chronic progressive degenerative joint disease, such as osteoarthritis (OA) is positively related to age. The medical economy is facing a major burden, because of the high disability rate seen in patients with OA. Therefore, to prevent and treat OA, exploring the diagnostic biomarkers of OA will be of great significance. METHODS: Differentially expressed genes (DEGs) were obtained from the Gene Expression Omnibus database using the RobustRankAggreg R package, and a protein–protein interaction network was constructed. The module was obtained from Cytoscape, and the four algorithms of degree, MNC, closeness, and MCC in CytoHubba were used to identify the hub genes. A diagnostic model was constructed using Support Vector Machines (SVM), and the ability of the model to predict was evaluated by other cohorts. RESULTS: From normal and OA samples, 136 DEGs were identified, out of which 45 were downregulated in the normal group and 91 were upregulated in the OA group. These genes were associated with the extracellular matrix-receptor interactions, the PI3K-Akt signaling pathway, and the protein digestion and absorption pathway, as per a functional enrichment analysis. Finally, we identified the 7 hub genes (COL6A3, COL1A2, COL1A1, MMP2, COL3A1, POST, and FN1). These genes have important roles and are widely involved in the immune response, apoptosis, inflammation, and bone development. These 7 genes were used to construct a diagnostic model by SVM, and it performed well in different cohorts. Additionally, we verified the methylation expression of these hub genes. CONCLUSIONS: The 7-genes signature can be used for the diagnosis of OA and can provide new ideas in the clinical decision-making for patients with OA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41065-022-00226-z. BioMed Central 2022-01-29 /pmc/articles/PMC8801091/ /pubmed/35093162 http://dx.doi.org/10.1186/s41065-022-00226-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Han, Yaguang Wu, Jun Gong, Zhenyu Zhou, Yiqin Li, Haobo Chen, Yi Qian, Qirong Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
title | Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
title_full | Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
title_fullStr | Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
title_full_unstemmed | Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
title_short | Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
title_sort | identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8801091/ https://www.ncbi.nlm.nih.gov/pubmed/35093162 http://dx.doi.org/10.1186/s41065-022-00226-z |
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