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Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction
Both primary Sjögren’s syndrome (pSS) and acute myocardial infarction (AMI) are intricately linked. However, their common mechanism is not fully understood. Herein, we examined the underlying network of molecular action associated with developing this complication. Datasets were downloaded from the...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630427/ https://www.ncbi.nlm.nih.gov/pubmed/37935719 http://dx.doi.org/10.1038/s41598-023-45896-5 |
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author | Hou, Qingbin Jiang, Jinping Na, Kun Zhang, Xiaolin Liu, Dan Jing, Quanmin Yan, Chenghui Han, Yaling |
author_facet | Hou, Qingbin Jiang, Jinping Na, Kun Zhang, Xiaolin Liu, Dan Jing, Quanmin Yan, Chenghui Han, Yaling |
author_sort | Hou, Qingbin |
collection | PubMed |
description | Both primary Sjögren’s syndrome (pSS) and acute myocardial infarction (AMI) are intricately linked. However, their common mechanism is not fully understood. Herein, we examined the underlying network of molecular action associated with developing this complication. Datasets were downloaded from the GEO database. We performed enrichment and protein–protein interaction analyses and screened key genes. We used external datasets to confirm the diagnostic performance for these hub genes. Transcription factor and microRNA regulatory networks were constructed for the validated hub genes. Finally, drug prediction and molecular docking validation were performed. We identified 62 common DEGs, many of which were enriched regarding inflammation and immune response. 5 DEGs were found as key hub genes (IGSF6, MMP9, S100A8, MNDA, and NCF2). They had high diagnostic performance in external datasets. Functional enrichment of these five hub genes showed that they were associated with the adaptive immune response. The Type 1T helper cell showed the most association among all cell types related to AMI and pSS. We identified 36 common TFs and 49 identical TF-miRNAs. The drugs, including Benzo, dexamethasone, and NADP, were predicted as potential therapeutic agents. Herein, we revealed common networks involving pSS and AMI etiologies. Knowledge of these networks and hub genes can enhance research into their associated mechanism and the development of future robust therapy. |
format | Online Article Text |
id | pubmed-10630427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106304272023-11-06 Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction Hou, Qingbin Jiang, Jinping Na, Kun Zhang, Xiaolin Liu, Dan Jing, Quanmin Yan, Chenghui Han, Yaling Sci Rep Article Both primary Sjögren’s syndrome (pSS) and acute myocardial infarction (AMI) are intricately linked. However, their common mechanism is not fully understood. Herein, we examined the underlying network of molecular action associated with developing this complication. Datasets were downloaded from the GEO database. We performed enrichment and protein–protein interaction analyses and screened key genes. We used external datasets to confirm the diagnostic performance for these hub genes. Transcription factor and microRNA regulatory networks were constructed for the validated hub genes. Finally, drug prediction and molecular docking validation were performed. We identified 62 common DEGs, many of which were enriched regarding inflammation and immune response. 5 DEGs were found as key hub genes (IGSF6, MMP9, S100A8, MNDA, and NCF2). They had high diagnostic performance in external datasets. Functional enrichment of these five hub genes showed that they were associated with the adaptive immune response. The Type 1T helper cell showed the most association among all cell types related to AMI and pSS. We identified 36 common TFs and 49 identical TF-miRNAs. The drugs, including Benzo, dexamethasone, and NADP, were predicted as potential therapeutic agents. Herein, we revealed common networks involving pSS and AMI etiologies. Knowledge of these networks and hub genes can enhance research into their associated mechanism and the development of future robust therapy. Nature Publishing Group UK 2023-11-06 /pmc/articles/PMC10630427/ /pubmed/37935719 http://dx.doi.org/10.1038/s41598-023-45896-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Article Hou, Qingbin Jiang, Jinping Na, Kun Zhang, Xiaolin Liu, Dan Jing, Quanmin Yan, Chenghui Han, Yaling Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction |
title | Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction |
title_full | Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction |
title_fullStr | Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction |
title_full_unstemmed | Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction |
title_short | Bioinformatics analyses of potentially common pathogenic networks for primary Sjögren’s syndrome complicated with acute myocardial infarction |
title_sort | bioinformatics analyses of potentially common pathogenic networks for primary sjögren’s syndrome complicated with acute myocardial infarction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10630427/ https://www.ncbi.nlm.nih.gov/pubmed/37935719 http://dx.doi.org/10.1038/s41598-023-45896-5 |
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