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Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics
Background: Osteoarthritis (OA) is one of the main causes of disability in the elderly population, accompanied by a series of underlying pathologic changes, such as cartilage degradation, synovitis, subchondral bone sclerosis, and meniscus injury. The present study aimed to identify key genes, signa...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419250/ https://www.ncbi.nlm.nih.gov/pubmed/34497524 http://dx.doi.org/10.3389/fphar.2021.730587 |
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author | Chang, Liang Yao, Hao Yao, Zhi Ho, Kevin Ki-Wai Ong, Michael Tim-Yun Dai, Bingyang Tong, Wenxue Xu, Jiankun Qin, Ling |
author_facet | Chang, Liang Yao, Hao Yao, Zhi Ho, Kevin Ki-Wai Ong, Michael Tim-Yun Dai, Bingyang Tong, Wenxue Xu, Jiankun Qin, Ling |
author_sort | Chang, Liang |
collection | PubMed |
description | Background: Osteoarthritis (OA) is one of the main causes of disability in the elderly population, accompanied by a series of underlying pathologic changes, such as cartilage degradation, synovitis, subchondral bone sclerosis, and meniscus injury. The present study aimed to identify key genes, signaling pathways, and miRNAs in knee OA associated with the entire joint components, and to explain the potential mechanisms using computational analysis. Methods: The differentially expressed genes (DEGs) in cartilage, synovium, subchondral bone, and meniscus were identified using the Gene Expression Omnibus 2R (GEO2R) analysis based on dataset from GSE43923, GSE12021, GSE98918, and GSE51588, respectively and visualized in Volcano Plot. Venn diagram analyses were performed to identify the overlapping DEGs (overlapping DEGs) that expressed in at least two types of tissues mentioned above. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, protein-protein interaction (PPI) analysis, and module analysis were conducted. Furthermore, qRT-PCR was performed to validate above results using our clinical specimens. Results: As a result, a total of 236 overlapping DEGs were identified, of which 160 were upregulated and 76 were downregulated. Through enrichment analysis and constructing the PPI network and miRNA-mRNA network, knee OA-related key genes, such as HEY1, AHR, VEGFA, MYC, and CXCL12 were identified. Clinical validation by qRT-PCR experiments further supported above computational results. In addition, knee OA-related key miRNAs such as miR-101, miR-181a, miR-29, miR-9, and miR-221, and pathways such as Wnt signaling, HIF-1 signaling, PI3K-Akt signaling, and axon guidance pathways were also identified. Among above identified knee OA-related key genes, pathways and miRNAs, genes such as AHR, HEY1, MYC, GAP43, and PTN, pathways like axon guidance, and miRNAs such as miR-17, miR-21, miR-155, miR-185, and miR-1 are lack of research and worthy for future investigation. Conclusion: The present informatic study for the first time provides insight to the potential therapeutic targets of knee OA by comprehensively analyzing the overlapping genes differentially expressed in multiple joint components and their relevant signaling pathways and interactive miRNAs. |
format | Online Article Text |
id | pubmed-8419250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84192502021-09-07 Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics Chang, Liang Yao, Hao Yao, Zhi Ho, Kevin Ki-Wai Ong, Michael Tim-Yun Dai, Bingyang Tong, Wenxue Xu, Jiankun Qin, Ling Front Pharmacol Pharmacology Background: Osteoarthritis (OA) is one of the main causes of disability in the elderly population, accompanied by a series of underlying pathologic changes, such as cartilage degradation, synovitis, subchondral bone sclerosis, and meniscus injury. The present study aimed to identify key genes, signaling pathways, and miRNAs in knee OA associated with the entire joint components, and to explain the potential mechanisms using computational analysis. Methods: The differentially expressed genes (DEGs) in cartilage, synovium, subchondral bone, and meniscus were identified using the Gene Expression Omnibus 2R (GEO2R) analysis based on dataset from GSE43923, GSE12021, GSE98918, and GSE51588, respectively and visualized in Volcano Plot. Venn diagram analyses were performed to identify the overlapping DEGs (overlapping DEGs) that expressed in at least two types of tissues mentioned above. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, protein-protein interaction (PPI) analysis, and module analysis were conducted. Furthermore, qRT-PCR was performed to validate above results using our clinical specimens. Results: As a result, a total of 236 overlapping DEGs were identified, of which 160 were upregulated and 76 were downregulated. Through enrichment analysis and constructing the PPI network and miRNA-mRNA network, knee OA-related key genes, such as HEY1, AHR, VEGFA, MYC, and CXCL12 were identified. Clinical validation by qRT-PCR experiments further supported above computational results. In addition, knee OA-related key miRNAs such as miR-101, miR-181a, miR-29, miR-9, and miR-221, and pathways such as Wnt signaling, HIF-1 signaling, PI3K-Akt signaling, and axon guidance pathways were also identified. Among above identified knee OA-related key genes, pathways and miRNAs, genes such as AHR, HEY1, MYC, GAP43, and PTN, pathways like axon guidance, and miRNAs such as miR-17, miR-21, miR-155, miR-185, and miR-1 are lack of research and worthy for future investigation. Conclusion: The present informatic study for the first time provides insight to the potential therapeutic targets of knee OA by comprehensively analyzing the overlapping genes differentially expressed in multiple joint components and their relevant signaling pathways and interactive miRNAs. Frontiers Media S.A. 2021-08-23 /pmc/articles/PMC8419250/ /pubmed/34497524 http://dx.doi.org/10.3389/fphar.2021.730587 Text en Copyright © 2021 Chang, Yao, Yao, Ho, Ong, Dai, Tong, Xu and Qin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Chang, Liang Yao, Hao Yao, Zhi Ho, Kevin Ki-Wai Ong, Michael Tim-Yun Dai, Bingyang Tong, Wenxue Xu, Jiankun Qin, Ling Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics |
title | Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics |
title_full | Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics |
title_fullStr | Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics |
title_full_unstemmed | Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics |
title_short | Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics |
title_sort | comprehensive analysis of key genes, signaling pathways and mirnas in human knee osteoarthritis: based on bioinformatics |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419250/ https://www.ncbi.nlm.nih.gov/pubmed/34497524 http://dx.doi.org/10.3389/fphar.2021.730587 |
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