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Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data

Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are two major types of joint diseases. The present study aimed to identify hub genes involved in the pathogenesis and further explore the potential treatment targets of RA and OA. Methods: The gene expression profile of GSE12021 was downl...

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Autores principales: Zuo, Bin, Zhu, JunFeng, Xiao, Fei, Wang, ChengLong, Shen, Yun, Chen, XiaoDong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744737/
https://www.ncbi.nlm.nih.gov/pubmed/33325525
http://dx.doi.org/10.1042/BSR20193823
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author Zuo, Bin
Zhu, JunFeng
Xiao, Fei
Wang, ChengLong
Shen, Yun
Chen, XiaoDong
author_facet Zuo, Bin
Zhu, JunFeng
Xiao, Fei
Wang, ChengLong
Shen, Yun
Chen, XiaoDong
author_sort Zuo, Bin
collection PubMed
description Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are two major types of joint diseases. The present study aimed to identify hub genes involved in the pathogenesis and further explore the potential treatment targets of RA and OA. Methods: The gene expression profile of GSE12021 was downloaded from Gene Expression Omnibus (GEO). Total 31 samples (12 RA, 10 OA and 9 NC samples) were used. The differentially expressed genes (DEGs) in RA versus NC, OA versus NC and RA versus OA groups were screened using limma package. We also verified the DEGs in GSE55235 and GSE100786. Functional annotation and protein–protein interaction (PPI) network construction of OA‐ and RA‐specific DEGs were performed. Finally, the candidate small molecules as potential drugs to treat RA and OA were predicted in CMap database. Results: 165 up-regulated and 163 down-regulated DEGs between RA and NC samples, 73 up-regulated and 293 down-regulated DEGs between OA and NC samples, 92 up-regulated and 98 down-regulated DEGs between RA and OA samples were identified. Immune response and TNF signaling pathway were significantly enriched pathways for RA‐ and OA‐specific DEGs, respectively. The hub genes were mainly associated with ‘Primary immunodeficiency’ (RA vs. NC group), ‘Ribosome’ (OA vs. NC group), and ‘Chemokine signaling pathway’ (RA vs. OA group). Arecoline and Cefamandole were the most promising small molecule to reverse the RA and OA gene expression. Conclusion: Our findings suggest new insights into the underlying pathogenesis of RA and OA, which may improve the diagnosis and treatment of these intractable chronic diseases.
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spelling pubmed-77447372020-12-29 Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data Zuo, Bin Zhu, JunFeng Xiao, Fei Wang, ChengLong Shen, Yun Chen, XiaoDong Biosci Rep Bioinformatics Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are two major types of joint diseases. The present study aimed to identify hub genes involved in the pathogenesis and further explore the potential treatment targets of RA and OA. Methods: The gene expression profile of GSE12021 was downloaded from Gene Expression Omnibus (GEO). Total 31 samples (12 RA, 10 OA and 9 NC samples) were used. The differentially expressed genes (DEGs) in RA versus NC, OA versus NC and RA versus OA groups were screened using limma package. We also verified the DEGs in GSE55235 and GSE100786. Functional annotation and protein–protein interaction (PPI) network construction of OA‐ and RA‐specific DEGs were performed. Finally, the candidate small molecules as potential drugs to treat RA and OA were predicted in CMap database. Results: 165 up-regulated and 163 down-regulated DEGs between RA and NC samples, 73 up-regulated and 293 down-regulated DEGs between OA and NC samples, 92 up-regulated and 98 down-regulated DEGs between RA and OA samples were identified. Immune response and TNF signaling pathway were significantly enriched pathways for RA‐ and OA‐specific DEGs, respectively. The hub genes were mainly associated with ‘Primary immunodeficiency’ (RA vs. NC group), ‘Ribosome’ (OA vs. NC group), and ‘Chemokine signaling pathway’ (RA vs. OA group). Arecoline and Cefamandole were the most promising small molecule to reverse the RA and OA gene expression. Conclusion: Our findings suggest new insights into the underlying pathogenesis of RA and OA, which may improve the diagnosis and treatment of these intractable chronic diseases. Portland Press Ltd. 2020-12-16 /pmc/articles/PMC7744737/ /pubmed/33325525 http://dx.doi.org/10.1042/BSR20193823 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the .
spellingShingle Bioinformatics
Zuo, Bin
Zhu, JunFeng
Xiao, Fei
Wang, ChengLong
Shen, Yun
Chen, XiaoDong
Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
title Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
title_full Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
title_fullStr Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
title_full_unstemmed Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
title_short Identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
title_sort identification of novel biomarkers and candidate small molecule drugs in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis of high‐throughput data
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744737/
https://www.ncbi.nlm.nih.gov/pubmed/33325525
http://dx.doi.org/10.1042/BSR20193823
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