Cargando…
Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis
OBJECTIVES: The present study aimed to identify different key genes and pathways between postmenopausal females and males by studying differentially expressed genes (DEGs). METHODS: GSE32317 and GSE55457 gene expression data were downloaded from the GEO database, and DEGs were discovered using R sof...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Society of Musculoskeletal and Neuronal Interactions
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9438520/ https://www.ncbi.nlm.nih.gov/pubmed/36046996 |
_version_ | 1784781842635816960 |
---|---|
author | Xu, Junchang Yan, Zijian Wu, Guihua Zheng, Yongling Liao, Xiaolong Zou, Feng |
author_facet | Xu, Junchang Yan, Zijian Wu, Guihua Zheng, Yongling Liao, Xiaolong Zou, Feng |
author_sort | Xu, Junchang |
collection | PubMed |
description | OBJECTIVES: The present study aimed to identify different key genes and pathways between postmenopausal females and males by studying differentially expressed genes (DEGs). METHODS: GSE32317 and GSE55457 gene expression data were downloaded from the GEO database, and DEGs were discovered using R software to obtain overlapping DEGs. The interaction between overlapping DEGs was further analyzed by establishing the protein-protein interaction (PPI) network. Finally, GO and KEGG were used for enrichment analysis. RESULTS: 924 overlapping DEGs between postmenopausal women and men with osteoarthritis (OA) were identified, including 674 up-regulated genes and 249 down-regulated ones. And 10 hub genes were identified in the PPI network, including BMP4, KDM6A, JMJD1C, NFATC1, PRKX, SRF, ZFX, LAMTOR5, UFD1L and AMBN. The findings of the functional enrichment analysis suggested that these genes were predominantly expressed in MAPK signaling pathway as well as the Thyroid hormone signaling pathway, indicating that those two pathways may be involved in onset and disease progression of OA in postmenopausal patients. CONCLUSION: BMP4, KDM6A, JMJD1C, PRKX, ZFX and LAMTOR5 are expected to play crucial roles in disease development in postmenopausal patients and may be ideal targets or prognostic markers for the treatment of OA. |
format | Online Article Text |
id | pubmed-9438520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | International Society of Musculoskeletal and Neuronal Interactions |
record_format | MEDLINE/PubMed |
spelling | pubmed-94385202022-09-16 Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis Xu, Junchang Yan, Zijian Wu, Guihua Zheng, Yongling Liao, Xiaolong Zou, Feng J Musculoskelet Neuronal Interact Original Article OBJECTIVES: The present study aimed to identify different key genes and pathways between postmenopausal females and males by studying differentially expressed genes (DEGs). METHODS: GSE32317 and GSE55457 gene expression data were downloaded from the GEO database, and DEGs were discovered using R software to obtain overlapping DEGs. The interaction between overlapping DEGs was further analyzed by establishing the protein-protein interaction (PPI) network. Finally, GO and KEGG were used for enrichment analysis. RESULTS: 924 overlapping DEGs between postmenopausal women and men with osteoarthritis (OA) were identified, including 674 up-regulated genes and 249 down-regulated ones. And 10 hub genes were identified in the PPI network, including BMP4, KDM6A, JMJD1C, NFATC1, PRKX, SRF, ZFX, LAMTOR5, UFD1L and AMBN. The findings of the functional enrichment analysis suggested that these genes were predominantly expressed in MAPK signaling pathway as well as the Thyroid hormone signaling pathway, indicating that those two pathways may be involved in onset and disease progression of OA in postmenopausal patients. CONCLUSION: BMP4, KDM6A, JMJD1C, PRKX, ZFX and LAMTOR5 are expected to play crucial roles in disease development in postmenopausal patients and may be ideal targets or prognostic markers for the treatment of OA. International Society of Musculoskeletal and Neuronal Interactions 2022 /pmc/articles/PMC9438520/ /pubmed/36046996 Text en Copyright: © Journal of Musculoskeletal and Neuronal Interactions https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 4.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Xu, Junchang Yan, Zijian Wu, Guihua Zheng, Yongling Liao, Xiaolong Zou, Feng Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
title | Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
title_full | Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
title_fullStr | Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
title_full_unstemmed | Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
title_short | Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
title_sort | identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9438520/ https://www.ncbi.nlm.nih.gov/pubmed/36046996 |
work_keys_str_mv | AT xujunchang identificationofkeygenesandpathwaysassociatedwithsexdifferenceinosteoarthritisbasedonbioinformaticsanalysis AT yanzijian identificationofkeygenesandpathwaysassociatedwithsexdifferenceinosteoarthritisbasedonbioinformaticsanalysis AT wuguihua identificationofkeygenesandpathwaysassociatedwithsexdifferenceinosteoarthritisbasedonbioinformaticsanalysis AT zhengyongling identificationofkeygenesandpathwaysassociatedwithsexdifferenceinosteoarthritisbasedonbioinformaticsanalysis AT liaoxiaolong identificationofkeygenesandpathwaysassociatedwithsexdifferenceinosteoarthritisbasedonbioinformaticsanalysis AT zoufeng identificationofkeygenesandpathwaysassociatedwithsexdifferenceinosteoarthritisbasedonbioinformaticsanalysis |