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Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis
Osteoarthritis (OA) is a high prevalent musculoskeletal problem, which can cause severe pain, constitute a huge social and economic burden, and seriously damage the quality of life. This study was intended to identify genetic characteristics of subchondral bone in patients with OA and to elucidate t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489699/ https://www.ncbi.nlm.nih.gov/pubmed/32925767 http://dx.doi.org/10.1097/MD.0000000000022142 |
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author | Yang, Zhanyu Ni, Jiangdong Kuang, Letian Gao, Yongquan Tao, Shibin |
author_facet | Yang, Zhanyu Ni, Jiangdong Kuang, Letian Gao, Yongquan Tao, Shibin |
author_sort | Yang, Zhanyu |
collection | PubMed |
description | Osteoarthritis (OA) is a high prevalent musculoskeletal problem, which can cause severe pain, constitute a huge social and economic burden, and seriously damage the quality of life. This study was intended to identify genetic characteristics of subchondral bone in patients with OA and to elucidate the potential molecular mechanisms involved. Data of gene expression profiles (GSE51588), which contained 40 OA samples and 10 normal samples, was obtained from the Gene Expression Omnibus (GEO). The raw data were integrated to obtain differentially expressed genes (DEGs) and were further analyzed with bioinformatic analysis. The protein–protein interaction (PPI) networks were built and analyzed via Search Tool for the Retrieval of Interacting Genes (STRING). The significant modules and hub genes were identified via Cytoscape. Moreover, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis were performed. Totally 235 DEGs were differentially expressed in the subchondral bone from OA patients compared with those of normal individuals, of which 78 were upregulated and 157 were downregulated. Eight hub genes were identified, including DEFA4, ARG1, LTF, RETN, PGLYRP1, OLFM4, ORM1, and BPI. The enrichment analyses of the DEGs and significant modules indicated that DEGs were mainly involved in inflammatory response, extracellular space, RAGE receptor binding, and amoebiasis pathway. The present study provides a novel and in-depth understanding of pathogenesis of the OA subchondral bone at molecular level. DEFA4, ARG1, LTF, RETN, PGLYRP1, OLFM4, ORM1, and BPI may be the new candidate targets for diagnosis and therapies on patients with OA in the future. |
format | Online Article Text |
id | pubmed-7489699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-74896992020-09-24 Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis Yang, Zhanyu Ni, Jiangdong Kuang, Letian Gao, Yongquan Tao, Shibin Medicine (Baltimore) 7000 Osteoarthritis (OA) is a high prevalent musculoskeletal problem, which can cause severe pain, constitute a huge social and economic burden, and seriously damage the quality of life. This study was intended to identify genetic characteristics of subchondral bone in patients with OA and to elucidate the potential molecular mechanisms involved. Data of gene expression profiles (GSE51588), which contained 40 OA samples and 10 normal samples, was obtained from the Gene Expression Omnibus (GEO). The raw data were integrated to obtain differentially expressed genes (DEGs) and were further analyzed with bioinformatic analysis. The protein–protein interaction (PPI) networks were built and analyzed via Search Tool for the Retrieval of Interacting Genes (STRING). The significant modules and hub genes were identified via Cytoscape. Moreover, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis were performed. Totally 235 DEGs were differentially expressed in the subchondral bone from OA patients compared with those of normal individuals, of which 78 were upregulated and 157 were downregulated. Eight hub genes were identified, including DEFA4, ARG1, LTF, RETN, PGLYRP1, OLFM4, ORM1, and BPI. The enrichment analyses of the DEGs and significant modules indicated that DEGs were mainly involved in inflammatory response, extracellular space, RAGE receptor binding, and amoebiasis pathway. The present study provides a novel and in-depth understanding of pathogenesis of the OA subchondral bone at molecular level. DEFA4, ARG1, LTF, RETN, PGLYRP1, OLFM4, ORM1, and BPI may be the new candidate targets for diagnosis and therapies on patients with OA in the future. Lippincott Williams & Wilkins 2020-09-11 /pmc/articles/PMC7489699/ /pubmed/32925767 http://dx.doi.org/10.1097/MD.0000000000022142 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 7000 Yang, Zhanyu Ni, Jiangdong Kuang, Letian Gao, Yongquan Tao, Shibin Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
title | Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
title_full | Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
title_fullStr | Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
title_full_unstemmed | Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
title_short | Identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
title_sort | identification of genes and pathways associated with subchondral bone in osteoarthritis via bioinformatic analysis |
topic | 7000 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489699/ https://www.ncbi.nlm.nih.gov/pubmed/32925767 http://dx.doi.org/10.1097/MD.0000000000022142 |
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