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Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis
BACKGROUND: Systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) are common systemic autoimmune diseases that share a wide range of clinical manifestations and serological features. This study investigates genes, signaling pathways, and transcription factors (TFs) shared between S...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442653/ https://www.ncbi.nlm.nih.gov/pubmed/37614232 http://dx.doi.org/10.3389/fimmu.2023.1212330 |
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author | Cui, Yanling Zhang, Huina Wang, Zhen Gong, Bangdong Al-Ward, Hisham Deng, Yaxuan Fan, Orion Wang, Junbang Zhu, Wenmin Sun, Yi Eve |
author_facet | Cui, Yanling Zhang, Huina Wang, Zhen Gong, Bangdong Al-Ward, Hisham Deng, Yaxuan Fan, Orion Wang, Junbang Zhu, Wenmin Sun, Yi Eve |
author_sort | Cui, Yanling |
collection | PubMed |
description | BACKGROUND: Systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) are common systemic autoimmune diseases that share a wide range of clinical manifestations and serological features. This study investigates genes, signaling pathways, and transcription factors (TFs) shared between SLE and pSS. METHODS: Gene expression profiles of SLE and pSS were obtained from the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to identify shared genes related to SLE and pSS. Overlapping genes were then subject to Gene Ontology (GO) and protein-protein interaction (PPI) network analyses. Cytoscape plugins cytoHubba and iRegulon were subsequently used to screen shared hub genes and predict TFs. In addition, gene set variation analysis (GSVA) and CIBERSORTx were used to calculate the correlations between hub genes and immune cells as well as related pathways. To confirm these results, hub genes and TFs were verified in microarray and single-cell RNA sequencing (scRNA-seq) datasets. RESULTS: Following WGCNA and limma analysis, 152 shared genes were identified. These genes were involved in interferon (IFN) response and cytokine-mediated signaling pathway. Moreover, we screened six shared genes, namely IFI44L, ISG15, IFIT1, USP18, RSAD2 and ITGB2, out of which three genes, namely IFI44L, ISG15 and ITGB2 were found to be highly expressed in both microarray and scRNA-seq datasets. IFN response and ITGB2 signaling pathway were identified as potentially relevant pathways. In addition, STAT1 and IRF7 were identified as common TFs in both diseases. CONCLUSION: This study revealed IFI44L, ISG15 and ITGB2 as the shared genes and identified STAT1 and IRF7 as the common TFs of SLE and pSS. Notably, the IFN response and ITGB2 signaling pathway played vital roles in both diseases. Our study revealed common pathogenetic characteristics of SLE and pSS. The particular roles of these pivotal genes and mutually overlapping pathways may provide a basis for further mechanistic research. |
format | Online Article Text |
id | pubmed-10442653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104426532023-08-23 Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis Cui, Yanling Zhang, Huina Wang, Zhen Gong, Bangdong Al-Ward, Hisham Deng, Yaxuan Fan, Orion Wang, Junbang Zhu, Wenmin Sun, Yi Eve Front Immunol Immunology BACKGROUND: Systemic lupus erythematosus (SLE) and primary Sjögren’s syndrome (pSS) are common systemic autoimmune diseases that share a wide range of clinical manifestations and serological features. This study investigates genes, signaling pathways, and transcription factors (TFs) shared between SLE and pSS. METHODS: Gene expression profiles of SLE and pSS were obtained from the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to identify shared genes related to SLE and pSS. Overlapping genes were then subject to Gene Ontology (GO) and protein-protein interaction (PPI) network analyses. Cytoscape plugins cytoHubba and iRegulon were subsequently used to screen shared hub genes and predict TFs. In addition, gene set variation analysis (GSVA) and CIBERSORTx were used to calculate the correlations between hub genes and immune cells as well as related pathways. To confirm these results, hub genes and TFs were verified in microarray and single-cell RNA sequencing (scRNA-seq) datasets. RESULTS: Following WGCNA and limma analysis, 152 shared genes were identified. These genes were involved in interferon (IFN) response and cytokine-mediated signaling pathway. Moreover, we screened six shared genes, namely IFI44L, ISG15, IFIT1, USP18, RSAD2 and ITGB2, out of which three genes, namely IFI44L, ISG15 and ITGB2 were found to be highly expressed in both microarray and scRNA-seq datasets. IFN response and ITGB2 signaling pathway were identified as potentially relevant pathways. In addition, STAT1 and IRF7 were identified as common TFs in both diseases. CONCLUSION: This study revealed IFI44L, ISG15 and ITGB2 as the shared genes and identified STAT1 and IRF7 as the common TFs of SLE and pSS. Notably, the IFN response and ITGB2 signaling pathway played vital roles in both diseases. Our study revealed common pathogenetic characteristics of SLE and pSS. The particular roles of these pivotal genes and mutually overlapping pathways may provide a basis for further mechanistic research. Frontiers Media S.A. 2023-08-08 /pmc/articles/PMC10442653/ /pubmed/37614232 http://dx.doi.org/10.3389/fimmu.2023.1212330 Text en Copyright © 2023 Cui, Zhang, Wang, Gong, Al-Ward, Deng, Fan, Wang, Zhu and Sun https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Cui, Yanling Zhang, Huina Wang, Zhen Gong, Bangdong Al-Ward, Hisham Deng, Yaxuan Fan, Orion Wang, Junbang Zhu, Wenmin Sun, Yi Eve Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis |
title | Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis |
title_full | Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis |
title_fullStr | Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis |
title_full_unstemmed | Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis |
title_short | Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysis |
title_sort | exploring the shared molecular mechanisms between systemic lupus erythematosus and primary sjögren’s syndrome based on integrated bioinformatics and single-cell rna-seq analysis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442653/ https://www.ncbi.nlm.nih.gov/pubmed/37614232 http://dx.doi.org/10.3389/fimmu.2023.1212330 |
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