Cargando…
Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis
BACKGROUND: Ankylosing spondylitis (AS) is one of the most common immune-mediated arthritic diseases worldwide. Despite considerable efforts to elucidate its pathogenesis, the molecular mechanisms underlying AS are still not fully understood. METHODS: To identify candidate genes involved in AS progr...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10186804/ https://www.ncbi.nlm.nih.gov/pubmed/37193965 http://dx.doi.org/10.1186/s12891-023-06490-y |
_version_ | 1785042631494991872 |
---|---|
author | Wang, Han Jin, Hongbo Liu, Zhiyang Tan, Chengju Wei, Lin Fu, Mingfen Huang, Yizhuan |
author_facet | Wang, Han Jin, Hongbo Liu, Zhiyang Tan, Chengju Wei, Lin Fu, Mingfen Huang, Yizhuan |
author_sort | Wang, Han |
collection | PubMed |
description | BACKGROUND: Ankylosing spondylitis (AS) is one of the most common immune-mediated arthritic diseases worldwide. Despite considerable efforts to elucidate its pathogenesis, the molecular mechanisms underlying AS are still not fully understood. METHODS: To identify candidate genes involved in AS progression, the researchers downloaded the microarray dataset GSE25101 from the Gene Expression Omnibus (GEO) database. They identified differentially expressed genes (DEGs) and functionally enriched them for analysis. They also constructed a protein–protein interaction network (PPI) using STRING and performed cytoHubba modular analysis, immune cell and immune function analysis, functional analysis and drug prediction.The results showed that DEGs were mainly associated with histone modifications, chromatin organisation, transcriptional coregulator activity, transcriptional co-activator activity, histone acetyltransferase complexes and protein acetyltransferase complexes. RESULTS: The researchers analysed the differences in expression between the CONTROL and TREAT groups in terms of immunity to determine their effect on TNF-α secretion. By obtaining hub genes, they predicted two therapeutic agents, AY 11–7082 and myricetin. CONCLUSION: The DEGs, hub genes and predicted drugs identified in this study contribute to our understanding of the molecular mechanisms underlying the onset and progression of AS. They also provide candidate targets for the diagnosis and treatment of AS. |
format | Online Article Text |
id | pubmed-10186804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101868042023-05-17 Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis Wang, Han Jin, Hongbo Liu, Zhiyang Tan, Chengju Wei, Lin Fu, Mingfen Huang, Yizhuan BMC Musculoskelet Disord Research BACKGROUND: Ankylosing spondylitis (AS) is one of the most common immune-mediated arthritic diseases worldwide. Despite considerable efforts to elucidate its pathogenesis, the molecular mechanisms underlying AS are still not fully understood. METHODS: To identify candidate genes involved in AS progression, the researchers downloaded the microarray dataset GSE25101 from the Gene Expression Omnibus (GEO) database. They identified differentially expressed genes (DEGs) and functionally enriched them for analysis. They also constructed a protein–protein interaction network (PPI) using STRING and performed cytoHubba modular analysis, immune cell and immune function analysis, functional analysis and drug prediction.The results showed that DEGs were mainly associated with histone modifications, chromatin organisation, transcriptional coregulator activity, transcriptional co-activator activity, histone acetyltransferase complexes and protein acetyltransferase complexes. RESULTS: The researchers analysed the differences in expression between the CONTROL and TREAT groups in terms of immunity to determine their effect on TNF-α secretion. By obtaining hub genes, they predicted two therapeutic agents, AY 11–7082 and myricetin. CONCLUSION: The DEGs, hub genes and predicted drugs identified in this study contribute to our understanding of the molecular mechanisms underlying the onset and progression of AS. They also provide candidate targets for the diagnosis and treatment of AS. BioMed Central 2023-05-16 /pmc/articles/PMC10186804/ /pubmed/37193965 http://dx.doi.org/10.1186/s12891-023-06490-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Han Jin, Hongbo Liu, Zhiyang Tan, Chengju Wei, Lin Fu, Mingfen Huang, Yizhuan Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
title | Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
title_full | Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
title_fullStr | Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
title_full_unstemmed | Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
title_short | Screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
title_sort | screening and identification of key chromatin regulator biomarkers for ankylosing spondylitis and drug prediction: evidence from bioinformatics analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10186804/ https://www.ncbi.nlm.nih.gov/pubmed/37193965 http://dx.doi.org/10.1186/s12891-023-06490-y |
work_keys_str_mv | AT wanghan screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis AT jinhongbo screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis AT liuzhiyang screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis AT tanchengju screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis AT weilin screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis AT fumingfen screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis AT huangyizhuan screeningandidentificationofkeychromatinregulatorbiomarkersforankylosingspondylitisanddrugpredictionevidencefrombioinformaticsanalysis |