Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis

Abstract Background Osteoarthritis (OA) is a worldwide musculoskeletal disorder. However, disease-modifying therapies for OA are not available. Here, we aimed to characterize the molecular signatures of OA and to identify novel therapeutic targets and strategies to improve the treatment of OA. Metho...

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Main Authors: Song Shi, Fuyin Wan, Zhenyu Zhou, Ran Tao, Yue Lu, Ming Zhou, Fan Liu, Yake Liu
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Journal of Orthopaedic Surgery and Research
Subjects:
Online Access:https://doi.org/10.1186/s13018-021-02402-9
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spelling doaj-e35fa66a88934ec1a266206a57f939192021-04-18T11:29:19ZengBMCJournal of Orthopaedic Surgery and Research1749-799X2021-04-0116111310.1186/s13018-021-02402-9Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysisSong Shi0Fuyin Wan1Zhenyu Zhou2Ran Tao3Yue Lu4Ming Zhou5Fan Liu6Yake Liu7Department of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityDepartment of Orthopaedics, Affiliated Hospital of Nantong UniversityAbstract Background Osteoarthritis (OA) is a worldwide musculoskeletal disorder. However, disease-modifying therapies for OA are not available. Here, we aimed to characterize the molecular signatures of OA and to identify novel therapeutic targets and strategies to improve the treatment of OA. Methods We collected genome-wide transcriptome data performed on 132 OA and 74 normal human cartilage or synovium tissues from 7 independent datasets. Differential gene expression analysis and functional enrichment were performed to identify genes and pathways that were dysregulated in OA. The computational drug repurposing method was used to uncover drugs that could be repurposed to treat OA. Results We identified several pathways associated with the development of OA, such as extracellular matrix organization, inflammation, bone development, and ossification. By protein-protein interaction (PPI) network analysis, we prioritized several hub genes, such as JUN, CDKN1A, VEGFA, and FOXO3. Moreover, we repurposed several FDA-approved drugs, such as cardiac glycosides, that could be used in the treatment of OA. Conclusions We proposed that the hub genes we identified would play a role in cartilage homeostasis and could be important diagnostic and therapeutic targets. Drugs such as cardiac glycosides provided new possibilities for the treatment of OA.https://doi.org/10.1186/s13018-021-02402-9OsteoarthritisTranscriptional profilingDrug repurposing
collection DOAJ
language English
format Article
sources DOAJ
author Song Shi
Fuyin Wan
Zhenyu Zhou
Ran Tao
Yue Lu
Ming Zhou
Fan Liu
Yake Liu
spellingShingle Song Shi
Fuyin Wan
Zhenyu Zhou
Ran Tao
Yue Lu
Ming Zhou
Fan Liu
Yake Liu
Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
Journal of Orthopaedic Surgery and Research
Osteoarthritis
Transcriptional profiling
Drug repurposing
author_facet Song Shi
Fuyin Wan
Zhenyu Zhou
Ran Tao
Yue Lu
Ming Zhou
Fan Liu
Yake Liu
author_sort Song Shi
title Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
title_short Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
title_full Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
title_fullStr Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
title_full_unstemmed Identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
title_sort identification of key regulators responsible for dysregulated networks in osteoarthritis by large-scale expression analysis
publisher BMC
series Journal of Orthopaedic Surgery and Research
issn 1749-799X
publishDate 2021-04-01
description Abstract Background Osteoarthritis (OA) is a worldwide musculoskeletal disorder. However, disease-modifying therapies for OA are not available. Here, we aimed to characterize the molecular signatures of OA and to identify novel therapeutic targets and strategies to improve the treatment of OA. Methods We collected genome-wide transcriptome data performed on 132 OA and 74 normal human cartilage or synovium tissues from 7 independent datasets. Differential gene expression analysis and functional enrichment were performed to identify genes and pathways that were dysregulated in OA. The computational drug repurposing method was used to uncover drugs that could be repurposed to treat OA. Results We identified several pathways associated with the development of OA, such as extracellular matrix organization, inflammation, bone development, and ossification. By protein-protein interaction (PPI) network analysis, we prioritized several hub genes, such as JUN, CDKN1A, VEGFA, and FOXO3. Moreover, we repurposed several FDA-approved drugs, such as cardiac glycosides, that could be used in the treatment of OA. Conclusions We proposed that the hub genes we identified would play a role in cartilage homeostasis and could be important diagnostic and therapeutic targets. Drugs such as cardiac glycosides provided new possibilities for the treatment of OA.
topic Osteoarthritis
Transcriptional profiling
Drug repurposing
url https://doi.org/10.1186/s13018-021-02402-9
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